| Item Type | Journal Article |
|---|---|
| Author | Kenneth Lange |
| Author | Xun-Jian Li |
| Author | Hua Zhou |
| Date | 2025-08-04 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://www.tandfonline.com/doi/full/10.1080/00031305.2025.2526535 |
| Accessed | 8/10/2025, 4:22:59 PM |
| Pages | 1-11 |
| Publication | The American Statistician |
| DOI | 10.1080/00031305.2025.2526535 |
| Journal Abbr | The American Statistician |
| ISSN | 0003-1305, 1537-2731 |
| Date Added | 8/10/2025, 4:22:59 PM |
| Modified | 8/10/2025, 4:23:46 PM |
| Item Type | Journal Article |
|---|---|
| Author | Alexandra Nowbar Nowbar |
| Author | Christopher Rajkumar |
| Author | Michael Foley |
| Author | Fiyyaz Ahmed-Jushuf |
| Author | James Howard Howard |
| Author | Henry Seligman |
| Author | Ricardo Petraco |
| Author | Sayan Sen |
| Author | Sukhjinder Nijjer Nijjer |
| Author | Matthew Shun-Shin Shun-Shin |
| Author | Thomas Keeble Keeble |
| Author | Afzal Sohaib |
| Author | David Collier |
| Author | Patrick McVeigh |
| Author | Frank Harrell Harrell |
| Author | Darrel Francis Francis |
| Author | Rasha Al-Lamee Al-Lamee |
| Date | 04/2022 |
| Short Title | A double-blind randomised placebo-controlled trial of percutaneous coronary intervention for the relief of stable angina without antianginal medications |
| Library Catalog | DOI.org (Crossref) |
| URL | https://eurointervention.pcronline.com/doi/10.4244/EIJ-D-21-00649 |
| Accessed | 12/28/2025, 10:04:33 AM |
| Volume | 17 |
| Pages | 1490-1497 |
| Publication | EuroIntervention |
| DOI | 10.4244/EIJ-D-21-00649 |
| Issue | 18 |
| ISSN | 1774-024X |
| Date Added | 12/28/2025, 10:04:33 AM |
| Modified | 12/28/2025, 10:04:33 AM |
| Item Type | Journal Article |
|---|---|
| Author | Michael J. Foley |
| Author | Christopher A. Rajkumar |
| Author | Fiyyaz Ahmed-Jushuf |
| Author | Florentina Simader |
| Author | Rachel H. Pathimagaraj |
| Author | Sukhjinder Nijjer |
| Author | Sayan Sen |
| Author | Ricardo Petraco |
| Author | Gerald Clesham |
| Author | Thomas Johnson |
| Author | Frank E. Harrell Jr |
| Author | Peter Kellman |
| Author | Darrel Francis |
| Author | Matthew Shun-Shin |
| Author | James Howard |
| Author | Graham D. Cole |
| Author | Rasha Al-Lamee |
| Date | 02/2024 |
| Short Title | A double-blind, randomised, placebo-controlled trial of the coronary sinus Reducer in refractory angina |
| Library Catalog | DOI.org (Crossref) |
| URL | https://eurointervention.pcronline.com/doi/10.4244/EIJ-D-23-00567 |
| Accessed | 12/28/2025, 10:15:21 AM |
| Volume | 20 |
| Pages | e216-e223 |
| Publication | EuroIntervention |
| DOI | 10.4244/EIJ-D-23-00567 |
| Issue | 3 |
| ISSN | 1969-6213 |
| Date Added | 12/28/2025, 10:15:21 AM |
| Modified | 12/28/2025, 10:15:21 AM |
| Item Type | Journal Article |
|---|---|
| Author | Dakota Vaughan |
| Author | Frank E. Harrell |
| Author | Sean P. Donahue |
| Date | 09/2022 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://linkinghub.elsevier.com/retrieve/pii/S0161642022003311 |
| Accessed | 12/28/2025, 10:08:37 AM |
| Volume | 129 |
| Pages | 1065-1067 |
| Publication | Ophthalmology |
| DOI | 10.1016/j.ophtha.2022.04.026 |
| Issue | 9 |
| Journal Abbr | Ophthalmology |
| ISSN | 01616420 |
| Date Added | 12/28/2025, 10:08:37 AM |
| Modified | 12/28/2025, 10:08:37 AM |
| Item Type | Journal Article |
|---|---|
| Author | Edward Tang Qian |
| Author | Cheryl L. Gatto |
| Author | Olga Amusina |
| Author | Mary Lynn Dear |
| Author | William Hiser |
| Author | Reagan Buie |
| Author | Sunil Kripalani |
| Author | Frank E. Harrell |
| Author | Robert E. Freundlich |
| Author | Yue Gao |
| Author | Wu Gong |
| Author | Cassandra Hennessy |
| Author | Jillann Grooms |
| Author | Megan Mattingly |
| Author | Shashi K. Bellam |
| Author | Jessica Burke |
| Author | Arwa Zakaria |
| Author | Eduard E. Vasilevskis |
| Author | Frederic T. Billings |
| Author | Jill M. Pulley |
| Author | Gordon R. Bernard |
| Author | Christopher J. Lindsell |
| Author | Todd W. Rice |
| Author | Vanderbilt Learning Healthcare System Platform Investigators |
| Author | Robert Dittus |
| Author | Shon Dwyer |
| Author | Paul Harris |
| Author | Tina Hartert |
| Author | Jim Hayman |
| Author | Catherine Ivory |
| Author | Kevin Johnson |
| Author | Ruth Kleinpell |
| Author | Lee Ann Liska |
| Author | Patrick Luther |
| Author | Jay Morrison |
| Author | Thomas Nantais |
| Author | Mariann Piano |
| Author | Kris Rhem |
| Author | Russell Rothman |
| Author | Matt Semler |
| Author | Robin Steaban |
| Author | Philip Walker |
| Author | Consuelo Wilkins |
| Author | Adam Wright |
| Author | Autumn Zuckerman |
| Date | 2022-06-01 |
| Language | en |
| Short Title | Assessment of Awake Prone Positioning in Hospitalized Adults With COVID-19 |
| Library Catalog | DOI.org (Crossref) |
| URL | https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/2791385 |
| Accessed | 12/28/2025, 10:06:25 AM |
| Volume | 182 |
| Pages | 612 |
| Publication | JAMA Internal Medicine |
| DOI | 10.1001/jamainternmed.2022.1070 |
| Issue | 6 |
| Journal Abbr | JAMA Intern Med |
| ISSN | 2168-6106 |
| Date Added | 12/28/2025, 10:06:25 AM |
| Modified | 12/28/2025, 10:06:25 AM |
| Item Type | Journal Article |
|---|---|
| Author | Hiral Master |
| Author | Jeffrey Annis |
| Author | Shi Huang |
| Author | Joshua A. Beckman |
| Author | Francis Ratsimbazafy |
| Author | Kayla Marginean |
| Author | Robert Carroll |
| Author | Karthik Natarajan |
| Author | Frank E. Harrell |
| Author | Dan M. Roden |
| Author | Paul Harris |
| Author | Evan L. Brittain |
| Abstract | Abstract The association between physical activity and human disease has not been examined using commercial devices linked to electronic health records. Using the electronic health records data from the All of Us Research Program, we show that step count volumes as captured by participants’ own Fitbit devices were associated with risk of chronic disease across the entire human phenome. Of the 6,042 participants included in the study, 73% were female, 84% were white and 71% had a college degree, and participants had a median age of 56.7 (interquartile range 41.5–67.6) years and body mass index of 28.1 (24.3–32.9) kg m –2 . Participants walked a median of 7,731.3 (5,866.8–9,826.8) steps per day over the median activity monitoring period of 4.0 (2.2–5.6) years with a total of 5.9 million person-days of monitoring. The relationship between steps per day and incident disease was inverse and linear for obesity ( n = 368), sleep apnea ( n = 348), gastroesophageal reflux disease ( n = 432) and major depressive disorder ( n = 467), with values above 8,200 daily steps associated with protection from incident disease. The relationships with incident diabetes ( n = 156) and hypertension ( n = 482) were nonlinear with no further risk reduction above 8,000–9,000 steps. Although validation in a more diverse sample is needed, these findings provide a real-world evidence-base for clinical guidance regarding activity levels that are necessary to reduce disease risk. |
| Date | 11/2022 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://www.nature.com/articles/s41591-022-02012-w |
| Accessed | 12/28/2025, 10:09:21 AM |
| Volume | 28 |
| Pages | 2301-2308 |
| Publication | Nature Medicine |
| DOI | 10.1038/s41591-022-02012-w |
| Issue | 11 |
| Journal Abbr | Nat Med |
| ISSN | 1078-8956, 1546-170X |
| Date Added | 12/28/2025, 10:09:21 AM |
| Modified | 12/28/2025, 10:09:21 AM |
| Item Type | Journal Article |
|---|---|
| Author | Samuel Heuts |
| Author | Michal J. Kawczynski |
| Author | Ahmed Sayed |
| Author | Sarah M. Urbut |
| Author | Arthur M. Albuquerque |
| Author | John M. Mandrola |
| Author | Sanjay Kaul |
| Author | Frank E. Harrell |
| Author | Andrea Gabrio |
| Author | James M. Brophy |
| Date | 01/2025 |
| Language | en |
| Short Title | Bayesian Analytical Methods in Cardiovascular Clinical Trials |
| Library Catalog | DOI.org (Crossref) |
| URL | https://linkinghub.elsevier.com/retrieve/pii/S0828282X24011309 |
| Accessed | 12/28/2025, 10:28:51 AM |
| Volume | 41 |
| Pages | 30-44 |
| Publication | Canadian Journal of Cardiology |
| DOI | 10.1016/j.cjca.2024.11.002 |
| Issue | 1 |
| Journal Abbr | Canadian Journal of Cardiology |
| ISSN | 0828282X |
| Date Added | 12/28/2025, 10:28:51 AM |
| Modified | 12/28/2025, 10:30:13 AM |
| Item Type | Journal Article |
|---|---|
| Author | Feng Gu |
| Author | Jiaqing Chen |
| Author | Jinjing Wang |
| Author | Yibo Long |
| Author | Xiaofan Wang |
| Author | Yangxin Huang |
| Abstract | ABSTRACT In the realm of clinical medical research, semi‐competing risks data are usually observed in practice, yet there are few studies on the joint models of longitudinal and semi‐competing risks data. In this paper, a joint model for longitudinal and semi‐competing risks data is proposed. Based on the expectile regression, a linear mixed‐effects longitudinal sub‐model is formulated, and a Cox proportional hazards survival sub‐model is considered under the framework of semi‐competing risks. The two sub‐models are linked by a shared longitudinal trajectory function. To accommodate the time‐varying relationship between the longitudinal response variable and covariates, as well as to introduce flexibility to the structural linkage between longitudinal and survival processes, we incorporate the time‐varying coefficients into the joint model in the form of nonparametric functions. The simultaneous Bayesian inference method is utilized to estimate the model parameters, which not only overcomes the convergence problem, but also improves the accuracy of the parameter estimation while effectively reducing the computational burden. The simulation studies are conducted to assess the performance of the proposed joint model and methodology. Finally, we analyze a dataset from the Multicenter AIDS Cohort Study to illustrate the real application of the proposed model and method. In both simulation studies and empirical analyses, joint modeling methods demonstrate performance that meets expected effects. |
| Date | 08/2025 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://onlinelibrary.wiley.com/doi/10.1002/sim.70219 |
| Accessed | 8/10/2025, 4:35:09 PM |
| Volume | 44 |
| Pages | e70219 |
| Publication | Statistics in Medicine |
| DOI | 10.1002/sim.70219 |
| Issue | 18-19 |
| Journal Abbr | Statistics in Medicine |
| ISSN | 0277-6715, 1097-0258 |
| Date Added | 8/10/2025, 4:35:09 PM |
| Modified | 8/10/2025, 4:36:21 PM |
| Item Type | Journal Article |
|---|---|
| Author | Ewan C Goligher |
| Author | Anna Heath |
| Author | Michael O Harhay |
| Date | 09/2024 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://linkinghub.elsevier.com/retrieve/pii/S0140673624012959 |
| Accessed | 1/28/2026, 2:49:13 PM |
| Volume | 404 |
| Pages | 1067-1076 |
| Publication | The Lancet |
| DOI | 10.1016/S0140-6736(24)01295-9 |
| Issue | 10457 |
| Journal Abbr | The Lancet |
| ISSN | 01406736 |
| Date Added | 1/28/2026, 2:49:13 PM |
| Modified | 1/28/2026, 2:49:42 PM |
| Item Type | Journal Article |
|---|---|
| Author | Junhui Mi |
| Author | Rahul D. Tendulkar |
| Author | Sarah M. C. Sittenfeld |
| Author | Sujata Patil |
| Author | Emily C. Zabor |
| Abstract | ABSTRACT Methods to handle missing data have been extensively explored in the context of estimation and descriptive studies, with multiple imputation being the most widely used method in clinical research. However, in the context of clinical risk prediction models, where the goal is often to achieve high prediction accuracy and to make predictions for future patients, there are different considerations regarding the handling of missing covariate data. As a result, deterministic imputation is better suited to the setting of clinical risk prediction models, since the outcome is not included in the imputation model and the imputation method can be easily applied to future patients. In this paper, we provide a tutorial demonstrating how to conduct bootstrapping followed by deterministic imputation of missing covariate data to construct and internally validate the performance of a clinical risk prediction model in the presence of missing data. Simulation study results are provided to help guide when imputation may be appropriate in real‐world applications. |
| Date | 08/2025 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://onlinelibrary.wiley.com/doi/10.1002/sim.70203 |
| Accessed | 8/10/2025, 4:31:30 PM |
| Volume | 44 |
| Pages | e70203 |
| Publication | Statistics in Medicine |
| DOI | 10.1002/sim.70203 |
| Issue | 18-19 |
| Journal Abbr | Statistics in Medicine |
| ISSN | 0277-6715, 1097-0258 |
| Date Added | 8/10/2025, 4:31:30 PM |
| Modified | 8/10/2025, 4:32:40 PM |
| Item Type | Journal Article |
|---|---|
| Author | Sinclair Awounvo |
| Author | Meinhard Kieser |
| Author | Manuel Feißt |
| Date | 8/2025 |
| Language | en |
| Short Title | Combining multiple imputation with internal model validation in clinical prediction modeling |
| Library Catalog | DOI.org (Crossref) |
| URL | https://linkinghub.elsevier.com/retrieve/pii/S0895435625002495 |
| Accessed | 8/10/2025, 4:51:27 PM |
| Pages | 111916 |
| Publication | Journal of Clinical Epidemiology |
| DOI | 10.1016/j.jclinepi.2025.111916 |
| Journal Abbr | Journal of Clinical Epidemiology |
| ISSN | 08954356 |
| Date Added | 8/10/2025, 4:51:27 PM |
| Modified | 8/10/2025, 4:52:00 PM |
| Item Type | Journal Article |
|---|---|
| Author | Frank E Harrell |
| Date | 08/2024 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://journals.sagepub.com/doi/10.1177/17407745241251609 |
| Accessed | 12/28/2025, 10:23:09 AM |
| Volume | 21 |
| Pages | 412-414 |
| Publication | Clinical Trials |
| DOI | 10.1177/17407745241251609 |
| Issue | 4 |
| Journal Abbr | Clinical Trials |
| ISSN | 1740-7745, 1740-7753 |
| Date Added | 12/28/2025, 10:23:09 AM |
| Modified | 12/28/2025, 10:23:09 AM |
| Item Type | Journal Article |
|---|---|
| Author | Kelly W. Harris |
| Author | Thomas V. Cunningham |
| Author | D. Micah Hester |
| Author | Kelly Armstrong |
| Author | Ahra Kim |
| Author | Frank E. Harrell |
| Author | Joseph B. Fanning |
| Date | 2021-04-03 |
| Language | en |
| Short Title | Comparison Is Not a Zero-Sum Game |
| Library Catalog | DOI.org (Crossref) |
| URL | https://www.tandfonline.com/doi/full/10.1080/23294515.2020.1844820 |
| Accessed | 12/28/2025, 9:57:59 AM |
| Volume | 12 |
| Pages | 123-136 |
| Publication | AJOB Empirical Bioethics |
| DOI | 10.1080/23294515.2020.1844820 |
| Issue | 2 |
| Journal Abbr | AJOB Empirical Bioethics |
| ISSN | 2329-4515, 2329-4523 |
| Date Added | 12/28/2025, 9:57:59 AM |
| Modified | 12/28/2025, 9:57:59 AM |
| Item Type | Preprint |
|---|---|
| Author | Tetiana Gorbach |
| Author | Xavier de Luna |
| Author | Juha Karvanen |
| Author | Ingeborg Waernbaum |
| Abstract | This article contributes to the discussion on the relationship between the Neyman-Rubin and the graphical frameworks for causal inference. We present specific examples of data-generating mechanisms - such as those involving undirected or deterministic relationships and cycles - where analyses using a directed acyclic graph are challenging, but where the tools from the Neyman-Rubin causal framework are readily applicable. We also provide examples of data-generating mechanisms with M-bias, trapdoor variables, and complex front-door structures, where the application of the Neyman-Rubin approach is complicated, but the graphical approach is directly usable. The examples offer insights into commonly used causal inference frameworks and aim to improve comprehension of the languages for causal reasoning among a broad audience. |
| Date | 2025 |
| Library Catalog | DOI.org (Datacite) |
| URL | https://arxiv.org/abs/2512.09130 |
| Accessed | 12/11/2025, 8:27:21 AM |
| Rights | Creative Commons Attribution 4.0 International |
| Extra | Version Number: 1 |
| DOI | 10.48550/ARXIV.2512.09130 |
| Repository | arXiv |
| Date Added | 12/11/2025, 8:27:21 AM |
| Modified | 12/11/2025, 8:28:25 AM |
<h2>Other</h2> Under consideration at The American Statistician; not yet accepted
| Item Type | Journal Article |
|---|---|
| Author | Leah Pirondini |
| Author | John Gregson |
| Author | Ruth Owen |
| Author | Tim Collier |
| Author | Stuart Pocock |
| Date | 05/2022 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://linkinghub.elsevier.com/retrieve/pii/S2213177922001743 |
| Accessed | 1/3/2026, 8:47:52 AM |
| Volume | 10 |
| Pages | 297-305 |
| Publication | JACC: Heart Failure |
| DOI | 10.1016/j.jchf.2022.02.007 |
| Issue | 5 |
| Journal Abbr | JACC: Heart Failure |
| ISSN | 22131779 |
| Date Added | 1/3/2026, 8:47:52 AM |
| Modified | 1/3/2026, 8:48:24 AM |
| Item Type | Journal Article |
|---|---|
| Author | Alexandra N Nowbar |
| Author | James P Howard |
| Author | Matthew J Shun-Shin |
| Author | Christopher Rajkumar |
| Author | Michael Foley |
| Author | Arunima Basu |
| Author | Akshit Goel |
| Author | Sapna Patel |
| Author | Ahmer Adnan |
| Author | Catherine J Beattie |
| Author | Thomas R Keeble |
| Author | Afzal Sohaib |
| Author | David Collier |
| Author | Patrick McVeigh |
| Author | Frank E Harrell |
| Author | Darrel P Francis |
| Author | Rasha K Al-Lamee |
| Abstract | Abstract Aims The traditional approach to documenting angina outcomes in clinical trials is to ask the patient to recall their symptoms at the end of a month. With the ubiquitous availability of smartphones and tablets, daily contemporaneous documentation might be possible. Methods and results The ORBITA-2 symptom smartphone app was developed with a user-centred iterative design and testing cycle involving a focus group of previous ORBITA participants. The feasibility and acceptability were assessed in an internal pilot of participants in the ongoing ORBITA-2 trial. Seven days of app entries by ORBITA-2 participants were compared with subsequent participant recall at the end of the 7-day period. The design focus group tested a prototype app. They reported that the final version captured their symptoms and was easy to use. In the completion assessment group, 141 of 142 (99%) completed the app in full and 47 of 141 (33%) without reminders. In the recall assessment group, 29 of 29 (100%) participants said they could recall the previous day’s symptoms, and 82% of them recalled correctly. For 2 days previously, 88% said they could recall and of those, 87% recalled correctly. The proportion saying they could recall their symptoms fell progressively thereafter: 89, 67, 61, 50%, and at 7 days, 55% (P < 0.001 for trend). The proportion of recalling correctly also fell progressively to 55% at 7 days (P = 0.04 for trend). Conclusion Episode counts of angina are difficult to recall after a few days. For trials such as ORBITA-2 focusing on angina, daily symptom collection via a smartphone app will increase the validity of the results. |
| Date | 2022-07-06 |
| Language | en |
| Short Title | Daily angina documentation versus subsequent recall |
| Library Catalog | DOI.org (Crossref) |
| URL | https://academic.oup.com/ehjdh/article/3/2/276/6566267 |
| Accessed | 12/28/2025, 10:06:56 AM |
| Rights | https://creativecommons.org/licenses/by-nc/4.0/ |
| Volume | 3 |
| Pages | 276-283 |
| Publication | European Heart Journal - Digital Health |
| DOI | 10.1093/ehjdh/ztac015 |
| Issue | 2 |
| ISSN | 2634-3916 |
| Date Added | 12/28/2025, 10:06:56 AM |
| Modified | 12/28/2025, 10:06:56 AM |
| Item Type | Journal Article |
|---|---|
| Author | Pedro Lopez-Ayala |
| Author | Richard D Riley |
| Author | Gary S Collins |
| Author | Tobias Zimmermann |
| Date | 2025-07-16 |
| Language | en |
| Short Title | Dealing with continuous variables and modelling non-linear associations in healthcare data |
| Library Catalog | Crossref |
| URL | https://www.bmj.com/lookup/doi/10.1136/bmj-2024-082440 |
| Accessed | 7/16/2025, 1:29:28 PM |
| Rights | http://www.bmj.com/company/legal-information/terms-conditions/legal-information/tdm-licencepolicy |
| Extra | Publisher: BMJ |
| Volume | 390 |
| Pages | e082440 |
| Publication | BMJ |
| DOI | 10.1136/bmj-2024-082440 |
| ISSN | 1756-1833 |
| Date Added | 7/16/2025, 1:29:28 PM |
| Modified | 7/16/2025, 1:30:25 PM |
| Item Type | Journal Article |
|---|---|
| Author | Orestis Efthimiou |
| Author | Michael Seo |
| Author | Konstantina Chalkou |
| Author | Thomas Debray |
| Author | Matthias Egger |
| Author | Georgia Salanti |
| Date | 2024-09-03 |
| Language | en |
| Short Title | Developing clinical prediction models |
| Library Catalog | DOI.org (Crossref) |
| URL | https://www.bmj.com/lookup/doi/10.1136/bmj-2023-078276 |
| Accessed | 7/29/2025, 5:12:14 PM |
| Pages | e078276 |
| Publication | BMJ |
| DOI | 10.1136/bmj-2023-078276 |
| Journal Abbr | BMJ |
| ISSN | 1756-1833 |
| Date Added | 7/29/2025, 5:12:14 PM |
| Modified | 7/29/2025, 5:13:27 PM |
| Item Type | Journal Article |
|---|---|
| Author | Stephen W. Patrick |
| Author | James C. Slaughter |
| Author | Frank E. Harrell |
| Author | Peter R. Martin |
| Author | Katherine Hartmann |
| Author | Judith Dudley |
| Author | Shannon Stratton |
| Author | William O. Cooper |
| Date | 02/2021 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://linkinghub.elsevier.com/retrieve/pii/S002234762031297X |
| Accessed | 12/28/2025, 9:51:10 AM |
| Volume | 229 |
| Pages | 154-160.e6 |
| Publication | The Journal of Pediatrics |
| DOI | 10.1016/j.jpeds.2020.10.030 |
| Journal Abbr | The Journal of Pediatrics |
| ISSN | 00223476 |
| Date Added | 12/28/2025, 9:51:10 AM |
| Modified | 12/28/2025, 9:51:10 AM |
| Item Type | Journal Article |
|---|---|
| Author | Sarah S. Osmundson |
| Author | Alese Halvorson |
| Author | Kristin N. Graves |
| Author | Clara Wang |
| Author | Stephen Bruehl |
| Author | Carlos G. Grijalva |
| Author | Dan France |
| Author | Katherine Hartmann |
| Author | Shilpa Mokshagundam |
| Author | Frank E. Harrell |
| Abstract | OBJECTIVE: To develop and validate a prediction model for postdischarge opioid use in patients undergoing cesarean birth. METHODS: We conducted a prospective cohort study of patients undergoing cesarean birth. Patients were enrolled postoperatively, and they completed pain and opioid use questionnaires 14 days after cesarean birth. Clinical data were abstracted from the electronic health record (EHR). Participants were prescribed 30 tablets of hydrocodone 5 mg–acetaminophen 325 mg at discharge and were queried about postdischarge opioid use. The primary outcome was total morphine milligram equivalents used. We constructed three proportional odds predictive models of postdischarge opioid use: a full model with 34 predictors available before hospital discharge, an EHR model that excluded questionnaire data, and a reduced model. The reduced model used forward selection to sequentially add predictors until 90% of the full model performance was achieved. Predictors were ranked a priori based on data from the literature and prior research. Predictive accuracy was estimated using discrimination (concordance index). RESULTS: Between 2019 and 2020, 459 participants were enrolled and 279 filled the standardized study prescription. Of the 398 with outcome measurements, participants used a median of eight tablets (interquartile range 1–18 tablets) after discharge, 23.5% used no opioids, and 23.0% used all opioids. Each of the models demonstrated high accuracy predicting postdischarge opioid use (concordance index range 0.74–0.76 for all models). We selected the reduced model as our final model given its similar model performance with the fewest number of predictors, all obtained from the EHR (inpatient opioid use, tobacco use, and depression or anxiety). CONCLUSION: A model with three predictors readily found in the EHR—inpatient opioid use, tobacco use, and depression or anxiety—accurately estimated postdischarge opioid use. This represents an opportunity for individualizing opioid prescriptions after cesarean birth. |
| Date | 05/2022 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://journals.lww.com/10.1097/AOG.0000000000004759 |
| Accessed | 12/28/2025, 10:05:02 AM |
| Volume | 139 |
| Pages | 888-897 |
| Publication | Obstetrics & Gynecology |
| DOI | 10.1097/AOG.0000000000004759 |
| Issue | 5 |
| ISSN | 0029-7844 |
| Date Added | 12/28/2025, 10:05:02 AM |
| Modified | 12/28/2025, 10:05:02 AM |
| Item Type | Journal Article |
|---|---|
| Author | Kristin R. Archer |
| Author | Mohamad Bydon |
| Author | Inamullah Khan |
| Author | Hui Nian |
| Author | Jacquelyn S. Pennings |
| Author | Frank E. Harrell |
| Author | Ahilan Sivaganesan |
| Author | Silky Chotai |
| Author | Matthew J. McGirt |
| Author | Kevin T. Foley |
| Author | Steven D. Glassman |
| Author | Praveen V. Mummaneni |
| Author | Erica F. Bisson |
| Author | John J. Knightly |
| Author | Christopher I. Shaffrey |
| Author | Anthony L. Asher |
| Author | Clinton J. Devin |
| Abstract | Study Design. Retrospective analysis of prospectively collected registry data. Objective. To develop and validate prediction models for 12-month patient-reported outcomes of disability, pain, and myelopathy in patients undergoing elective cervical spine surgery. Summary of Background Data. Predictive models have the potential to be utilized preoperatively to set expectations, adjust modifiable characteristics, and provide a patient-centered model of care. Methods. This study was conducted using data from the cervical module of the Quality Outcomes Database. The outcomes of interest were disability (Neck Disability Index:), pain (Numeric Rating Scale), and modified Japanese Orthopaedic Association score for myelopathy. Multivariable proportional odds ordinal regression models were developed for patients with cervical radiculopathy and myelopathy. Patient demographic, clinical, and surgical covariates as well as baseline patient-reported outcomes scores were included in all models. The models were internally validated using bootstrap resampling to estimate the likely performance on a new sample of patients. Results. Four thousand nine hundred eighty-eight patients underwent surgery for radiculopathy and 2641 patients for myelopathy. The most important predictor of poor postoperative outcomes at 12-months was the baseline Neck Disability Index score for patients with radiculopathy and modified Japanese Orthopaedic Association score for patients with myelopathy. In addition, symptom duration, workers’ compensation, age, employment, and ambulatory and smoking status had a statistically significant impact on all outcomes ( P < 0.001). Clinical and surgical variables contributed very little to predictive models, with posterior approach being associated with higher odds of having worse 12-month outcome scores in both the radiculopathy and myelopathy cohorts ( P < 0.001). The full models overall discriminative performance ranged from 0.654 to 0.725. Conclusions. These predictive models provide individualized risk-adjusted estimates of 12-month disability, pain, and myelopathy outcomes for patients undergoing spine surgery for degenerative cervical disease. Predictive models have the potential to be used as a shared decision-making tool for evidence-based preoperative counselling. Level of Evidence: 2. |
| Date | 2020-11-15 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://journals.lww.com/10.1097/BRS.0000000000003610 |
| Accessed | 12/28/2025, 9:48:51 AM |
| Volume | 45 |
| Pages | 1541-1552 |
| Publication | Spine |
| DOI | 10.1097/BRS.0000000000003610 |
| Issue | 22 |
| ISSN | 0362-2436, 1528-1159 |
| Date Added | 12/28/2025, 9:48:51 AM |
| Modified | 12/28/2025, 9:48:51 AM |
| Item Type | Journal Article |
|---|---|
| Author | Javed Butler |
| Author | Muhammad Shariq Usman |
| Author | Frank E. Harrell |
| Author | Milton Packer |
| Date | 01/2025 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://linkinghub.elsevier.com/retrieve/pii/S0735109724106055 |
| Accessed | 12/28/2025, 10:40:53 AM |
| Volume | 85 |
| Pages | 190-195 |
| Publication | Journal of the American College of Cardiology |
| DOI | 10.1016/j.jacc.2024.12.005 |
| Issue | 2 |
| Journal Abbr | Journal of the American College of Cardiology |
| ISSN | 07351097 |
| Date Added | 12/28/2025, 10:40:53 AM |
| Modified | 12/28/2025, 10:40:53 AM |
| Item Type | Journal Article |
|---|---|
| Author | Gustav Nilsonne |
| Author | Frank E. Harrell |
| Date | 01/2021 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://www.nature.com/articles/s41587-020-00768-5 |
| Accessed | 12/28/2025, 9:50:28 AM |
| Volume | 39 |
| Pages | 27-27 |
| Publication | Nature Biotechnology |
| DOI | 10.1038/s41587-020-00768-5 |
| Issue | 1 |
| Journal Abbr | Nat Biotechnol |
| ISSN | 1087-0156, 1546-1696 |
| Date Added | 12/28/2025, 9:50:28 AM |
| Modified | 12/28/2025, 9:50:28 AM |
| Item Type | Journal Article |
|---|---|
| Author | Brian R Lindman |
| Author | Linda D Gillam |
| Author | Megan Coylewright |
| Author | Frederick G P Welt |
| Author | Sammy Elmariah |
| Author | Stephanie A Smith |
| Author | David A McKeel |
| Author | Natalie Jackson |
| Author | Kush Mukerjee |
| Author | Harrison Cloud |
| Author | Narden Hanna |
| Author | Jenelle Purpura |
| Author | Hannah Ellis |
| Author | Vong Martinez |
| Author | Alexandra M Selberg |
| Author | Shi Huang |
| Author | Frank E Harrell |
| Abstract | Abstract Aims Impaired physical function is common in patients undergoing transcatheter aortic valve replacement (TAVR) and associated with worse outcomes. Participation in centre-based cardiac rehabilitation (CR) after cardiovascular procedures is sub-optimal. We aimed to test a home-based mobile health exercise intervention as an alternative or complementary approach. Methods and results At five centres, after a run-in period, eligible individuals treated with TAVR were randomized 1:1 at their 1-month post-TAVR visit to an intervention group [activity monitor (AM) with personalized daily step goal and resistance exercises] or a control group for 6 weeks. Among 50 participants, average age was 76 years, 34% were female, average STS score was 2.9 ± 1.8, and 40% had Short Physical Performance Battery (SPPB) ≤9. Daily compliance with wearing the AM and performing exercises averaged 85–90%. In the intention to treat population, there was no evidence that the intervention improved the co-primary endpoints: daily steps +769 (95% CI −244 to +1783); SPPB +0.68 (−0.27 to 1.53); and Kansas City Cardiomyopathy Questionnaire −1.7 (−9.1 to 7.1). The intervention did improve secondary physical activity parameters, including moderate-to-intense daily active minutes (P < 0.05). In a pre-specified analysis including participants who did not participate in CR (n = 30), the intervention improved several measures of physical activity: +1730 (100–3360) daily steps; +66 (28–105) daily active minutes; +53 (27–80) moderate-to-intense active minutes; and −157 (−265 to −50) sedentary minutes. Conclusion Among selected participants treated with TAVR, this study did not provide evidence that a pragmatic home-based mobile health exercise intervention improved daily steps, physical performance or QoL for the overall cohort. However, the intervention did improve several measures of daily activity, particularly among individuals not participating in CR. Trial registry Clinicaltrials.gov NCT03270124. |
| Date | 2021-05-04 |
| Language | en |
| Short Title | Effect of a pragmatic home-based mobile health exercise intervention after transcatheter aortic valve replacement |
| Library Catalog | DOI.org (Crossref) |
| URL | https://academic.oup.com/ehjdh/article/2/1/90/6128571 |
| Accessed | 12/28/2025, 9:55:21 AM |
| Rights | http://creativecommons.org/licenses/by-nc/4.0/ |
| Volume | 2 |
| Pages | 90-103 |
| Publication | European Heart Journal - Digital Health |
| DOI | 10.1093/ehjdh/ztab007 |
| Issue | 1 |
| ISSN | 2634-3916 |
| Date Added | 12/28/2025, 9:55:21 AM |
| Modified | 12/28/2025, 9:55:47 AM |
| Item Type | Journal Article |
|---|---|
| Author | Wesley H. Self |
| Author | Matthew W. Semler |
| Author | Lindsay M. Leither |
| Author | Jonathan D. Casey |
| Author | Derek C. Angus |
| Author | Roy G. Brower |
| Author | Steven Y. Chang |
| Author | Sean P. Collins |
| Author | John C. Eppensteiner |
| Author | Michael R. Filbin |
| Author | D. Clark Files |
| Author | Kevin W. Gibbs |
| Author | Adit A. Ginde |
| Author | Michelle N. Gong |
| Author | Frank E. Harrell |
| Author | Douglas L. Hayden |
| Author | Catherine L. Hough |
| Author | Nicholas J. Johnson |
| Author | Akram Khan |
| Author | Christopher J. Lindsell |
| Author | Michael A. Matthay |
| Author | Marc Moss |
| Author | Pauline K. Park |
| Author | Todd W. Rice |
| Author | Bryce R. H. Robinson |
| Author | David A. Schoenfeld |
| Author | Nathan I. Shapiro |
| Author | Jay S. Steingrub |
| Author | Christine A. Ulysse |
| Author | Alexandra Weissman |
| Author | Donald M. Yealy |
| Author | B. Taylor Thompson |
| Author | Samuel M. Brown |
| Author | National Heart, Lung, and Blood Institute PETAL Clinical Trials Network |
| Date | 2020-12-01 |
| Language | en |
| Short Title | Effect of Hydroxychloroquine on Clinical Status at 14 Days in Hospitalized Patients With COVID-19 |
| Library Catalog | DOI.org (Crossref) |
| URL | https://jamanetwork.com/journals/jama/fullarticle/2772922 |
| Accessed | 12/28/2025, 9:49:35 AM |
| Volume | 324 |
| Pages | 2165 |
| Publication | JAMA |
| DOI | 10.1001/jama.2020.22240 |
| Issue | 21 |
| Journal Abbr | JAMA |
| ISSN | 0098-7484 |
| Date Added | 12/28/2025, 9:49:35 AM |
| Modified | 12/28/2025, 9:49:35 AM |
| Item Type | Journal Article |
|---|---|
| Author | Zachary L. Cox |
| Author | Sean P. Collins |
| Author | Gabriel A. Hernandez |
| Author | A. Thomas McRae |
| Author | Beth T. Davidson |
| Author | Kirkwood Adams |
| Author | Mark Aaron |
| Author | Luke Cunningham |
| Author | Cathy A. Jenkins |
| Author | Christopher J. Lindsell |
| Author | Frank E. Harrell |
| Author | Christina Kampe |
| Author | Karen F. Miller |
| Author | William B. Stubblefield |
| Author | JoAnn Lindenfeld |
| Date | 04/2024 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://linkinghub.elsevier.com/retrieve/pii/S0735109724003760 |
| Accessed | 12/28/2025, 9:40:29 AM |
| Volume | 83 |
| Pages | 1295-1306 |
| Publication | Journal of the American College of Cardiology |
| DOI | 10.1016/j.jacc.2024.02.009 |
| Issue | 14 |
| Journal Abbr | Journal of the American College of Cardiology |
| ISSN | 07351097 |
| Date Added | 12/28/2025, 9:40:29 AM |
| Modified | 12/28/2025, 9:40:29 AM |
| Item Type | Journal Article |
|---|---|
| Author | Peter C. Austin |
| Author | Frank E. Harrell |
| Author | Douglas S. Lee |
| Author | Ewout W. Steyerberg |
| Abstract | Abstract Machine learning is increasingly being used to predict clinical outcomes. Most comparisons of different methods have been based on empirical analyses in specific datasets. We used Monte Carlo simulations to determine when machine learning methods perform better than statistical learning methods in a specific setting. We evaluated six learning methods: stochastic gradient boosting machines using trees as the base learners, random forests, artificial neural networks, the lasso, ridge regression, and linear regression estimated using ordinary least squares (OLS). Our simulations were informed by empirical analyses in patients with acute myocardial infarction (AMI) and congestive heart failure (CHF) and used six data-generating processes, each based on one of the six learning methods, to simulate continuous outcomes in the derivation and validation samples. The outcome was systolic blood pressure at hospital discharge, a continuous outcome. We applied the six learning methods in each of the simulated derivation samples and evaluated performance in the simulated validation samples. The primary observation was that neural networks tended to result in estimates with worse predictive accuracy than the other five methods in both disease samples and across all six data-generating processes. Boosted trees and OLS regression tended to perform well across a range of scenarios. |
| Date | 2022-06-03 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://www.nature.com/articles/s41598-022-13015-5 |
| Accessed | 12/28/2025, 10:07:38 AM |
| Volume | 12 |
| Pages | 9312 |
| Publication | Scientific Reports |
| DOI | 10.1038/s41598-022-13015-5 |
| Issue | 1 |
| Journal Abbr | Sci Rep |
| ISSN | 2045-2322 |
| Date Added | 12/28/2025, 10:07:38 AM |
| Modified | 12/28/2025, 10:07:38 AM |
| Item Type | Journal Article |
|---|---|
| Author | Brian R. Lindman |
| Author | Devraj Sukul |
| Author | Marc R. Dweck |
| Author | Mahesh V. Madhavan |
| Author | Benoit J. Arsenault |
| Author | Megan Coylewright |
| Author | W. David Merryman |
| Author | David E. Newby |
| Author | John Lewis |
| Author | Frank E. Harrell |
| Author | Michael J. Mack |
| Author | Martin B. Leon |
| Author | Catherine M. Otto |
| Author | Philippe Pibarot |
| Date | 12/2021 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://linkinghub.elsevier.com/retrieve/pii/S0735109721077445 |
| Accessed | 12/28/2025, 10:00:13 AM |
| Volume | 78 |
| Pages | 2354-2376 |
| Publication | Journal of the American College of Cardiology |
| DOI | 10.1016/j.jacc.2021.09.1367 |
| Issue | 23 |
| Journal Abbr | Journal of the American College of Cardiology |
| ISSN | 07351097 |
| Date Added | 12/28/2025, 10:00:13 AM |
| Modified | 12/28/2025, 10:00:13 AM |
| Item Type | Journal Article |
|---|---|
| Author | Marco Caccamo |
| Author | Frank E. Harrell |
| Author | Anna R. Hemnes |
| Abstract | Abstract Selection of endpoints for clinical trials in pulmonary arterial hypertension (PAH) is challenging because of the small numbers of patients and the changing expectations of patients, clinicians, and regulators in this evolving therapy area. The most commonly used primary endpoint in PAH trials has been 6‐min walk distance (6MWD), leading to the approval of several targeted therapies. However, single surrogate endpoints such as 6MWD or hemodynamic parameters may not correlate with clinical outcomes. Composite endpoints of clinical worsening have been developed to reflect patients' overall condition more accurately, although there is no standard definition of worsening. Recently there has been a shift to composite endpoints assessing clinical improvement, and risk scores developed from registry data are increasingly being used. Biomarkers are another area of interest, although brain natriuretic peptide and its N ‐terminal prohormone are the only markers used for risk assessment or as endpoints in PAH. A range of other genetic, metabolic, and immunologic markers is currently under investigation, along with conventional and novel imaging modalities. Patient‐reported outcomes are an increasingly important part of evaluating new therapies, and several PAH‐specific tools are now available. In the future, alternative statistical techniques and trial designs, such as patient enrichment strategies, will play a role in evaluating PAH‐targeted therapies. In addition, modern sequencing techniques, imaging analyses, and high‐dimensional statistical modeling/machine learning may reveal novel markers that can play a role in the diagnosis and monitoring of PAH. |
| Date | 07/2023 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://onlinelibrary.wiley.com/doi/10.1002/pul2.12271 |
| Accessed | 12/28/2025, 10:12:00 AM |
| Volume | 13 |
| Pages | e12271 |
| Publication | Pulmonary Circulation |
| DOI | 10.1002/pul2.12271 |
| Issue | 3 |
| Journal Abbr | Pulm. circ. |
| ISSN | 2045-8940, 2045-8940 |
| Date Added | 12/28/2025, 10:12:00 AM |
| Modified | 12/28/2025, 10:12:00 AM |
| Item Type | Journal Article |
|---|---|
| Author | Alex Carriero |
| Author | Anne De Hond |
| Author | Bram Cappers |
| Author | Fernando Paulovich |
| Author | Sanne Abeln |
| Author | Karel Gm Moons |
| Author | Maarten Van Smeden |
| Date | 2025-12-05 |
| Language | en |
| Short Title | Explainable AI in healthcare |
| Library Catalog | DOI.org (Crossref) |
| URL | https://diagnprognres.biomedcentral.com/articles/10.1186/s41512-025-00213-8 |
| Accessed | 12/5/2025, 7:59:48 AM |
| Volume | 9 |
| Pages | 29 |
| Publication | Diagnostic and Prognostic Research |
| DOI | 10.1186/s41512-025-00213-8 |
| Issue | 1 |
| Journal Abbr | Diagn Progn Res |
| ISSN | 2397-7523 |
| Date Added | 12/5/2025, 7:59:48 AM |
| Modified | 12/5/2025, 8:00:45 AM |
Figure 1 is a nice summary of colliders, confounders, etc.
| Item Type | Journal Article |
|---|---|
| Author | Megan M. Shuey |
| Author | Shi Huang |
| Author | Rebecca T. Levinson |
| Author | Eric Farber‐Eger |
| Author | Katherine N. Cahill |
| Author | Joshua A. Beckman |
| Author | John R. Koethe |
| Author | Heidi J. Silver |
| Author | Kevin D. Niswender |
| Author | Nancy J. Cox |
| Author | Frank E. Harrell |
| Author | Quinn S. Wells |
| Abstract | Abstract Objective Body mass index (BMI) is the most commonly used predictor of weight‐related comorbidities and outcomes. However, the presumed relationship between height and weight intrinsic to BMI may introduce bias with respect to prediction of clinical outcomes. A series of analyses comparing the performance of models representing weight and height as separate interacting variables to models using BMI were performed using Vanderbilt University Medical Center's deidentified electronic health records and landmark methodology. Methods Use of BMI or height‐weight interaction in prediction models for established weight‐related cardiometabolic traits and metabolic syndrome was evaluated. Specifically, prediction models for hypertension, diabetes mellitus, low high‐density lipoprotein, and elevated triglycerides, atrial fibrillation, coronary artery disease, heart failure, and peripheral artery disease were developed. Model performance was evaluated using likelihood ratio, R 2 , and Somers' Dxy rank correlation. Differences in model predictions were visualized using heat maps. Results Compared to BMI, the maximally flexible height‐weight interaction model demonstrated improved prediction, higher likelihood ratio, R 2 , and Somers' Dxy rank correlation, for event‐free probability for all outcomes. The degree of improvement to the prediction model differed based on the outcome and across the height and weight range. Conclusions Because alternative measures of body composition such as waist‐to‐hip ratio are not routinely collected in the clinic clinical risk models quantifying risk based on height and weight measurements alone are essential to improve practice. Compared to BMI, modeling height and weight as independent, interacting variables results in less bias and improved predictive accuracy for all tested traits. Considering an individual's height and weight opposed to BMI is a better method for quantifying individual disease risk. |
| Date | 02/2022 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://onlinelibrary.wiley.com/doi/10.1002/osp4.543 |
| Accessed | 12/28/2025, 10:01:37 AM |
| Volume | 8 |
| Pages | 124-130 |
| Publication | Obesity Science & Practice |
| DOI | 10.1002/osp4.543 |
| Issue | 1 |
| Journal Abbr | Obesity Science & Practice |
| ISSN | 2055-2238, 2055-2238 |
| Date Added | 12/28/2025, 10:01:37 AM |
| Modified | 12/28/2025, 10:02:26 AM |
| Item Type | Journal Article |
|---|---|
| Author | Michael J. Foley |
| Author | Christopher A. Rajkumar |
| Author | Fiyyaz Ahmed-Jushuf |
| Author | Florentina Simader |
| Author | Shayna Chotai |
| Author | Henry Seligman |
| Author | Krzysztof Macierzanka |
| Author | John R. Davies |
| Author | Thomas R. Keeble |
| Author | Peter O’Kane |
| Author | Peter Haworth |
| Author | Helen Routledge |
| Author | Tushar Kotecha |
| Author | Gerald Clesham |
| Author | Rupert Williams |
| Author | Jehangir Din |
| Author | Sukhjinder S. Nijjer |
| Author | Nick Curzen |
| Author | Manas Sinha |
| Author | Ricardo Petraco |
| Author | James Spratt |
| Author | Sayan Sen |
| Author | Graham D. Cole |
| Author | Frank E. Harrell |
| Author | James P. Howard |
| Author | Darrel P. Francis |
| Author | Matthew J. Shun-Shin |
| Author | Rasha Al-Lamee |
| Author | Christopher Rajkumar |
| Author | Michael Foley |
| Author | Fiyyaz Ahmed-Jushuf |
| Author | Florentina Simader |
| Author | Sashiananthan Ganesananthan |
| Author | Danqi Wang |
| Author | Muhammad Mohsin |
| Author | Rachel Pathimagaraj |
| Author | Brian Wang |
| Author | Krzysztof Macierzanka |
| Author | Ricardo Petraco |
| Author | Ramzi Khamis |
| Author | Graham Cole |
| Author | James Howard |
| Author | Jamil Mayet |
| Author | Darrel Francis |
| Author | Matthew Shun-Shin |
| Author | Rasha Al-Lamee |
| Author | Arif Kokhar |
| Author | Aisha Gohar |
| Author | Ioannis Lampadakis |
| Author | Henry Seligman |
| Author | Sukhjinder Njjer |
| Author | Sayan Sen |
| Author | Punit Ramrakha |
| Author | Raffi Kaprielian |
| Author | Iqbal Malik |
| Author | Masood Khan |
| Author | Amarjit Sethi |
| Author | Rodney Foale |
| Author | Thomas Keeble |
| Author | Kare Tang |
| Author | John Davies |
| Author | Reto Gamma |
| Author | Gerald Clesham |
| Author | Jason Dungu |
| Author | Alamgir Kabir |
| Author | Shah Mohd Nazri |
| Author | Peter O’Kane |
| Author | Jonathan Hinton |
| Author | Jehangir Din |
| Author | Alexandra Nowbar |
| Author | Tushar Kotecha |
| Author | Peter Haworth |
| Author | James Spratt |
| Author | Rupert Williams |
| Author | Claudia Cosgrove |
| Author | Pitt Lim |
| Author | Helen Routledge |
| Author | Lal Mughal |
| Author | Jasper Trevelyan |
| Author | Manas Sinha |
| Author | Nick Curzen |
| Author | James Wilkinson |
| Author | Rohit Sirohi |
| Author | Alison Calver |
| Author | John Rawlins |
| Author | Richard Jabbour |
| Author | Neil Ruparelia |
| Author | Joban Sehmi |
| Author | Tim Kinnaird |
| Author | Fairoz Abdul |
| Author | Vasileios Panoulas |
| Author | Afzal Sohaib |
| Author | David Collier |
| Author | Frank E. Harrell |
| Abstract | BACKGROUND: ORBITA-2 (the Placebo-Controlled Trial of Percutaneous Coronary Intervention for the Relief of Stable Angina) provided evidence for the role of percutaneous coronary intervention (PCI) for angina relief in stable coronary artery disease. Fractional flow reserve (FFR) and instantaneous wave-free ratio (iFR) are often used to guide PCI; however, their ability to predict placebo-controlled angina improvement is unknown. METHODS: Participants with angina, ischemia, and stable coronary artery disease were enrolled, and anti-anginal medications were stopped. Participants reported angina episodes daily for 2 weeks using the ORBITA smartphone symptom application (ORBITA-app). At the research angiogram, FFR and iFR were measured. After sedation and auditory isolation, participants were randomized to PCI or placebo before entering a 12-week blinded follow-up phase with daily angina reporting. The ability of FFR and iFR, analyzed as continuous variables, to predict the placebo-controlled effect of PCI was tested using Bayesian proportional odds modeling. RESULTS: Invasive physiology data were available for 279 patients (140 PCI and 139 placebo). The median (interquartile range) age was 65 years (59.0–70.5), and 223 (79.9%) were male. Median FFR was 0.60 (0.46–0.73), and median iFR was 0.76 (0.50–0.86). The lower the FFR or iFR, the greater the placebo-controlled improvement with PCI across all end points. There was strong evidence that a patient with an FFR at the lower quartile would have a greater placebo-controlled improvement in angina symptom score with PCI than a patient at the upper quartile (FFR, 0.46 versus 0.73: odds ratio, 2.01; 95% credible interval, 1.79–2.26; probability of interaction, >99.9%). Similarly, there was strong evidence that a patient with an iFR at the lower quartile would have greater placebo-controlled improvement in angina symptom score with PCI than a patient with an iFR at the upper quartile (iFR, 0.50 versus 0.86: odds ratio, 2.13; 95% credible interval, 1.87–2.45; probability of interaction, >99.9%). The relationship between benefit and physiology was seen in both Rose angina and Rose nonangina. CONCLUSIONS: Physiological stenosis severity, as measured by FFR and iFR, predicts placebo-controlled angina relief from PCI. Invasive coronary physiology can be used to target PCI to those patients who are most likely to experience benefit. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT03742050. |
| Date | 2025-01-21 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://www.ahajournals.org/doi/10.1161/CIRCULATIONAHA.124.072281 |
| Accessed | 12/28/2025, 10:30:42 AM |
| Volume | 151 |
| Pages | 202-214 |
| Publication | Circulation |
| DOI | 10.1161/CIRCULATIONAHA.124.072281 |
| Issue | 3 |
| Journal Abbr | Circulation |
| ISSN | 0009-7322, 1524-4539 |
| Date Added | 12/28/2025, 10:30:42 AM |
| Modified | 12/28/2025, 10:30:42 AM |
| Item Type | Journal Article |
|---|---|
| Author | David J. Maron |
| Author | Jonathan D. Newman |
| Author | Rebecca Anthopolos |
| Author | Ying Lu |
| Author | Susanna Stevens |
| Author | William E. Boden |
| Author | Kreton Mavromatis |
| Author | Jason Linefsky |
| Author | Rajesh G. Nair |
| Author | Olga Bockeria |
| Author | Gilbert Gosselin |
| Author | Gian P. Perna |
| Author | Elena Demchenko |
| Author | David Foo |
| Author | Michael D. Shapiro |
| Author | Mary Ann Champagne |
| Author | Christie Ballantyne |
| Author | Peter McCullough |
| Author | Jose Luis Lopez-Sendon |
| Author | Frank Rockhold |
| Author | Frank Harrell |
| Author | Yves Rosenberg |
| Author | Gregg W. Stone |
| Author | Sripal Bangalore |
| Author | Harmony R. Reynolds |
| Author | John A. Spertus |
| Author | Judith S. Hochman |
| Date | 04/2025 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://linkinghub.elsevier.com/retrieve/pii/S0735109725003213 |
| Accessed | 12/28/2025, 10:44:24 AM |
| Volume | 85 |
| Pages | 1317-1331 |
| Publication | Journal of the American College of Cardiology |
| DOI | 10.1016/j.jacc.2025.01.028 |
| Issue | 12 |
| Journal Abbr | Journal of the American College of Cardiology |
| ISSN | 07351097 |
| Date Added | 12/28/2025, 10:44:24 AM |
| Modified | 12/28/2025, 10:44:24 AM |
| Item Type | Journal Article |
|---|---|
| Author | Giovanni Davogustto |
| Author | Quinn S. Wells |
| Author | Frank E. Harrell |
| Author | Stephen J. Greene |
| Author | Dan M. Roden |
| Author | Lynne W. Stevenson |
| Date | 05/2024 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://linkinghub.elsevier.com/retrieve/pii/S2213177924001616 |
| Accessed | 12/28/2025, 10:17:42 AM |
| Volume | 12 |
| Pages | 864-875 |
| Publication | JACC: Heart Failure |
| DOI | 10.1016/j.jchf.2024.02.003 |
| Issue | 5 |
| Journal Abbr | JACC: Heart Failure |
| ISSN | 22131779 |
| Date Added | 12/28/2025, 10:17:42 AM |
| Modified | 12/28/2025, 10:17:42 AM |
| Item Type | Journal Article |
|---|---|
| Author | Melissa H. Bloodworth |
| Author | Patrick J. Staso |
| Author | Shi Huang |
| Author | Eric Farber-Eger |
| Author | Kevin D. Niswender |
| Author | Frank E. Harrell |
| Author | Quinn S. Wells |
| Author | Leonard B. Bacharier |
| Author | Megan M. Shuey |
| Author | Katherine N. Cahill |
| Date | 12/2024 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://linkinghub.elsevier.com/retrieve/pii/S1081120624015096 |
| Accessed | 12/28/2025, 10:26:16 AM |
| Volume | 133 |
| Pages | 660-666.e5 |
| Publication | Annals of Allergy, Asthma & Immunology |
| DOI | 10.1016/j.anai.2024.09.005 |
| Issue | 6 |
| Journal Abbr | Annals of Allergy, Asthma & Immunology |
| ISSN | 10811206 |
| Date Added | 12/28/2025, 10:26:16 AM |
| Modified | 12/28/2025, 10:26:16 AM |
| Item Type | Journal Article |
|---|---|
| Author | Ken Monahan |
| Author | Edward Gould |
| Author | Todd Rice |
| Author | Patty Wright |
| Author | Eduard Vasilevskis |
| Author | Frank Harrell |
| Author | Monique Drago |
| Author | Sarah Mitchell |
| Abstract | Background Many academic medical centers transitioned from in-person to remote conferences due to the COVID-19 pandemic, but the impact on faculty attendance is unknown. Objective This study aims to evaluate changes in attendance at medical grand rounds (MGR) following the transition from an in-person to remote format and as a function of the COVID-19 census at Vanderbilt Medical Center. Methods We obtained the faculty attendee characteristics from Department of Medicine records. Attendance was recorded using a SMS text message–based system. The daily COVID-19 census was recorded independently by hospital administration. The main attendance metric was the proportion of eligible faculty that attended each MGR. Comparisons were made for the entire cohort and for individual faculty. Results The observation period was from March 2019 to June 2021 and included 101 MGR conferences with more than 600 eligible faculty. Overall attendance was unchanged during the in-person and remote formats (12,536/25,808, 48.6% vs 16,727/32,680, 51.2%; P=.44) and did not change significantly during a surge in the COVID-19 census. Individual faculty members attendance rates varied widely. Absolute differences between formats were less than –20% or greater than 20% for one-third (160/476, 33.6%) of faculty. Pulmonary or critical care faculty attendance increased during the remote format compared to in person (1450/2616, 55.4% vs 1004/2045, 49.1%; P<.001). A cloud-based digital archive of MGR lectures was accessed by <1% of faculty per conference. Conclusions Overall faculty attendance at MGR did not change following the transition to a remote format, regardless of the COVID-19 census, but individual attendance habits fluctuated in a bidirectional manner. Incentivizing the use of a digital archive may represent an opportunity to increase faculty consumption of MGR. |
| Date | 2024-1-3 |
| Language | en |
| Short Title | Impact of the COVID-19 Pandemic on Medical Grand Rounds Attendance |
| Library Catalog | DOI.org (Crossref) |
| URL | https://mededu.jmir.org/2024/1/e43705 |
| Accessed | 12/28/2025, 10:13:48 AM |
| Volume | 10 |
| Pages | e43705 |
| Publication | JMIR Medical Education |
| DOI | 10.2196/43705 |
| Journal Abbr | JMIR Med Educ |
| ISSN | 2369-3762 |
| Date Added | 12/28/2025, 10:13:48 AM |
| Modified | 12/28/2025, 10:13:48 AM |
| Item Type | Journal Article |
|---|---|
| Author | Benjamin C. Park |
| Author | Alexandra L. Alving-Trinh |
| Author | Heather L. Prigmore |
| Author | Frank E. Harrell |
| Author | Karim Sarhane |
| Author | Jeremy T. Joseph |
| Author | Harrison Thomas |
| Author | Alexander L. Lupi |
| Author | Galen Perdikis |
| Author | Kent K. Higdon |
| Abstract | Background: With ongoing investigations of the impact of device texturing on breast implant–associated anaplastic large-cell lymphoma (BIA-ALCL), studies have begun comparing complication profiles of tissue expanders. However, there is a paucity of timing and severity data of complications. The aim of this study was to provide a comparative survival analysis of postoperative complications between smooth (STEs) and textured tissue expanders (TTEs) in breast reconstruction. Methods: A single-institution experience with tissue expander breast reconstruction was reviewed for complications up to 1 year after second-stage reconstruction from 2014 to 2020. Demographics, comorbidities, operation-related variables, and complications were evaluated. Kaplan-Meier curves, Cox proportional hazard models, and a consensus-based ordinal logistic regression model were used to compare complication profiles. Results: Of 919 total patients, 600 (65.3%) received TTEs and 319 (34.7%) received STEs. There was increased risk of infection ( P < 0.0001), seroma ( P = 0.046), expander malposition ( P < 0.0001), and wound dehiscence ( P = 0.019) in STEs compared with TTEs. However, there was also a decreased risk of capsular contracture ( P = 0.005) in STEs compared with TTEs. Failure of breast reconstruction ( P < 0.001) and wound dehiscence ( P = 0.018) occurred significantly earlier in STEs compared with TTEs. Predictors for significantly higher severity complications included the following: smooth tissue expander use ( P = 0.007), shorter time to complication ( P < 0.0001), higher body mass index ( P = 0.005), smoking history ( P = 0.025), and nipple-sparing mastectomy ( P = 0.012). Conclusions: Differences in the timing and severity of complications contribute to the safety profiles of tissue expanders. STEs are associated with increased odds of higher severity and earlier complications. Therefore, tissue expander selection may depend on underlying risk factors and severity predictors. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, III. |
| Date | 06/2024 |
| Language | en |
| Short Title | Impact of Tissue Expander Surface Texture on Two-Stage Breast Reconstruction Outcomes |
| Library Catalog | DOI.org (Crossref) |
| URL | https://journals.lww.com/10.1097/PRS.0000000000010763 |
| Accessed | 12/28/2025, 10:18:24 AM |
| Volume | 153 |
| Pages | 1053e-1062e |
| Publication | Plastic & Reconstructive Surgery |
| DOI | 10.1097/PRS.0000000000010763 |
| Issue | 6 |
| ISSN | 0032-1052 |
| Date Added | 12/28/2025, 10:18:24 AM |
| Modified | 12/28/2025, 10:18:24 AM |
| Item Type | Journal Article |
|---|---|
| Author | Fiyyaz Ahmed-Jushuf |
| Author | Michael J. Foley |
| Author | Christopher A. Rajkumar |
| Author | Shayna Chotai |
| Author | Florentina A. Simader |
| Author | Danqi Wang |
| Author | Krzysztof Macierzanka |
| Author | Joban Sehmi |
| Author | Gajen Kanaganayagam |
| Author | Guy Lloyd |
| Author | Niall Keenan |
| Author | Nina Bual |
| Author | John R. Davies |
| Author | Thomas R. Keeble |
| Author | Peter D. O’Kane |
| Author | Peter Haworth |
| Author | Helen Routledge |
| Author | Tushar Kotecha |
| Author | Rupert Williams |
| Author | Jehangir Din |
| Author | Sukhjinder S. Nijjer |
| Author | Nick Curzen |
| Author | Manas Sinha |
| Author | Neil Ruparelia |
| Author | Reto Gamma |
| Author | James C. Spratt |
| Author | Graham D. Cole |
| Author | Frank E. Harrell |
| Author | James P. Howard |
| Author | Darrel P. Francis |
| Author | Matthew J. Shun-Shin |
| Author | Rasha K. Al-Lamee |
| Author | Christopher Rajkumar |
| Author | Michael Foley |
| Author | Fiyyaz Ahmed-Jushuf |
| Author | Florentina Simader |
| Author | Sashiananthan Ganesananthan |
| Author | Danqi Wang |
| Author | Muhammad Mohsin |
| Author | Rachel Pathimagaraj |
| Author | Brian Wang |
| Author | Krzysztof Macierzanka |
| Author | Ricardo Petraco |
| Author | Ramzi Khamis |
| Author | Graham Cole |
| Author | James Howard |
| Author | Jamil Mayet |
| Author | Darrel Francis |
| Author | Matthew Shun-Shin |
| Author | Rasha Al-Lamee |
| Author | Arif Kokhar |
| Author | Aisha Gohar |
| Author | Ioannis Lampadakis |
| Author | Henry Seligman |
| Author | Sukhjinder Njjer |
| Author | Sayan Sen |
| Author | Punit Ramrakha |
| Author | Raffi Kaprielian |
| Author | Iqbal Malik |
| Author | Masood Khan |
| Author | Amarjit Sethi |
| Author | Rodney Foale |
| Author | Thomas Keeble |
| Author | Kare Tang |
| Author | John Davies |
| Author | Reto Gamma |
| Author | Gerald Clesham |
| Author | Jason Dungu |
| Author | Alamgir Kabir |
| Author | Shah Mohd Nazri |
| Author | Peter O’Kane |
| Author | Jonathan Hinton |
| Author | Jehangir Din |
| Author | Alexandra Nowbar |
| Author | Tushar Kotecha |
| Author | Peter Haworth |
| Author | James Spratt |
| Author | Rupert Williams |
| Author | Claudia Cosgrove |
| Author | Pitt Lim |
| Author | Helen Routledge |
| Author | Lal Mughal |
| Author | Jasper Trevelyan |
| Author | Manas Sinha |
| Author | Nick Curzen |
| Author | James Wilkinson |
| Author | Rohit Sirohi |
| Author | Alison Calver |
| Author | John Rawlins |
| Author | Richard Jabbour |
| Author | Neil Ruparelia |
| Author | Joban Sehmi |
| Author | Tim Kinnaird |
| Author | Fairoz Abdul |
| Author | Vasileios Panoulas |
| Author | Afzal Sohaib |
| Author | David Collier |
| Author | Frank E. Harrell |
| Date | 05/2025 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://linkinghub.elsevier.com/retrieve/pii/S0735109725053008 |
| Accessed | 12/28/2025, 10:45:01 AM |
| Volume | 85 |
| Pages | 1740-1753 |
| Publication | Journal of the American College of Cardiology |
| DOI | 10.1016/j.jacc.2025.02.034 |
| Issue | 18 |
| Journal Abbr | Journal of the American College of Cardiology |
| ISSN | 07351097 |
| Date Added | 12/28/2025, 10:45:01 AM |
| Modified | 12/28/2025, 10:45:01 AM |
| Item Type | Journal Article |
|---|---|
| Author | Md. Belal Hossain |
| Author | Mohsen Sadatsafavi |
| Author | James C. Johnston |
| Author | Hubert Wong |
| Author | Victoria J. Cook |
| Author | Mohammad Ehsanul Karim |
| Date | 2025-08-04 |
| Language | en |
| Short Title | LASSO-Based Survival Prediction Modeling with Multiply Imputed Data |
| Library Catalog | DOI.org (Crossref) |
| URL | https://www.tandfonline.com/doi/full/10.1080/00031305.2025.2526545 |
| Accessed | 8/10/2025, 4:29:44 PM |
| Pages | 1-12 |
| Publication | The American Statistician |
| DOI | 10.1080/00031305.2025.2526545 |
| Journal Abbr | The American Statistician |
| ISSN | 0003-1305, 1537-2731 |
| Date Added | 8/10/2025, 4:29:44 PM |
| Modified | 8/10/2025, 4:30:16 PM |
| Item Type | Journal Article |
|---|---|
| Author | Christopher J. Lindsell |
| Author | Cheryl L. Gatto |
| Author | Mary Lynn Dear |
| Author | Reagan Buie |
| Author | Todd W. Rice |
| Author | Jill M. Pulley |
| Author | Tina V. Hartert |
| Author | Sunil Kripalani |
| Author | Frank E. Harrell |
| Author | Daniel W. Byrne |
| Author | Mitchell C. Edgeworth |
| Author | Robin Steaban |
| Author | Robert S. Dittus |
| Author | Gordon R. Bernard |
| Abstract | Different models of learning health systems are emerging. At Vanderbilt University Medical Center, the Learning Health Care System (LHS) Platform was established with the goal of creating generalizable knowledge. This differentiates the LHS Platform from other efforts that have adopted a quality improvement paradigm. By supporting pragmatic trials at the intersection of research, operations, and clinical care, the LHS Platform was designed to yield evidence for advancing content and processes of care through carefully designed, rigorous study. The LHS Platform provides the necessary infrastructure and governance to leverage translational, transdisciplinary team science to inform clinical and operational decision making across the health system. The process transforms a clinical or operational question into a research question amenable to a pragmatic trial. Scientific, technical, procedural, and human infrastructure is maintained for the design and execution of individual LHS projects. This includes experienced pragmatic trialists, project management, data science inclusive of biostatistics and clinical informatics, and regulatory support. Careful attention is paid to stakeholder engagement, including health care providers and the community. Capturing lessons from each new study, the LHS Platform continues to mature with plans to integrate implementation science and to complement clinical and process outcomes with cost and value considerations. The Vanderbilt University Medical Center LHS Platform is now a pillar of the health care system and leads the evolving culture of learning from what we do and doing what we learn. |
| Date | 09/2021 |
| Language | en |
| Short Title | Learning From What We Do, and Doing What We Learn |
| Library Catalog | DOI.org (Crossref) |
| URL | https://journals.lww.com/10.1097/ACM.0000000000004021 |
| Accessed | 12/28/2025, 9:59:30 AM |
| Volume | 96 |
| Pages | 1291-1299 |
| Publication | Academic Medicine |
| DOI | 10.1097/ACM.0000000000004021 |
| Issue | 9 |
| ISSN | 1040-2446 |
| Date Added | 12/28/2025, 9:59:30 AM |
| Modified | 12/28/2025, 9:59:30 AM |
| Item Type | Journal Article |
|---|---|
| Author | Jonathan S. Schildcrout |
| Author | Frank E. Harrell |
| Author | Patrick J. Heagerty |
| Author | Sebastien Haneuse |
| Author | Chiara Di Gravio |
| Author | Shawn P. Garbett |
| Author | Paul J. Rathouz |
| Author | Bryan E. Shepherd |
| Abstract | Studies of critically ill, hospitalized patients often follow participants and characterize daily health status using an ordinal outcome variable. Statistically, longitudinal proportional odds models are a natural choice in these settings since such models can parsimoniously summarize differences across patient groups and over time. However, when one or more of the outcome states is absorbing, the proportional odds assumption for the follow‐up time parameter will likely be violated, and more flexible longitudinal models are needed. Motivated by the VIOLET Study (Ginde et al), a parallel‐arm, randomized clinical trial of Vitamin in critically ill patients, we discuss and contrast several treatment effect estimands based on time‐dependent odds ratio parameters, and we detail contemporary modeling approaches. In VIOLET, the outcome is a four‐level ordinal variable where the lowest ”not alive” state is absorbing and the highest ”at‐home” state is nearly absorbing. We discuss flexible extensions of the proportional odds model for longitudinal data that can be used for either model‐based inference, where the odds ratio estimator is taken directly from the model fit, or for model‐assisted inferences, where heterogeneity across cumulative log odds dichotomizations is modeled and results are summarized to obtain an overall odds ratio estimator. We focus on direct estimation of cumulative probability model (CPM) parameters using likelihood‐based analysis procedures that naturally handle absorbing states. We illustrate the modeling procedures, the relative precision of model‐based and model‐assisted estimators, and the possible differences in the values for which the estimators are consistent through simulations and analysis of the VIOLET Study data. |
| Date | 2022-06-30 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://onlinelibrary.wiley.com/doi/10.1002/sim.9366 |
| Accessed | 12/28/2025, 10:08:05 AM |
| Volume | 41 |
| Pages | 2497-2512 |
| Publication | Statistics in Medicine |
| DOI | 10.1002/sim.9366 |
| Issue | 14 |
| Journal Abbr | Statistics in Medicine |
| ISSN | 0277-6715, 1097-0258 |
| Date Added | 12/28/2025, 10:08:05 AM |
| Modified | 12/28/2025, 10:08:05 AM |
| Item Type | Journal Article |
|---|---|
| Author | Thomas M. Braun |
| Abstract | Summary In contrast with typical Phase III clinical trials, there is little existing methodology for determining the appropriate numbers of patients to enroll in adaptive Phase I trials. And, as stated by Dennis Lindley in a more general context, “[t]he simple practical question of ‘What size of sample should I take’ is often posed to a statistician, and it is a question that is embarrassingly difficult to answer.” Historically, simulation has been the primary option for determining sample sizes for adaptive Phase I trials, and although useful, can be problematic and time-consuming when a sample size is needed relatively quickly. We propose a computationally fast and simple approach that uses Beta distributions to approximate the posterior distributions of DLT rates of each dose and determines an appropriate sample size through posterior coverage rates. We provide sample sizes produced by our methods for a vast number of realistic Phase I trial settings and demonstrate that our sample sizes are generally larger than those produced by a competing approach that is based upon the nonparametric optimal design. |
| Date | 2018-09-01 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://academic.oup.com/biometrics/article/74/3/1065-1071/7525822 |
| Accessed | 12/11/2025, 4:35:46 PM |
| Rights | https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model |
| Volume | 74 |
| Pages | 1065-1071 |
| Publication | Biometrics |
| DOI | 10.1111/biom.12872 |
| Issue | 3 |
| ISSN | 0006-341X, 1541-0420 |
| Date Added | 12/11/2025, 4:35:46 PM |
| Modified | 12/11/2025, 4:37:26 PM |
| Item Type | Journal Article |
|---|---|
| Author | Christopher A. Rajkumar |
| Author | Michael J. Foley |
| Author | Fiyyaz Ahmed-Jushuf |
| Author | Florentina A. Simader |
| Author | Muhammad Mohsin |
| Author | Sashiananthan Ganesananthan |
| Author | Alexandra N. Nowbar |
| Author | Shayna Chotai |
| Author | Sayan Sen |
| Author | Ricardo Petraco |
| Author | Sukhjinder S. Nijjer |
| Author | Joban Sehmi |
| Author | Neil Ruparelia |
| Author | Jason N. Dungu |
| Author | Alamgir Kabir |
| Author | Kare Tang |
| Author | Reto Gamma |
| Author | John R. Davies |
| Author | Tushar Kotecha |
| Author | Graham D. Cole |
| Author | James P. Howard |
| Author | Thomas R. Keeble |
| Author | Gerald Clesham |
| Author | Peter D. O’Kane |
| Author | Frank E. Harrell |
| Author | Darrel P. Francis |
| Author | Matthew J. Shun-Shin |
| Author | Rasha K. Al-Lamee |
| Date | 07/2024 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://linkinghub.elsevier.com/retrieve/pii/S0735109724068244 |
| Accessed | 12/28/2025, 10:22:01 AM |
| Volume | 84 |
| Pages | 1-12 |
| Publication | Journal of the American College of Cardiology |
| DOI | 10.1016/j.jacc.2024.04.001 |
| Issue | 1 |
| Journal Abbr | Journal of the American College of Cardiology |
| ISSN | 07351097 |
| Date Added | 12/28/2025, 10:22:01 AM |
| Modified | 12/28/2025, 10:22:01 AM |
| Item Type | Journal Article |
|---|---|
| Author | Eva A. Mistry |
| Author | Sharon D. Yeatts |
| Author | Pooja Khatri |
| Author | Akshitkumar M. Mistry |
| Author | Michelle Detry |
| Author | Kert Viele |
| Author | Frank E. Harrell |
| Author | Roger J. Lewis |
| Abstract | National Institutes of Health Stroke Scale (NIHSS), measured a few hours to days after stroke onset, is an attractive outcome measure for stroke research. NIHSS at the time of presentation (baseline NIHSS) strongly predicts the follow-up NIHSS. Because of the need to account for the baseline NIHSS in the analysis of follow-up NIHSS as an outcome measure, a common and intuitive approach is to define study outcome as the change in NIHSS from baseline to follow-up (ΔNIHSS). However, this approach has important limitations. Analyzing ΔNIHSS implies a very strong assumption about the relationship between baseline and follow-up NIHSS that is unlikely to be satisfied, drawing into question the validity of the resulting statistical analysis. This reduces the precision of the estimates of treatment effects and the power of clinical trials that use this approach to analysis. ANCOVA allows for the analysis of follow-up NIHSS as the dependent variable while adjusting for baseline NIHSS as a covariate in the model and addresses several challenges of using ΔNIHSS outcome using simple bivariate comparisons (eg, a t test, Wilcoxon rank-sum, linear regression without adjustment for baseline) for stroke research. In this article, we use clinical trial simulations to illustrate that variability in NIHSS outcome is less when follow-up NIHSS is adjusted for baseline compared to ΔNIHSS and how a reduction in this variability improves the power. We outline additional, important clinical and statistical arguments to support the superiority of ANCOVA using the final measurement of the NIHSS adjusted for baseline over, and caution against using, the simple bivariate comparison of absolute NIHSS change (ie, delta). |
| Date | 04/2022 |
| Language | en |
| Short Title | National Institutes of Health Stroke Scale as an Outcome in Stroke Research |
| Library Catalog | DOI.org (Crossref) |
| URL | https://www.ahajournals.org/doi/10.1161/STROKEAHA.121.034859 |
| Accessed | 12/28/2025, 10:03:11 AM |
| Volume | 53 |
| Publication | Stroke |
| DOI | 10.1161/STROKEAHA.121.034859 |
| Issue | 4 |
| Journal Abbr | Stroke |
| ISSN | 0039-2499, 1524-4628 |
| Date Added | 12/28/2025, 10:03:11 AM |
| Modified | 12/28/2025, 10:03:11 AM |
| Item Type | Journal Article |
|---|---|
| Author | Zhou Tang |
| Author | Ted Westling |
| Date | 2025-10-13 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://www.tandfonline.com/doi/full/10.1080/10618600.2025.2547064 |
| Accessed | 10/15/2025, 11:24:15 AM |
| Pages | 1-12 |
| Publication | Journal of Computational and Graphical Statistics |
| DOI | 10.1080/10618600.2025.2547064 |
| Journal Abbr | Journal of Computational and Graphical Statistics |
| ISSN | 1061-8600, 1537-2715 |
| Date Added | 10/15/2025, 11:24:15 AM |
| Modified | 10/15/2025, 11:25:24 AM |
| Item Type | Journal Article |
|---|---|
| Author | Emily Shives |
| Author | Yared Gurmu |
| Author | Wonyul Lee |
| Author | Emily Morris |
| Author | Yan Wang |
| Abstract | ABSTRACT Many rare disease clinical trials are underpowered to detect a moderate treatment effect of an investigational product due to the limited number of participants available for the trials. In addition, given the complex, multisystemic nature of many rare diseases, it is challenging to confidently prespecify a single primary efficacy endpoint that is applicable to all trial participants with a heterogeneous clinical manifestation of their disease. Traditional trial designs and analysis methods often used in more common diseases to analyze the same endpoint(s) for all patients may be inefficient or impractical for a rare disease with heterogeneous clinical manifestations. To address these issues, we propose a novel trial design and analytic approach that allows for an evaluation of stratum‐specific efficacy endpoints in a broader population of participants. We develop several nonparametric global test methods that can accommodate the novel design and provide global evaluation of treatment effects. Using a case example in patients with Fabry disease, our simulation studies illustrate that the novel design evaluated using the global test methods may be more sensitive to detect a treatment effect compared to the traditional design that uses the same endpoint(s) for all patients. |
| Date | 08/2025 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://onlinelibrary.wiley.com/doi/10.1002/sim.70206 |
| Accessed | 8/10/2025, 4:37:45 PM |
| Volume | 44 |
| Pages | e70206 |
| Publication | Statistics in Medicine |
| DOI | 10.1002/sim.70206 |
| Issue | 18-19 |
| Journal Abbr | Statistics in Medicine |
| ISSN | 0277-6715, 1097-0258 |
| Date Added | 8/10/2025, 4:37:45 PM |
| Modified | 8/10/2025, 4:38:13 PM |
| Item Type | Journal Article |
|---|---|
| Author | Matthew Elmo G. Gayoso |
| Author | Giovanni Davogustto |
| Author | Robert L. Abraham |
| Author | George H. Crossley |
| Author | Travis D. Richardson |
| Author | Quinn S. Wells |
| Author | Arvindh N. Kanagasundram |
| Author | Gregory F. Michaud |
| Author | William G. Stevenson |
| Author | Frank E. Harrell |
| Author | Yue Gao |
| Author | Jay A. Montgomery |
| Date | 12/2025 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://linkinghub.elsevier.com/retrieve/pii/S1547527125024294 |
| Accessed | 12/28/2025, 10:48:35 AM |
| Volume | 22 |
| Pages | 3231-3238 |
| Publication | Heart Rhythm |
| DOI | 10.1016/j.hrthm.2025.05.006 |
| Issue | 12 |
| Journal Abbr | Heart Rhythm |
| ISSN | 15475271 |
| Date Added | 12/28/2025, 10:48:35 AM |
| Modified | 12/28/2025, 10:48:35 AM |
| Item Type | Journal Article |
|---|---|
| Author | Neel M. Butala |
| Author | Hector Tamez |
| Author | Eric A. Secemsky |
| Author | J. Aaron Grantham |
| Author | John A. Spertus |
| Author | David J. Cohen |
| Author | Philip Jones |
| Author | Adam C. Salisbury |
| Author | Suzanne V. Arnold |
| Author | Frank Harrell |
| Author | William Lombardi |
| Author | Dimitrios Karmpaliotis |
| Author | Jeffrey Moses |
| Author | James Sapontis |
| Author | Robert W. Yeh |
| Abstract | Background Given that percutaneous coronary intervention (PCI) of a chronic total occlusion (CTO) is indicated primarily for symptom relief, identifying patients most likely to benefit is critically important for patient selection and shared decision‐making. Therefore, we identified factors associated with residual angina frequency after CTO PCI and developed a model to predict postprocedure anginal burden. Methods and Results Among patients in the OPEN‐CTO (Outcomes, Patient Health Status, and Efficiency in Chronic Total Occlusion Hybrid Procedures) registry, we evaluated the association between patient characteristics and residual angina frequency at 6 months, as assessed by the Seattle Angina Questionnaire Angina Frequency Scale. We then constructed a prediction model for angina status after CTO PCI using ordinal regression. Among 901 patients undergoing CTO PCI, 28% had no angina, 31% had monthly angina, 30% had weekly angina, and 12% had daily angina at baseline. Six months later, 53% of patients had a ≥20‐point increase in Seattle Angina Questionnaire Angina Frequency Scale score. The final model to predict residual angina after CTO PCI included baseline angina frequency, baseline nitroglycerin use frequency, dyspnea symptoms, depressive symptoms, number of antianginal medications, PCI indication, and presence of multiple CTO lesions and had a C index of 0.78. Baseline angina frequency and nitroglycerin use frequency explained 71% of the predictive power of the model, and the relationship between model components and angina improvement at 6 months varied by baseline angina status. Conclusions A 7‐component OPEN‐AP (OPEN‐CTO Angina Prediction) score can predict angina improvement and residual angina after CTO PCI using variables commonly available before intervention. These findings have implications for appropriate patient selection and counseling for CTO PCI. |
| Date | 2022-05-17 |
| Language | en |
| Short Title | Predicting Residual Angina After Chronic Total Occlusion Percutaneous Coronary Intervention |
| Library Catalog | DOI.org (Crossref) |
| URL | https://www.ahajournals.org/doi/10.1161/JAHA.121.024056 |
| Accessed | 12/28/2025, 10:05:45 AM |
| Volume | 11 |
| Pages | e024056 |
| Publication | Journal of the American Heart Association |
| DOI | 10.1161/JAHA.121.024056 |
| Issue | 10 |
| Journal Abbr | JAHA |
| ISSN | 2047-9980 |
| Date Added | 12/28/2025, 10:05:45 AM |
| Modified | 12/28/2025, 10:05:45 AM |
| Item Type | Journal Article |
|---|---|
| Author | Peter C Austin |
| Author | Frank E Harrell |
| Author | Ewout W Steyerberg |
| Abstract | Machine learning approaches are increasingly suggested as tools to improve prediction of clinical outcomes. We aimed to identify when machine learning methods perform better than a classical learning method. We hereto examined the impact of the data-generating process on the relative predictive accuracy of six machine and statistical learning methods: bagged classification trees, stochastic gradient boosting machines using trees as the base learners, random forests, the lasso, ridge regression, and unpenalized logistic regression. We performed simulations in two large cardiovascular datasets which each comprised an independent derivation and validation sample collected from temporally distinct periods: patients hospitalized with acute myocardial infarction (AMI, n = 9484 vs. n = 7000) and patients hospitalized with congestive heart failure (CHF, n = 8240 vs. n = 7608). We used six data-generating processes based on each of the six learning methods to simulate outcomes in the derivation and validation samples based on 33 and 28 predictors in the AMI and CHF data sets, respectively. We applied six prediction methods in each of the simulated derivation samples and evaluated performance in the simulated validation samples according to c-statistic, generalized R 2 , Brier score, and calibration. While no method had uniformly superior performance across all six data-generating process and eight performance metrics, (un)penalized logistic regression and boosted trees tended to have superior performance to the other methods across a range of data-generating processes and performance metrics. This study confirms that classical statistical learning methods perform well in low-dimensional settings with large data sets. |
| Date | 06/2021 |
| Language | en |
| Short Title | Predictive performance of machine and statistical learning methods |
| Library Catalog | DOI.org (Crossref) |
| URL | https://journals.sagepub.com/doi/10.1177/09622802211002867 |
| Accessed | 12/28/2025, 9:58:39 AM |
| Volume | 30 |
| Pages | 1465-1483 |
| Publication | Statistical Methods in Medical Research |
| DOI | 10.1177/09622802211002867 |
| Issue | 6 |
| Journal Abbr | Stat Methods Med Res |
| ISSN | 0962-2802, 1477-0334 |
| Date Added | 12/28/2025, 9:58:39 AM |
| Modified | 12/28/2025, 9:58:39 AM |
| Item Type | Journal Article |
|---|---|
| Author | Georg Heinze |
| Author | Mark Baillie |
| Author | Lara Lusa |
| Author | Willi Sauerbrei |
| Author | Carsten Oliver Schmidt |
| Author | Frank E. Harrell |
| Author | Marianne Huebner |
| Author | on behalf of TG2 and TG3 of the STRATOS initiative |
| Abstract | Abstract Statistical regression models are used for predicting outcomes based on the values of some predictor variables or for describing the association of an outcome with predictors. With a data set at hand, a regression model can be easily fit with standard software packages. This bears the risk that data analysts may rush to perform sophisticated analyses without sufficient knowledge of basic properties, associations in and errors of their data, leading to wrong interpretation and presentation of the modeling results that lacks clarity. Ignorance about special features of the data such as redundancies or particular distributions may even invalidate the chosen analysis strategy. Initial data analysis (IDA) is prerequisite to regression analyses as it provides knowledge about the data needed to confirm the appropriateness of or to refine a chosen model building strategy, to interpret the modeling results correctly, and to guide the presentation of modeling results. In order to facilitate reproducibility, IDA needs to be preplanned, an IDA plan should be included in the general statistical analysis plan of a research project, and results should be well documented. Biased statistical inference of the final regression model can be minimized if IDA abstains from evaluating associations of outcome and predictors, a key principle of IDA. We give advice on which aspects to consider in an IDA plan for data screening in the context of regression modeling to supplement the statistical analysis plan. We illustrate this IDA plan for data screening in an example of a typical diagnostic modeling project and give recommendations for data visualizations. |
| Date | 2024-08-08 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-024-02294-3 |
| Accessed | 12/28/2025, 10:23:48 AM |
| Volume | 24 |
| Pages | 178 |
| Publication | BMC Medical Research Methodology |
| DOI | 10.1186/s12874-024-02294-3 |
| Issue | 1 |
| Journal Abbr | BMC Med Res Methodol |
| ISSN | 1471-2288 |
| Date Added | 12/28/2025, 10:23:48 AM |
| Modified | 12/28/2025, 10:23:48 AM |
| Item Type | Journal Article |
|---|---|
| Author | Michael W Robbins |
| Author | Lane Burgette |
| Abstract | Abstract Resampling techniques have become increasingly popular for estimation of uncertainty. However, data are often fraught with missing values that are commonly imputed to facilitate analysis. This article addresses the issue of using resampling methods such as a jackknife or bootstrap in conjunction with imputations that have been sampled stochastically, in the vein of multiple imputation. We derive the theory needed to illustrate two key points regarding the use of resampling methods in lieu of traditional combining rules. First, imputations should be independently generated multiple times within each replicate group of a jackknife or bootstrap. Second, the number of multiply imputed datasets per replicate group must dramatically exceed the number of replicate groups for a jackknife; however, this is not the case in a bootstrap approach. We also discuss bias-adjusted analogues of the jackknife and bootstrap that are argued to require fewer imputed datasets. A simulation study is provided to support these theoretical conclusions. |
| Date | 2025-07-30 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://academic.oup.com/biomet/advance-article/doi/10.1093/biomet/asaf059/8219454 |
| Accessed | 7/31/2025, 12:14:17 PM |
| Rights | https://creativecommons.org/licenses/by-nc-nd/4.0/ |
| Pages | asaf059 |
| Publication | Biometrika |
| DOI | 10.1093/biomet/asaf059 |
| ISSN | 0006-3444, 1464-3510 |
| Date Added | 7/31/2025, 12:14:17 PM |
| Modified | 7/31/2025, 12:14:46 PM |
| Item Type | Journal Article |
|---|---|
| Author | Jeffrey D. Blume |
| Author | Lucy D’Agostino McGowan |
| Author | William D. Dupont |
| Author | Robert A. Greevy |
| Editor | Neil R. Smalheiser |
| Date | 2018-3-22 |
| Language | en |
| Short Title | Second-generation p-values |
| Library Catalog | DOI.org (Crossref) |
| URL | https://dx.plos.org/10.1371/journal.pone.0188299 |
| Accessed | 9/4/2025, 8:51:13 AM |
| Volume | 13 |
| Pages | e0188299 |
| Publication | PLOS ONE |
| DOI | 10.1371/journal.pone.0188299 |
| Issue | 3 |
| Journal Abbr | PLoS ONE |
| ISSN | 1932-6203 |
| Date Added | 9/4/2025, 8:51:13 AM |
| Modified | 9/4/2025, 8:51:41 AM |
| Item Type | Journal Article |
|---|---|
| Author | Natalie A. Dilts |
| Author | Frank E. Harrell |
| Author | Christopher J. Lindsell |
| Author | Samuel Nwosu |
| Author | Thomas G. Stewart |
| Author | Matthew S. Shotwell |
| Author | Jill M. Pulley |
| Author | Terri L. Edwards |
| Author | Emily Sheffer Serdoz |
| Author | Katelyn Benhoff |
| Author | Gordon R. Bernard |
| Abstract | Abstract Introduction: As clinical trials were rapidly initiated in response to the COVID-19 pandemic, Data and Safety Monitoring Boards (DSMBs) faced unique challenges overseeing trials of therapies never tested in a disease not yet characterized. Traditionally, individual DSMBs do not interact or have the benefit of seeing data from other accruing trials for an aggregated analysis to meaningfully interpret safety signals of similar therapeutics. In response, we developed a compliant DSMB Coordination (DSMBc) framework to allow the DSMB from one study investigating the use of SARS-CoV-2 convalescent plasma to treat COVID-19 to review data from similar ongoing studies for the purpose of safety monitoring. Methods: The DSMBc process included engagement of DSMB chairs and board members, execution of contractual agreements, secure data acquisition, generation of harmonized reports utilizing statistical graphics, and secure report sharing with DSMB members. Detailed process maps, a secure portal for managing DSMB reports, and templates for data sharing and confidentiality agreements were developed. Results: Four trials participated. Data from one trial were successfully harmonized with that of an ongoing trial. Harmonized reports allowing for visualization and drill down into the data were presented to the ongoing trial’s DSMB. While DSMB deliberations are confidential, the Chair confirmed successful review of the harmonized report. Conclusion: It is feasible to coordinate DSMB reviews of multiple independent studies of a similar therapeutic in similar patient cohorts. The materials presented mitigate challenges to DSMBc and will help expand these initiatives so DSMBs may make more informed decisions with all available information. |
| Date | 2022 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://www.cambridge.org/core/product/identifier/S2059866122003879/type/journal_article |
| Accessed | 12/28/2025, 10:03:52 AM |
| Rights | https://creativecommons.org/licenses/by/4.0/ |
| Volume | 6 |
| Pages | e49 |
| Publication | Journal of Clinical and Translational Science |
| DOI | 10.1017/cts.2022.387 |
| Issue | 1 |
| Journal Abbr | J. Clin. Trans. Sci. |
| ISSN | 2059-8661 |
| Date Added | 12/28/2025, 10:03:52 AM |
| Modified | 12/28/2025, 10:03:52 AM |
| Item Type | Journal Article |
|---|---|
| Author | Amelia W Maiga |
| Author | Madison Cook |
| Author | Mina F Nordness |
| Author | Yue Gao |
| Author | Shayan Rakhit |
| Author | Erika L Rivera |
| Author | Frank E Harrell |
| Author | Kenneth W Sharp |
| Author | Mayur B Patel |
| Abstract | BACKGROUND: The Glasgow Outcome Scale Extended (GOSE) is a measure of recovery after traumatic brain injury (TBI). Public surveys rate some GOSE states as worse than death. Direct family experience caring for patients with TBI may impact views of post-TBI disability. STUDY DESIGN: We conducted a national cross-sectional computer-adaptive survey of surrogates of TBI dependents incurring injury more than 1 year earlier. Using a standard gamble approach in randomized order, surrogates evaluated preferences for post-TBI GOSE states from GOSE 2 (bedridden, unaware) to GOSE 8 (good recovery). We calculated median (interquartile range [IQR]) health utilities for each post-TBI state, ranging from −1 to 1, with 0 as reference (death = GOSE 1), and assessed sociodemographic associations using proportional odds logistic regression modeling. RESULTS: Of 515 eligible surrogates, 298 (58%) completed scenarios. Surrogates were median aged 46 (IQR 35 to 60), 54% married, with Santa Clara strength of faith 14 (10 to 18). TBI dependents had a median GOSE5 (3 to 7). Median (IQR) health utility ratings for GOSE 2, GOSE 3, and GOSE 4 were −0.06 (−0.50 to −0.01), −0.01 (−0.30 to 0.45), and 0.30 (−0.01 to 0.80), rated worse than death by 91%, 65%, and 40%, respectively. Surrogates rated GOSE 4 (daily partial help) worse than the general population. Married surrogates rated GOSE 4 higher (p < 0.01). Higher strength of faith was associated with higher utility scores across GOSE states (p = 0.034). CONCLUSIONS: In this index study of surrogate perceptions about disability after TBI, poor neurologic outcomes—vegetative, needing all-day or partial daily assistance—were perceived as worse than death by at least 1 in 3 surrogates. Surrogate perceptions differed from the unexposed public. Long-term perceptions about post-TBI disability may inform earlier, tailored shared decision-making after neurotrauma. |
| Date | 04/2024 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://journals.lww.com/10.1097/XCS.0000000000000960 |
| Accessed | 12/28/2025, 10:15:58 AM |
| Volume | 238 |
| Pages | 589-597 |
| Publication | Journal of the American College of Surgeons |
| DOI | 10.1097/XCS.0000000000000960 |
| Issue | 4 |
| ISSN | 1072-7515 |
| Date Added | 12/28/2025, 10:15:58 AM |
| Modified | 12/28/2025, 10:15:58 AM |
| Item Type | Journal Article |
|---|---|
| Author | Jeffrey A. Freiberg |
| Author | Justin K. Siemann |
| Author | Edward T. Qian |
| Author | Benjamin J. Ereshefsky |
| Author | Cassandra Hennessy |
| Author | Joanna L. Stollings |
| Author | Taylor M. Rali |
| Author | Frank E. Harrell |
| Author | Cheryl L. Gatto |
| Author | Todd W. Rice |
| Author | George E. Nelson |
| Author | for the Vanderbilt Center for Learning Healthcare |
| Abstract | Abstract Background Vancomycin, an antibiotic with activity against methicillin-resistant Staphylococcus aureus (MRSA), is frequently included in empiric treatment for community-acquired pneumonia (CAP) despite the fact that MRSA is rarely implicated in CAP. Conducting polymerase chain reaction (PCR) testing on nasal swabs to identify the presence of MRSA colonization has been proposed as an antimicrobial stewardship intervention to reduce the use of vancomycin. Observational studies have shown reductions in vancomycin use after implementation of MRSA colonization testing, and this approach has been adopted by CAP guidelines. However, the ability of this intervention to safely reduce vancomycin use has yet to be tested in a randomized controlled trial. Methods STOP-Vanc is a pragmatic, prospective, single center, non-blinded randomized trial. The objective of this study is to test whether the use of MRSA PCR testing can safely reduce inappropriate vancomycin use in an intensive care setting. Adult patients with suspicion for CAP who are receiving vancomycin and admitted to the Medical Intensive Care Unit at Vanderbilt University Medical Center will be screened for eligibility. Eligible patients will be enrolled and randomized in a 1:1 ratio to either receive MRSA nasal swab PCR testing in addition to usual care (intervention group), or usual care alone (control group). PCR testing results will be transmitted through the electronic health record to the treating clinicians. Primary providers of intervention group patients with negative swab results will also receive a page providing clinical guidance recommending discontinuation of vancomycin. The primary outcome will be vancomycin-free hours alive, defined as the expected number of hours alive and free of the use of vancomycin within the first 7 days following trial enrollment estimated using a proportional odds ratio model. Secondary outcomes include 30-day all-cause mortality and time alive off vancomycin. Discussion STOP-Vanc will provide the first randomized controlled trial data regarding the use of MRSA nasal swab PCR testing to guide antibiotic de-escalation. This study will provide important information regarding the effect of MRSA PCR testing and antimicrobial stewardship guidance on clinical outcomes in an intensive care unit setting. Trial registration ClinicalTrials.gov NCT06272994. Registered on February 22, 2024. |
| Date | 2024-12-28 |
| Language | en |
| Short Title | Swab Testing to Optimize Pneumonia treatment with empiric Vancomycin (STOP-Vanc) |
| Library Catalog | DOI.org (Crossref) |
| URL | https://trialsjournal.biomedcentral.com/articles/10.1186/s13063-024-08705-6 |
| Accessed | 12/28/2025, 10:26:51 AM |
| Volume | 25 |
| Pages | 854 |
| Publication | Trials |
| DOI | 10.1186/s13063-024-08705-6 |
| Issue | 1 |
| Journal Abbr | Trials |
| ISSN | 1745-6215 |
| Date Added | 12/28/2025, 10:26:51 AM |
| Modified | 12/28/2025, 10:26:51 AM |
| Item Type | Journal Article |
|---|---|
| Author | Florentina A. Simader |
| Author | Christopher A. Rajkumar |
| Author | Michael J. Foley |
| Author | Fiyyaz Ahmed-Jushuf |
| Author | Shayna Chotai |
| Author | Nina Bual |
| Author | Arif Khokhar |
| Author | Aisha Gohar |
| Author | Ioannis Lampadakis |
| Author | Sashiananthan Ganesananthan |
| Author | Rachel H. Pathimagaraj |
| Author | Alexandra Nowbar |
| Author | John R. Davies |
| Author | Tom R. Keeble |
| Author | Peter D. O’Kane |
| Author | Peter Haworth |
| Author | Helen Routledge |
| Author | Tushar Kotecha |
| Author | James C. Spratt |
| Author | Rupert Williams |
| Author | Sukhjinder S. Nijjer |
| Author | Sayan Sen |
| Author | Nick Curzen |
| Author | Manas Sinha |
| Author | James P. Howard |
| Author | Graham Cole |
| Author | Frank E. Harrell |
| Author | Darrel P. Francis |
| Author | Matthew J. Shun-Shin |
| Author | Rasha K. Al-Lamee |
| Author | Christopher Rajkumar |
| Author | Michael Foley |
| Author | Fiyyaz Ahmed-Jushuf |
| Author | Florentina Simader |
| Author | Sashiananthan Ganesananthan |
| Author | Danqi Wang |
| Author | Muhammad Mohsin |
| Author | Rachel Pathimagaraj |
| Author | Krzysztof Macierzanka |
| Author | Ricardo Petraco |
| Author | Ramzi Khamis |
| Author | Graham Cole |
| Author | James Howard |
| Author | Jamil Mayet |
| Author | Darrel Francis |
| Author | Arif Kokhar |
| Author | Aisha Gohar |
| Author | Ioannis Lampadakis |
| Author | Henry Seligman |
| Author | Amit Kaura |
| Author | Sukhjinder Nijjer |
| Author | Sayan Sen |
| Author | Punit Ramrakha |
| Author | Raffi Kaprielian |
| Author | Iqbal Malik |
| Author | Masood Khan |
| Author | Amarjit Sethi |
| Author | Rodney Foale |
| Author | Thomas Keeble |
| Author | Kare Tang |
| Author | John Davies |
| Author | Reto Gamma |
| Author | Gerald Clesham |
| Author | Jason Dungu |
| Author | Alamgir Kabir |
| Author | Shah Mohd Nazri |
| Author | Peter O’Kane |
| Author | Jonathan Hinton |
| Author | Jehangir Din |
| Author | Alexandra Nowbar |
| Author | Tushar Kotecha |
| Author | Peter Haworth |
| Author | James Spratt |
| Author | Rupert Williams |
| Author | Claudia Cosgrove |
| Author | Pitt Lim |
| Author | Helen Routledge |
| Author | Lal Mughal |
| Author | Jasper Trevelyan |
| Author | Manas Sinha |
| Author | Nick Curzen |
| Author | James Wilkinson |
| Author | Rohit Sirohi |
| Author | Alison Calver |
| Author | John Rawlins |
| Author | Richard Jabbour |
| Author | Neil Ruparelia |
| Author | Joban Sehmi |
| Author | Tim Kinnaird |
| Author | Fairoz Abdul |
| Author | Vasileios Panoulas |
| Author | David Collier |
| Author | George Thornton |
| Author | Afzal Sohaib |
| Author | Rasha K. Al-Lamee |
| Date | 07/2024 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://linkinghub.elsevier.com/retrieve/pii/S0735109724069481 |
| Accessed | 12/28/2025, 10:22:34 AM |
| Volume | 84 |
| Pages | 13-24 |
| Publication | Journal of the American College of Cardiology |
| DOI | 10.1016/j.jacc.2024.04.016 |
| Issue | 1 |
| Journal Abbr | Journal of the American College of Cardiology |
| ISSN | 07351097 |
| Date Added | 12/28/2025, 10:22:34 AM |
| Modified | 12/28/2025, 10:22:34 AM |
| Item Type | Journal Article |
|---|---|
| Author | Suhail A. Doi |
| Author | Luis Furuya-Kanamori |
| Author | Chang Xu |
| Author | Tawanda Chivese |
| Author | Lifeng Lin |
| Author | Omran A.H. Musa |
| Author | George Hindy |
| Author | Lukman Thalib |
| Author | Frank E. Harrell |
| Date | 02/2022 |
| Language | en |
| Short Title | The Odds Ratio is “portable” across baseline risk but not the Relative Risk |
| Library Catalog | DOI.org (Crossref) |
| URL | https://linkinghub.elsevier.com/retrieve/pii/S0895435621002419 |
| Accessed | 12/28/2025, 10:01:01 AM |
| Volume | 142 |
| Pages | 288-293 |
| Publication | Journal of Clinical Epidemiology |
| DOI | 10.1016/j.jclinepi.2021.08.003 |
| Journal Abbr | Journal of Clinical Epidemiology |
| ISSN | 08954356 |
| Date Added | 12/28/2025, 10:01:01 AM |
| Modified | 12/28/2025, 10:01:01 AM |
| Item Type | Journal Article |
|---|---|
| Author | Cosby A. Stone |
| Author | Heather L. Prigmore |
| Author | Allison B. McCoy |
| Author | Joanna L. Stollings |
| Author | Mary Lynn Dear |
| Author | William Hiser |
| Author | Grace Van Winkle |
| Author | Sunil Kripalani |
| Author | Adam Wright |
| Author | Frank E. Harrell |
| Author | Todd W. Rice |
| Author | Christopher J. Lindsell |
| Author | Elizabeth J. Phillips |
| Date | 10/2025 |
| Language | en |
| Short Title | The Pragmatic Removal of Penicillin Allergy Electronic Health Record Labels (PROPEL) Trial |
| Library Catalog | DOI.org (Crossref) |
| URL | https://linkinghub.elsevier.com/retrieve/pii/S2213219825006385 |
| Accessed | 12/28/2025, 10:47:36 AM |
| Volume | 13 |
| Pages | 2747-2755 |
| Publication | The Journal of Allergy and Clinical Immunology: In Practice |
| DOI | 10.1016/j.jaip.2025.07.006 |
| Issue | 10 |
| Journal Abbr | The Journal of Allergy and Clinical Immunology: In Practice |
| ISSN | 22132198 |
| Date Added | 12/28/2025, 10:47:36 AM |
| Modified | 12/28/2025, 10:47:36 AM |
| Item Type | Journal Article |
|---|---|
| Author | Christopher A. Rajkumar |
| Author | Michael J. Foley |
| Author | Fiyyaz Ahmed-Jushuf |
| Author | Shayna Chotai |
| Author | Florentina A. Simader |
| Author | Muhammad Mohsin |
| Author | Ahmed Salih |
| Author | Sashiananthan Ganesananthan |
| Author | Nina Bual |
| Author | Ricardo Petraco |
| Author | Sukhjinder S. Nijjer |
| Author | Sayan Sen |
| Author | Joban Sehmi |
| Author | Neil Ruparelia |
| Author | Jason N. Dungu |
| Author | Alamgir Kabir |
| Author | Kare Tang |
| Author | Reto Gamma |
| Author | John R. Davies |
| Author | Tushar Kotecha |
| Author | Graham D. Cole |
| Author | James P. Howard |
| Author | Thomas R. Keeble |
| Author | Gerald J. Clesham |
| Author | Peter D. O’Kane |
| Author | Frank E. Harrell |
| Author | Darrel P. Francis |
| Author | Matthew J. Shun-Shin |
| Author | Rasha K. Al-Lamee |
| Abstract | BACKGROUND: Little correlation exists between the burden of ischemia and severity of angina in patients with stable coronary artery disease. This placebo-controlled, n-of-1 study investigated the relationship between ischemia, the collateral circulation, and symptoms in stable coronary artery disease. Additionally, it explored the association between progressive collateral recruitment and ischemic preconditioning. METHODS: Fifty-one participants with severe single-vessel coronary artery disease and angina were recruited. Antianginal medications were stopped, and daily angina symptoms were documented using a dedicated smartphone application (ORBITA [Objective Randomized Blinded Investigation With Optimal Medical Therapy of Angioplasty in Stable Angina] app) for 14 days before undergoing invasive pressure wire studies and coronary flow reserve assessment. Each participant then underwent four 60-s episodes of low-pressure balloon occlusion across their coronary stenosis. Each episode was paired with an audiovisually identical placebo inflation in a randomized order. After each episode, participants scored pain intensity on a 10-point scale, and a placebo-controlled pain intensity score was calculated. Collateral flow index was calculated from simultaneous measures of aortic, right atrial, and distal coronary wedge pressure during balloon occlusion. Higher Pr values from Bayesian models indicate a greater likelihood of association. RESULTS: The mean (±SD) age of participants was 63±9 years, and 78% were men. The median (interquartile range) fractional flow reserve was 0.68 (0.57–0.79), the median instantaneous wave-free ratio was 0.80 (0.48–0.89), and the median coronary flow reserve was 1.42 (1.08–1.85). Daily angina frequency showed little correlation with severity of ischemia, as assessed by fractional flow reserve (Somers’ D 0.124, Pr =0.057) or instantaneous wave-free ratio (Somers’ D 0.056, Pr =0.150). However, there was strong evidence of an association between lower fractional flow reserve and instantaneous wave-free ratio values and greater collateral flow (Somers’ D 0.302, Pr =0.998 and Somers’ D 0.316, Pr =0.999, respectively). There was also strong evidence of an association between more collateralization (higher collateral flow index) and lower pain intensity scores (Somers’ D 0.341, Pr =0.999). Finally, pain intensity scores and collateral flow index remained stable between sequential balloon occlusion episodes within individual patients, indicating little evidence of ischemic preconditioning. CONCLUSIONS: Coronary collateralization is associated with ischemic burden and may reduce the intensity of ischemic chest pain. This may explain the nonlinear relationship between stenosis, ischemia, and angina. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT04280575. |
| Date | 2025-12-02 |
| Language | en |
| Short Title | The Role of the Collateral Circulation in Stable Angina |
| Library Catalog | DOI.org (Crossref) |
| URL | https://www.ahajournals.org/doi/10.1161/CIRCULATIONAHA.125.074687 |
| Accessed | 12/28/2025, 10:49:16 AM |
| Volume | 152 |
| Pages | 1541-1551 |
| Publication | Circulation |
| DOI | 10.1161/CIRCULATIONAHA.125.074687 |
| Issue | 22 |
| Journal Abbr | Circulation |
| ISSN | 0009-7322, 1524-4539 |
| Date Added | 12/28/2025, 10:49:16 AM |
| Modified | 12/28/2025, 10:49:16 AM |
| Item Type | Journal Article |
|---|---|
| Author | Christopher J. Lindsell |
| Author | Matthew Shotwell |
| Author | Kevin J. Anstrom |
| Author | Scott Berry |
| Author | Erica Brittain |
| Author | Frank E. Harrell |
| Author | Nancy Geller |
| Author | Birgit Grund |
| Author | Michael D. Hughes |
| Author | Prasanna Jagannathan |
| Author | Eric Leifer |
| Author | Carlee B. Moser |
| Author | Karen L. Price |
| Author | Michael Proschan |
| Author | Thomas Stewart |
| Author | Sonia Thomas |
| Author | Giota Touloumi |
| Author | Lisa LaVange |
| Abstract | Abstract The Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) Cross-Trial Statistics Group gathered lessons learned from statisticians responsible for the design and analysis of the 11 ACTIV therapeutic master protocols to inform contemporary trial design as well as preparation for a future pandemic. The ACTIV master protocols were designed to rapidly assess what treatments might save lives, keep people out of the hospital, and help them feel better faster. Study teams initially worked without knowledge of the natural history of disease and thus without key information for design decisions. Moreover, the science of platform trial design was in its infancy. Here, we discuss the statistical design choices made and the adaptations forced by the changing pandemic context. Lessons around critical aspects of trial design are summarized, and recommendations are made for the organization of master protocols in the future. |
| Date | 2024 |
| Language | en |
| Short Title | The statistical design and analysis of pandemic platform trials |
| Library Catalog | DOI.org (Crossref) |
| URL | https://www.cambridge.org/core/product/identifier/S2059866124005144/type/journal_article |
| Accessed | 12/28/2025, 10:25:35 AM |
| Rights | http://creativecommons.org/licenses/by/4.0/ |
| Volume | 8 |
| Pages | e155 |
| Publication | Journal of Clinical and Translational Science |
| DOI | 10.1017/cts.2024.514 |
| Issue | 1 |
| Journal Abbr | J. Clin. Trans. Sci. |
| ISSN | 2059-8661 |
| Date Added | 12/28/2025, 10:25:35 AM |
| Modified | 12/28/2025, 10:25:35 AM |
| Item Type | Journal Article |
|---|---|
| Author | Ahmed Sayed |
| Author | Ramachandran S. Vasan |
| Author | Frank E. Harrell |
| Author | Javed Butler |
| Date | 12/2025 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://linkinghub.elsevier.com/retrieve/pii/S0735109725093118 |
| Accessed | 12/28/2025, 10:49:54 AM |
| Volume | 86 |
| Pages | 2542-2564 |
| Publication | JACC |
| DOI | 10.1016/j.jacc.2025.09.1503 |
| Issue | 25 |
| Journal Abbr | JACC |
| ISSN | 07351097 |
| Date Added | 12/28/2025, 10:49:54 AM |
| Modified | 12/28/2025, 10:49:54 AM |
| Item Type | Journal Article |
|---|---|
| Author | Richard D Riley |
| Author | Gary S Collins |
| Author | Laura Kirton |
| Author | Kym Ie Snell |
| Author | Joie Ensor |
| Author | Rebecca Whittle |
| Author | Paula Dhiman |
| Author | Maarten Van Smeden |
| Author | Xiaoxuan Liu |
| Author | Joseph Alderman |
| Author | Krishnarajah Nirantharakumar |
| Author | Jay Manson-Whitton |
| Author | Andrew J Westwood |
| Author | Jean-Baptiste Cazier |
| Author | Karel G M Moons |
| Author | Glen P Martin |
| Author | Matthew Sperrin |
| Author | Alastair K Denniston |
| Author | Frank E Harrell |
| Author | Lucinda Archer |
| Date | 2025-02-13 |
| Language | en |
| Short Title | Uncertainty of risk estimates from clinical prediction models |
| Library Catalog | DOI.org (Crossref) |
| URL | https://www.bmj.com/lookup/doi/10.1136/bmj-2024-080749 |
| Accessed | 12/28/2025, 10:41:31 AM |
| Pages | e080749 |
| Publication | BMJ |
| DOI | 10.1136/bmj-2024-080749 |
| Journal Abbr | BMJ |
| ISSN | 1756-1833 |
| Date Added | 12/28/2025, 10:41:31 AM |
| Modified | 12/28/2025, 10:41:31 AM |
| Item Type | Journal Article |
|---|---|
| Author | Fernando G. Zampieri |
| Author | Jonathan D. Casey |
| Author | Manu Shankar-Hari |
| Author | Frank E. Harrell |
| Author | Michael O. Harhay |
| Date | 2021-03-01 |
| Language | en |
| Library Catalog | DOI.org (Crossref) |
| URL | https://www.atsjournals.org/doi/10.1164/rccm.202006-2381CP |
| Accessed | 12/28/2025, 9:53:36 AM |
| Volume | 203 |
| Pages | 543-552 |
| Publication | American Journal of Respiratory and Critical Care Medicine |
| DOI | 10.1164/rccm.202006-2381CP |
| Issue | 5 |
| Journal Abbr | Am J Respir Crit Care Med |
| ISSN | 1073-449X, 1535-4970 |
| Date Added | 12/28/2025, 9:53:36 AM |
| Modified | 12/28/2025, 9:54:43 AM |
| Item Type | Journal Article |
|---|---|
| Author | The Medical Outreach Subteam of the Drug Information Association Bayesian Scientific Working Group |
| Author | Jennifer Clark |
| Author | Natalia Muhlemann |
| Author | Fanni Natanegara |
| Author | Andrew Hartley |
| Author | Deborah Wenkert |
| Author | Fei Wang |
| Author | Frank E. Harrell |
| Author | Ross Bray |
| Date | 05/2023 |
| Language | en |
| Short Title | Why are not There More Bayesian Clinical Trials? |
| Library Catalog | DOI.org (Crossref) |
| URL | https://link.springer.com/10.1007/s43441-021-00357-x |
| Accessed | 12/28/2025, 10:09:54 AM |
| Volume | 57 |
| Pages | 417-425 |
| Publication | Therapeutic Innovation & Regulatory Science |
| DOI | 10.1007/s43441-021-00357-x |
| Issue | 3 |
| Journal Abbr | Ther Innov Regul Sci |
| ISSN | 2168-4790, 2168-4804 |
| Date Added | 12/28/2025, 10:09:54 AM |
| Modified | 12/28/2025, 10:10:31 AM |
| Item Type | Journal Article |
|---|---|
| Author | The Medical Outreach Team of the Drug Information Association Bayesian Scientific Working Group |
| Author | Ross Bray |
| Author | Andrew Hartley |
| Author | Deborah Wenkert |
| Author | Natalia Muehlemann |
| Author | Fanni Natanegara |
| Author | Frank E. Harrell |
| Author | Fei Wang |
| Author | Jennifer Clark |
| Date | 05/2023 |
| Language | en |
| Short Title | Why are There not More Bayesian Clinical Trials? |
| Library Catalog | DOI.org (Crossref) |
| URL | https://link.springer.com/10.1007/s43441-022-00482-1 |
| Accessed | 12/28/2025, 10:11:11 AM |
| Volume | 57 |
| Pages | 426-435 |
| Publication | Therapeutic Innovation & Regulatory Science |
| DOI | 10.1007/s43441-022-00482-1 |
| Issue | 3 |
| Journal Abbr | Ther Innov Regul Sci |
| ISSN | 2168-4790, 2168-4804 |
| Date Added | 12/28/2025, 10:11:11 AM |
| Modified | 12/28/2025, 10:11:40 AM |
| Item Type | Journal Article |
|---|---|
| Author | Jo Ellen Wilson |
| Author | Myrick C. Shinall |
| Author | Taylor C. Leath |
| Author | Li Wang |
| Author | Frank E. Harrell |
| Author | Laura D. Wilson |
| Author | Mina F. Nordness |
| Author | Shayan Rakhit |
| Author | Michael R. De Riesthal |
| Author | Melissa C. Duff |
| Author | Pratik P. Pandharipande |
| Author | Mayur B. Patel |
| Abstract | Objective: The aim of this study was to determine the health utility states of the most commonly used traumatic brain injury (TBI) clinical trial endpoint, the Extended Glasgow Outcome Scale (GOSE). Summary Background Data: Health utilities represent the strength of one's preferences under conditions of uncertainty. There are insufficient data to indicate how an individual would value levels of disability after a TBI. Methods: This was a cross-sectional web-based online convenience sampling adaptive survey. Using a standard gamble approach, participants evaluated their preferences for GOSE health states 1 year after a hypothetical TBI. The categorical GOSE was studied from vegetative state (GOSE2) to upper good recovery (GOSE8). Median (25th percentile, 75th percentile) health utility values for different GOSE states after TBI, ranging from −1 (worse than death) to 1 (full health), with 0 as reference (death). Results: Of 3508 eligible participants, 3235 (92.22%) completed the survey. Participants rated lower GOSE states as having lower utility, with some states rated as worse than death, though the relationship was nonlinear and intervals were unequal between health states. Over 75% of participants rated a vegetative state (GOSE2, absence of awareness and bedridden) and about 50% rated lower severe disability (GOSE3, housebound needing all-day assistance) as conditions worse than death. Conclusions: In the largest investigation of public perceptions about post-TBI disability, we demonstrate unequally rated health states, with some states perceived as worse than death. Although limited by selection bias, these results may guide future comparative-effectiveness research and shared medical decision-making after neurologic injury. |
| Date | 03/2021 |
| Language | en |
| Short Title | Worse Than Death |
| Library Catalog | DOI.org (Crossref) |
| URL | https://journals.lww.com/10.1097/SLA.0000000000003389 |
| Accessed | 12/28/2025, 9:52:19 AM |
| Volume | 273 |
| Pages | 500-506 |
| Publication | Annals of Surgery |
| DOI | 10.1097/SLA.0000000000003389 |
| Issue | 3 |
| ISSN | 0003-4932, 1528-1140 |
| Date Added | 12/28/2025, 9:52:19 AM |
| Modified | 12/28/2025, 9:56:15 AM |
| Item Type | Journal Article |
|---|---|
| Author | Amelia W. Maiga |
| Author | Madison R. Cook |
| Author | Mina F. Nordness |
| Author | Yue Gao |
| Author | Shayan Rakhit |
| Author | Erika L. Rivera |
| Author | Frank E. Harrell |
| Author | Mayur B. Patel |
| Abstract | Objective: To quantify health utilities of the Glasgow Outcome Scale–Extended (GOSE) states after actual traumatic brain injury (TBI). Background: Recovery after TBI is measured using the GOSE, a validated clinical trial endpoint. A recent public survey quantified the health utilities of some GOSE states after hypothetical TBI as worse than death. However, no health utilities exist for disability after actual TBI. Methods: This national computer-adaptive survey followed Enhancing the Quality and Transparency of Health Research-Checklist for Reporting Results of Internet E-Surveys guidelines and recruited adult TBI survivors (injury >1 year prior) through their available surrogates. Using a standard gamble approach in randomized order, participants gave preferences for post-TBI categorical health states ranging from GOSE 2 to GOSE 8. We calculated median (interquartile range) health utilities for each GOSE state, from −1 (worse than death) to 1 (full health), with 0 as reference (death, GOSE 1). Results: Of 515 eligible, 298 surrogates (58%) consented and completed the scenarios on TBI survivors’ behalf. TBI survivors had a current median GOSE 5 (3–7). GOSE 2, GOSE 3, and GOSE 4 were rated worse than death by 89%, 64%, and 38%, respectively. The relationship was nonlinear, and intervals were unequal between states, with a bimodal distribution for GOSE 4. Conclusions: In this index study of actual post-TBI disability, poor neurological outcomes represented by GOSE 2 to GOSE 4 were perceived as worse than death by at least one in 3 survivors. Similar to previously reported public perceptions after a hypothetical TBI, these long-term perceptions may inform earlier post-TBI shared decision-making, as well as help shape value-based research and quality of care. Level of Evidence: Level II—economic and value-based evaluations. |
| Date | 07/2024 |
| Language | en |
| Short Title | Would You Rather |
| Library Catalog | DOI.org (Crossref) |
| URL | https://journals.lww.com/10.1097/SLA.0000000000006274 |
| Accessed | 12/28/2025, 10:21:17 AM |
| Volume | 280 |
| Pages | 144-149 |
| Publication | Annals of Surgery |
| DOI | 10.1097/SLA.0000000000006274 |
| Issue | 1 |
| ISSN | 0003-4932 |
| Date Added | 12/28/2025, 10:21:17 AM |
| Modified | 12/28/2025, 10:21:17 AM |