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53. Are novel glucose‐lowering agents' cardiorenal benefits generalizable to individuals of Black race? A meta‐trial sequential analysis to address disparities in cardiovascular and renal outcome trials enrolment

Author

Tang, Huilin, primary, Kimmel, Stephen E., additional, Hernandez, Inmaculada, additional, Brooks, Maria M., additional, Cusi, Kenneth, additional, Smith, Steven M., additional, Shi, Weilong, additional, Winterstein, Almut G., additional, Magnani, Jared W., additional, and Guo, Jingchuan, additional

Published
2021
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54. Comparative Safety of Dipeptidyl Peptidase‐4 Inhibitors and Sudden Cardiac Arrest and Ventricular Arrhythmia: Population‐Based Cohort Studies

Author

Dawwas, Ghadeer K., primary, Hennessy, Sean, additional, Brensinger, Colleen M., additional, Deo, Rajat, additional, Bilker, Warren B., additional, Soprano, Samantha E., additional, Dhopeshwarkar, Neil, additional, Flory, James H., additional, Bloomgarden, Zachary T., additional, Aquilante, Christina L., additional, Kimmel, Stephen E., additional, and Leonard, Charles E., additional

Published
2021
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56. Warfarin pharmacogenetics: a single VKORC1 polymorphism is predictive of dose across 3 racial groups

Author

Limdi, Nita A., Wadelius, Mia, Cavallari, Larisa, Eriksson, Niclas, Crawford, Dana C., Lee, Ming-Ta M., Chen, Chien-Hsiun, Motsinger-Reif, Alison, Sagreiya, Hersh, Liu, Nianjun, Wu, Alan H.B., Gage, Brian F., Jorgensen, Andrea, Pirmohamed, Munir, Shin, Jae-Gook, Suarez-Kurtz, Guilherme, Kimmel, Stephen E., Johnson, Julie A., Klein, Teri E., and Wagner, Michael J.

Published
2010
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62. Development and Validation of a Seizure Prediction Model in Neonates After Cardiac Surgery

Author

Naim, Maryam Y., primary, Putt, Mary, additional, Abend, Nicholas S., additional, Mastropietro, Christopher W., additional, Frank, Deborah U., additional, Chen, Jonathan M., additional, Fuller, Stephanie, additional, Gangemi, James J., additional, Gaynor, J. William, additional, Heinan, Kristin, additional, Licht, Daniel J., additional, Mascio, Christopher E., additional, Massey, Shavonne, additional, Roeser, Mark E., additional, Smith, Clyde J., additional, and Kimmel, Stephen E., additional

Published
2021
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67. Additional file 1 of Comparison of dynamic updating strategies for clinical prediction models

Author

Schnellinger, Erin M., Yang, Wei, and Kimmel, Stephen E.

Abstract

Additional file 1: Table 1. Sample size, number of deaths, and mortality risk per quarter in the post-baseline period. Figure 1. Proportion of deaths versus time in the post-baseline period. Figure 2. Overall calibration for each update strategy when update interval equals 1 quarter and 100% new data are used. Triangles represent deciles of predicted probabilities; vertical lines at bottom of plot represent the distribution of subjects stratified by outcome status (below x-axis = alive, above x-axis = dead). Figure 3. Brier Score versus time when update interval equals 1 quarter and 100% new data are used. Figure 4. AUC vs. time when update interval equals 1 quarter and 100% new data are used. Figure 5. Hosmer-Lemeshow statistic vs. time when update interval equals 1 quarter and 100% new data are used. Figure 6. Calibration vs. time when update interval equals 1 quarter and 100% new data are used. A) calibration intercept (calibration-in-the-large); B) calibration slope. Table 2. Pairwise comparisons (Wilcoxon Signed Rank Test) of Brier Score (BS) at each quarter when the update interval equals 1, 2, 4, or 8 quarters and 100% new data are used for each update. Values represent the median difference (p-value) in BS between the strategy listed in the row header and that listed in the column header. Negative differences indicate that the row header has lower BS (performs better) than the column header; positive differences indicate that the row header has higher BS (performs worse) than the column header. Table 3. Pairwise comparisons (Wilcoxon Signed Rank Test) of Brier Score (BS) at each quarter when the sliding window equals 1, 2, 4, or 8 quarters and the update interval equals 1 quarter. Values represent the median difference (p-value) in BS between the strategy listed in the row header and that listed in the column header. Negative differences indicate that the row header has lower BS (performs better) than the column header; positive differences indicate that the row header has higher BS (performs worse) than the column header. Table 4. Brier Score (BS), AUC, Hosmer-Lemeshow statistic, calibration intercept and slope (from logistic calibration), and number of updates performed under each update strategy when the sliding window equals 4 or 8 quarters and the update interval equals 4 quarters. Table 5. Number of times each candidate update model was selected by the Closed Testing Procedure when the sliding window equals 4 or 8 quarters and the update interval equals 4 quarters. Table 6. Pairwise comparisons (Wilcoxon Signed Rank Test) of Brier Score (BS) at each quarter when the sliding window equals 4 or 8 quarters and the update interval equals 4 quarters. Values represent the median difference (p-value) in BS between the strategy listed in the row header and that listed in the column header. Negative differences indicate that the row header has lower BS (performs better) than the column header; positive differences indicate that the row header has higher BS (performs worse) than the column header. Figure 7. Boxplot of difference in Brier Score between each update strategy and never update calculated at each quarter versus sliding window length, when the update interval equals 4 quarters. Horizontal bars represent medians and interquartile ranges (IQR). Negative values reflect improvement compared never update. Figure 8. Overall calibration for each update strategy when update interval equals 4 quarters and 100% new data are used. Triangles represent deciles of predicted probabilities; vertical lines at bottom of plot represent the distribution of subjects stratified by outcome status (below x-axis = alive, above x-axis = dead). Figure 9. Brier Score versus time when update interval equals 4 quarters and 100% new data are used. Figure 10. AUC vs. time when update interval equals 4 quarters and 100% new data are used. Figure 11. Hosmer-Lemeshow statistic vs. time when update interval equals 4 quarters and 100% new data are used. Figure 12. Calibration vs. time when update interval equals 4 quarters and 100% new data are used. A) calibration intercept (calibration-in-the-large); B) calibration slope.

Published
2021
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74. Comparable Cardiorenal Benefits of SGLT2 Inhibitors and GLP-1RAs in Asian and White Populations: An Updated Meta-analysis of Results From Randomized Outcome Trials.

Author

Huilin Tang, Kimmel, Stephen E., Smith, Steven M., Cusi, Kenneth, Weilong Shi, Gurka, Matthew, Winterstein, Almut G., and Guo, Jingchuan

Abstract

Background: Whether the cardiorenal benefits of sodium-glucose cotransporter 2 (SGLT2) inhibitors and glucagon-like peptide 1 receptor agonists (GLP-1RAs) are comparable between White and Asian populations remains unclear.Purpose: To compare the cardiorenal benefits of SGLT2 inhibitors and GLP-1RAs between White and Asian populations and to compare the cardiorenal benefits between the two agents in Asian patients.Data Sources: Electronic databases were searched up to 28 March 2021.Study Selection: We included the cardiovascular (CV) and renal outcome trials of SGLT2 inhibitors and GLP-1RAs where investigators reported major adverse CV events (MACE), CV death/hospitalization for heart failure (HHF), or composite renal outcomes with stratification by race.Data Extraction: We extracted the hazard ratio of each outcome stratified by race (Asian vs. White populations).Data Synthesis: In 10 SGLT2 inhibitor trials, there was no significant difference between Asian and White populations for MACE (P = 0.55), CV death/HHF (P = 0.87), or composite renal outcomes (P = 0.97). In seven GLP-1RA trials, we observed a similar MACE benefit between Asian and White populations (P = 0.10). In our networkmeta-analysis we found a comparable benefit for MACE between SGLT2 inhibitors and GLP-1RAs in Asian patients.Limitations: The data were from stratified analyses.Conclusions: There appear to be comparable cardiorenal benefits of SGLT2 inhibitors and GLP-1RAs between Asian and White participants enrolled in CV and renal outcome trials; the two therapies seem to have similar CV benefits for Asian participants. [ABSTRACT FROM AUTHOR]

Published
2022
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75. Factors Associated with Utilization of Saxagliptin in the US and UK: 939.

Author

Nezamzadeh, Melissa S, Haynes, Kevin, Carbonari, Dena M, Newcomb, Craig, Roy, Jason, Cardillo, Serena, Leidl, Kimberly BF, Ives, Jennifer Wood, DeVore, Stephanie, Horne, Laura, Blak, Betina, Esposito, Daina, Holick, Crystal, Van Staa, Tjeerd, Bhullar, Harshvinder, Strom, Brian L, Re, Vincent Lo, III, Ming, Eileen E, Hennessy, Sean, Reese, Peter P, Reddy, Rajender K, Margolis, David, Apter, Andrea, Kimmel, Stephen E, Freeman, Cristin P, and Razzaghi, Hanieh

Published
2013

77. Epidemiologic features of the presentation of critical congenital heart disease: implications for screening

Author

Schultz, Amy H., Localio, A. Russell, Clark, Bernard J., Ravishankar, Chitra, Videon, Nancy, and Kimmel, Stephen E.

Subjects
Company distribution practices, Congenital heart disease -- Distribution, Congenital heart disease -- Demographic aspects, Congenital heart disease -- Research, Infants (Newborn) -- Medical examination, Infants (Newborn) -- Usage, Infants (Newborn) -- Research
Published
2008

79. sj-pdf-2-pul-10.1177_2045894020966889 - Supplemental material for Risk factors for 30-day readmission in adults hospitalized for pulmonary hypertension

Author

Bhattacharya, Priyanka T., Hameed, Asif M. Abdul, Shubhadeep T. Bhattacharya, Chirinos, Julio A., Hwang, Wei-Ting, Birati, Edo Y., Menachem, Jonathan N., Saurav Chatterjee, Giri, Jay S., Kawut, Steven M., Kimmel, Stephen E., and Mazurek, Jeremy A.

Subjects
110203 Respiratory Diseases, FOS: Clinical medicine, Cardiology
Abstract

Supplemental material, sj-pdf-2-pul-10.1177_2045894020966889 for Risk factors for 30-day readmission in adults hospitalized for pulmonary hypertension by Priyanka T. Bhattacharya, Asif M. Abdul Hameed, Shubhadeep T. Bhattacharya, Julio A. Chirinos, Wei-Ting Hwang, Edo Y. Birati, Jonathan N. Menachem, Saurav Chatterjee, Jay S. Giri, Steven M. Kawut, Stephen E. Kimmel and Jeremy A. Mazurek in Pulmonary Circulation

Published
2020
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80. sj-pdf-1-pul-10.1177_2045894020966889 - Supplemental material for Risk factors for 30-day readmission in adults hospitalized for pulmonary hypertension

Author

Bhattacharya, Priyanka T., Hameed, Asif M. Abdul, Shubhadeep T. Bhattacharya, Chirinos, Julio A., Hwang, Wei-Ting, Birati, Edo Y., Menachem, Jonathan N., Saurav Chatterjee, Giri, Jay S., Kawut, Steven M., Kimmel, Stephen E., and Mazurek, Jeremy A.

Subjects
110203 Respiratory Diseases, FOS: Clinical medicine, Cardiology
Abstract

Supplemental material, sj-pdf-1-pul-10.1177_2045894020966889 for Risk factors for 30-day readmission in adults hospitalized for pulmonary hypertension by Priyanka T. Bhattacharya, Asif M. Abdul Hameed, Shubhadeep T. Bhattacharya, Julio A. Chirinos, Wei-Ting Hwang, Edo Y. Birati, Jonathan N. Menachem, Saurav Chatterjee, Jay S. Giri, Steven M. Kawut, Stephen E. Kimmel and Jeremy A. Mazurek in Pulmonary Circulation

Published
2020
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81. ACCF/AHA/SCAI 2007 Update of the Clinical Competence Statement on Cardiac Interventional Procedures: A Report of the American College of Cardiology Foundation/American Heart Association/American College of Physicians Task Force on Clinical Competence and Training (Writing Committee to Update the 1998 Clinical Competence Statement on Recommendations for the Assessment and Maintenance of Proficiency in Coronary Interventional Procedures)

Author

King, Spencer B., III, Aversano, Thomas, Ballard, William L., Beekman, Robert H., III, Cowley, Michael J., Ellis, Stephen G., Faxon, David P., Hannan, Edward L., Hirshfeld, John W., Jr, Jacobs, Alice K., Kellett, Mirle A., Jr, Kimmel, Stephen E., Landzberg, Joel S., McKeever, Louis S., Moscucci, Mauro, Pomerantz, Richard M., Smith, Karen M., Vetrovec, George W., Creager, Mark A., Holmes, David R., Jr, Newby, L. Kristin, Weitz, Howard H., Merli, Geno, Piña, Ileana, Rodgers, George P., and Tracy, Cynthia M.

Published
2007
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84. Examples of Automated Databases

Author

Stergachis, Andy, primary, Saunders, Kathleen W., additional, Davis, Robert L., additional, Kimmel, Stephen E., additional, Schinnar, Rita, additional, Chan, K. Arnold, additional, Shatin, Deborah, additional, Rawson, Nigel S.B., additional, Hennessy, Sean, additional, Downey, Winanne, additional, Stang, Maryrose, additional, Beck, Patricia, additional, Osei, William, additional, Leufkens, Hubert G., additional, Macdonald, Thomas M., additional, and Gelfand, Joel M., additional

Published
2013
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85. Bioethical Issues in Pharmacoepidemiologic Research

Author

Bothwell, Laura E., Richterich, Annika, Greene, Jeremy A., Strom, Brian L., Kimmel, Stephen E., Hennessey, Sean, Literature & Art, and RS: FASoS AMC

Subjects
Brexit, business.industry, Informed consent, Law, Political science, Pharmacovigilance, Conflict of interest, Medicine, East Asia, Engineering ethics, Bioethics, Pharmacoepidemiology, business
Abstract

Because the bioethical issues involved in pharmacoepidemiologic research are closely related to changing patterns of drug usage and changing technologies of surveillance and data analysis, it is impossible to understand them without attention to historical and sociological perspectives. The field of pharmacoepidemiology emerged as a result of broader recent developments in medical therapeutics, concomitant with the expansion and refinement of the field of bioethics. Some key bioethical principles relevant to pharmacoepidemiologic research have remained significant over time, others have only gained attention in recent years. This chapter briefly introduces historical and sociological dimensions of pharmacoepidemiology from an international perspective, with an eye to commonalities and differences in national variations in ethical approaches to the field.

Published
2019

89. Correction: Developing a common framework for evaluating the implementation of genomic medicine interventions in clinical care: the IGNITE Network’s Common Measures Working Group

Author

Orlando, Lori A., primary, Sperber, Nina R., additional, Voils, Corrine, additional, Nichols, Marshall, additional, Myers, Rachel A., additional, Wu, R. Ryanne, additional, Rakhra-Burris, Tejinder, additional, Levy, Kenneth D., additional, Levy, Mia, additional, Pollin, Toni I., additional, Guan, Yue, additional, Horowitz, Carol R., additional, Ramos, Michelle, additional, Kimmel, Stephen E., additional, McDonough, Caitrin W., additional, Madden, Ebony B., additional, and Damschroder, Laura J., additional

Published
2020
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90. Risk factors for 30‐day readmission in adults hospitalized for pulmonary hypertension

Author

Bhattacharya, Priyanka T., primary, Hameed, Asif M. Abdul, additional, Bhattacharya, Shubhadeep T., additional, Chirinos, Julio A., additional, Hwang, Wei‐Ting, additional, Birati, Edo Y., additional, Menachem, Jonathan N., additional, Chatterjee, Saurav, additional, Giri, Jay S., additional, Kawut, Steven M., additional, Kimmel, Stephen E., additional, and Mazurek, Jeremy A., additional

Published
2020
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91. Role of computerized physician order entry systems in facilitating medication errors

Author

Koppel, Ross, Metlay, Joshua P., Cohen, Abigail, Abaluck, Brian, Localio, A. Russell, Kimmel, Stephen E., and Strom, Brian L.

Subjects
Physicians -- Practice, Medication errors -- Risk factors
Abstract

A study is conducted to identify and quantify the role of computerized physician order entry (CPOE) systems in facilitating medical prescription errors risks. The study found that a leading CPOE system often facilitated medication error risks, with many reported to occur frequently.

Published
2005

95. Safety of saxagliptin: rationale for and design of a series of postmarketing observational studies

Author

Lo Re, Vincent, III, Haynes, Kevin, Ming, Eileen E., Wood Ives, Jennifer, Horne, Laura N., Fortier, Kimberly, Carbonari, Dena M., Hennessy, Sean, Cardillo, Serena, Reese, Peter P., Reddy, Rajender K., Margolis, David, Apter, Andrea, Kimmel, Stephen E., Roy, Jason, Freeman, Cristin P., Razzaghi, Hanieh, Holick, Crystal N., Esposito, Daina B., Van Staa, Tjeerd-Pieter, Bhullar, Harshvinder, and Strom, Brian L.

Published
2012
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97. Are novel glucose‐lowering agents' cardiorenal benefits generalizable to individuals of Black race? A meta‐trial sequential analysis to address disparities in cardiovascular and renal outcome trials enrolment.

Author

Tang, Huilin, Kimmel, Stephen E., Hernandez, Inmaculada, Brooks, Maria M., Cusi, Kenneth, Smith, Steven M., Shi, Weilong, Winterstein, Almut G., Magnani, Jared W., and Guo, Jingchuan

Subjects
*SEQUENTIAL analysis, *BLACK people, *NEPRILYSIN, *SODIUM-glucose cotransporters, *MAJOR adverse cardiovascular events
Abstract

Importantly, our trial sequential analysis suggests that the sample size available provided inadequate statistical power to detect a significant treatment effect for CV outcomes in Black participants. CONCLUSIONS Although Black participants account for 11.7% of the diabetes population in the United States,8 participation of Black patients in clinical trials that evaluated novel glucose-lowering agents from 2013 to 2021 was less than 5% of trial enrollees. The composite endpoint of CV death/HHF was available in six trials (five trials for Black participants and six trials for White participants) (Figure 1). A meta-trial sequential analysis to address disparities in cardiovascular and renal outcome trials enrolment. [Extracted from the article]

Published
2022
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98. Comparative Safety of Dipeptidyl Peptidase‐4 Inhibitors and Sudden Cardiac Arrest and Ventricular Arrhythmia: Population‐Based Cohort Studies.

Author

Dawwas, Ghadeer K., Hennessy, Sean, Brensinger, Colleen M., Deo, Rajat, Bilker, Warren B., Soprano, Samantha E., Dhopeshwarkar, Neil, Flory, James H., Bloomgarden, Zachary T., Aquilante, Christina L., Kimmel, Stephen E., and Leonard, Charles E.

Subjects
CD26 antigen, CARDIAC arrest, VENTRICULAR arrhythmia, COHORT analysis, SITAGLIPTIN, LINAGLIPTIN
Abstract

In vivo studies suggest that arrhythmia risk may be greater with less selective dipeptidyl peptidase‐4 inhibitors, but evidence from population‐based studies is missing. We aimed to compare saxagliptin, sitagliptin, and linagliptin with regard to risk of sudden cardiac arrest (SCA)/ventricular arrhythmia (VA). We conducted high‐dimensional propensity score (hdPS) matched, new‐user cohort studies. We analyzed Medicaid and Optum Clinformatics separately. We identified new users of saxagliptin, sitagliptin (both databases), and linagliptin (Optum only). We defined SCA/VA outcomes using emergency department and inpatient diagnoses. We identified and then controlled for confounders via a data‐adaptive, hdPS approach. We generated marginal hazard ratios (HRs) via Cox proportional hazards regression using a robust variance estimator while adjusting for calendar year. We identified the following matched comparisons: saxagliptin vs. sitagliptin (23,895 vs. 96,972) in Medicaid, saxagliptin vs. sitagliptin (48,388 vs. 117,383) in Optum, and linagliptin vs. sitagliptin (36,820 vs. 78,701) in Optum. In Medicaid, use of saxagliptin (vs. sitagliptin) was associated with an increased rate of SCA/VA (adjusted HR (aHR), 2.01, 95% confidence interval (CI) 1.24–3.25). However, in Optum data, this finding was not present (aHR, 0.79, 95% CI 0.41–1.51). Further, we found no association between linagliptin (vs. sitagliptin) and SCA/VA (aHR, 0.65, 95% CI 0.36–1.17). We found discordant results regarding the association between SCA/VA with saxagliptin compared with sitagliptin in two independent datasets. It remains unclear whether these findings are due to heterogeneity of treatment effect in the different populations, chance, or unmeasured confounding. [ABSTRACT FROM AUTHOR]

Published
2022
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