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5. Comparative Effectiveness of Aspirin Dosing in Cardiovascular Disease

Author

Jones, W Schuyler, Mulder, Hillary, Wruck, Lisa M, Pencina, Michael J, Kripalani, Sunil, Muñoz, Daniel, Crenshaw, David L, Effron, Mark B, Re, Richard N, Gupta, Kamal, Anderson, R David, Pepine, Carl J, Handberg, Eileen M, Manning, Brittney R, Jain, Sandeep K, Girotra, Saket, Riley, Danielle, DeWalt, Darren A, Whittle, Jeff, Goldberg, Ythan H, Roger, Veronique L, Hess, Rachel, Benziger, Catherine P, Farrehi, Peter, Zhou, Li, Ford, Daniel E, Haynes, Kevin, VanWormer, Jeffrey J, Knowlton, Kirk U, Kraschnewski, Jennifer L, Polonsky, Tamar S, Fintel, Dan J, Ahmad, Faraz S, McClay, James C, Campbell, James R, Bell, Douglas S, Fonarow, Gregg C, Bradley, Steven M, Paranjape, Anuradha, Roe, Matthew T, Robertson, Holly R, Curtis, Lesley H, Sharlow, Amber G, Berdan, Lisa G, Hammill, Bradley G, Harris, Debra F, Qualls, Laura G, Marquis-Gravel, Guillaume, Modrow, Madelaine F, Marcus, Gregory M, Carton, Thomas W, Nauman, Elizabeth, Waitman, Lemuel R, Kho, Abel N, Shenkman, Elizabeth A, McTigue, Kathleen M, Kaushal, Rainu, Masoudi, Frederick A, Antman, Elliott M, Davidson, Desiree R, Edgley, Kevin, Merritt, James G, Brown, Linda S, Zemon, Doris N, McCormick, Thomas E, Alikhaani, Jacqueline D, Gregoire, Kenneth C, Rothman, Russell L, Harrington, Robert A, and Hernandez, Adrian F

Subjects
Clinical Trials and Supportive Activities, Heart Disease - Coronary Heart Disease, Cardiovascular, Patient Safety, Comparative Effectiveness Research, Clinical Research, Heart Disease, Evaluation of treatments and therapeutic interventions, 6.1 Pharmaceuticals, Good Health and Well Being, Aged, Aspirin, Atherosclerosis, Cardiovascular Diseases, Female, Hemorrhage, Hospitalization, Humans, Male, Medication Adherence, Middle Aged, Myocardial Infarction, Platelet Aggregation Inhibitors, Secondary Prevention, Stroke, ADAPTABLE Team, Medical and Health Sciences, General & Internal Medicine
Abstract

BackgroundThe appropriate dose of aspirin to lower the risk of death, myocardial infarction, and stroke and to minimize major bleeding in patients with established atherosclerotic cardiovascular disease is a subject of controversy.MethodsUsing an open-label, pragmatic design, we randomly assigned patients with established atherosclerotic cardiovascular disease to a strategy of 81 mg or 325 mg of aspirin per day. The primary effectiveness outcome was a composite of death from any cause, hospitalization for myocardial infarction, or hospitalization for stroke, assessed in a time-to-event analysis. The primary safety outcome was hospitalization for major bleeding, also assessed in a time-to-event analysis.ResultsA total of 15,076 patients were followed for a median of 26.2 months (interquartile range [IQR], 19.0 to 34.9). Before randomization, 13,537 (96.0% of those with available information on previous aspirin use) were already taking aspirin, and 85.3% of these patients were previously taking 81 mg of daily aspirin. Death, hospitalization for myocardial infarction, or hospitalization for stroke occurred in 590 patients (estimated percentage, 7.28%) in the 81-mg group and 569 patients (estimated percentage, 7.51%) in the 325-mg group (hazard ratio, 1.02; 95% confidence interval [CI], 0.91 to 1.14). Hospitalization for major bleeding occurred in 53 patients (estimated percentage, 0.63%) in the 81-mg group and 44 patients (estimated percentage, 0.60%) in the 325-mg group (hazard ratio, 1.18; 95% CI, 0.79 to 1.77). Patients assigned to 325 mg had a higher incidence of dose switching than those assigned to 81 mg (41.6% vs. 7.1%) and fewer median days of exposure to the assigned dose (434 days [IQR, 139 to 737] vs. 650 days [IQR, 415 to 922]).ConclusionsIn this pragmatic trial involving patients with established cardiovascular disease, there was substantial dose switching to 81 mg of daily aspirin and no significant differences in cardiovascular events or major bleeding between patients assigned to 81 mg and those assigned to 325 mg of aspirin daily. (Funded by the Patient-Centered Outcomes Research Institute; ADAPTABLE ClinicalTrials.gov number, NCT02697916.).

Published
2021

7. Reproductive Experiences and Cardiovascular Disease Care in Pregnancy-Capable and Postmenopausal Individuals: Insights From the American Heart Association Research Goes Red Registry

Author

Rao, Shiavax J., Kwapong, Yaa A., Boakye, Ellen, Mallya, Pratheek, Zhao, Juan, Akel, William, Hong, Haoyun, Li, Shen, Oyeka, Chigolum P., Metlock, Faith Elise, Ouyang, Pamela, Blumenthal, Roger S., Nasir, Khurram, Khandelwal, Abha, Kinzy, Claire, Mehta, Laxmi S., Roger, Veronique L., Hall, Jennifer L., and Sharma, Garima

Published
2023
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26. Next-Generation Sequencing of CYP2C19 in Stent Thrombosis: Implications for Clopidogrel Pharmacogenomics

Author

Morales-Rosado, Joel A., Goel, Kashish, Zhang, Lingxin, Åkerblom, Axel, Baheti, Saurabh, Black, John L., Eriksson, Niclas, Wallentin, Lars, James, Stefan, Storey, Robert F., Goodman, Shaun G., Jenkins, Gregory D., Eckloff, Bruce W., Bielinski, Suzette J., Sicotte, Hugues, Johnson, Stephen, Roger, Veronique L., Wang, Liewei, Weinshilboum, Richard, Klee, Eric W., Rihal, Charanjit S., and Pereira, Naveen L.

Published
2021
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27. The impact of multimorbidity and functional limitation on quality of life in patients with heart failure: A multi‐site study.

Author

Manemann, Sheila M., Hade, Erinn M., Haller, Irina V., Horne, Benjamin D., Benziger, Catherine P., Lampert, Brent C., Rasmusson, Kismet D., Roger, Veronique L., Weston, Susan A., Killian, Jill M., and Chamberlain, Alanna M.

Subjects
RESEARCH funding, FATIGUE (Physiology), FUNCTIONAL status, HEART failure, TREATMENT effectiveness, ANXIETY, DESCRIPTIVE statistics, ODDS ratio, QUALITY of life, RESEARCH, SLEEP, PAIN, CONFIDENCE intervals, COMPARATIVE studies, COMORBIDITY, ACTIVITIES of daily living, MENTAL depression
Abstract

Background: Multimorbidity and functional limitation are associated with poor outcomes in heart failure (HF). However, the individual and combined effect of these on health‐related quality of life in patients with HF is not well understood. Methods: Patients aged ≥30 years with two or more HF diagnostic codes and one or more HF‐related prescription drugs from four U.S. institutions were mailed a survey to measure patient‐centric factors including functional status (activities of daily living [ADLs]) and health‐related quality of life (PROMIS‐29 Health Profile). Patients with HF from January 1, 2013 to February 1, 2018 were included. Multimorbidity was defined as ≥2 non‐cardiovascular comorbidities; functional limitation as any limitation in at least one of eight ADLs. Patients were categorized into four groups by multimorbidity (Yes/No) and functional limitation (Yes/No). We dichotomized the PROMIS‐29 sub‐scale scores at the median and calculated odd ratios for the four multimorbidity/functional limitation groups. Results: A total of 3330 patients with HF returned the survey (response rate 31%); 3020 completed the questions of interest and were retained. Among these patients (45% female; mean age 73 [standard deviation: 12] years), 29% had neither multimorbidity nor functional limitation, 24% had multimorbidity only, 22% had functional limitation only, and 25% had both. After adjustment, having functional limitation only was associated with higher anxiety (odds ratio [OR]: 3.44, 95% confidence interval [CI]: 2.66–4.45), depression (OR: 3.11, 95% CI: 2.39–4.06), and fatigue (OR: 4.19, 95% CI: 3.25–5.40); worse sleep (OR: 2.14, 95% CI: 1.69–2.72) and pain (OR: 6.73, 95% CI: 5.15–8.78); and greater difficulty with social activities (OR: 9.40, 95% CI: 7.19–12.28) compared with having neither. Results were similar for having both multimorbidity and functional limitation. Conclusion: Patients with only functional limitation have similar poor health‐related quality of life scores as those with both multimorbidity and functional limitation, underscoring the important role that physical functioning plays in the well‐being of patients with HF. [ABSTRACT FROM AUTHOR]

Published
2024
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30. Incidence and outcomes of high bleeding risk patients with type 1 and type 2 myocardial infarction in a community-based cohort: Application of the Academic Research Consortium High Bleeding Risk Criteria

Author

Breen, Thomas J., primary, Raphael, Claire E., additional, Ingraham, Brenden, additional, Lane, Conor, additional, Huxley, Sam, additional, Roger, Veronique L., additional, Jaffe, Allan, additional, Lewis, Bradley, additional, Sandoval, Yader B., additional, Prasad, Abhiram, additional, Rihal, Charanjit S., additional, Gulati, Rajiv, additional, and Singh, Mandeep, additional

Published
2023
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35. Bicuspid aortic valve: long-term morbidity and mortality

Author

Yang, Li-Tan, primary, Ye, Zi, additional, Wajih Ullah, Muhammad, additional, Maleszewski, Joseph J, additional, Scott, Christopher G, additional, Padang, Ratnasari, additional, Pislaru, Sorin V, additional, Nkomo, Vuyisile T, additional, Mankad, Sunil V, additional, Pellikka, Patricia A, additional, Oh, Jae K, additional, Roger, Veronique L, additional, Enriquez-Sarano, Maurice, additional, and Michelena, Hector I, additional

Published
2023
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37. Natural Language Processing and Machine Learning for Identifying Incident Stroke From Electronic Health Records: Algorithm Development and Validation

Author

Zhao, Yiqing, Fu, Sunyang, Bielinski, Suzette J, Decker, Paul A, Chamberlain, Alanna M, Roger, Veronique L, Liu, Hongfang, and Larson, Nicholas B

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract

BackgroundStroke is an important clinical outcome in cardiovascular research. However, the ascertainment of incident stroke is typically accomplished via time-consuming manual chart abstraction. Current phenotyping efforts using electronic health records for stroke focus on case ascertainment rather than incident disease, which requires knowledge of the temporal sequence of events. ObjectiveThe aim of this study was to develop a machine learning–based phenotyping algorithm for incident stroke ascertainment based on diagnosis codes, procedure codes, and clinical concepts extracted from clinical notes using natural language processing. MethodsThe algorithm was trained and validated using an existing epidemiology cohort consisting of 4914 patients with atrial fibrillation (AF) with manually curated incident stroke events. Various combinations of feature sets and machine learning classifiers were compared. Using a heuristic rule based on the composition of concepts and codes, we further detected the stroke subtype (ischemic stroke/transient ischemic attack or hemorrhagic stroke) of each identified stroke. The algorithm was further validated using a cohort (n=150) stratified sampled from a population in Olmsted County, Minnesota (N=74,314). ResultsAmong the 4914 patients with AF, 740 had validated incident stroke events. The best-performing stroke phenotyping algorithm used clinical concepts, diagnosis codes, and procedure codes as features in a random forest classifier. Among patients with stroke codes in the general population sample, the best-performing model achieved a positive predictive value of 86% (43/50; 95% CI 0.74-0.93) and a negative predictive value of 96% (96/100). For subtype identification, we achieved an accuracy of 83% in the AF cohort and 80% in the general population sample. ConclusionsWe developed and validated a machine learning–based algorithm that performed well for identifying incident stroke and for determining type of stroke. The algorithm also performed well on a sample from a general population, further demonstrating its generalizability and potential for adoption by other institutions.

Published
2021
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45. Abstract P524: Metabolic Vulnerability and Frailty for Risk Stratification in Heart Failure: A Community Cohort Study

Author

Kumar, Sant, primary, Conners, Katie, additional, Joo, Jungnam, additional, Turecamo, Sarah, additional, Sampson, Maureen, additional, Wolska, Anna T, additional, Remaley, Alan T, additional, Connelly, Margery, additional, Otvos, James D, additional, Larson, Nicholas B, additional, Bielinski, Suzette J, additional, Shearer, Joe, additional, and Roger, Veronique L, additional

Published
2023
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