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Demissei BG, Ko K, Huang A, Lee DJ, Doucette AG, Smith AM, Wilcox NS, Reibel J, Sun L, Agarwal M, Haas NB, Hollis G, Shpilsky JE, Takvorian SU, Vaughn DJ, Chen J, Hubbard RA, Powell-Wiley T, Yancy C, Narayan V, Ky B. Social Determinants of Health Mediate Racial Disparities in Cardiovascular Disease in Men With Prostate Cancer. JACC CardioOncol 2024; 6:390-401. [PMID: 38983382 PMCID: PMC11229552 DOI: 10.1016/j.jaccao.2024.04.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 03/18/2024] [Accepted: 04/01/2024] [Indexed: 07/11/2024] Open
Abstract
Background Cardiovascular disease (CVD) is a significant cause of morbidity and mortality in men with prostate cancer; however, data on racial disparities in CVD outcomes are limited. Objectives We quantified the disparities in CVD according to self-identified race and the role of the structural social determinants of health in mediating disparities in prostate cancer patients. Methods A retrospective cohort study of 3,543 prostate cancer patients treated with systemic androgen deprivation therapy (ADT) between 2008 and 2021 at a quaternary, multisite health care system was performed. The multivariable adjusted association between self-reported race (Black vs White) and incident major adverse cardiovascular events (MACE) after ADT initiation was evaluated using cause-specific proportional hazards. Mediation analysis determined the role of theme-specific and overall social vulnerability index (SVI) in explaining the racial disparities in CVD outcomes. Results Black race was associated with an increased hazard of MACE (HR: 1.38; 95% CI: 1.16-1.65; P < 0.001). The association with Black race was strongest for incident heart failure (HR: 1.79; 95% CI: 1.32-2.43), cerebrovascular disease (HR: 1.98; 95% CI: 1.37-2.87), and peripheral artery disease (HR: 1.76; 95% CI: 1.26-2.45) (P < 0.001). SVI, specifically the socioeconomic status theme, mediated 98% of the disparity in MACE risk between Black and White patients. Conclusions Black patients are significantly more likely to experience adverse CVD outcomes after systemic ADT compared with their White counterparts. These disparities are mediated by socioeconomic status and other structural determinants of health as captured by census tract SVI. Our findings motivate multilevel interventions focused on addressing socioeconomic vulnerability.
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Affiliation(s)
- Biniyam G Demissei
- Department of Medicine, Division of Cardiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Kyunga Ko
- Department of Medicine, Division of Cardiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Anran Huang
- Department of Medicine, Division of Cardiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Daniel J Lee
- Department of Surgery, Division of Urology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Abigail G Doucette
- Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Amanda M Smith
- Department of Medicine, Division of Cardiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Nicholas S Wilcox
- Department of Medicine, Division of Cardiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Jacob Reibel
- Division of Hematology and Oncology, Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Lova Sun
- Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Division of Hematology and Oncology, Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Manuj Agarwal
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Naomi B Haas
- Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Division of Hematology and Oncology, Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Genevieve Hollis
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Jason E Shpilsky
- Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Division of Hematology and Oncology, Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Samuel U Takvorian
- Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Division of Hematology and Oncology, Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - David J Vaughn
- Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Division of Hematology and Oncology, Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Jinbo Chen
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Rebecca A Hubbard
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Tiffany Powell-Wiley
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
- Intramural Research Program, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, Maryland, USA
| | - Clyde Yancy
- Department of Medicine, Division of Cardiology, Northwestern University Medical School, Chicago, Illinois, USA
| | - Vivek Narayan
- Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Division of Hematology and Oncology, Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Bonnie Ky
- Department of Medicine, Division of Cardiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Chuzi S, Tanaka Y, Bavishi A, Bruce M, Van Wagner LB, Wilcox JE, Ahmad FS, Ladner DP, Lagu T, Khan SS. Association Between End-Stage Liver Disease and Incident Heart Failure in an Integrated Health System. J Gen Intern Med 2023; 38:2445-2452. [PMID: 37095330 PMCID: PMC10465455 DOI: 10.1007/s11606-023-08199-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 04/05/2023] [Indexed: 04/26/2023]
Abstract
BACKGROUND End-stage liver disease (ESLD) and heart failure (HF) often coexist and are associated with significant morbidity and mortality. However, the true incidence of HF among patients with ESLD remains understudied. OBJECTIVE This study aims to evaluate the association between ESLD and incident HF in a real-world clinical cohort. DESIGN AND PARTICIPANTS A retrospective electronic health records database analysis of individuals with ESLD and frequency-matched controls without ESLD in a large integrated health system. MAIN MEASURES The primary outcome was incident HF, which was defined by the International Classification of Disease codes and manually adjudicated by physician reviewers. The Kaplan-Meier method was used to estimate the cumulative incidence of HF. Multivariate proportional hazards models adjusted for shared metabolic factors (diabetes, hypertension, chronic kidney disease, coronary heart disease, body mass index) were used to compare the risk of HF in patients with and without ESLD. KEY RESULTS Of 5004 patients (2502 with ESLD and 2502 without ESLD), the median (Q1-Q3) age was 57.0 (55.0-65.0) years, 59% were male, and 18% had diabetes. Over a median (Q1-Q3) follow-up of 2.3 (0.6-6.0) years, 121 incident HF cases occurred. Risk for incident HF was significantly higher for patients with ESLD compared with the non-ESLD group (adjusted HR: 4.67; 95% CI: 2.82-7.75; p < 0.001), with the majority of the ESLD group (70.7%) having HF with preserved ejection fraction (ejection fraction ≥ 50%). CONCLUSION ESLD was significantly associated with a higher risk of incident HF, independent of shared metabolic risk factors, with the predominant phenotype being HF with preserved ejection fraction.
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Affiliation(s)
- Sarah Chuzi
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
| | - Yoshihiro Tanaka
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Center for Arrhythmia Research, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Avni Bavishi
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Matthew Bruce
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Lisa B Van Wagner
- Division of Digestive and Liver Diseases, University of Texas Southwestern, Dallas, TX, USA
| | - Jane E Wilcox
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Faraz S Ahmad
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Daniela P Ladner
- Center for Health Services and Outcomes Research, Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Northwestern University Transplant Outcomes Research Collaborative (NUTORC), Chicago, IL, USA
- Department of Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Tara Lagu
- Center for Health Services and Outcomes Research, Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Division of Hospital Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Sadiya S Khan
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Center for Health Services and Outcomes Research, Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
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Thomas RD, Kosowan L, Rabey M, Bell A, Connelly KA, Hawkins NM, Casey CG, Singer AG. Validation of a Case Definition to Identify Patients Diagnosed With Cardiovascular Disease in Canadian Primary Care Practices. CJC Open 2023; 5:567-576. [PMID: 37496780 PMCID: PMC10366639 DOI: 10.1016/j.cjco.2023.04.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 04/17/2023] [Indexed: 07/28/2023] Open
Abstract
Background Cardiovascular disease (CVD) is a leading cause of death globally. This study validates a primary care-based electronic medical record case definition for CVD. Methods This retrospective, cross-sectional study explores electronic medical record data from 1574 primary care providers participating in the Canadian Primary Care Sentinel Surveillance Network. A reference standard was created by reviewing medical records of a subset of patients in this network (n = 2017) for coronary artery disease (CAD), cerebrovascular disease (CeVD), and peripheral vascular disease (PVD). Together, these data produced a CVD reference. We applied validated case definitions to an active patient population (≥ 1 visit between January 1, 2018 and December 31, 2019) to estimate prevalence using the exact binomial test (N = 689,301). Descriptive statistics, χ2 tests, and t tests characterized patients with vs without CVD. Results The optimal CVD Case Definition 2 had a sensitivity of 68.5% (95% Confidence Interval [CI]: 61.6%-74.8%), a specificity of 97.8% (95% CI: 97.0%-98.4%), a positive predictive value of 77.7% (95% CI: 71.6%-82.7%), and a negative predictive value of 96.5% (95% CI: 95.8%-97.1%). Included in this CVD definition was a strong CAD case definition with sensitivity of 91.6% (95% CI: 84.6%-96.1%), specificity of 98.3% (95% CI: 97.6%-98.8%), a PPV of 74.8% (95% CI: 67.8%-80.7%), and an NPV of 99.5% (95% CI: 99.1%-99.7%). This CVD definition also included CeVD and PVD case definitions with low sensitivity (77.6% and 36.6%) but high specificity (98.6% and 99.0%). The estimated prevalence of CVD among primary care patients is 11.2% (95% CI, 11.1%-11.3%; n = 77,064); the majority had CAD (6.4%). Conclusions This study validated a definition of CVD and its component parts-CAD, CeVD, and PVD. Understanding the prevalence and disease burden for patients with CVD within primary care settings can improve prevention and disease management.
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Affiliation(s)
| | - Leanne Kosowan
- Department of Family Medicine, Rady Faculty of Health Sciences University of Manitoba, Winnipeg, Manitoba, Canada
| | - Mary Rabey
- Faculty of Medicine, University of Limerick, Limerick, Ireland
| | - Alan Bell
- Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Kim A. Connelly
- Keenan Research Centre for Biomedical Science, Unity Health, St. Michael’s Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Nathaniel M. Hawkins
- Centre for Cardiovascular Innovation, Division of Cardiology, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - Alexander G. Singer
- Department of Family Medicine, Rady Faculty of Health Sciences University of Manitoba, Winnipeg, Manitoba, Canada
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Sanders MA, Muntner P, Wei R, Shimbo D, Schwartz JE, Qian L, Bowling CB, Cannavale K, Harrison TN, Lustigova E, Sim JJ, Reynolds K. Comparison of Blood Pressure Measurements from Clinical Practice and a Research Study At Kaiser Permanente Southern California. Am J Hypertens 2023; 36:283-286. [PMID: 36851820 PMCID: PMC10200552 DOI: 10.1093/ajh/hpad020] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 02/27/2023] [Indexed: 03/01/2023] Open
Abstract
BACKGROUND Accurate blood pressure (BP) measurement is essential to identify and manage hypertension. Prior studies have reported a difference between BP measured in routine patient care and in research studies. We aimed to investigate the agreement between BP measured in routine care and research-grade BP in Kaiser Permanente Southern California, a large, integrated healthcare system with initiatives to standardize BP measurements during routine patient care visits. METHODS We included adults ≥65 years old with hypertension, taking antihypertensive medication, and participating in the Ambulatory Blood Pressure in Older Adults (AMBROSIA) study in 2019-2021. Clinic BP from routine care visits was extracted from the electronic health record. Research-grade BP was obtained by trained AMBROSIA study staff via an automatic oscillometric device. The mean difference between routine care and research-grade BP, limits of agreement, and correlation were assessed. RESULTS We included 309 participants (mean age 75 years; 54% female; 49% non-Hispanic white). Compared with measurements from routine care, mean research-grade systolic BP (SBP) was 0.1 mm Hg higher (95% CI: -1.5 to 1.8) and diastolic BP (DBP) was 0.4 mm Hg lower (95% CI: -1.6 to 0.7). Limits of agreement were -29 to 30 mm Hg for SBP and -21 to 20 mm Hg for DBP. The intraclass correlation coefficient was 0.42 (95% CI: 0.33 to 0.51) for SBP and 0.43 (95% CI: 0.34 to 0.52) for DBP. CONCLUSIONS High within-person variation and moderate correlation were present between BP measured in routine care and following a research protocol suggesting the importance of standardized measurements.
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Affiliation(s)
- Mark A Sanders
- Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, California, USA
| | - Paul Muntner
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Rong Wei
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA
| | - Daichi Shimbo
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Joseph E Schwartz
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
- Department of Psychiatry, Stony Brook University, Stony Brook, New York, USA
| | - Lei Qian
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA
| | - C Barrett Bowling
- Durham Veterans Affairs Geriatric Research Education and Clinical Center, Durham Veterans Affairs Medical Center (VAMC), Durham, North Carolina, USA
- Department of Medicine, Duke University, Durham, North Carolina, USA
| | - Kimberly Cannavale
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA
| | - Teresa N Harrison
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA
| | - Eva Lustigova
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA
| | - John J Sim
- Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, California, USA
- Division of Nephrology and Hypertension, Kaiser Permanente Los Angeles Medical Center, Los Angeles, California, USA
| | - Kristi Reynolds
- Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, California, USA
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA
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Alhabeeb W, Tash AA, Alshamiri M, Arafa M, Balghith MA, ALmasood A, Eltayeb A, Elghetany H, Hassan T, Alshemmari O. National Heart Center/Saudi Heart Association 2023 Guidelines on the Management of Hypertension. J Saudi Heart Assoc 2023; 35:16-39. [PMID: 37020975 PMCID: PMC10069676 DOI: 10.37616/2212-5043.1328] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Revised: 12/27/2022] [Accepted: 01/30/2023] [Indexed: 03/17/2023] Open
Abstract
Background Hypertension is a highly prevalent disease in Saudi Arabia with poor control rates. Updated guidelines are needed to guide the management of hypertension and improve treatment outcomes. Methodology A panel of experts representing the National Heart Center (NHC) and the Saudi Heart Association (SHA) reviewed existing evidence and formulated guidance relevant to the local population, clinical practice and the healthcare system. The recommendations were reviewed to ensure scientific and medical accuracy. Recommendations Hypertension was defined and a new classification was proposed as relevant to the Saudi population. Recommendations on diagnosis, clinical evaluation, cardiovascular assessment were detailed, along with guidance on measurement modalities and screening/follow-up. Non-pharmacological management is the first line of hypertension treatment. Pharmacological therapy should be used appropriately as needed. Treatment priority is to control blood pressure regardless of the drug class used. The choice of treatment should be tailored to the patient profile in order to achieve treatment targets and ensure patient compliance. Recommendations were provided on pharmacological options available in Saudi Arabia, as well as guidance on the treatment of special conditions. Conclusion Hypertension management should be based on appropriate screening, timely diagnosis and lifestyle changes supplemented with pharmacological therapy, as needed. Clinical management should be individualized, and careful consideration should be given to special conditions and patient groups.
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Affiliation(s)
- Waleed Alhabeeb
- Department of Cardiac Sciences, King Saud University, Riyadh,
Saudi Arabia
| | - Adel A. Tash
- Consultant Cardiac Surgeon, Adult Cardiac Surgery, Ministry of Health,
Saudi Arabia
| | - Mostafa Alshamiri
- Professor of Cardiac Sciences, King Saud University Medical College, Riyadh,
Saudi Arabia
| | - Mohamed Arafa
- Professor of Cardiac Sciences, King Saud University,
Saudi Arabia
| | - Mohammed A. Balghith
- Senior Cardiologist, King Abdulaziz, National Guard Hospital, Riyadh,
Saudi Arabia
| | - Ali ALmasood
- Consultant Cardiologist, Specialized Medical Center, Riyadh,
Saudi Arabia
| | - Abdulla Eltayeb
- Senior Cardiologist, Almana Group of Hospitals, Dammam,
Saudi Arabia
| | - Hossam Elghetany
- Consultant Cardiologist, Dr. Soliman Fakeeh Hospital, Jeddah,
Saudi Arabia
| | - Taher Hassan
- Consultant Cardiologist, Bugshan Center,
Saudi Arabia
| | - Owayed Alshemmari
- Consultant Cardiologist Dr. Sulaiman Alhabib Hospital, Ar-Rayyan Hospital, Riyadh,
Saudi Arabia
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Spirito A, Sticchi A, Praz F, Gräni C, Messerli F, Siontis GC. Impact of design characteristics among studies comparing coronary computed tomography angiography to noninvasive functional testing in chronic coronary syndromes. Am Heart J 2023; 256:104-116. [PMID: 36400186 DOI: 10.1016/j.ahj.2022.10.087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Revised: 10/11/2022] [Accepted: 10/13/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Coronary computed tomography angiography (CCTA) is widely adopted to detect obstructive coronary artery disease (CAD) in patients with chronic coronary syndromes (CCS). However, it is unknown to which extent study-specific characteristics yield different conclusions. METHODS We summarized non-randomized and randomized studies comparing CCTA and noninvasive functional testing for CCS with information on the outcome of myocardial infarction (MI). We evaluated the differential effect according to study characteristics using random-effect meta-analysis with Hartung-Knapp-Sidik-Jonkman adjustments. RESULTS Fifteen studies (8 non-randomized, 7 randomized) were included. CCTA was associated with decrease in relative (odds ratio (OR) 0.54, 95%CI 0.47 to 0.62, P < .001) and absolute MI risk (risk difference (RD) -0.4%, 95%CI -0.6 to -0.1, P = .005). The results remained consistent among the non-randomized (RD -0.4%, 95%CI -0.7 to -0.1, P=.029), but not among the randomized trials where there was no difference in the observed risk (RD 0.2%, 95%CI -0.6 to 0.1, P = .158). CCTA was not associated with MI reduction in studies with clinical outcome definition (OR 0.77, 95%CI 0.41 to 1.44, P = .212), research driven follow-up (OR 0.54, 95%CI 0.24 to 1.21, P = .090), central event assessment (OR 0.63, 95%CI 0.21 to 1.86, P = .207), outcome adjudication (OR 0.74, 95%CI 0.24 to 2.23, P = .178), or at low-risk of bias (OR 0.74, 95%CI 0.24 to 2.23, P = .178). CONCLUSIONS Among studies of any design, CCTA was associated with lower risk of MI in CCS compared to noninvasive functional testing. This benefit was diminished among studies with clinical outcome definition, central outcome assessment/adjudication or at low-risk of bias.
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Affiliation(s)
- Alessandro Spirito
- Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alessandro Sticchi
- Department of Cardiology, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Fabien Praz
- Department of Cardiology, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Christoph Gräni
- Department of Cardiology, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Franz Messerli
- Department of Cardiology, Bern University Hospital, University of Bern, Bern, Switzerland
| | - George Cm Siontis
- Department of Cardiology, Bern University Hospital, University of Bern, Bern, Switzerland.
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Kim Y, Kim W, Kim JK, Moon JY, Park S, Park CW, Park HS, Song SH, Yoo TH, Lee SY, Lee EY, Lee J, Jin K, Cha DR, Cha JJ, Han SY. Blood Pressure Control in Patients with Diabetic Kidney Disease. Electrolyte Blood Press 2022; 20:39-48. [PMID: 36688208 PMCID: PMC9827046 DOI: 10.5049/ebp.2022.20.2.39] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 11/21/2022] [Accepted: 12/05/2022] [Indexed: 01/06/2023] Open
Abstract
Diabetic kidney disease (DKD) is the most common cause of end-stage kidney disease. Blood pressure (BP) control can reduce the risks of cardiovascular (CV) morbidity, mortality, and kidney disease progression. Recently, the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines have suggested the implementation of a more intensive BP control with a target systolic BP (SBP) of <120 mmHg based on the evidence that the CV benefits obtained is outweighed by the kidney injury risk associated with a lower BP target. However, an extremely low BP level may paradoxically aggravate renal function and CV outcomes. Herein, we aimed to review the existing literature regarding optimal BP control using medications for DKD.
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Affiliation(s)
- Yaeni Kim
- Department of Internal Medicine, Seoul St. Mary's Hospital, The Catholic University, Seoul, Republic of Korea
| | - Won Kim
- Department of Internal Medicine, Jeonbuk National University Medical School, Jeonju, Republic of Korea
| | - Jwa-Kyung Kim
- Department of Internal Medicine & Kidney Research Institute, Hallym University Sacred Heart Hospital, Anyang, Republic of Korea
| | - Ju Young Moon
- Division of Nephrology, Department of Internal Medicine, Kyung Hee University, Seoul, Republic of Korea
| | - Samel Park
- Department of Internal Medicine, Soonchunhyang University Cheonan Hospital, Cheonan, Republic of Korea
| | - Cheol Whee Park
- Department of Internal Medicine, Seoul St. Mary's Hospital, The Catholic University, Seoul, Republic of Korea
| | - Hoon Suk Park
- Division of Nephrology, Department of Internal Medicine, Eunpyeong St. Mary's Hospital, The Catholic University, Seoul, Republic of Korea
| | - Sang Heon Song
- Department of Internal Medicine & Biomedical Research Institute, Pusan National University Hospital, Busan, Republic of Korea
| | - Tae-Hyun Yoo
- Department of Internal Medicine, College of Medicine, Institute of Kidney Disease Research, Yonsei University, Seoul, Republic of Korea
| | - So-Young Lee
- Department of Internal Medicine, CHA Bundang Medical Center, CHA University, Seongnam, Republic of Korea
| | - Eun Young Lee
- Department of Internal Medicine, Soonchunhyang University Cheonan Hospital, Cheonan, Republic of Korea
| | - Jeonghwan Lee
- Department of Internal Medicine, Seoul National University Boramae Medical Center, Seoul, Republic of Korea
| | - Kyubok Jin
- Department of Internal Medicine, Keimyung University School of Medicine, Keimyung University Kidney Institute, Daegu, Republic of Korea
| | - Dae Ryong Cha
- Department of Internal Medicine, Korea University Ansan Hospital, Ansan, Republic of Korea
| | - Jin Joo Cha
- Department of Internal Medicine, Korea University Ansan Hospital, Ansan, Republic of Korea
| | - Sang Youb Han
- Department of Internal Medicine, Inje University College of Medicine, Ilsan-Paik Hospital, Goyang, Republic of Korea
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Patterns in Prenatal Physical Activity and Sedentary Behavior: Associations With Blood Pressure and Placental Features in the MoMHealth Cohort. J Phys Act Health 2022; 19:658-665. [PMID: 36049747 DOI: 10.1123/jpah.2021-0585] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 05/13/2022] [Accepted: 07/25/2022] [Indexed: 11/18/2022]
Abstract
BACKGROUND Moderate to vigorous physical activity (MVPA) and sedentary behavior (SED) are associated with blood pressure (BP) and adverse pregnancy outcomes. The authors investigated associations of prenatal MVPA and SED patterns with BP and with placental malperfusion features. METHODS Women enrolled in this prospective cohort study in the first trimester. MVPA, SED, and BP were measured objectively each trimester. MVPA and SED trajectories were constructed. Placental examinations were conducted in a subset. Associations of trajectories with BPs were assessed with linear regression adjusted for age, race, education, prepregnancy body mass index, and gestational age. Associations with placental malperfusion lesions and weight were adjusted for key covariates. RESULTS One hundred eleven participants were included; placental exams were available in 50. Participants with high (vs low) SED were younger and more likely to have adverse pregnancy outcomes. High SED (vs low) was associated with higher first trimester systolic (β = 5.3; 95% confidence interval, 0.0 to 10.6) and diastolic (β = 5.0; 95% confidence interval, 1.4 to 8.6) and higher second trimester diastolic (β = 4.9; 95% confidence interval, 1.6 to 8.2) BP. Medium and high MVPA groups were associated with lower postpartum diastolic BP. Trajectories were not associated with placental malperfusion. CONCLUSIONS MVPA and SED patterns were differentially associated with prenatal and postpartum BP. Encouraging favorable levels of both might help women achieve lower BP during and after pregnancy.
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Hebert SA, Ibrahim HN. Hypertension Management in Patients with Chronic Kidney Disease. Methodist Debakey Cardiovasc J 2022; 18:41-49. [PMID: 36132579 PMCID: PMC9461694 DOI: 10.14797/mdcvj.1119] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Accepted: 05/03/2022] [Indexed: 11/29/2022] Open
Abstract
Hypertension and chronic kidney disease are closely linked. Patients with chronic kidney disease have hypertension almost universally and uncontrolled hypertension accelerates the decline in kidney function. The pathophysiology of hypertension in chronic kidney disease is complex, but is largely related to reduced nephron mass, sympathetic nervous system overactivation, involvement of the renin-angiotensin-aldosterone system, and generalized endothelial dysfunction. Consensus guidelines for blood pressure targets have adopted a blood pressure <120/80 mm Hg in native chronic kidney disease and <130/80 mm Hg in kidney transplant recipients. Guidelines also strongly advocate for renin-angiotensin-aldosterone system blockade as the first-line therapy.
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Affiliation(s)
- Sean A Hebert
- Department of Surgery, Division of Immunology and Organ Transplantation, The University of Texas Health Science Center at Houston (UTHealth), Houston, Texas, US
| | - Hassan N Ibrahim
- Department of Surgery, Division of Immunology and Organ Transplantation, The University of Texas Health Science Center at Houston (UTHealth), Houston, Texas, US
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10
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Lloyd-Jones DM. Cumulative Blood Pressure Measurement for Cardiovascular Disease Prediction: Promise and Pitfalls. J Am Coll Cardiol 2022; 80:1156-1158. [PMID: 36109109 DOI: 10.1016/j.jacc.2022.07.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 07/25/2022] [Indexed: 12/13/2022]
Affiliation(s)
- Donald M Lloyd-Jones
- Departments of Preventive Medicine, Medicine, and Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
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11
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Wang TD, Chiang CE, Chao TH, Cheng HM, Wu YW, Wu YJ, Lin YH, Chen MYC, Ueng KC, Chang WT, Lee YH, Wang YC, Chu PH, Chao TF, Kao HL, Hou CJY, Lin TH. 2022 Guidelines of the Taiwan Society of Cardiology and the Taiwan Hypertension Society for the Management of Hypertension. ACTA CARDIOLOGICA SINICA 2022; 38:225-325. [PMID: 35673334 PMCID: PMC9121756 DOI: 10.6515/acs.202205_38(3).20220321a] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 03/22/2022] [Indexed: 11/23/2022]
Abstract
Hypertension is the most important modifiable cause of cardiovascular (CV) disease and all-cause mortality worldwide. Despite the positive correlations between blood pressure (BP) levels and later CV events since BP levels as low as 100/60 mmHg have been reported in numerous epidemiological studies, the diagnostic criteria of hypertension and BP thresholds and targets of antihypertensive therapy have largely remained at the level of 140/90 mmHg in the past 30 years. The publication of both the SPRINT and STEP trials (comprising > 8,500 Caucasian/African and Chinese participants, respectively) provided evidence to shake this 140/90 mmHg dogma. Another dogma regarding hypertension management is the dependence on office (or clinic) BP measurements. Although standardized office BP measurements have been widely recommended and adopted in large-scale CV outcome trials, the practice of office BP measurements has never been ideal in real-world practice. Home BP monitoring (HBPM) is easy to perform, more likely to be free of environmental and/or emotional stress, feasible to document long-term BP variations, of good reproducibility and reliability, and more correlated with hypertension-mediated organ damage (HMOD) and CV events, compared to routine office BP measurements. In the 2022 Taiwan Hypertension Guidelines of the Taiwan Society of Cardiology (TSOC) and the Taiwan Hypertension Society (THS), we break these two dogmas by recommending the definition of hypertension as ≥ 130/80 mmHg and a universal BP target of < 130/80 mmHg, based on standardized HBPM obtained according to the 722 protocol. The 722 protocol refers to duplicate BP readings taken per occasion ("2"), twice daily ("2"), over seven consecutive days ("7"). To facilitate implementation of the guidelines, a series of flowcharts encompassing assessment, adjustment, and HBPM-guided hypertension management are provided. Other key messages include that: 1) lifestyle modification, summarized as the mnemonic S-ABCDE, should be applied to people with elevated BP and hypertensive patients to reduce life-time BP burden; 2) all 5 major antihypertensive drugs (angiotensin-converting enzyme inhibitors [A], angiotensin receptor blockers [A], β-blockers [B], calcium-channel blockers [C], and thiazide diuretics [D]) are recommended as first-line antihypertensive drugs; 3) initial combination therapy, preferably in a single-pill combination, is recommended for patients with BP ≥ 20/10 mmHg above targets; 4) a target hierarchy (HBPM-HMOD- ambulatory BP monitoring [ABPM]) should be considered to optimize hypertension management, which indicates reaching the HBPM target first and then keeping HMOD stable or regressed, otherwise ABPM can be arranged to guide treatment adjustment; and 5) renal denervation can be considered as an alternative BP-lowering strategy after careful clinical and imaging evaluation.
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Affiliation(s)
- Tzung-Dau Wang
- Cardiovascular Center and Divisions of Cardiology and Hospital Medicine, Department of Internal Medicine, National Taiwan University Hospital
- Department of Internal Medicine, School of Medicine, National Taiwan University College of Medicine
| | - Chern-En Chiang
- General Clinical Research Center and Division of Cardiology, Department of Medicine, Taipei Veterans General Hospital
- School of Medicine, National Yang Ming Chiao Tung University, Taipei
| | - Ting-Hsing Chao
- Department of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan
| | - Hao-Min Cheng
- School of Medicine, Institute of Public Health and Community Medicine Research Center, and Institute of Health and Welfare Policy, National Yang Ming Chiao Tung University
- Center for Evidence-based Medicine, Department of Medical Education, Taipei Veterans General Hospital, Taipei
| | - Yen-Wen Wu
- School of Medicine, National Yang Ming Chiao Tung University, Taipei
- Division of Cardiology, Cardiovascular Medical Center, and Department of Nuclear Medicine, Far Eastern Memorial Hospital
| | - Yih-Jer Wu
- Department of Medicine, Mackay Medical College, New Taipei City
- Cardiovascular Center, Department of Internal Medicine, MacKay Memorial Hospital
| | - Yen-Hung Lin
- Cardiovascular Center and Division of Cardiology, Department of Internal Medicine, National Taiwan University Hospital, Taipei
| | - Michael Yu-Chih Chen
- Division of Cardiology, Department of Internal Medicine, Buddhist Tzu Chi General Hospital, Hualien
| | - Kwo-Chang Ueng
- Department of Internal Medicine, Chung-Shan Medical University Hospital, Taichung
| | - Wei-Ting Chang
- Division of Cardiology, Department of Internal Medicine, Chi-Mei Medical Center, Tainan
| | - Ying-Hsiang Lee
- Department of Medicine, Mackay Medical College, New Taipei City
- Cardiovascular Center, Department of Internal Medicine, MacKay Memorial Hospital
| | - Yu-Chen Wang
- Division of Cardiology, Department of Medicine, Asia University Hospital
- Department of Medical Laboratory Science and Biotechnology, Asia University
- Division of Cardiology, Department of Internal Medicine, China Medical University College of Medicine and Hospital, Taichung
| | - Pao-Hsien Chu
- Department of Cardiology, Chang Gung Memorial Hospital
- School of Medicine, Chang Gung University, Taoyuan
| | - Tzu-Fan Chao
- Division of Cardiology, Department of Medicine, Taipei Veterans General Hospital
- Institute of Clinical Medicine and Cardiovascular Research Center, National Yang Ming Chiao Tung University, Taipei
| | - Hsien-Li Kao
- Department of Internal Medicine, School of Medicine, National Taiwan University College of Medicine
- Cardiovascular Center and Division of Cardiology, Department of Internal Medicine, National Taiwan University Hospital, Taipei
| | - Charles Jia-Yin Hou
- Department of Medicine, Mackay Medical College, New Taipei City
- Cardiovascular Center, Department of Internal Medicine, MacKay Memorial Hospital
| | - Tsung-Hsien Lin
- Division of Cardiology, Department of Internal Medicine Kaohsiung Medical University Hospital
- Faculty of Medicine and Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
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12
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Diaz-Garelli F, Long A, Bancks MP, Bertoni AG, Narayanan A, Wells BJ. Developing a Data Quality Standard Primer for Cardiovascular Risk Assessment from Electronic Health Record Data Using the DataGauge Process. AMIA ... ANNUAL SYMPOSIUM PROCEEDINGS. AMIA SYMPOSIUM 2022; 2021:388-397. [PMID: 35308992 PMCID: PMC8861746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The learning health systems aim to support the needs of patients with chronic diseases, which require methods that account for electronic health recorded (EHR) data limitations. EHR data is often used to calculate cardiovascular risk scores. However, it is unclear whether EHR data presents high enough quality to provide accurate estimates. Still, there is currently no open standard available to assess data quality for such applications. We applied the DataGauge process to develop a data quality standard based on expert clinical, analytical and informatics knowledge by conducting four interviews and one focus group that produced 61 individual data quality requirements. These requirements covered all standard data quality dimensions and uncovered 705 quality issues in EHR data for 456 patients. These requirements will be expanded and further validated in future work. Our work initiates the development of open and explicit data quality standards for specific secondary uses of clinical data.
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Affiliation(s)
| | - Andrew Long
- University of North Carolina at Charlotte. Charlotte NC
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13
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Sakhuja S, Jaeger BC, Akinyelure OP, Bress AP, Shimbo D, Schwartz JE, Hardy ST, Howard G, Drawz P, Muntner P. Potential impact of systematic and random errors in blood pressure measurement on the prevalence of high office blood pressure in the United States. J Clin Hypertens (Greenwich) 2022; 24:263-270. [PMID: 35137521 PMCID: PMC8925005 DOI: 10.1111/jch.14418] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 11/22/2021] [Accepted: 12/08/2021] [Indexed: 11/29/2022]
Abstract
The authors examined the proportion of US adults that would have their high blood pressure (BP) status changed if systolic BP (SBP) and diastolic BP (DBP) were measured with systematic bias and/or random error versus following a standardized protocol. Data from the 2017-2018 National Health and Nutrition Examination Survey (NHANES; n = 5176) were analyzed. BP was measured up to three times using a mercury sphygmomanometer by a trained physician following a standardized protocol and averaged. High BP was defined as SBP ≥130 mm Hg or DBP ≥80 mm Hg. Among US adults not taking antihypertensive medication, 32.0% (95%CI: 29.6%,34.4%) had high BP. If SBP and DBP were measured with systematic bias, 5 mm Hg for SBP and 3.5 mm Hg for DBP higher and lower than in NHANES, the proportion with high BP was estimated to be 44.4% (95%CI: 42.6%,46.2%) and 21.9% (95%CI 19.5%,24.4%). Among US adults taking antihypertensive medication, 60.6% (95%CI: 57.2%,63.9%) had high BP. If SBP and DBP were measured 5 and 3.5 mm Hg higher and lower than in NHANES, the proportion with high BP was estimated to be 71.8% (95%CI: 68.3%,75.0%) and 48.4% (95%CI: 44.6%,52.2%), respectively. If BP was measured with random error, with standard deviations of 15 mm Hg for SBP and 7 mm Hg for DBP, 21.4% (95%CI: 19.8%,23.0%) of US adults not taking antihypertensive medication and 20.5% (95%CI: 17.7%,23.3%) taking antihypertensive medication had their high BP status re-categorized. In conclusions, measuring BP with systematic or random errors may result in the misclassification of high BP for a substantial proportion of US adults.
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Affiliation(s)
- Swati Sakhuja
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Byron C Jaeger
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | | | - Adam P Bress
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Daichi Shimbo
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Joseph E Schwartz
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA.,Department of Psychiatry and Behavioral Health, Renaissance School of Medicine, Stony Brook, New York, USA
| | - Shakia T Hardy
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - George Howard
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Paul Drawz
- Division of Nephrology and Hypertension, University of Minnesota, Minneapolis, Minnesota, USA
| | - Paul Muntner
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
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14
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Rethy LB, McCabe ME, Kershaw KN, Ahmad FS, Lagu T, Pool LR, Khan SS. Neighborhood Poverty and Incident Heart Failure: an Analysis of Electronic Health Records from 2005 to 2018. J Gen Intern Med 2021; 36:3719-3727. [PMID: 33963504 PMCID: PMC8642536 DOI: 10.1007/s11606-021-06785-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 03/31/2021] [Indexed: 01/09/2023]
Abstract
BACKGROUND Neighborhood-level characteristics, such as poverty, have been associated with risk factors for heart failure (HF), including hypertension and diabetes mellitus. However, the independent association between neighborhood poverty and incident HF remains understudied. OBJECTIVE To evaluate the association between neighborhood poverty and incident HF using a "real-world" clinical cohort. DESIGN Retrospective cohort study of electronic health records from a large healthcare network. Individuals' residential addresses were geocoded at the census-tract level and categorized by poverty tertiles based on American Community Survey data (2007-2011). PARTICIPANTS Patients from Northwestern Medicine who were 30-80 years, free of cardiovascular disease at index visit (January 1, 2005-December 1, 2013), and followed for at least 5 years. MAIN MEASURES The association of neighborhood-level poverty tertile (low, intermediate, and high) and incident HF was analyzed using generalized linear mixed effect models adjusting for demographics (age, sex, race/ethnicity) and HF risk factors (body mass index, diabetes mellitus, hypertension, smoking status). KEY RESULTS Of 28,858 patients included, 75% were non-Hispanic (NH) White, 43% were men, 15% lived in a high-poverty neighborhood, and 522 (1.8%) were diagnosed with incident HF. High-poverty neighborhoods were associated with a 1.80 (1.35, 2.39) times higher risk of incident HF compared with low-poverty neighborhoods after adjustment for demographics and HF risk factors. CONCLUSIONS In a large healthcare network, incident HF was associated with neighborhood poverty independent of demographic and clinical risk factors. Neighborhood-level interventions may be needed to complement individual-level strategies to prevent and curb the growing burden of HF.
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Affiliation(s)
- Leah B Rethy
- Deparment of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Megan E McCabe
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Kiarri N Kershaw
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Faraz S Ahmad
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Tara Lagu
- Division of Hospital Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Lindsay R Pool
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Sadiya S Khan
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA.
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
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15
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Lane-Cordova AD, Wilcox S, Fernhall B, Liu J. Agreement between blood pressure from research study visits versus electronic medical records and associations with hypertensive disorder diagnoses in pregnant women with overweight/obesity. Blood Press Monit 2021; 26:341-347. [PMID: 34001756 PMCID: PMC8419020 DOI: 10.1097/mbp.0000000000000542] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVES Blood pressure (BP) abstracted from electronic medical records (EMR) is moderately correlated to BP in nonpregnant adults with limited agreement. Little is known about the agreement of research versus EMR BP measured during pregnancy or associations of EMR BP with hypertensive disorder of pregnancy (HDP) diagnoses. METHODS BP was measured according to guidelines at in-person research study visits in 214 women with prepregnancy overweight or obesity (44.4% African American, mean age = 29.8 ± 4.8 years) at weeks 16 and 32 of pregnancy. Clinic BP readings that occurred within 1 week of the study visits were abstracted from the EMR. We assessed correlations between sources using Pearson's coefficients; the agreement was evaluated with Bland-Altman plots. We compared differences in the proportion of women with an HDP diagnosis in the EMR between women with versus without a hypertensive EMR BP measurement. RESULTS SBP and DBP from study visits and the EMR were modestly moderately correlated at both time points; 0.20 < r < 0.44; P < 0.05 for all. The average mean difference was 10.5 mmHg for SBP and <1 mmHg for DBP in early and 7.3 mmHg for SBP and -1.7 mmHg for DBP in late pregnancy. Women with at least one hypertensive BP reading in the EMR were more likely to have an HDP diagnosis recorded in the EMR; 43.5 versus 3.3%; P < 0.01. CONCLUSION EMR SBP was higher but moderately correlated with research quality BP in early and late pregnancy. Women with a hypertensive EMR BP measurement were more likely to have an HDP diagnosis in the EMR.
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Affiliation(s)
- Abbi D Lane-Cordova
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina
| | - Sara Wilcox
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina
| | - Bo Fernhall
- Department of Kinesiology and Nutrition, College of Applied Health Sciences, University of Illinois at Chicago, Chicago, Illinois
| | - Jihong Liu
- Department of Epidemiology and Biostatistics, Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA
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16
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Zhou M, Wang Q, Zheng C, John Rush A, Volkow ND, Xu R. Drug repurposing for opioid use disorders: integration of computational prediction, clinical corroboration, and mechanism of action analyses. Mol Psychiatry 2021; 26:5286-5296. [PMID: 33432189 PMCID: PMC7797705 DOI: 10.1038/s41380-020-01011-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 12/11/2020] [Accepted: 12/17/2020] [Indexed: 12/13/2022]
Abstract
Morbidity and mortality from opioid use disorders (OUD) and other substance use disorders (SUD) is a major public health crisis, yet there are few medications to treat them. There is an urgency to accelerate SUD medication development. We present an integrated drug repurposing strategy that combines computational prediction, clinical corroboration using electronic health records (EHRs) of over 72.9 million patients and mechanisms of action analysis. Among top-ranked repurposed candidate drugs, tramadol, olanzapine, mirtazapine, bupropion, and atomoxetine were associated with increased odds of OUD remission (adjusted odds ratio: 1.51 [1.38-1.66], 1.90 [1.66-2.18], 1.38 [1.31-1.46], 1.37 [1.29-1.46], 1.48 [1.25-1.76], p value < 0.001, respectively). Genetic and functional analyses showed these five candidate drugs directly target multiple OUD-associated genes including BDNF, CYP2D6, OPRD1, OPRK1, OPRM1, HTR1B, POMC, SLC6A4 and OUD-associated pathways, including opioid signaling, G-protein activation, serotonin receptors, and GPCR signaling. In summary, we developed an integrated drug repurposing approach and identified five repurposed candidate drugs that might be of value for treating OUD patients, including those suffering from comorbid conditions.
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Affiliation(s)
- Mengshi Zhou
- Center for Artificial Intelligence in Drug Discovery, Case Western Reserve University, Cleveland, OH, USA
- Department of Mathematics & Statistics, Saint Cloud State University, Saint Cloud, MN, USA
| | - QuanQiu Wang
- Center for Artificial Intelligence in Drug Discovery, Case Western Reserve University, Cleveland, OH, USA
| | - Chunlei Zheng
- Center for Artificial Intelligence in Drug Discovery, Case Western Reserve University, Cleveland, OH, USA
| | - A John Rush
- Duke University School of Medicine, Durham, NC, USA
- Duke-National University of Singapore, Singapore, Singapore
- Texas-Tech Health Sciences Center, Permian Basin, Odessa, TX, USA
| | - Nora D Volkow
- National Institute on Drug Abuse, National Institutes of Health, Bethesda, MD, USA
| | - Rong Xu
- Center for Artificial Intelligence in Drug Discovery, Case Western Reserve University, Cleveland, OH, USA.
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Wang Q, Davis PB, Gurney ME, Xu R. COVID-19 and dementia: Analyses of risk, disparity, and outcomes from electronic health records in the US. Alzheimers Dement 2021; 17:1297-1306. [PMID: 33559975 PMCID: PMC8014535 DOI: 10.1002/alz.12296] [Citation(s) in RCA: 144] [Impact Index Per Article: 48.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2020] [Revised: 11/06/2020] [Accepted: 12/18/2020] [Indexed: 01/05/2023]
Abstract
INTRODUCTION At present, there is limited data on the risks, disparity, and outcomes for COVID-19 in patients with dementia in the United States. METHODS This is a retrospective case-control analysis of patient electronic health records (EHRs) of 61.9 million adult and senior patients (age ≥ 18 years) in the United States up to August 21, 2020. RESULTS Patients with dementia were at increased risk for COVID-19 compared to patients without dementia (adjusted odds ratio [AOR]: 2.00 [95% confidence interval (CI), 1.94-2.06], P < .001), with the strongest effect for vascular dementia (AOR: 3.17 [95% CI, 2.97-3.37], P < .001), followed by presenile dementia (AOR: 2.62 [95% CI, 2.28-3.00], P < .001), Alzheimer's disease (AOR: 1.86 [95% CI, 1.77-1.96], P < .001), senile dementia (AOR: 1.99 [95% CI, 1.86-2.13], P < .001) and post-traumatic dementia (AOR: 1.67 [95% CI, 1.51-1.86] P < .001). Blacks with dementia had higher risk of COVID-19 than Whites (AOR: 2.86 [95% CI, 2.67-3.06], P < .001). The 6-month mortality and hospitalization risks in patients with dementia and COVID-19 were 20.99% and 59.26%, respectively. DISCUSSION These findings highlight the need to protect patients with dementia as part of the strategy to control the COVID-19 pandemic.
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Affiliation(s)
- QuanQiu Wang
- Center for Artificial Intelligence in Drug DiscoverySchool of MedicineCase Western Reserve UniversityClevelandOhioUSA
| | - Pamela B. Davis
- Center for Clinical InvestigationSchool of MedicineCase Western Reserve UniversityClevelandOhioUSA
| | | | - Rong Xu
- Center for Artificial Intelligence in Drug DiscoverySchool of MedicineCase Western Reserve UniversityClevelandOhioUSA
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18
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Rivera AS, Sinha A, Ahmad FS, Thorp E, Wilcox JE, Lloyd-Jones DM, Feinstein MJ. Long-Term Trajectories of Left Ventricular Ejection Fraction in Patients With Chronic Inflammatory Diseases and Heart Failure: An Analysis of Electronic Health Records. Circ Heart Fail 2021; 14:e008478. [PMID: 34372666 PMCID: PMC8373674 DOI: 10.1161/circheartfailure.121.008478] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Accepted: 05/26/2021] [Indexed: 11/16/2022]
Abstract
BACKGROUND Immune regulation and inflammation play a role in the pathogenesis and progression of acute and chronic heart failure (HF). Although the clinical course of acute, severe inflammatory cardiomyopathy is well described, the effects of chronic systemic inflammation on cardiovascular function over time are less clear. To investigate this question, we compared trajectories over time in left ventricular ejection fraction for patients with HF with different chronic inflammatory diseases (CIDs): HIV, systemic lupus erythematosus, systemic sclerosis, rheumatoid arthritis, inflammatory bowel disease, and/or psoriasis. METHODS Using a database of patients receiving care in a large metropolitan health care system since January 1, 2000, we analyzed serial, clinically indicated echocardiograms from patients with HF with CIDs and frequency-matched patients with HF without CIDs. We included patients with ≥3 serial echocardiograms (N=974; median 6.1 years between first and most recent echo). We assessed left ventricular ejection fraction trajectories over time using latent trajectory models, then investigated differences in left ventricular ejection fraction trajectories for specific CID subtypes compared with controls. RESULTS Overall, the majority of patients studied (N=687; 70.5%) had left ventricular ejection fraction trajectories consistent with HF with preserved or midrange EF, whereas 255 (26.2%) had HF with reduced EF and 32 (3.3%) had HF with recovered EF. Compared with non-CID controls with HF, patients with rheumatoid arthritis, inflammatory bowel disease, and systemic lupus erythematosus were significantly more likely than controls to have HF with preserved or midrange EF whereas patients with HIV were significantly more likely to have HF with reduced EF. CONCLUSIONS Among patients with HF with CIDs, distinct left ventricular ejection fraction trajectory patterns associate with different specific individual CIDs. This highlights the heterogeneity of HF subtypes and changes over time across different CIDs.
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Affiliation(s)
- Adovich S. Rivera
- Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine
| | - Arjun Sinha
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine
| | - Faraz S. Ahmad
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine
| | - Edward Thorp
- Department of Pathology, Northwestern University Feinberg School of Medicine
| | - Jane E. Wilcox
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine
| | - Donald M. Lloyd-Jones
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine
| | - Matthew J. Feinstein
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine
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19
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Sandhu AT, Tisdale RL, Rodriguez F, Stafford RS, Maron DJ, Hernandez-Boussard T, Lewis E, Heidenreich PA. Disparity in the Setting of Incident Heart Failure Diagnosis. Circ Heart Fail 2021; 14:e008538. [PMID: 34311559 PMCID: PMC9070116 DOI: 10.1161/circheartfailure.121.008538] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
BACKGROUND Early heart failure (HF) recognition can reduce morbidity, yet HF is often initially diagnosed only after a patient clinically worsens. We sought to identify characteristics that predict diagnosis in the acute care setting versus the outpatient setting. METHODS We estimated the proportion of incident HF diagnosed in the acute care setting (inpatient hospital or emergency department) versus outpatient setting based on diagnostic codes from a claims database covering commercial insurance and Medicare Advantage between 2003 and 2019. After excluding new-onset HF potentially caused by a concurrent acute cause (eg, acute myocardial infarction), we identified demographic, clinical, and socioeconomic predictors of diagnosis setting. Patients were linked to their primary care clinicians to evaluate diagnosis setting variation across clinicians. RESULTS Of 959 438 patients with new HF, 38% were diagnosed in acute care. Of these, 46% had potential HF symptoms in the prior 6 months. Over time, the relative odds of acute care diagnosis increased by 3.2% annually after adjustment for patient characteristics (95% CI, 3.1%-3.3%). Acute care diagnosis setting was more likely for women compared with men (adjusted odds ratio, 1.11 [95% CI, 1.10-1.12]) and for Black patients compared with White patients (adjusted odds ratio, 1.18 [95% CI, 1.16-1.19]). The proportion of acute care diagnosis varied substantially (interquartile range: 24%-39%) among clinicians after adjusting for patient-level risk factors. CONCLUSIONS A large proportion of first HF diagnoses occur in the acute care setting, particularly among women and Black patients, yet many had potential HF symptoms in the months before acute care visits. These results raise concerns that many HF diagnoses are missed in the outpatient setting. Earlier diagnosis could allow for timelier high-value interventions, addressing disparities and reducing the progression of HF.
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Affiliation(s)
- Alexander T Sandhu
- Division of Cardiovascular Medicine and the Cardiovascular Institute, Department of Medicine (A.T.S., F.R., D.J.M., E.L., P.A.H.), Stanford University, CA
| | - Rebecca L Tisdale
- Veteran's Affairs Palo Alto Healthcare System, CA (R.L.T., P.A.H.).,Stanford Health Policy, Centers for Health Policy/Primary Care and Outcomes Research, Department of Medicine, Stanford University School of Medicine, CA (R.L.T.)
| | - Fatima Rodriguez
- Division of Cardiovascular Medicine and the Cardiovascular Institute, Department of Medicine (A.T.S., F.R., D.J.M., E.L., P.A.H.), Stanford University, CA.,Stanford Prevention Research Center, Stanford University School of Medicine, CA (F.R., R.S.S., D.J.M.)
| | - Randall S Stafford
- Stanford Prevention Research Center, Stanford University School of Medicine, CA (F.R., R.S.S., D.J.M.)
| | - David J Maron
- Division of Cardiovascular Medicine and the Cardiovascular Institute, Department of Medicine (A.T.S., F.R., D.J.M., E.L., P.A.H.), Stanford University, CA.,Stanford Prevention Research Center, Stanford University School of Medicine, CA (F.R., R.S.S., D.J.M.)
| | - Tina Hernandez-Boussard
- Department of Medicine (R.S.S., T.H.-B.), and Department of Biomedical Data Sciences (T.H.-B.), Stanford University, CA
| | - Eldrin Lewis
- Division of Cardiovascular Medicine and the Cardiovascular Institute, Department of Medicine (A.T.S., F.R., D.J.M., E.L., P.A.H.), Stanford University, CA
| | - Paul A Heidenreich
- Division of Cardiovascular Medicine and the Cardiovascular Institute, Department of Medicine (A.T.S., F.R., D.J.M., E.L., P.A.H.), Stanford University, CA.,Veteran's Affairs Palo Alto Healthcare System, CA (R.L.T., P.A.H.)
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20
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Lee JY, Han SH. Blood pressure control in patients with chronic kidney disease. Korean J Intern Med 2021; 36:780-794. [PMID: 34153181 PMCID: PMC8273817 DOI: 10.3904/kjim.2021.181] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 05/17/2021] [Indexed: 12/26/2022] Open
Abstract
Uncontrolled blood pressure (BP) in patients with chronic kidney disease (CKD) can lead to serious adverse outcomes. To prevent the occurrence of cardiovascular events (CVEs), and end-stage kidney disease, achieving an optimal BP level is important. Recently, there has been a paradigm shift in the management of BP largely as a result of the Systolic Blood Pressure Intervention Trial (SPRINT), which showed a reduction in CVEs by lowering systolic BP to 120 mmHg. A lower systolic blood pressure (SBP) target has been accepted by the Kidney Disease: Improving Global Outcomes (KDIGO) 2021 guidelines. However, whether intensive control of SBP targeting < 120 mmHg is also effective in patients with CKD is controversial. Notably, this lower target SBP is associated with a higher risk of adverse kidney outcomes. Unfortunately, there have been no randomized controlled trials on this issue involving only patients with CKD, particularly those with advanced CKD. In this review, we discuss the optimal control of BP in patients with CKD in terms of reduction in death and CVEs as well as attenuation of CKD progression based on the evidence-based literature.
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Affiliation(s)
| | - Seung Hyeok Han
- Correspondence to Seung Hyeok Han, M.D. Department of Internal Medicine, Institute of Kidney Disease Research, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea Tel: +82-2-2228-1984 Fax: +82-2-393-6884 E-mail:
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21
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Naccarelli GV, Ruzieh M, Wolbrette DL, Sendra-Ferrer M, van Harskamp J, Bentz B, Caputo G, McConkey N, Mills K, Wasemiller S, Plamenac J, Leslie D, Glasser FD, Abendroth TW. Oral Anticoagulation Use in High-Risk Patients Is Improved by Elimination of False-Positive and Inactive Atrial Fibrillation Cases. Am J Med 2021; 134:e366-e373. [PMID: 33359273 DOI: 10.1016/j.amjmed.2020.11.024] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 11/04/2020] [Accepted: 11/10/2020] [Indexed: 11/28/2022]
Abstract
BACKGROUND Multiple registries have reported that >40% of high-risk atrial fibrillation patients are not taking oral anticoagulants. The purpose of our study was to determine the presence or absence of active atrial fibrillation and CHA2DS2-VASc (Congestive heart failure, Hypertension, Age ≥75 y, Diabetes mellitus, prior Stroke [or transient ischemic attack or thromboembolism], Vascular disease, Age 65-74 y, Sex category) risk factors to accurately identify high-risk atrial fibrillation (CHA2DS2-VASc ≥2) patients requiring oral anticoagulants and the magnitude of the anticoagulant treatment gap. METHODS We retrospectively adjudicated 6514 patients with atrial fibrillation documented by at least one of: billing diagnosis, electronic medical record encounter diagnosis, electronic medical record problem list, or electrocardiogram interpretation. RESULTS After review, 4555/6514 (69.9%) had active atrial fibrillation, while 1201 had no documented history of atrial fibrillation and 758 had a history of atrial fibrillation that was no longer active. After removing the 1201 patients without a confirmed atrial fibrillation diagnosis, oral anticoagulant use in high-risk patients increased to 71.1% (P < .0001 compared with 62.9% at baseline). Oral anticoagulant use increased to 79.7% when the 758 inactive atrial fibrillation patients were also eliminated from the analysis (P < .0001 compared with baseline). In the active high-risk atrial fibrillation group, there was no significant difference in the use of oral anticoagulants between men (80.7%) and women (78.8%) with a CHA2DS2-VASc ≥2, or in women with a CHA2DS2-VASc ≥3 (79.9%). CONCLUSIONS Current registries and health system health records with unadjudicated diagnoses over-report the number of high-risk atrial fibrillation patients not taking oral anticoagulants. Expert adjudication identifies a smaller treatment gap than previously described.
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Affiliation(s)
- Gerald V Naccarelli
- Penn State University Heart and Vascular Institute, Penn State University College of Medicine, Hershey, Pa.
| | | | - Deborah L Wolbrette
- Penn State University Heart and Vascular Institute, Penn State University College of Medicine, Hershey, Pa
| | - Mauricio Sendra-Ferrer
- Division of Cardiovascular Medicine, University of Missouri School of Medicine, Columbia
| | | | - Barbara Bentz
- Penn State University Heart and Vascular Institute, Penn State University College of Medicine, Hershey, Pa
| | - Gregory Caputo
- Division of Internal Medicine, Penn State University College of Medicine, Hershey, Pa
| | - Nathan McConkey
- Penn State University Heart and Vascular Institute, Penn State University College of Medicine, Hershey, Pa
| | - Kevin Mills
- Penn State University Heart and Vascular Institute, Penn State University College of Medicine, Hershey, Pa
| | | | - Jovan Plamenac
- Penn State University Heart and Vascular Institute, Penn State University College of Medicine, Hershey, Pa
| | - Douglas Leslie
- Department of Public Health Sciences, Penn State University College of Medicine, Hershey, Pa
| | - Frendy D Glasser
- Penn State University Center for Quality Innovation, Hershey, Pa
| | - Thomas W Abendroth
- Penn State University Center for Quality Innovation, Hershey, Pa; Penn State University College of Medicine, Penn State Health, The Milton S. Hershey Medical Center, Hershey, Pa
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22
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Rodrigues C, Odutayo A, Patel S, Agarwal A, da Costa BR, Lin E, Yeh RW, Jüni P, Goodman SG, Farkouh ME, Udell JA. Accuracy of Cardiovascular Trial Outcome Ascertainment and Treatment Effect Estimates from Routine Health Data: A Systematic Review and Meta-Analysis. CIRCULATION. CARDIOVASCULAR QUALITY AND OUTCOMES 2021; 14:e007903. [PMID: 33993728 DOI: 10.1161/circoutcomes.120.007903] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Registry-based randomized controlled trials allow for outcome ascertainment using routine health data (RHD). While this method provides a potential solution to the rising cost and complexity of clinical trials, comparative analyses of outcome ascertainment by clinical end point committee (CEC) adjudication compared with RHD sources are sparse. Among cardiovascular trials, we set out to systematically compare the incidence of cardiovascular events and estimated randomized treatment effects ascertained from RHD versus traditional clinical evaluation and adjudication. METHODS We searched MEDLINE (1976 to August 2020) for studies where outcome ascertainment was performed by both RHD and CEC adjudication to compare the incidence of cardiovascular events and treatment effects. We derived ratios of hazard ratios to compare treatment effects from RHD and CEC adjudication. We pooled ratios of hazard ratios using an inverse variance random-effects meta-analysis. RESULTS Nine studies (1988-2020; 32 156 patients) involving 10 randomized control trials compared outcome ascertainment with RHD and CEC in patients with or at risk of cardiovascular disease. There was a high degree of agreement and interrater reliability between CEC and RHD outcome determination for all-cause mortality (agreement percentage: 98.4%-100% and κ: 0.95-1.0) and cardiovascular mortality (agreement percentage: 97.8%-99.9% and κ: 0.66-0.99). For myocardial infarction, the κ values ranged from 0.67-0.98, and for stroke the values ranged from 0.52-0.89. In contrast, the κ value for peripheral artery disease was low (κ: 0.27). There was little difference in the randomized treatment effect derived from CEC and RHD ascertainment of events based on the ratios of hazard ratio, with pooled ratios of hazard ratios ranging from 0.93 (95% CI, 0.63-1.39) for cardiovascular mortality to 1.27 (95% CI, 0.67-2.41) for stroke. CONCLUSIONS Clinical outcome ascertainment using retrospectively acquired RHD displayed high levels of agreement with CEC adjudication for identifying all-cause mortality and cardiovascular outcomes. Importantly, cardiovascular treatment effects in randomized control trials determined from RHD and CEC resulted in similar point estimates. Overall, our review supports the use of RHD as a potential alternative source for clinical outcome ascertainment in cardiovascular trials. Validation studies with prospectively planned linkage are warranted.
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Affiliation(s)
- Craig Rodrigues
- Women's College Research Institute, Toronto, Canada (C.R., S.P., E.L., J.A.U.).,School of Medicine, Queen's University, Kingston, Canada (C.R.)
| | - Ayodele Odutayo
- Applied Health Research Centre, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Canada (A.O., B.R.d.C., P.J., S.G.G., M.E.F., J.A.U.).,Department of Medicine, Faculty of Medicine (A.O., S.P., A.A., P.J., S.G.G., M.E.F., J.A.U.), University of Toronto, Toronto, Canada
| | - Sagar Patel
- Women's College Research Institute, Toronto, Canada (C.R., S.P., E.L., J.A.U.).,Department of Medicine, Faculty of Medicine (A.O., S.P., A.A., P.J., S.G.G., M.E.F., J.A.U.), University of Toronto, Toronto, Canada
| | - Arnav Agarwal
- Department of Medicine, Faculty of Medicine (A.O., S.P., A.A., P.J., S.G.G., M.E.F., J.A.U.), University of Toronto, Toronto, Canada
| | - Bruno Roza da Costa
- Applied Health Research Centre, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Canada (A.O., B.R.d.C., P.J., S.G.G., M.E.F., J.A.U.).,Institute of Health Policy, Management, and Evaluation (B.R.d.C., P.J., J.A.U.), University of Toronto, Toronto, Canada.,Institute of Primary Health Care (BIHAM), University of Bern, Switzerland (B.R.d.C.)
| | - Ethan Lin
- Women's College Research Institute, Toronto, Canada (C.R., S.P., E.L., J.A.U.).,Faculty of Medicine, University of Ottawa, Canada (E.L.)
| | - Robert W Yeh
- Smith Center for Outcomes Research, Beth Israel Deaconess Medical Center, Boston, MA (R.W.Y.)
| | - Peter Jüni
- Applied Health Research Centre, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Canada (A.O., B.R.d.C., P.J., S.G.G., M.E.F., J.A.U.).,Department of Medicine, Faculty of Medicine (A.O., S.P., A.A., P.J., S.G.G., M.E.F., J.A.U.), University of Toronto, Toronto, Canada.,Institute of Health Policy, Management, and Evaluation (B.R.d.C., P.J., J.A.U.), University of Toronto, Toronto, Canada
| | - Shaun G Goodman
- Applied Health Research Centre, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Canada (A.O., B.R.d.C., P.J., S.G.G., M.E.F., J.A.U.).,Department of Medicine, Faculty of Medicine (A.O., S.P., A.A., P.J., S.G.G., M.E.F., J.A.U.), University of Toronto, Toronto, Canada
| | - Michael E Farkouh
- Applied Health Research Centre, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Canada (A.O., B.R.d.C., P.J., S.G.G., M.E.F., J.A.U.).,Department of Medicine, Faculty of Medicine (A.O., S.P., A.A., P.J., S.G.G., M.E.F., J.A.U.), University of Toronto, Toronto, Canada.,Peter Munk Cardiac Centre, University Health Network, Toronto, Canada (M.E.F., J.A.U.)
| | - Jacob A Udell
- Women's College Research Institute, Toronto, Canada (C.R., S.P., E.L., J.A.U.).,Applied Health Research Centre, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Canada (A.O., B.R.d.C., P.J., S.G.G., M.E.F., J.A.U.).,Department of Medicine, Faculty of Medicine (A.O., S.P., A.A., P.J., S.G.G., M.E.F., J.A.U.), University of Toronto, Toronto, Canada.,Institute of Health Policy, Management, and Evaluation (B.R.d.C., P.J., J.A.U.), University of Toronto, Toronto, Canada.,Peter Munk Cardiac Centre, University Health Network, Toronto, Canada (M.E.F., J.A.U.).,ICES, Toronto, Canada (J.A.U.).,Cardiovascular Division, Department of Medicine, Women's College Hospital, Toronto, Canada (J.A.U.)
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23
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Wang Q, Berger NA, Xu R. When hematologic malignancies meet COVID-19 in the United States: Infections, death and disparities. Blood Rev 2021; 47:100775. [PMID: 33187811 PMCID: PMC7833659 DOI: 10.1016/j.blre.2020.100775] [Citation(s) in RCA: 53] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 10/29/2020] [Accepted: 11/04/2020] [Indexed: 02/06/2023]
Abstract
Scientific data is limited on the risks, adverse outcomes and racial disparities for COVID-19 illness in individuals with hematologic malignancies in the United States. To fill this void, we screened and analyzed a nation-wide database of patient electronic health records (EHRs) of 73 million patients in the US (up to September 1st) for COVID-19 and eight major types of hematologic malignancies. Patients with hematologic malignancies had increased odds of COVID-19 infection compared with patients without hematologic malignancies for both all-time diagnosis (malignancy diagnosed in the past year or prior) (adjusted Odds ratio or AOR: 2.27 [2.17-2.36], p < 0.001) and recent diagnosis (malignancy diagnosed in the past year) (AOR:11.91 [11.31-12.53], p < 0.001), with strongest effect for recently diagnosed acute lymphoid leukemia (AOR: 31.03 [25.87-37.27], p < 0.001), essential thrombocythemia (AOR: 20.65 [19.10-22.32], p < 0.001), acute myeloid leukemia (AOR: 18.94 [15.79-22.73], p < 0.001), multiple myeloma (AOR: 14.21 [12.72-15.89], p < 0.001). Among patients with hematologic malignancies, African Americans had higher odds of COVID-19 infection than Caucasians with largest racial disparity for multiple myeloma (AOR: 4.23 [3.21-5.56], p < 0.001). Patients with recently diagnosed hematologic malignancies had worse outcomes (hospitalization: 51.9%, death: 14.8%) than COVID-19 patients without hematologic malignancies (hospitalization: 23.5%, death: 5.1%) (p < 0.001) and hematologic malignancy patients without COVID-19 (hospitalization: 15.0%, death: 4.1%) (p < 0.001).
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Affiliation(s)
- QuanQiu Wang
- Center for Artificial Intelligence in Drug Discovery, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Nathan A Berger
- Center for Science, Health, and Society, School of Medicine, Case Western Reserve University, Cleveland, OH, USA; Case Comprehensive Cancer Center, School of Medicine, Case Western Reserve University, Cleveland, OH, USA.
| | - Rong Xu
- Center for Artificial Intelligence in Drug Discovery, School of Medicine, Case Western Reserve University, Cleveland, OH, USA; Case Comprehensive Cancer Center, School of Medicine, Case Western Reserve University, Cleveland, OH, USA.
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24
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Cheung AK, Chang TI, Cushman WC, Furth SL, Hou FF, Ix JH, Knoll GA, Muntner P, Pecoits-Filho R, Sarnak MJ, Tobe SW, Tomson CR, Mann JF. KDIGO 2021 Clinical Practice Guideline for the Management of Blood Pressure in Chronic Kidney Disease. Kidney Int 2021; 99:S1-S87. [PMID: 33637192 DOI: 10.1016/j.kint.2020.11.003] [Citation(s) in RCA: 412] [Impact Index Per Article: 137.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 11/02/2020] [Indexed: 12/19/2022]
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25
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Wang Q, Xu R, Volkow ND. Increased risk of COVID-19 infection and mortality in people with mental disorders: analysis from electronic health records in the United States. World Psychiatry 2021; 20:124-130. [PMID: 33026219 PMCID: PMC7675495 DOI: 10.1002/wps.20806] [Citation(s) in RCA: 412] [Impact Index Per Article: 137.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Concerns have been expressed that persons with a pre-existing mental disorder may represent a population at increased risk for COVID-19 infec-tion and with a higher likelihood of adverse outcomes of the infection, but there is no systematic research evidence in this respect. This study assessed the impact of a recent (within past year) diagnosis of a mental disorder - including attention-deficit/hyperactivity disorder (ADHD), bipolar disorder, depression and schizophrenia - on the risk for COVID-19 infection and related mortality and hospitalization rates. We analyzed a nation-wide database of electronic health records of 61 million adult patients from 360 hospitals and 317,000 providers, across 50 states in the US, up to July 29, 2020. Patients with a recent diagnosis of a mental disorder had a significantly increased risk for COVID-19 infection, an effect strongest for depression (adjusted odds ratio, AOR=7.64, 95% CI: 7.45-7.83, p<0.001) and schizophrenia (AOR=7.34, 95% CI: 6.65-8.10, p<0.001). Among patients with a recent diagnosis of a mental disorder, African Americans had higher odds of COVID-19 infection than Caucasians, with the strongest ethnic disparity for depression (AOR=3.78, 95% CI: 3.58-3.98, p<0.001). Women with mental disorders had higher odds of COVID-19 infection than males, with the strongest gender disparity for ADHD (AOR=2.03, 95% CI: 1.73-2.39, p<0.001). Patients with both a recent diagnosis of a mental disorder and COVID-19 infection had a death rate of 8.5% (vs. 4.7% among COVID-19 patients with no mental disorder, p<0.001) and a hospitalization rate of 27.4% (vs. 18.6% among COVID-19 patients with no mental disorder, p<0.001). These findings identify individuals with a recent diagnosis of a mental disorder as being at increased risk for COVID-19 infection, which is further exacerbated among African Americans and women, and as having a higher frequency of some adverse outcomes of the infection. This evidence highlights the need to identify and address modifiable vulnerability factors for COVID-19 infection and to prevent delays in health care provision in this population.
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Affiliation(s)
- QuanQiu Wang
- Center for Artificial Intelligence in Drug Discovery, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Rong Xu
- Center for Artificial Intelligence in Drug Discovery, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Nora D Volkow
- National Institute on Drug Abuse, National Institutes of Health, Bethesda, MD, USA
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26
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Lee S, Doktorchik C, Martin EA, D'Souza AG, Eastwood C, Shaheen AA, Naugler C, Lee J, Quan H. Electronic Medical Record-Based Case Phenotyping for the Charlson Conditions: Scoping Review. JMIR Med Inform 2021; 9:e23934. [PMID: 33522976 PMCID: PMC7884219 DOI: 10.2196/23934] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 11/20/2020] [Accepted: 12/05/2020] [Indexed: 12/16/2022] Open
Abstract
Background Electronic medical records (EMRs) contain large amounts of rich clinical information. Developing EMR-based case definitions, also known as EMR phenotyping, is an active area of research that has implications for epidemiology, clinical care, and health services research. Objective This review aims to describe and assess the present landscape of EMR-based case phenotyping for the Charlson conditions. Methods A scoping review of EMR-based algorithms for defining the Charlson comorbidity index conditions was completed. This study covered articles published between January 2000 and April 2020, both inclusive. Embase (Excerpta Medica database) and MEDLINE (Medical Literature Analysis and Retrieval System Online) were searched using keywords developed in the following 3 domains: terms related to EMR, terms related to case finding, and disease-specific terms. The manuscript follows the Preferred Reporting Items for Systematic reviews and Meta-analyses extension for Scoping Reviews (PRISMA) guidelines. Results A total of 274 articles representing 299 algorithms were assessed and summarized. Most studies were undertaken in the United States (181/299, 60.5%), followed by the United Kingdom (42/299, 14.0%) and Canada (15/299, 5.0%). These algorithms were mostly developed either in primary care (103/299, 34.4%) or inpatient (168/299, 56.2%) settings. Diabetes, congestive heart failure, myocardial infarction, and rheumatology had the highest number of developed algorithms. Data-driven and clinical rule–based approaches have been identified. EMR-based phenotype and algorithm development reflect the data access allowed by respective health systems, and algorithms vary in their performance. Conclusions Recognizing similarities and differences in health systems, data collection strategies, extraction, data release protocols, and existing clinical pathways is critical to algorithm development strategies. Several strategies to assist with phenotype-based case definitions have been proposed.
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Affiliation(s)
- Seungwon Lee
- Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Alberta Health Services, Calgary, AB, Canada.,Data Intelligence for Health Lab, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Chelsea Doktorchik
- Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Elliot Asher Martin
- Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Alberta Health Services, Calgary, AB, Canada
| | - Adam Giles D'Souza
- Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Alberta Health Services, Calgary, AB, Canada
| | - Cathy Eastwood
- Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Abdel Aziz Shaheen
- Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Christopher Naugler
- Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Pathology and Laboratory Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Joon Lee
- Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Data Intelligence for Health Lab, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Cardiac Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Hude Quan
- Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
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Wang Q, Berger NA, Xu R. Analyses of Risk, Racial Disparity, and Outcomes Among US Patients With Cancer and COVID-19 Infection. JAMA Oncol 2021; 7:220-227. [PMID: 33300956 PMCID: PMC7729584 DOI: 10.1001/jamaoncol.2020.6178] [Citation(s) in RCA: 263] [Impact Index Per Article: 87.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Accepted: 08/21/2020] [Indexed: 12/15/2022]
Abstract
Importance Patients with specific cancers may be at higher risk than those without cancer for coronavirus disease 2019 (COVID-19) and its severe outcomes. At present, limited data are available on the risk, racial disparity, and outcomes for COVID-19 illness in patients with cancer. Objectives To investigate how patients with specific types of cancer are at risk for COVID-19 infection and its adverse outcomes and whether there are cancer-specific race disparities for COVID-19 infection. Design, Setting, and Participants This retrospective case-control analysis of patient electronic health records included 73.4 million patients from 360 hospitals and 317 000 clinicians across 50 US states to August 14, 2020. The odds of COVID-19 infections for 13 common cancer types and adverse outcomes were assessed. Exposures The exposure groups were patients diagnosed with a specific cancer, whereas the unexposed groups were patients without the specific cancer. Main Outcomes and Measures The adjusted odds ratio (aOR) and 95% CI were estimated using the Cochran-Mantel-Haenszel test for the risk of COVID-19 infection. Results Among the 73.4 million patients included in the analysis (53.6% female), 2 523 920 had at least 1 of the 13 common cancers diagnosed (all cancer diagnosed within or before the last year), and 273 140 had recent cancer (cancer diagnosed within the last year). Among 16 570 patients diagnosed with COVID-19, 1200 had a cancer diagnosis and 690 had a recent cancer diagnosis of at least 1 of the 13 common cancers. Those with recent cancer diagnosis were at significantly increased risk for COVID-19 infection (aOR, 7.14 [95% CI, 6.91-7.39]; P < .001), with the strongest association for recently diagnosed leukemia (aOR, 12.16 [95% CI, 11.03-13.40]; P < .001), non-Hodgkin lymphoma (aOR, 8.54 [95% CI, 7.80-9.36]; P < .001), and lung cancer (aOR, 7.66 [95% CI, 7.07-8.29]; P < .001) and weakest for thyroid cancer (aOR, 3.10 [95% CI, 2.47-3.87]; P < .001). Among patients with recent cancer diagnosis, African Americans had a significantly higher risk for COVID-19 infection than White patients; this racial disparity was largest for breast cancer (aOR, 5.44 [95% CI, 4.69-6.31]; P < .001), followed by prostate cancer (aOR, 5.10 [95% CI, 4.34-5.98]; P < .001), colorectal cancer (aOR, 3.30 [95% CI, 2.55-4.26]; P < .001), and lung cancer (aOR, 2.53 [95% CI, 2.10-3.06]; P < .001). Patients with cancer and COVID-19 had significantly worse outcomes (hospitalization, 47.46%; death, 14.93%) than patients with COVID-19 without cancer (hospitalization, 24.26%; death, 5.26%) (P < .001) and patients with cancer without COVID-19 (hospitalization, 12.39%; death, 4.03%) (P < .001). Conclusions and Relevance In this case-control study, patients with cancer were at significantly increased risk for COVID-19 infection and worse outcomes, which was further exacerbated among African Americans. These findings highlight the need to protect and monitor patients with cancer as part of the strategy to control the pandemic.
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Affiliation(s)
- QuanQiu Wang
- Center for Artificial Intelligence in Drug Discovery, School of Medicine, Case Western Reserve University, Cleveland, Ohio
| | - Nathan A. Berger
- Center for Science, Health, and Society, School of Medicine, Case Western Reserve University, Cleveland, Ohio
- Case Comprehensive Cancer Center, School of Medicine, Case Western Reserve University, Cleveland, Ohio
| | - Rong Xu
- Center for Artificial Intelligence in Drug Discovery, School of Medicine, Case Western Reserve University, Cleveland, Ohio
- Case Comprehensive Cancer Center, School of Medicine, Case Western Reserve University, Cleveland, Ohio
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Wang Q, Davis PB, Xu R. COVID-19 risk, disparities and outcomes in patients with chronic liver disease in the United States. EClinicalMedicine 2021; 31:100688. [PMID: 33521611 PMCID: PMC7834443 DOI: 10.1016/j.eclinm.2020.100688] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 11/27/2020] [Accepted: 12/01/2020] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Scientific evidence is lacking regarding the risk of patients with chronic liver disease (CLD) for COVID-19, and how these risks are affected by age, gender and race. METHODS We performed a case-control study of electronic health records of 62.2 million patients (age >18 years) in the US up to October 1st, 2020, including 1,034,270 patients with CLD, 16,530 with COVID-19, and 820 with both COVID-19 and CLD. We assessed the risk, disparities, and outcomes of COVID-19 in patients with six major CLDs. FINDINGS Patients with a recent medical encounter for CLD were at significantly increased risk for COVID-19 compared with patients without CLD, with the strongest effect in patients with chronic non-alcoholic liver disease [adjusted odd ratio (AOR)=13.11, 95% CI: 12.49-13.76, p < 0.001] and non-alcoholic cirrhosis (AOR=11.53, 95% CI: 10.69-12.43, p < 0.001), followed by chronic hepatitis C (AOR=8.93, 95% CI:8.25-9.66, p < 0.001), alcoholic liver damage (AOR=7.05, 95% CI:6.30-7.88, p < 0.001), alcoholic liver cirrhosis (AOR=7.00, 95% CI:6.15-7.97, p < 0.001) and chronic hepatitis B (AOR=4.37, 95% CI:3.35-5.69, p < 0.001). African Americans with CLD were twice more likely to develop COVID-19 than Caucasians. Patients with COVID-19 and a recent encounter for CLD had a death rate of 10.3% (vs. 5.5% among COVID-19 patients without CLD, p < 0.001) and a hospitalization rate of 41.0% (vs. 23.9% among COVID-19 patients without CLD, p < 0.001). INTERPRETATION Patients with CLD, especially African Americans, were at increased risk for COVID-19, highlighting the need to protect these patients from exposure to virus infection. FUNDING National Institutes of Health (AG057557, AG061388, AG062272, 1UL1TR002548-01), American Cancer Society (RSG-16-049-01-MPC).
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Affiliation(s)
- QuanQiu Wang
- Center for Artificial Intelligence in Drug Discovery, School of Medicine, Case Western Reserve University, 2103 Cornell Rd, Cleveland 44106, OH, USA
| | - Pamela B. Davis
- Center for Clinical Investigation, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Rong Xu
- Center for Artificial Intelligence in Drug Discovery, School of Medicine, Case Western Reserve University, 2103 Cornell Rd, Cleveland 44106, OH, USA
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Wang QQ, Kaelber DC, Xu R, Volkow ND. COVID-19 risk and outcomes in patients with substance use disorders: analyses from electronic health records in the United States. Mol Psychiatry 2021; 26:30-39. [PMID: 32929211 PMCID: PMC7488216 DOI: 10.1038/s41380-020-00880-7] [Citation(s) in RCA: 385] [Impact Index Per Article: 128.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 08/20/2020] [Accepted: 09/03/2020] [Indexed: 12/25/2022]
Abstract
The global pandemic of COVID-19 is colliding with the epidemic of opioid use disorders (OUD) and other substance use disorders (SUD) in the United States (US). Currently, there is limited data on risks, disparity, and outcomes for COVID-19 in individuals suffering from SUD. This is a retrospective case-control study of electronic health records (EHRs) data of 73,099,850 unique patients, of whom 12,030 had a diagnosis of COVID-19. Patients with a recent diagnosis of SUD (within past year) were at significantly increased risk for COVID-19 (adjusted odds ratio or AOR = 8.699 [8.411-8.997], P < 10-30), an effect that was strongest for individuals with OUD (AOR = 10.244 [9.107-11.524], P < 10-30), followed by individuals with tobacco use disorder (TUD) (AOR = 8.222 ([7.925-8.530], P < 10-30). Compared to patients without SUD, patients with SUD had significantly higher prevalence of chronic kidney, liver, lung diseases, cardiovascular diseases, type 2 diabetes, obesity and cancer. Among patients with recent diagnosis of SUD, African Americans had significantly higher risk of COVID-19 than Caucasians (AOR = 2.173 [2.01-2.349], P < 10-30), with strongest effect for OUD (AOR = 4.162 [3.13-5.533], P < 10-25). COVID-19 patients with SUD had significantly worse outcomes (death: 9.6%, hospitalization: 41.0%) than general COVID-19 patients (death: 6.6%, hospitalization: 30.1%) and African Americans with COVID-19 and SUD had worse outcomes (death: 13.0%, hospitalization: 50.7%) than Caucasians (death: 8.6%, hospitalization: 35.2%). These findings identify individuals with SUD, especially individuals with OUD and African Americans, as having increased risk for COVID-19 and its adverse outcomes, highlighting the need to screen and treat individuals with SUD as part of the strategy to control the pandemic while ensuring no disparities in access to healthcare support.
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Affiliation(s)
- Quan Qiu Wang
- Center for Artificial Intelligence in Drug Discovery, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - David C Kaelber
- Departments of Internal Medicine and Pediatrics and the Center for Clinical Informatics Research and Education, The MetroHealth System, Cleveland, OH, USA
| | - Rong Xu
- Center for Artificial Intelligence in Drug Discovery, School of Medicine, Case Western Reserve University, Cleveland, OH, USA.
| | - Nora D Volkow
- National Institute on Drug Abuse, National Institutes of Health, Bethesda, MD, USA.
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30
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Tang O, Foti K, Miller ER, Appel LJ, Juraschek SP. Factors Associated With Physician Recommendation of Home Blood Pressure Monitoring and Blood Pressure in the US Population. Am J Hypertens 2020; 33:852-859. [PMID: 32542320 DOI: 10.1093/ajh/hpaa093] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Revised: 05/15/2020] [Accepted: 06/12/2020] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Hypertension guidelines recommend home blood pressure monitoring (HBPM) to help achieve blood pressure (BP) control. We hypothesized that HBPM use with a physician recommendation would be associated with lower BP and greater medication adherence. METHODS We used data from 6,320 adults with hypertension in the National Health and Nutrition Examination Survey 2009-2014 to characterize the association of (i) provider recommendation for HBPM and (ii) HBPM use on 2 outcomes: measured BP (linear regression) and medication adherence (logistic regression). Provider recommendation, HBPM use, and medication use were self-reported. RESULTS Among adults with hypertension, 30.1% reported a physician recommendation for HBPM, among whom 82.0% reported using HBPM. Among those who did not report a physician recommendation for HBPM, 28.3% used HBPM. Factors associated with a physician recommendation were having health insurance, higher education attainment, hypertension awareness, and having a prescription for antihypertensive medication. Among those who reported receiving a physician recommendation, those who used HBPM had a mean BP that was 3.1/4.5 mm Hg lower than those who did not. Those who reported having a physician recommendation and using HBPM were more likely to report hypertension medication adherence (odds ratio 2.9; 95% confidence interval: 2.0, 4.4). CONCLUSIONS HBPM use was associated with lower BP and higher medication adherence. Use of HBPM was higher among those with a physician recommendation. These results support a role for physicians in counseling and partnering with patients on HBPM use for BP management.
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Affiliation(s)
- Olive Tang
- Department of Medicine, The Johns Hopkins School of Medicine, Baltimore, Maryland, USA
- Department of Epidemiology, The Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- The Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, Maryland, USA
| | - Kathryn Foti
- Department of Epidemiology, The Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- The Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, Maryland, USA
| | - Edgar R Miller
- Department of Medicine, The Johns Hopkins School of Medicine, Baltimore, Maryland, USA
- The Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, Maryland, USA
| | - Lawrence J Appel
- Department of Medicine, The Johns Hopkins School of Medicine, Baltimore, Maryland, USA
- Department of Epidemiology, The Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- The Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, Maryland, USA
| | - Stephen P Juraschek
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
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31
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A Retrospective Study of Suicide Attempts in Patients With Pulmonary Hypertension. Heart Lung Circ 2020; 29:e231-e237. [DOI: 10.1016/j.hlc.2020.02.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Accepted: 02/10/2020] [Indexed: 11/18/2022]
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Population-level surveillance of congenital heart defects among adolescents and adults in Colorado: Implications of record linkage. Am Heart J 2020; 226:75-84. [PMID: 32526532 DOI: 10.1016/j.ahj.2020.04.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Accepted: 04/14/2020] [Indexed: 11/23/2022]
Abstract
BACKGROUND The objective was to describe the design of a population-level electronic health record (EHR) and insurance claims-based surveillance system of adolescents and adults with congenital heart defects (CHDs) in Colorado and to evaluate the bias introduced by duplicate cases across data sources. METHODS The Colorado CHD Surveillance System ascertained individuals aged 11-64 years with a CHD based on International Classification of Diseases, Ninth Revision, Clinical Modification diagnostic coding between 2011 and 2013 from a diverse network of health care systems and an All Payer Claims Database (APCD). A probability-based identity reconciliation algorithm identified duplicate cases. Logistic regression was conducted to investigate bias introduced by duplicate cases on the relationship between CHD severity (severe compared to moderate/mild) and adverse outcomes including all-cause mortality, inpatient hospitalization, and major adverse cardiac events (myocardial infarction, congestive heart failure, or cerebrovascular event). Sensitivity analyses were conducted to investigate bias introduced by the sole use or exclusion of APCD data. RESULTS A total of 12,293 unique cases were identified, of which 3,476 had a within or between data source duplicate. Duplicate cases were more likely to be in the youngest age group and have private health insurance, a severe heart defect, a CHD comorbidity, and higher health care utilization. We found that failure to resolve duplicate cases between data sources would inflate the relationship between CHD severity and both morbidity and mortality outcomes by ~15%. Sensitivity analyses indicate that scenarios in which APCD was excluded from case finding or relied upon as the sole source of case finding would also result in an overestimation of the relationship between a CHD severity and major adverse outcomes. DISCUSSION Aggregated EHR- and claims-based surveillance systems of adolescents and adults with CHD that fail to account for duplicate records will introduce considerable bias into research findings. CONCLUSION Population-level surveillance systems for rare chronic conditions, such as congenital heart disease, based on aggregation of EHR and claims data require sophisticated identity reconciliation methods to prevent bias introduced by duplicate cases.
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Lenders JWM, Deinum J, Passauer J, Januszewicz A, Chan OYA, Prejbisz A. Low Quality of Reports on Blood Pressure in Patients Adrenalectomized for Unilateral Primary Aldosteronism. J Clin Endocrinol Metab 2020; 105:5813969. [PMID: 32249895 DOI: 10.1210/clinem/dgaa159] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2019] [Accepted: 03/27/2020] [Indexed: 11/19/2022]
Abstract
CONTEXT Adrenalectomy is the preferred treatment for unilateral primary aldosteronism but the results of long-term control of blood pressure (BP) are far from optimal. One possible explanation relates to the quality of the assessment of treatment effects on BP. PURPOSE OF THE STUDY To examine the quality of reporting BP measurements in studies assessing the outcome of adrenalectomy on BP. METHODS We conducted a systematic review searching 3 databases (PubMed, EMBASE, Web of Science) for articles published from January 1, 1990, onwards. Sixty-six studies, each reporting on more than 50 adrenalectomized patients, were eligible for full analysis. RESULTS In 37 of the analyzed 66 studies (56.1%) BP values both before and after adrenalectomy were reported. In 19.7% (13/66) of the studies the method of BP measurement was described. The number of visits and number of BP recordings per visit on which BP results were based were reported in <15% of papers. The criteria for the diagnosis of hypertension were described in 72.7% (48/66) of the studies. The used definitions of improvement of BP control after adrenalectomy were variable, with 84.8% of the studies not providing any quantitative criteria to define reduction in BP. CONCLUSION We conclude that the quality of reporting on BP control after adrenalectomy for primary aldosteronism shows substantial deficiencies and inconsistencies, thus impacting negatively on accurate assessment of effects of adrenalectomy on BP control. Future studies should adhere to accepted recommendations of correct BP measurement and should provide detailed description of the methods used for BP measurement.
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Affiliation(s)
- Jacques W M Lenders
- Department of Internal Medicine, Division of Vascular Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Medicine III, University Hospital Carl Gustav Carus at the TU Dresden, Dresden, Germany
| | - Jaap Deinum
- Department of Internal Medicine, Division of Vascular Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Medicine III, University Hospital Carl Gustav Carus at the TU Dresden, Dresden, Germany
| | - Jens Passauer
- Department of Medicine III, University Hospital Carl Gustav Carus at the TU Dresden, Dresden, Germany
| | | | - On Ying A Chan
- University Library, Radboud University Medical Center, Nijmegen, The Netherlands
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Ahmad FS, Ricket IM, Hammill BG, Eskenazi L, Robertson HR, Curtis LH, Dobi CD, Girotra S, Haynes K, Kizer JR, Kripalani S, Roe MT, Roumie CL, Waitman R, Jones WS, Weiner MG. Computable Phenotype Implementation for a National, Multicenter Pragmatic Clinical Trial: Lessons Learned From ADAPTABLE. Circ Cardiovasc Qual Outcomes 2020; 13:e006292. [PMID: 32466729 DOI: 10.1161/circoutcomes.119.006292] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
BACKGROUND Many large-scale cardiovascular clinical trials are plagued with escalating costs and low enrollment. Implementing a computable phenotype, which is a set of executable algorithms, to identify a group of clinical characteristics derivable from electronic health records or administrative claims records, is essential to successful recruitment in large-scale pragmatic clinical trials. This methods paper provides an overview of the development and implementation of a computable phenotype in ADAPTABLE (Aspirin Dosing: a Patient-Centric Trial Assessing Benefits and Long-Term Effectiveness)-a pragmatic, randomized, open-label clinical trial testing the optimal dose of aspirin for secondary prevention of atherosclerotic cardiovascular disease events. METHODS AND RESULTS A multidisciplinary team developed and tested the computable phenotype to identify adults ≥18 years of age with a history of atherosclerotic cardiovascular disease without safety concerns around using aspirin and meeting trial eligibility criteria. Using the computable phenotype, investigators identified over 650 000 potentially eligible patients from the 40 participating sites from Patient-Centered Outcomes Research Network-a network of Clinical Data Research Networks, Patient-Powered Research Networks, and Health Plan Research Networks. Leveraging diverse recruitment methods, sites enrolled 15 076 participants from April 2016 to June 2019. During the process of developing and implementing the ADAPTABLE computable phenotype, several key lessons were learned. The accuracy and utility of a computable phenotype are dependent on the quality of the source data, which can be variable even with a common data model. Local validation and modification were required based on site factors, such as recruitment strategies, data quality, and local coding patterns. Sustained collaboration among a diverse team of researchers is needed during computable phenotype development and implementation. CONCLUSIONS The ADAPTABLE computable phenotype served as an efficient method to recruit patients in a multisite pragmatic clinical trial. This process of development and implementation will be informative for future large-scale, pragmatic clinical trials. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02697916.
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Affiliation(s)
- Faraz S Ahmad
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (F.S.A.)
| | - Iben M Ricket
- Louisiana Public Health Institute, New Orleans (I.M.R.)
| | - Bradley G Hammill
- Duke University School of Medicine, Durham, NC (B.G.H., M.T.R., W.S.J.).,Duke Clinical Research Institute, Durham, NC (B.G.H., L.E., H.R., L.H.C., M.T.R., W.S.J.)
| | - Lisa Eskenazi
- Duke Clinical Research Institute, Durham, NC (B.G.H., L.E., H.R., L.H.C., M.T.R., W.S.J.)
| | - Holly R Robertson
- Duke Clinical Research Institute, Durham, NC (B.G.H., L.E., H.R., L.H.C., M.T.R., W.S.J.)
| | - Lesley H Curtis
- Duke Clinical Research Institute, Durham, NC (B.G.H., L.E., H.R., L.H.C., M.T.R., W.S.J.)
| | - Cecilia D Dobi
- Department of Clinical Sciences, Lewis Katz School of Medicine at Temple University, Philadelphia, PA (C.D.D.)
| | - Saket Girotra
- University of Iowa Carver College of Medicine, Iowa City (S.G.).,Iowa City Veteran Affairs Medical Center (S.G.)
| | - Kevin Haynes
- Scientific Affairs, HealthCore, Inc., Wilmington, DE (K.H.)
| | - Jorge R Kizer
- Cardiology Section, San Francisco Veterans Affairs Health Care System, CA (J.R.K.).,Department of Medicine and Department of Epidemiology and Biostatistics, University of California San Francisco (J.R.K.)
| | - Sunil Kripalani
- Department of Medicine, Vanderbilt University Medical Center, Veterans Health Administration-Tennessee Valley Healthcare System Geriatric Research Education Clinical Center, Health Services Research and Development Center, Nashville, TN (S.K., C.L.R.)
| | - Mathew T Roe
- Duke University School of Medicine, Durham, NC (B.G.H., M.T.R., W.S.J.).,Duke Clinical Research Institute, Durham, NC (B.G.H., L.E., H.R., L.H.C., M.T.R., W.S.J.)
| | - Christianne L Roumie
- Department of Medicine, Vanderbilt University Medical Center, Veterans Health Administration-Tennessee Valley Healthcare System Geriatric Research Education Clinical Center, Health Services Research and Development Center, Nashville, TN (S.K., C.L.R.)
| | - Russ Waitman
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS (R.W.)
| | - W Schuyler Jones
- Duke University School of Medicine, Durham, NC (B.G.H., M.T.R., W.S.J.).,Duke Clinical Research Institute, Durham, NC (B.G.H., L.E., H.R., L.H.C., M.T.R., W.S.J.)
| | - Mark G Weiner
- Department of Population Health Sciences, Weill Cornell Medicine, New York Presbyterian-Weill Cornell Campus, New York (M.G.W.)
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Strom JB, Faridi KF, Butala NM, Zhao Y, Tamez H, Valsdottir LR, Brennan JM, Shen C, Popma JJ, Kazi DS, Yeh RW. Use of Administrative Claims to Assess Outcomes and Treatment Effect in Randomized Clinical Trials for Transcatheter Aortic Valve Replacement: Findings From the EXTEND Study. Circulation 2020; 142:203-213. [PMID: 32436390 DOI: 10.1161/circulationaha.120.046159] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND Whether passively collected data can substitute for adjudicated outcomes to reproduce the magnitude and direction of treatment effect observed in cardiovascular clinical trials is not well known. METHODS We linked adults ≥65 years of age in the HiR (US CoreValve Pivotal High Risk) and SURTAVI trials (Surgical or Transcatheter Aortic Valve Replacement in Intermediate-Risk Patients) to 100% Medicare inpatient claims, January 1, 2011, to December 31, 2016. Primary (eg, death and stroke) and secondary trial end points were compared across treatment arms (eg, transcatheter aortic valve replacement [TAVR] versus surgical aortic valve replacement [SAVR]) using trial-adjudicated outcomes versus outcomes derived from claims at 1 year (HiR) or 2 years (SURTAVI). RESULTS Among 600 linked HiR participants (linkage rate, 80.0%), the rate of the trial's primary end point of all-cause mortality occurred in 13.7% of patients receiving TAVR and 16.4% of patients receiving SAVR at 1 year by using both trial data (hazard ratio, 0.84 [95% CI, 0.65-1.09]; P=0.33) and claims data (hazard ratio, 0.86 [95% CI, 0.66-1.11]; P=0.34; interaction P value=0.80). Noninferiority of TAVR relative to SAVR was seen by using both trial- and claims-based outcomes (Pnoninferiority<0.001 for both). Among 1005 linked SURTAVI trial participants (linkage rate, 60.5%), the trial's primary end point was 12.9% for TAVR and 13.1% for SAVR using trial data (hazard ratio, 1.08 [95% CI, 0.79-1.48]; P=0.90), and 11.3% for TAVR and 12.5% for SAVR patients using claims data (hazard ratio, 1.02 [95% CI, 0.73-1.41]; P=0.58; interaction P value=0.89). TAVR was noninferior to SAVR when compared using both trial and claims (Pnoninferiority<0.001 for both). Rates of procedural secondary outcomes (eg, aortic valve reintervention, pacemaker rates) were more closely concordant between trial and claims data than nonprocedural outcomes (eg, stroke, bleeding, cardiogenic shock). CONCLUSIONS In the HiR and SURTAVI trials, ascertainment of trial primary end points using claims reproduced both the magnitude and direction of treatment effect in comparison with adjudicated event data, but nonfatal and nonprocedural secondary outcomes were not as well reproduced. Use of claims to substitute for adjudicated outcomes in traditional trial treatment comparisons may be valid and feasible for all-cause mortality and certain procedural outcomes but may be less suitable for other end points.
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Affiliation(s)
- Jordan B Strom
- Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology, Boston, MA (J.B.S., Y.Z., H.T., L.R.V., C.S., D.S.K., R.W.Y.).,Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA (J.B.S., K.F.F., Y.Z., H.T., L.R.V., C.S., J.J.P., D.S.K., R.W.Y.).,Harvard Medical School, Boston, MA (J.B.S., N.M.B., Y.Z., H.T., L.R.V., C.S., J.J.P., D.S.K., R.W.Y.)
| | - Kamil F Faridi
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA (J.B.S., K.F.F., Y.Z., H.T., L.R.V., C.S., J.J.P., D.S.K., R.W.Y.).,Section of Cardiovascular Medicine, Yale School of Medicine (K.F.F.)
| | - Neel M Butala
- Harvard Medical School, Boston, MA (J.B.S., N.M.B., Y.Z., H.T., L.R.V., C.S., J.J.P., D.S.K., R.W.Y.).,Division of Cardiology, Massachusetts General Hospital, Boston (N.M.B.)
| | - Yuansong Zhao
- Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology, Boston, MA (J.B.S., Y.Z., H.T., L.R.V., C.S., D.S.K., R.W.Y.).,Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA (J.B.S., K.F.F., Y.Z., H.T., L.R.V., C.S., J.J.P., D.S.K., R.W.Y.).,Harvard Medical School, Boston, MA (J.B.S., N.M.B., Y.Z., H.T., L.R.V., C.S., J.J.P., D.S.K., R.W.Y.)
| | - Hector Tamez
- Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology, Boston, MA (J.B.S., Y.Z., H.T., L.R.V., C.S., D.S.K., R.W.Y.).,Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA (J.B.S., K.F.F., Y.Z., H.T., L.R.V., C.S., J.J.P., D.S.K., R.W.Y.).,Harvard Medical School, Boston, MA (J.B.S., N.M.B., Y.Z., H.T., L.R.V., C.S., J.J.P., D.S.K., R.W.Y.)
| | - Linda R Valsdottir
- Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology, Boston, MA (J.B.S., Y.Z., H.T., L.R.V., C.S., D.S.K., R.W.Y.).,Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA (J.B.S., K.F.F., Y.Z., H.T., L.R.V., C.S., J.J.P., D.S.K., R.W.Y.).,Harvard Medical School, Boston, MA (J.B.S., N.M.B., Y.Z., H.T., L.R.V., C.S., J.J.P., D.S.K., R.W.Y.)
| | | | - Changyu Shen
- Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology, Boston, MA (J.B.S., Y.Z., H.T., L.R.V., C.S., D.S.K., R.W.Y.).,Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA (J.B.S., K.F.F., Y.Z., H.T., L.R.V., C.S., J.J.P., D.S.K., R.W.Y.).,Harvard Medical School, Boston, MA (J.B.S., N.M.B., Y.Z., H.T., L.R.V., C.S., J.J.P., D.S.K., R.W.Y.)
| | - Jeffrey J Popma
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA (J.B.S., K.F.F., Y.Z., H.T., L.R.V., C.S., J.J.P., D.S.K., R.W.Y.).,Harvard Medical School, Boston, MA (J.B.S., N.M.B., Y.Z., H.T., L.R.V., C.S., J.J.P., D.S.K., R.W.Y.).,Baim Institute for Clinical Research, Boston, MA (J.J.P., R.W.Y.)
| | - Dhruv S Kazi
- Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology, Boston, MA (J.B.S., Y.Z., H.T., L.R.V., C.S., D.S.K., R.W.Y.).,Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA (J.B.S., K.F.F., Y.Z., H.T., L.R.V., C.S., J.J.P., D.S.K., R.W.Y.).,Harvard Medical School, Boston, MA (J.B.S., N.M.B., Y.Z., H.T., L.R.V., C.S., J.J.P., D.S.K., R.W.Y.)
| | - Robert W Yeh
- Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology, Boston, MA (J.B.S., Y.Z., H.T., L.R.V., C.S., D.S.K., R.W.Y.).,Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA (J.B.S., K.F.F., Y.Z., H.T., L.R.V., C.S., J.J.P., D.S.K., R.W.Y.).,Harvard Medical School, Boston, MA (J.B.S., N.M.B., Y.Z., H.T., L.R.V., C.S., J.J.P., D.S.K., R.W.Y.).,Baim Institute for Clinical Research, Boston, MA (J.J.P., R.W.Y.)
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Prasada S, Rivera A, Nishtala A, Pawlowski AE, Sinha A, Bundy JD, Chadha SA, Ahmad FS, Khan SS, Achenbach C, Palella FJ, Ramsey-Goldman R, Lee YC, Silverberg JI, Taiwo BO, Shah SJ, Lloyd-Jones DM, Feinstein MJ. Differential Associations of Chronic Inflammatory Diseases With Incident Heart Failure. JACC-HEART FAILURE 2020; 8:489-498. [PMID: 32278678 DOI: 10.1016/j.jchf.2019.11.013] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Revised: 11/26/2019] [Accepted: 11/29/2019] [Indexed: 12/18/2022]
Abstract
OBJECTIVES The purpose of this study was to compare the risks of incident heart failure (HF) among a variety of chronic inflammatory diseases (CIDs) and to determine whether risks varied by severity of inflammation within each CID. BACKGROUND Individuals with CIDs are at elevated risk for cardiovascular diseases, but data are limited regarding risk for HF. METHODS An electronic health records database from a large urban medical system was examined, comparing individuals with CIDs with frequency-matched controls without CIDs, all of whom were receiving regular outpatient care. Rates of incident HF were determined by using the Kaplan-Meier method and subsequently used multivariate-adjusted proportional hazards models to compare HF risks for each CID. Exploratory analyses determined HF risks by proxy measurement of CID severity. RESULTS Of 37,636 patients (n = 18,278 patients with CIDs; and n = 19,358 controls without CIDs) there were 960 incident HF cases over a median of 3.6 years. Risks for incident HF were significantly or borderline significantly elevated for patients with systemic sclerosis (hazard ratio [HR]: 7.26; 95% confidence interval [CI]: 5.72 to 9.21; p < 0.01), systemic lupus erythematosus (HR: 3.15; 95% CI: 2.41 to 4.11; p < 0.01), rheumatoid arthritis (HR: 1.39; 95% CI: 1.13 to 1.71; p < 0.01), and human immunodeficiency virus (HR: 1.28; 95% CI: 0.99 to 1.66; p = 0.06). There was no association between psoriasis or inflammatory bowel disease and incident HF, although patients with those CIDs with higher levels of C-reactive protein had higher risks for HF than controls. CONCLUSIONS Systemic sclerosis and systemic lupus erythematosus were associated with the highest risks of HF, followed by rheumatoid arthritis and HIV. Measurements of inflammation were associated with HF risk across different CIDs.
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Affiliation(s)
- Sameer Prasada
- Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Adovich Rivera
- Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Arvind Nishtala
- Division of Cardiology, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Anna E Pawlowski
- Northwestern Medicine Enterprise Data Warehouse, Northwestern University, Chicago, Illinois
| | - Arjun Sinha
- Division of Cardiology, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Joshua D Bundy
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana
| | - Simran A Chadha
- Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Faraz S Ahmad
- Division of Cardiology, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois; Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Sadiya S Khan
- Division of Cardiology, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois; Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Chad Achenbach
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois; Division of Infectious Diseases, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Frank J Palella
- Division of Infectious Diseases, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Rosalind Ramsey-Goldman
- Division of Rheumatology, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Yvonne C Lee
- Division of Rheumatology, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Jonathan I Silverberg
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois; Department of Dermatology and Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Babafemi O Taiwo
- Division of Infectious Diseases, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Sanjiv J Shah
- Division of Cardiology, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Donald M Lloyd-Jones
- Division of Cardiology, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois; Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Matthew J Feinstein
- Division of Cardiology, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois; Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois.
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Pool LR, Ning H, Wilkins J, Lloyd-Jones DM, Allen NB. Use of Long-term Cumulative Blood Pressure in Cardiovascular Risk Prediction Models. JAMA Cardiol 2019; 3:1096-1100. [PMID: 30193291 DOI: 10.1001/jamacardio.2018.2763] [Citation(s) in RCA: 59] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Importance Long-term cumulative systolic blood pressure (SBP) is significantly associated with increased rates of atherosclerotic cardiovascular disease (ASCVD) development independent of single SBP levels. However, published ASCVD risk prediction algorithms only include currently measured SBP. Objective To determine whether including long-term (5- and 10-year) cumulative SBP in risk equations improves the predictive ability compared with single SBP measurements. Design, Setting, and Participants Adults aged 45 to 65 years at the time of risk estimation with at least 20 years of follow-up (5 and 10 years prior to risk estimation and 10 years of event follow-up). The Lifetime Risk Pooling Project included data from the following cohorts: Coronary Artery Risk Development in Young Adults Study, Atherosclerosis Risk in Communities Study, and Framingham Heart Study (both the original and offspring). Exposures Ten-year ASCVD risk, calculated using the approach of the 2013 American College of Cardiology/American Heart Association 10-year ASCVD risk equations, first with current SBP and then substituting 5- and 10-year cumulative SBP levels. Main Outcomes and Measures Incident ASCVD events that occurred over 10 years of follow-up, compared with the predicted risks, using the C statistic, net reclassification index at event rate, and the integrated discrimination index. Results This study included 11 767 participants with a mean (SD) age of 59.1 (4.7) years at risk estimation. A total of 6873 participants (58%) were women, and 1499 (13%) were African American. In the 10 years of follow-up from risk estimation, 1887 participants (16%) had an ASCVD event. There were no significant improvements in the C statistic when including 5- or 10-year cumulative SBP. However, the addition of cumulative SBP resulted in significant improvements in the net reclassification index at event rate (10-year net reclassification index for men, 0.04 [95% CI, 0.02-0.06]; 10-year net reclassification index for women, 0.03 [95% CI, 0.01-0.06]) and the relative integrated discrimination index (10-year relative integrated discrimination index for men, 0.12; 10-year relative integrated discrimination index for women, 0.10). Conclusions and Relevance Using long-term measures of cumulative blood pressure, instead of single measurements, can modestly improve the ability of cardiovascular disease risk prediction models to correctly classify individuals in terms of their risk for cardiovascular disease.
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Affiliation(s)
- Lindsay R Pool
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Hongyan Ning
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - John Wilkins
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Donald M Lloyd-Jones
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Norrina B Allen
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
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38
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Mosley JD, Benson MD, Smith JG, Melander O, Ngo D, Shaffer CM, Ferguson JF, Herzig MS, McCarty CA, Chute CG, Jarvik GP, Gordon AS, Palmer MR, Crosslin DR, Larson EB, Carrell DS, Kullo IJ, Pacheco JA, Peissig PL, Brilliant MH, Kitchner TE, Linneman JG, Namjou B, Williams MS, Ritchie MD, Borthwick KM, Kiryluk K, Mentch FD, Sleiman PM, Karlson EW, Verma SS, Zhu Y, Vasan RS, Yang Q, Denny JC, Roden DM, Gerszten RE, Wang TJ. Probing the Virtual Proteome to Identify Novel Disease Biomarkers. Circulation 2019; 138:2469-2481. [PMID: 30571344 DOI: 10.1161/circulationaha.118.036063] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Proteomic approaches allow measurement of thousands of proteins in a single specimen, which can accelerate biomarker discovery. However, applying these technologies to massive biobanks is not currently feasible because of the practical barriers and costs of implementing such assays at scale. To overcome these challenges, we used a "virtual proteomic" approach, linking genetically predicted protein levels to clinical diagnoses in >40 000 individuals. METHODS We used genome-wide association data from the Framingham Heart Study (n=759) to construct genetic predictors for 1129 plasma protein levels. We validated the genetic predictors for 268 proteins and used them to compute predicted protein levels in 41 288 genotyped individuals in the Electronic Medical Records and Genomics (eMERGE) cohort. We tested associations for each predicted protein with 1128 clinical phenotypes. Lead associations were validated with directly measured protein levels and either low-density lipoprotein cholesterol or subclinical atherosclerosis in the MDCS (Malmö Diet and Cancer Study; n=651). RESULTS In the virtual proteomic analysis in eMERGE, 55 proteins were associated with 89 distinct diagnoses at a false discovery rate q<0.1. Among these, 13 associations involved lipid (n=7) or atherosclerosis (n=6) phenotypes. We tested each association for validation in MDCS using directly measured protein levels. At Bonferroni-adjusted significance thresholds, levels of apolipoprotein E isoforms were associated with hyperlipidemia, and circulating C-type lectin domain family 1 member B and platelet-derived growth factor receptor-β predicted subclinical atherosclerosis. Odds ratios for carotid atherosclerosis were 1.31 (95% CI, 1.08-1.58; P=0.006) per 1-SD increment in C-type lectin domain family 1 member B and 0.79 (0.66-0.94; P=0.008) per 1-SD increment in platelet-derived growth factor receptor-β. CONCLUSIONS We demonstrate a biomarker discovery paradigm to identify candidate biomarkers of cardiovascular and other diseases.
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Affiliation(s)
- Jonathan D Mosley
- Department of Medicine (J.D.M., C.M.S., J.F.F., J.C.D., T.J.W.), Vanderbilt University Medical Center, Nashville, TN
| | - Mark D Benson
- Cardiovascular Division, Brigham and Women's Hospital, Boston, MA (M.D.B.).,Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA (M.D.B., M.S.H., R.E.G.)
| | - J Gustav Smith
- Molecular Epidemiology and Cardiology, Clinical Sciences, Lund University and Skåne University Hospital, Malmö, Sweden (J.G.S., O.M.)
| | - Olle Melander
- Molecular Epidemiology and Cardiology, Clinical Sciences, Lund University and Skåne University Hospital, Malmö, Sweden (J.G.S., O.M.)
| | - Debby Ngo
- Department of Medicine and the Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston (D.N.)
| | - Christian M Shaffer
- Department of Medicine (J.D.M., C.M.S., J.F.F., J.C.D., T.J.W.), Vanderbilt University Medical Center, Nashville, TN
| | - Jane F Ferguson
- Department of Medicine (J.D.M., C.M.S., J.F.F., J.C.D., T.J.W.), Vanderbilt University Medical Center, Nashville, TN
| | - Matthew S Herzig
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA (M.D.B., M.S.H., R.E.G.)
| | | | - Christopher G Chute
- Schools of Medicine, Public Health, and Nursing, Johns Hopkins University, Baltimore, MD (C.G.C.)
| | - Gail P Jarvik
- Departments of Medicine (J.P.J., A.S.G., M.R.P., E.B.L.), University of Washington, Seattle
| | - Adam S Gordon
- Departments of Medicine (J.P.J., A.S.G., M.R.P., E.B.L.), University of Washington, Seattle
| | - Melody R Palmer
- Departments of Medicine (J.P.J., A.S.G., M.R.P., E.B.L.), University of Washington, Seattle
| | - David R Crosslin
- Biomedical Informatics and Medical Education (D.R.C.), University of Washington, Seattle
| | - Eric B Larson
- Departments of Medicine (J.P.J., A.S.G., M.R.P., E.B.L.), University of Washington, Seattle.,Kaiser Permanente Washington Health Research Institute, Seattle, WA (E.B.L., D.S.C.)
| | - David S Carrell
- Kaiser Permanente Washington Health Research Institute, Seattle, WA (E.B.L., D.S.C.)
| | - Iftikhar J Kullo
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN (I.J.K.)
| | - Jennifer A Pacheco
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (J.A.P.)
| | - Peggy L Peissig
- Biomedical Informatics Research Center (P.L.P., J.G.L.), Marshfield Clinic Research Institute, WI
| | - Murray H Brilliant
- Center for Computational and Biomedical Informatics (M.H.B., T.E.K.), Marshfield Clinic Research Institute, WI
| | - Terrie E Kitchner
- Center for Computational and Biomedical Informatics (M.H.B., T.E.K.), Marshfield Clinic Research Institute, WI
| | - James G Linneman
- Biomedical Informatics Research Center (P.L.P., J.G.L.), Marshfield Clinic Research Institute, WI
| | - Bahram Namjou
- Cincinnati Children's Hospital Medical Center and University of Cincinnati, OH (B.N.)
| | - Marc S Williams
- Genomic Medicine Institute (M.S.W.), Geisinger Health System, Danville, PA
| | - Marylyn D Ritchie
- Departments of Bioinformatics and Genetics (M.D.R.), University of Pennsylvania, Philadelphia
| | - Kenneth M Borthwick
- Biomedical and Translational Informatics (K.M.B.), Geisinger Health System, Danville, PA
| | - Krzysztof Kiryluk
- Department of Medicine, College of Physicians and Surgeons, Columbia University, New York, NY (K.K.)
| | - Frank D Mentch
- Center for Applied Genomics, Children's Hospital of Philadelphia, PA (F.D.M., P.M.S.)
| | - Patrick M Sleiman
- Center for Applied Genomics, Children's Hospital of Philadelphia, PA (F.D.M., P.M.S.)
| | - Elizabeth W Karlson
- Department of Medicine, Division of Rheumatology, Immunology and Allergy, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (E.W.K.)
| | - Shefali S Verma
- Perelman School of Medicine, Department of Genetics (S.S.V.), University of Pennsylvania, Philadelphia
| | - Yineng Zhu
- Department of Biostatistics, Boston University School of Public Health, MA (Y.Z., Q.Y.)
| | | | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health, MA (Y.Z., Q.Y.)
| | - Josh C Denny
- Department of Medicine (J.D.M., C.M.S., J.F.F., J.C.D., T.J.W.), Vanderbilt University Medical Center, Nashville, TN.,Biomedical Informatics (J.C.D., D.M.R.), Vanderbilt University Medical Center, Nashville, TN
| | - Dan M Roden
- Biomedical Informatics (J.C.D., D.M.R.), Vanderbilt University Medical Center, Nashville, TN.,Department of Pharmacology (D.M.R.), Vanderbilt University Medical Center, Nashville, TN
| | - Robert E Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA (M.D.B., M.S.H., R.E.G.)
| | - Thomas J Wang
- Department of Medicine (J.D.M., C.M.S., J.F.F., J.C.D., T.J.W.), Vanderbilt University Medical Center, Nashville, TN
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Strom JB, Tamez H, Zhao Y, Valsdottir LR, Curtis J, Brennan JM, Shen C, Popma JJ, Mauri L, Yeh RW. Validating the use of registries and claims data to support randomized trials: Rationale and design of the Extending Trial-Based Evaluations of Medical Therapies Using Novel Sources of Data (EXTEND) Study. Am Heart J 2019; 212:64-71. [PMID: 30953936 DOI: 10.1016/j.ahj.2019.02.007] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Accepted: 02/19/2019] [Indexed: 11/29/2022]
Abstract
BACKGROUND Randomized controlled trials are the "gold standard" for comparing the safety and efficacy of therapies but may be limited due to high costs, lack of feasibility, and difficulty enrolling "real-world" patient populations. The Extending Trial-Based Evaluations of Medical Therapies Using Novel Sources of Data (EXTEND) Study seeks to evaluate whether data collected within procedural registries and claims databases can reproduce trial results by substituting surrogate non-trial-based variables for exposures and outcomes. METHODS AND RESULTS Patient-level data from 2 clinical trial programs-the Dual Antiplatelet Therapy Study and the United States CoreValve Studies-will be linked to a combination of national registry, administrative claims, and health system data. The concordance between baseline and outcomes data collected within nontrial data sets and trial information, including adjudicated end point events, will be assessed. We will compare the study results obtained using these alternative data sources to those derived using trial-ascertained variables and end points using trial-adjudicated end points and covariates. CONCLUSIONS Linkage of trials to registries and claims data represents an opportunity to use alternative data sources in place of and as adjuncts to randomized clinical trial data but requires further validation. The results of this research will help determine how these data sources can be used to improve our present and future understanding of new medical treatments.
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Affiliation(s)
- Jordan B Strom
- Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology; Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA; Harvard Medical School, Boston, MA
| | - Hector Tamez
- Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology; Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA; Harvard Medical School, Boston, MA
| | - Yuansong Zhao
- Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology; Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Linda R Valsdottir
- Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology; Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Jeptha Curtis
- Center for Outcomes Research and Evaluation, Yale University School of Medicine, New Haven, CT
| | | | - Changyu Shen
- Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology; Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA; Harvard Medical School, Boston, MA
| | - Jeffrey J Popma
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA; Harvard Medical School, Boston, MA; Baim Institute for Clinical Research, Boston, MA
| | | | - Robert W Yeh
- Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology; Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA; Harvard Medical School, Boston, MA; Baim Institute for Clinical Research, Boston, MA.
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40
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Joyner MJ. Depression Depresses Vasodilation. Circ Res 2019; 124:465-466. [DOI: 10.1161/circresaha.119.314595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Michael J. Joyner
- From the Department of Anesthesiology & Perioperative Medicine, Mayo Clinic, Rochester, MN 55905
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41
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Muntner P, Einhorn PT, Cushman WC, Whelton PK, Bello NA, Drawz PE, Green BB, Jones DW, Juraschek SP, Margolis KL, Miller ER, Navar AM, Ostchega Y, Rakotz MK, Rosner B, Schwartz JE, Shimbo D, Stergiou GS, Townsend RR, Williamson JD, Wright JT, Appel LJ. Blood Pressure Assessment in Adults in Clinical Practice and Clinic-Based Research: JACC Scientific Expert Panel. J Am Coll Cardiol 2019; 73:317-335. [PMID: 30678763 PMCID: PMC6573014 DOI: 10.1016/j.jacc.2018.10.069] [Citation(s) in RCA: 102] [Impact Index Per Article: 20.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2018] [Revised: 10/14/2018] [Accepted: 10/15/2018] [Indexed: 11/21/2022]
Abstract
The accurate measurement of blood pressure (BP) is essential for the diagnosis and management of hypertension. Restricted use of mercury devices, increased use of oscillometric devices, discrepancies between clinic and out-of-clinic BP, and concerns about measurement error with manual BP measurement techniques have resulted in uncertainty for clinicians and researchers. The National Heart, Lung, and Blood Institute of the U.S. National Institutes of Health convened a working group of clinicians and researchers in October 2017 to review data on BP assessment among adults in clinical practice and clinic-based research. In this report, the authors review the topics discussed during a 2-day meeting including the current state of knowledge on BP assessment in clinical practice and clinic-based research, knowledge gaps pertaining to current BP assessment methods, research and clinical needs to improve BP assessment, and the strengths and limitations of using BP obtained in clinical practice for research and quality improvement activities.
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Affiliation(s)
- Paul Muntner
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama.
| | - Paula T Einhorn
- Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute of the National Institutes of Health, Bethesda, Maryland
| | - William C Cushman
- Preventive Medicine Section, Medical Service, Veterans Affairs Medical Center, Memphis, Tennessee
| | - Paul K Whelton
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana
| | - Natalie A Bello
- Department of Medicine, Division of Cardiology, Columbia University Medical Center, New York, New York
| | - Paul E Drawz
- Division of Renal Diseases & Hypertension, University of Minnesota, Minneapolis, Minnesota
| | - Beverly B Green
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | - Daniel W Jones
- Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi
| | - Stephen P Juraschek
- Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts
| | | | - Edgar R Miller
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland
| | | | - Yechiam Ostchega
- National Center for Health Statistics of the Centers for Disease Control and Prevention, Hyattsville, Maryland
| | | | - Bernard Rosner
- Department of Medicine, Brigham's and Women's Hospital, Harvard University, Boston, Massachusetts
| | - Joseph E Schwartz
- Department of Psychiatry and Behavioral Sciences, Stony Brook University, Stony Brook, New York
| | - Daichi Shimbo
- The Hypertension Center, Columbia University Medical Center, New York, New York
| | - George S Stergiou
- Hypertension Center STRIDE-7, National and Kapodistrian University of Athens, School of Medicine, Third Department of Medicine, Sotiria Hospital, Athens, Greece
| | - Raymond R Townsend
- Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Jeff D Williamson
- Department of Medicine, Wake Forest University, Winston-Salem, North Carolina
| | - Jackson T Wright
- Department of Medicine, Case Western Reserve University, Cleveland, Ohio
| | - Lawrence J Appel
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland
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A Giant with Feet of Clay: On the Validity of the Data that Feed Machine Learning in Medicine. ORGANIZING FOR THE DIGITAL WORLD 2019. [DOI: 10.1007/978-3-319-90503-7_10] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
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43
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Tang O, Juraschek SP, Appel LJ, Cooper LA, Charleston J, Boonyasai RT, Carson KA, Yeh H, Miller ER. Comparison of automated clinical and research blood pressure measurements: Implications for clinical practice and trial design. J Clin Hypertens (Greenwich) 2018; 20:1676-1682. [PMID: 30403006 PMCID: PMC6289771 DOI: 10.1111/jch.13412] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Revised: 08/13/2018] [Accepted: 09/07/2018] [Indexed: 11/30/2022]
Abstract
Discrepancies between clinic and research blood pressure (BP) measurements lead to uncertainties in translating hypertension management guidelines into practice. We assessed the concordance between standardized automated clinic BP, from a primary care clinic, and research BP, from a randomized trial conducted at the same site. Mean single-visit clinic BP was higher by 4.4/3.8 mm Hg (P = 0.007/<0.001). Concordance in systolic BP (SBP) improved with closer proximity of measurements (difference = 2.5 mm Hg, P = 0.21 for visits within 7 days), but not averaging across multiple visits (difference =5.1(9.2) mm Hg; P < 0.001). This discrepancy was greater among female participants. Clinic-based difference in SBP between two visits was more variable than research-based change (SD = 19.6 vs 14.0; P = 0.002); a 2-arm trial using clinic measurements would need 95% more participants to achieve comparable power. Implementation of a bundled standardization intervention decreased discrepancies between clinic and research BP, compared to prior reports. However, clinic measurements remained higher and more variable, suggesting treatment to research-based targets may lead to overtreatment and using clinic BP approximately halves power in trials.
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Affiliation(s)
- Olive Tang
- The Johns Hopkins School of MedicineBaltimoreMaryland
- The Johns Hopkins Bloomberg School of Public HealthBaltimoreMaryland
| | - Stephen P. Juraschek
- Beth Israel Deaconess Medical CenterBostonMassachusetts
- Harvard Medical SchoolBostonMassachusetts
| | - Lawrence J. Appel
- The Johns Hopkins School of MedicineBaltimoreMaryland
- The Johns Hopkins Bloomberg School of Public HealthBaltimoreMaryland
- The Welch Center for Prevention, Epidemiology and Clinical ResearchJohns Hopkins UniversityBaltimoreMaryland
| | - Lisa A. Cooper
- The Johns Hopkins School of MedicineBaltimoreMaryland
- The Johns Hopkins Bloomberg School of Public HealthBaltimoreMaryland
- The Welch Center for Prevention, Epidemiology and Clinical ResearchJohns Hopkins UniversityBaltimoreMaryland
| | - Jeanne Charleston
- The Johns Hopkins Bloomberg School of Public HealthBaltimoreMaryland
| | | | - Kathryn A. Carson
- The Johns Hopkins Bloomberg School of Public HealthBaltimoreMaryland
- The Welch Center for Prevention, Epidemiology and Clinical ResearchJohns Hopkins UniversityBaltimoreMaryland
| | - Hsin‐Chieh Yeh
- The Johns Hopkins School of MedicineBaltimoreMaryland
- The Johns Hopkins Bloomberg School of Public HealthBaltimoreMaryland
- The Welch Center for Prevention, Epidemiology and Clinical ResearchJohns Hopkins UniversityBaltimoreMaryland
| | - Edgar R. Miller
- The Johns Hopkins School of MedicineBaltimoreMaryland
- The Johns Hopkins Bloomberg School of Public HealthBaltimoreMaryland
- The Welch Center for Prevention, Epidemiology and Clinical ResearchJohns Hopkins UniversityBaltimoreMaryland
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Al-Mallah MH. Coronary Artery Calcium Scoring: Do We Need More Prognostic Data Prior to Adoption in Clinical Practice? JACC Cardiovasc Imaging 2018; 11:1807-1809. [PMID: 30343075 DOI: 10.1016/j.jcmg.2017.11.041] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2017] [Revised: 11/08/2017] [Accepted: 11/16/2017] [Indexed: 10/28/2022]
Affiliation(s)
- Mouaz H Al-Mallah
- King Abdulaziz Cardiac Center, King Abdualaziz Medical City, Ministry of National Guard-Health Affairs, Riyadh, Kingdom of Saudi Arabia; King Saud bin Abdulaziz University for Health Sciences, Riyadh, Kingdom of Saudi Arabia; and the King Abdullah International Medical Research Center, Riyadh, Kingdom of Saudi Arabia.
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45
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Krittanawong C, Johnson KW, Hershman SG, Tang WW. Big data, artificial intelligence, and cardiovascular precision medicine. EXPERT REVIEW OF PRECISION MEDICINE AND DRUG DEVELOPMENT 2018. [DOI: 10.1080/23808993.2018.1528871] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Affiliation(s)
- Chayakrit Krittanawong
- Department of Internal Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kipp W. Johnson
- Institute for Next Generation Healthcare, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Steven G. Hershman
- Department of Medicine, Stanford University, Stanford, CA, USA
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, CA, USA
| | - W.H. Wilson Tang
- Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, OH, USA
- Department of Cellular and Molecular Medicine, Lerner Research Institute, Cleveland, OH, USA
- Center for Clinical Genomics, Cleveland Clinic, Cleveland, OH, USA
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46
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O'Brien EC, Li S, Thomas L, Wang TY, Roe MT, Peterson ED. The impact of clinical vs administrative claims coding on hospital risk-adjusted outcomes. Clin Cardiol 2018; 41:1225-1231. [PMID: 30141213 DOI: 10.1002/clc.23059] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2018] [Revised: 08/20/2018] [Accepted: 08/21/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Comorbid condition and hospital risk-adjusted outcomes prevalence were compared based on clinical registry vs administrative claims data. HYPOTHESIS Risk-adjusted outcomes will vary depending on the source of comorbidity data used. METHODS Clinical data from hospitalized Can Rapid Risk Stratification of Unstable Angina Patients Suppress Adverse Outcomes with Early Implementation of the American College of Cardiology/American Heart Association (ACC/AHA) Guidelines (CRUSADE) non-ST-segment elevation myocardial infarction (NSTEMI) patients ≥65 years was linked to Medicare claims. Eight common comorbid conditions were coded and compared between registry data (derived from medical record review) and claims data; hospital-level observed vs expected ratios and outlier status for 30-day readmission and mortality were calculated using logistic generalized estimating equations for clinical vs claims data. RESULTS Of 68 199 NSTEMI patients, 48.1% were female, 86.9% were white, and median age was 78. Degree of agreement between data sources for comorbid condition prevalence was 67.8% for myocardial infarction and 89.3% for diabetes. Overall, multivariable model performance was similar: Medicare mortality c-statistics is 0.69 vs CRUSADE is 0.71; readmission c-statistics is 0.59 for both. Hospital ratings were similar regardless of data source (mortality, R2 = 0.97863; readmission, R2 = 0.97858). Eighty-two hospitals were mortality outliers in claims-based models; of these, 70 were outliers in registry-based models. Forty-five hospitals were readmission outliers in claims-based models; of these, 39 were outliers in registry-based models. CONCLUSIONS There were significant differences in individual comorbid condition prevalence when derived from registries vs claims, but hospital-level outcomes were comparable.
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Affiliation(s)
| | - Shuang Li
- Duke Clinical Research Institute, Durham, North Carolina
| | - Laine Thomas
- Duke Clinical Research Institute, Durham, North Carolina
| | - Tracy Y Wang
- Duke Clinical Research Institute, Durham, North Carolina
| | - Matthew T Roe
- Duke Clinical Research Institute, Durham, North Carolina
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Ciemins EL, Ritchey MD, Joshi VV, Loustalot F, Hannan J, Cuddeback JK. Application of a Tool to Identify Undiagnosed Hypertension - United States, 2016. MMWR-MORBIDITY AND MORTALITY WEEKLY REPORT 2018; 67:798-802. [PMID: 30048423 PMCID: PMC6065206 DOI: 10.15585/mmwr.mm6729a2] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
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48
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Mewton N, Bergerot C, Cornu C. Letter by Mewton et al Regarding Article, "Validity of Cardiovascular Data From Electronic Sources: The Multi-Ethnic Study of Atherosclerosis and HealthLNK". Circulation 2018; 137:1759-1760. [PMID: 29661961 DOI: 10.1161/circulationaha.117.032045] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Nathan Mewton
- Clinical Investigation Center, Cardiovascular Hospital Louis Pradel, Inserm 1407, Lyon, France (N.W., C.B., C.C.).,Cardiology Department, Cardiovascular Hospital Louis Pradel, Hospices Civils de Lyon, Lyon, France (N.W., C.B.)
| | - Cyrille Bergerot
- Clinical Investigation Center, Cardiovascular Hospital Louis Pradel, Inserm 1407, Lyon, France (N.W., C.B., C.C.).,Cardiology Department, Cardiovascular Hospital Louis Pradel, Hospices Civils de Lyon, Lyon, France (N.W., C.B.)
| | - Catherine Cornu
- Clinical Investigation Center, Cardiovascular Hospital Louis Pradel, Inserm 1407, Lyon, France (N.W., C.B., C.C.)
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49
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Ahmad FS, Chan C, Rosenman MB, Post WS, Fort DG, Greenland P, Liu KJ, Kho AN, Allen NB. Response by Ahmad et al to Letter Regarding Article, "Validity of Cardiovascular Data From Electronic Sources: The Multi-Ethnic Study of Atherosclerosis and HealthLNK". Circulation 2018; 137:1761-1762. [PMID: 29661962 DOI: 10.1161/circulationaha.117.032881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Faraz S Ahmad
- Division of Epidemiology, Department of Preventive Medicine (F.S.A., C.C., P.G., K.J.L., N.B.A.).,Division of Cardiology, Department of Medicine (F.S.A., P.G.).,The Center for Health Information Partnerships, Institute of Public Health & Medicine (F.S.A., M.B.R., A.N.K.)
| | - Cheeling Chan
- Division of Epidemiology, Department of Preventive Medicine (F.S.A., C.C., P.G., K.J.L., N.B.A.)
| | - Marc B Rosenman
- The Center for Health Information Partnerships, Institute of Public Health & Medicine (F.S.A., M.B.R., A.N.K.).,Department of Pediatrics (M.B.R.)
| | - Wendy S Post
- Northwestern University Feinberg School of Medicine, Chicago, IL. Division of Cardiology, Department of Medicine, Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University School of Medicine, Baltimore, MD (W.S.P.).,Department of Epidemiology, Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (W.S.P.)
| | - Daniel G Fort
- Division of Health and Biomedical Informatics, Department of Preventive Medicine (D.G.F.)
| | - Philip Greenland
- Division of Epidemiology, Department of Preventive Medicine (F.S.A., C.C., P.G., K.J.L., N.B.A.).,Division of Cardiology, Department of Medicine (F.S.A., P.G.)
| | - Kiang J Liu
- Division of Epidemiology, Department of Preventive Medicine (F.S.A., C.C., P.G., K.J.L., N.B.A.)
| | - Abel N Kho
- The Center for Health Information Partnerships, Institute of Public Health & Medicine (F.S.A., M.B.R., A.N.K.).,Division of General Internal Medicine and Geriatrics, Department of Medicine (A.N.K.)
| | - Norrina B Allen
- Division of Epidemiology, Department of Preventive Medicine (F.S.A., C.C., P.G., K.J.L., N.B.A.)
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