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1. Guidance for unbiased predictive information for healthcare decision-making and equity (GUIDE): considerations when race may be a prognostic factor

Author

Keren Ladin, John Cuddeback, O. Kenrik Duru, Sharad Goel, William Harvey, Jinny G. Park, Jessica K. Paulus, Joyce Sackey, Richard Sharp, Ewout Steyerberg, Berk Ustun, David van Klaveren, Saul N. Weingart, and David M. Kent

Subjects
Computer applications to medicine. Medical informatics, R858-859.7
Abstract

Abstract Clinical prediction models (CPMs) are tools that compute the risk of an outcome given a set of patient characteristics and are routinely used to inform patients, guide treatment decision-making, and resource allocation. Although much hope has been placed on CPMs to mitigate human biases, CPMs may potentially contribute to racial disparities in decision-making and resource allocation. While some policymakers, professional organizations, and scholars have called for eliminating race as a variable from CPMs, others raise concerns that excluding race may exacerbate healthcare disparities and this controversy remains unresolved. The Guidance for Unbiased predictive Information for healthcare Decision-making and Equity (GUIDE) provides expert guidelines for model developers and health system administrators on the transparent use of race in CPMs and mitigation of algorithmic bias across contexts developed through a 5-round, modified Delphi process from a diverse 14-person technical expert panel (TEP). Deliberations affirmed that race is a social construct and that the goals of prediction are distinct from those of causal inference, and emphasized: the importance of decisional context (e.g., shared decision-making versus healthcare rationing); the conflicting nature of different anti-discrimination principles (e.g., anticlassification versus antisubordination principles); and the importance of identifying and balancing trade-offs in achieving equity-related goals with race-aware versus race-unaware CPMs for conditions where racial identity is prognostically informative. The GUIDE, comprising 31 key items in the development and use of CPMs in healthcare, outlines foundational principles, distinguishes between bias and fairness, and offers guidance for examining subgroup invalidity and using race as a variable in CPMs. This GUIDE presents a living document that supports appraisal and reporting of bias in CPMs to support best practice in CPM development and use.

Published
2024
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2. Fulfillment and Validity of the Kidney Health Evaluation Measure for People with Diabetes

Author

Silvia Ferrè, PhD, Amy Storfer-Isser, PhD, Kelsy Kinderknecht, MS, Elizabeth Montgomery, BS, Miriam Godwin, MS, Ashby Andrews, MA, MS, Stephan Dunning, MBA, Mary Barton, MD, Dan Roman, BS, John Cuddeback, MD, PhD, Nikita Stempniewicz, MS, Chi D. Chu, MD, Delphine S. Tuot, MD, and Joseph A. Vassalotti, MD

Subjects
Medicine (General), R5-920
Abstract

Objective: To evaluate the fulfillment and validity of the kidney health evaluation for people with diabetes (KED) Healthcare Effectiveness Data Information Set (HEDIS) measure. Patients and Methods: Optum Labs Data Warehouse (OLDW) was used to identify the nationally distributed US population aged 18 years and older, with diabetes, between January 1, 2017, and December 31, 2017. The OLDW includes deidentified medical, pharmacy, laboratory, and electronic health record (EHR) data. The KED fulfillment was defined in 2017 as both estimated glomerular filtration rate (eGFR) and urinary albumin-creatinine ratio testing within the measurement year. The KED validity was assessed using bivariate analyses of KED fulfillment with diabetes care measures in 2017 and chronic kidney disease (CKD) diagnosis and evidence-based kidney protective interventions in 2018. Results: Among eligible 5,635,619 Medicare fee-for-service beneficiaries, 736,875 Medicare advantage (MA) beneficiaries, and 660,987 commercial patients, KED fulfillment was 32.2%, 38.7%, and 37.7%, respectively. Albuminuria testing limited KED fulfillment with urinary albumin-creatinine ratio testing (90%). The KED fulfillment was positively associated with receipt of diabetes care in 2017, CKD diagnosis in 2018, and evidence-based kidney protective interventions in 2018. The KED fulfillment trended lower for Black race, Medicare-Medicaid dual eligibility status, low neighborhood income, and low education status. Conclusion: Less than 40% of adults with diabetes received guideline-recommended testing for CKD in 2017. Routine KED was associated with diabetes care and evidence-based CKD interventions. Increasing guideline-recommended testing for CKD among people with diabetes should lead to timely and equitable CKD detection and treatment.

Published
2023
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3. Development and Validation of Prediction Models of Adverse Kidney Outcomes in the Population With and Without Diabetes

Author

Morgan E, Grams, Nigel J, Brunskill, Shoshana H, Ballew, Yingying, Sang, Josef, Coresh, Kunihiro, Matsushita, Aditya, Surapaneni, Samira, Bell, Juan J, Carrero, Gabriel, Chodick, Marie, Evans, Hiddo J L, Heerspink, Lesley A, Inker, Kunitoshi, Iseki, Philip A, Kalra, H Lester, Kirchner, Brian J, Lee, Adeera, Levin, Rupert W, Major, James, Medcalf, Girish N, Nadkarni, David M J, Naimark, Ana C, Ricardo, Simon, Sawhney, Manish M, Sood, Natalie, Staplin, Nikita, Stempniewicz, Benedicte, Stengel, Keiichi, Sumida, Jamie P, Traynor, Jan, van den Brand, Chi-Pang, Wen, Mark, Woodward, Jae Won, Yang, Angela Yee-Moon, Wang, Navdeep, Tangri, John, Chalmers, Chi-Yuan, Hsu, Amanda, Anderson, Panduranga, Rao, Harold, Feldman, Alex R, Chang, Kevin, Ho, Jamie, Green, Moneeza, Siddiqui, Colin, Palmer, Varda, Shalev, Marie, Metzger, Martin, Flamant, Pascal, Houillier, Jean-Philippe, Haymann, John, Cuddeback, Elizabeth, Ciemins, Csaba P, Kovesdy, Marco, Trevisan, Carl Gustaf, Elinder, Björn, Wettermark, Philip, Kalra, Rajkumar, Chinnadurai, James, Tollitt, Darren, Green, Ron T, Gansevoort, Orlando, Gutierrez, Tsuneo, Konta, Anna, Köttgen, Andrew S, Levey, Kevan, Polkinghorne, Elke, Schäffner, Luxia, Zhang, Jingsha, Chen, Real World Studies in PharmacoEpidemiology, -Genetics, -Economics and -Therapy (PEGET), and Groningen Kidney Center (GKC)

Subjects
Advanced and Specialized Nursing, Endocrinology, Diabetes and Metabolism, Internal Medicine, Diabetes Mellitus, Albuminuria, Humans, Renal Insufficiency, Renal disorders Radboud Institute for Health Sciences [Radboudumc 11], Renal Insufficiency, Chronic, Kidney, Glomerular Filtration Rate
Abstract

OBJECTIVE To predict adverse kidney outcomes for use in optimizing medical management and clinical trial design. RESEARCH DESIGN AND METHODS In this meta-analysis of individual participant data, 43 cohorts (N = 1,621,817) from research studies, electronic medical records, and clinical trials with global representation were separated into development and validation cohorts. Models were developed and validated within strata of diabetes mellitus (presence or absence) and estimated glomerular filtration rate (eGFR; ≥60 or RESULTS There were 17,399 and 24,591 events in development and validation cohorts, respectively. Models predicting ≥40% eGFR decline or kidney failure incorporated age, sex, eGFR, albuminuria, systolic blood pressure, antihypertensive medication use, history of heart failure, coronary heart disease, atrial fibrillation, smoking status, and BMI, and, in those with diabetes, hemoglobin A1c, insulin use, and oral diabetes medication use. The median C-statistic was 0.774 (interquartile range [IQR] = 0.753, 0.782) in the diabetes and higher-eGFR validation cohorts; 0.769 (IQR = 0.758, 0.808) in the diabetes and lower-eGFR validation cohorts; 0.740 (IQR = 0.717, 0.763) in the no diabetes and higher-eGFR validation cohorts; and 0.750 (IQR = 0.731, 0.785) in the no diabetes and lower-eGFR validation cohorts. Incorporating the previous 2-year eGFR slope minimally improved model performance, and then only in the higher-eGFR cohorts. CONCLUSIONS Novel prediction equations for a decline of ≥40% in eGFR can be applied successfully for use in the general population in persons with and without diabetes with higher or lower eGFR.

Published
2022

4. Albuminuria Testing in Hypertension and Diabetes

Author

Jung-Im Shin, Alex R. Chang, Morgan E. Grams, Josef Coresh, Shoshana H. Ballew, Aditya Surapaneni, Kunihiro Matsushita, Henk J.G. Bilo, Juan J. Carrero, Gabriel Chodick, Kenn B. Daratha, Simerjot K. Jassal, Girish N. Nadkarni, Robert G. Nelson, Christoph Nowak, Nikita Stempniewicz, Keiichi Sumida, Jamie P. Traynor, Mark Woodward, Yingying Sang, Ron T. Gansevoort, John Chalmers, Katherine Tuttle, Radica Alicic, Sterling McPherson, Cami Jones, Gurmukteshwar Singh, Jamie Green, H. Lester Kirchner, Varda Shalev, Erwin P. Bottinger, Ruth J.F. Loos, Stephen B. Ellis, John Cuddeback, Elizabeth Ciemins, Emily Carbonara, Stephan Dunning, William C. Knowler, Helen C. Looker, Lyane M. Kieneker, Stephan J.L. Bakker, Hans L. Hillege, Pim van der Harst, Jacklyn Bergstrom, Joachim Ix, Csaba P. Kovesdy, Praveen Potukuchi, Marco Trevisan, Carl Gustaf Elinder, Björn Wettermark, Johan Ärnlöv, Patrick B. Mark, Peter C. Thomson, Colin C. Geddes, Gijs W.D. Landman, Kornelis J.J. van Hateren, Nanne Kleefstra, Orlando Gutierrez, Tsuneo Konta, Andrew S. Levey, Kevan Polkinghorne, Elke Schäffner, Jingsha Chen, Aditya Surapeneni, Groningen Kidney Center (GKC), and Cardiovascular Centre (CVC)

Subjects
Adult, medicine.medical_specialty, Article, Diabetes mellitus, Internal medicine, Internal Medicine, Diabetes Mellitus, Medicine, Albuminuria, Humans, Renal Insufficiency, Chronic, Aged, business.industry, Incidence (epidemiology), Odds ratio, Middle Aged, medicine.disease, Blood pressure, Meta-analysis, Creatinine, Cohort, Hypertension, medicine.symptom, business, Kidney disease, Glomerular Filtration Rate
Abstract

Albuminuria is an under-recognized component of chronic kidney disease definition, staging, and prognosis. Guidelines, particularly for hypertension, conflict on recommendations for urine albumin-to-creatinine ratio (ACR) measurement. Separately among 1 344 594 adults with diabetes and 2 334 461 nondiabetic adults with hypertension from the chronic kidney disease Prognosis Consortium, we assessed ACR testing, estimated the prevalence and incidence of ACR ≥30 mg/g and developed risk models for ACR ≥30 mg/g. The ACR screening rate (cohort range) was 35.1% (12.3%–74.5%) in diabetes and 4.1% (1.3%–20.7%) in hypertension. Screening was largely unrelated to the predicted risk of prevalent albuminuria. The median prevalence of ACR ≥30 mg/g across cohorts was 32.1% in diabetes and 21.8% in hypertension. Higher systolic blood pressure was associated with a higher prevalence of albuminuria (odds ratio [95% CI] per 20 mm Hg in diabetes, 1.50 [1.42–1.60]; in hypertension, 1.36 [1.28–1.45]). The ratio of undetected (due to lack of screening) to detected ACR ≥30 mg/g was estimated at 1.8 in diabetes and 19.5 in hypertension. Among those with ACR

Published
2021

5. Addressing Therapeutic Inertia in 2020 and Beyond: A 3-Year Initiative of the American Diabetes Association

Author

Kamlesh Khunti, Christine Beebe, John Cuddeback, Luigi F. Meneghini, Paul Scribner, Naeem D. Khan, Todd Hobbs, Debbie Kendall, Lucia M. Novak, Eden Miller, Robert A. Gabbay, Sandra Leal, and Swapnil Rajpathak

Subjects
American diabetes association, medicine.medical_specialty, Scope (project management), business.industry, Endocrinology, Diabetes and Metabolism, Psychological intervention, 030209 endocrinology & metabolism, Type 2 diabetes, medicine.disease, Perspectives in Clinical Diabetes, Test (assessment), 03 medical and health sciences, 0302 clinical medicine, Publishing, Family medicine, Internal Medicine, medicine, 030212 general & internal medicine, business, Glycemic, Therapeutic inertia
Abstract

Research has shown that getting to glycemic targets early on leads to better outcomes in people with type 2 diabetes; yet, there has been no improvement in the attainment of A1C targets in the past decade. One reason is therapeutic inertia: the lack of timely adjustment to the treatment regimen when a person’s therapeutic targets are not met. This article describes the scope and priorities of the American Diabetes Association’s 3-year Overcoming Therapeutic Inertia Initiative. Its planned activities include publishing a systematic review and meta-analysis of approaches to reducing therapeutic inertia, developing a registry of effective strategies, launching clinician awareness and education campaigns, leveraging electronic health record and clinical decision-support tools, influencing payer policies, and potentially executing pragmatic research to test promising interventions.

Published
2020

6. Author response for 'Strategies for overcoming therapeutic inertia in type 2 diabetes: A systematic review and meta‐analysis'

Author

Robert A. Gabbay, Michelle L. Litchman, Christine Beebe, Rhea E. Powell, Alyssa Crawford, Francesco Zaccardi, Xin Mei Chen, Paul Scribner, Rajesh R. Mehta, Kevin M. Pantalone, Lauren Kissela, Jessica W. Skelley, John Cuddeback, Luigi F. Meneghini, Swapnil Rajpathak, and Kamlesh Khunti

Subjects
medicine.medical_specialty, business.industry, Meta-analysis, medicine, Type 2 diabetes, Intensive care medicine, medicine.disease, business, Therapeutic inertia
Published
2021
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7. Development of Risk Prediction Equations for Incident Chronic Kidney Disease

Author

Robert G, Nelson Morgan, E Grams, Shoshana H, Ballew, Yingying, Sang, Fereidoun, Azizi, Steven J, Chadban, Layal, Chaker, Stephan C, Dunning, Caroline, Fox, Yoshihisa, Hirakawa, Kunitoshi, Iseki, Joachim, Ix, Tazeen H, Jafar, Anna, Köttgen, David M, J Naimark, Takayoshi, Ohkubo, Gordon J, Prescott Casey, M Rebholz, Charumathi, Sabanayagam, Toshimi, Sairenchi, Ben, Schöttker, Yugo, Shibagaki, Marcello, Tonelli, Luxia, Zhang, Ron T, Gansevoort, Kunihiro, Matsushita, Mark, Woodward, Josef, Coresh, Varda, Shalev, CKD Prognosis Consortium, John, Chalmers, Hisatomi, Arima, Vlado, Perkovic, Morgan, Grams, Kevan, Polkinghorne, Robert, Atkins, Steven, Chadban, Ming-Hui, Zhao, Fang, Wang, Jinwei, Wang, Frank, Sacks, Gary, Curhan, Michael, Shlipak, Mark, Sarnak, Ronit, Katz, Jade, Hiramoto, Hiroyasu, Iso, Isao, Muraki, Kazumasa, Yamagishi, Mitsumasa, Umesawa, Hermann, Brenner, Kai-Uwe, Saum, Dietrich, Rothenbacher, Shih-Jen, Hwang, Alex, Chang, Jamie, Green, Gurmukteshwar, Singh, H Lester, Kirchner, Corri, Black, Angharad, Marks, Gordon, Prescott, Laura, Clark, Nick, Fluck, Cirillo, Massimo, Stein, Hallan, Marius, Øvrehus, Knut, Langlo, Solfrid, Romundstad, Fujiko, Irie, Adolfo, Correa, Casey, Rebholz, Bessie, Young, L Ebony, Boulware, Stanford, Mwasongwe, Tsuyoshi, Watanabe, Kunihiro, Yamagata, Koichi, Asahi, Gabriel, Chodick, Carmen, Peralta, Erwin, Bottinger, Girish, Nadkarni, Stephen, Ellis, Rajiv, Nadukuru, Timothy, Kenealy, C Raina, Elley, John, Collins, Paul, Drury, Kei, Asayama, Masahiro, Kikuya, Hirohito, Metoki, Masaaki, Nakayama, Chiho, Iseki, Robert, Nelson, Helen, Looker, William, Knowler, Ron, Gansevoort, Stephan, Bakker, Hiddo, Heerspink, Simerjot, Jassal, Jaclyn, Bergstrom, Elizabeth, Barrett-Connor, Csaba, Kovesdy, Keiichi, Sumida, Kamyar, Kalantar-Zadeh, Sanaz, Sedaghat, Arfan, Ikram, Ewout, Hoorn, Abbas, Dehghan, Juan, Carrero, Marie, Evans, Carl-Gustaf, Elinder, Tien, Wong, Ching-Yu, Cheng, Chi-Pang, Wen, Chwen-Keng, Tsao, Min-Kuang, Tsai, Chien-Hua, Chen, Farhad, Hosseinpanah, Farzad, Hadaegh, Mohammadhassan, Mirbolouk, Marit, Solbu, Bjørn, Eriksen, Trond, Jenssen, Anne, Eggen, Lars, Lannfelt, Anders, Larsson, Johan, Ärnlöv, Henk, Bilo, Gijs, Landman, Kornelis, Hateren, Nanne, Kleefstra, Stephan, Dunning, Nikita, Stempniewicz, John, Cuddeback, Elizabeth, Ciemins, Shoshana, Ballew, Andrew, Levey, Jingsha, Chen, Lucia, Kwak, Aditya, Surapeneni, Mark, Woodward., Robert, G, Nelson, Morgan, E, Gram, Shoshana, H, Ballew, Yingying, Sang, Fereidoun, Azizi, Steven, J, Chadban, Layal, Chaker, Stephan, C, Dunning, Caroline, Fox, Yoshihisa, Hirakawa, Kunitoshi, Iseki, Joachim, Ix, Tazeen, H, Jafar, Anna, Köttgen, David, M, J, Naimark, Takayoshi, Ohkubo, Gordon, J, Prescott, Casey, M, Rebholz, Charumathi, Sabanayagam, Toshimi, Sairenchi, Ben, Schöttker, Yugo, Shibagaki, Marcello, Tonelli, Luxia, Zhang, Ron, T, Gansevoort, Kunihiro, Matsushita, Mark, Woodward, Josef, Coresh, Varda, Shalev, CKD Prognosis, Consortium, John, Chalmer, Hisatomi, Arima, Vlado, Perkovic, Morgan, Gram, Kevan, Polkinghorne, Robert, Atkin, Steven, Chadban, Ming-Hui, Zhao, Fang, Wang, Jinwei, Wang, Frank, Sack, Gary, Curhan, Michael, Shlipak, Mark, Sarnak, Ronit, Katz, Jade, Hiramoto, Hiroyasu, Iso, Isao, Muraki, Kazumasa, Yamagishi, Mitsumasa, Umesawa, Hermann, Brenner, Kai-Uwe, Saum, Dietrich, Rothenbacher, Shih-Jen, Hwang, Alex, Chang, Jamie, Green, Gurmukteshwar, Singh, H, Lester, Kirchner, Corri, Black, Angharad, Mark, Gordon, Prescott, Laura, Clark, Nick, Fluck, Cirillo, Massimo, Stein, Hallan, Marius, Øvrehu, Knut, Langlo, Solfrid, Romundstad, Fujiko, Irie, Adolfo, Correa, Casey, Rebholz, Bessie, Young, L, Ebony, Boulware, Stanford, Mwasongwe, Tsuyoshi, Watanabe, Kunihiro, Yamagata, Koichi, Asahi, Gabriel, Chodick, Carmen, Peralta, Erwin, Bottinger, Girish, Nadkarni, Stephen, Elli, Rajiv, Nadukuru, Timothy, Kenealy, C, Raina, Elley, John, Collin, Paul, Drury, Kei, Asayama, Masahiro, Kikuya, Hirohito, Metoki, Masaaki, Nakayama, Chiho, Iseki, Robert, Nelson, Helen, Looker, William, Knowler, Ron, Gansevoort, Stephan, Bakker, Hiddo, Heerspink, Simerjot, Jassal, Jaclyn, Bergstrom, Elizabeth, Barrett-Connor, Csaba, Kovesdy, Keiichi, Sumida, Kamyar, Kalantar-Zadeh, Sanaz, Sedaghat, Arfan, Ikram, Ewout, Hoorn, Abbas, Dehghan, Juan, Carrero, Marie, Evan, Carl-Gustaf, Elinder, Tien, Wong, Ching-Yu, Cheng, Chi-Pang, Wen, Chwen-Keng, Tsao, Min-Kuang, Tsai, Chien-Hua, Chen, Farhad, Hosseinpanah, Farzad, Hadaegh, Mohammadhassan, Mirbolouk, Marit, Solbu, Bjørn, Eriksen, Trond, Jenssen, Anne, Eggen, Lars, Lannfelt, Anders, Larsson, Johan, Ärnlöv, Henk, Bilo, Gijs, Landman, Kornelis, Hateren, Nanne, Kleefstra, Stephan, Dunning, Nikita, Stempniewicz, John, Cuddeback, Elizabeth, Ciemin, Shoshana, Ballew, Andrew, Levey, Jingsha, Chen, Lucia, Kwak, Aditya, Surapeneni, Mark, Woodward., Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), Groningen Institute for Organ Transplantation (GIOT), Lifestyle Medicine (LM), Real World Studies in PharmacoEpidemiology, -Genetics, -Economics and -Therapy (PEGET), Epidemiology, and Internal Medicine

Subjects
Male, medicine.medical_specialty, Renal function, Disease, Risk Assessment, 01 natural sciences, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Interquartile range, Internal medicine, Diabetes mellitus, medicine, CKD, Humans, 030212 general & internal medicine, 0101 mathematics, Renal Insufficiency, Chronic, Statistic, Aged, Original Investigation, business.industry, 010102 general mathematics, General Medicine, Middle Aged, Models, Theoretical, medicine.disease, MODEL, RENAL-DISEASE, Albuminuria, Female, medicine.symptom, business, Body mass index, Glomerular Filtration Rate, Kidney disease
Abstract

IMPORTANCE Early identification of individuals at elevated risk of developing chronic kidney disease (CKD) could improve clinical care through enhanced surveillance and better management of underlying health conditions.OBJECTIVE To develop assessment tools to identify individuals at increased risk of CKD, defined by reduced estimated glomerular filtration rate (eGFR).DESIGN, SETTING, AND PARTICIPANTS Individual-level data analysis of 34 multinational cohorts from the CKD Prognosis Consortium including 5 222 711 individuals from 28 countries. Data were collected from April 1970 through January 2017. A 2-stage analysis was performed, with each study first analyzed individually and summarized overall using a weighted average. Because clinical variables were often differentially available by diabetes status, models were developed separately for participants with diabetes and without diabetes. Discrimination and calibration were also tested in 9 external cohorts (n = 2 253 540).EXPOSURES Demographic and clinical factors.MAIN OUTCOMES AND MEASURES Incident eGFR of less than 60 mL/min/1.73 m(2).RESULTS Among 4 441 084 participants without diabetes (mean age, 54 years, 38% women), 660 856 incident cases (14.9%) of reduced eGFR occurred during a mean follow-up of 4.2 years. Of 781 627 participants with diabetes (mean age, 62 years, 13% women), 313 646 incident cases (40%) occurred during a mean follow-up of 3.9 years. Equations for the 5-year risk of reduced eGFR included age, sex, race/ethnicity, eGFR, history of cardiovascular disease, ever smoker, hypertension, body mass index, and albuminuria concentration. For participants with diabetes, the models also included diabetes medications, hemoglobin A(1c), and the interaction between the 2. The risk equations had a median C statistic for the 5-year predicted probability of 0.845 (interquartile range [IQR], 0.789-0.890) in the cohorts without diabetes and 0.801 (IQR, 0.750-0.819) in the cohorts with diabetes. Calibration analysis showed that 9 of 13 study populations (69%) had a slope of observed to predicted risk between 0.80 and 1.25. Discrimination was similar in 18 study populations in 9 external validation cohorts; calibration showed that 16 of 18 (89%) had a slope of observed to predicted risk between 0.80 and 1.25.CONCLUSIONS AND RELEVANCE Equations for predicting risk of incident chronic kidney disease developed from more than 5 million individuals from 34 multinational cohorts demonstrated high discrimination and variable calibration in diverse populations. Further study is needed to determine whether use of these equations to identify individuals at risk of developing chronic kidney disease will improve clinical care and patient outcomes.

Published
2019

9. Stage 2 hypertension: predictors of failure to achieve blood pressure control and the impact of adding one additional antihypertensive class

Author

Christopher G, Rowan, James, Flory, Nikita, Stempniewicz, John, Cuddeback, and Steven M, Brunelli

Subjects
Male, Blood Pressure, Middle Aged, Cohort Studies, Logistic Models, Treatment Outcome, Hypertension, Electronic Health Records, Humans, Drug Therapy, Combination, Female, Treatment Failure, Monte Carlo Method, Antihypertensive Agents, Aged, Follow-Up Studies, Retrospective Studies
Abstract

Controlling blood pressure (BP) for patients with stage 2 hypertension remains challenging. This research aimed to: (i) identify predictors of failure to achieve BP control, (ii) determine the association of adding one additional antihypertensive class with achieving BP control, and (iii) describe the prescribed antihypertensive regimens.Electronic medical record data from 25 multi-specialty medical groups in the USA were used. The study cohort included patients with stage 2 hypertension in 2012. BP control rates were determined at 6 months from the date of the stage 2 BP. Using multivariable logistic regression and validation by Monte Carlo simulation, we determined independent baseline predictors of not achieving BP control (140/90).Included were 107 903 patients. Baseline predictors of failure to achieve BP control included the following: a prior stage 2 BP, systolic BP ≥ 165, Black race, male sex, income ≤ $35 000, body mass index ≥ 30, age ≥ 65 years, and no office visits. Increasing from single-class to dual-class antihypertensive therapy was associated with a 42% increased odds of achieving BP control (odds ratio 1.42; 95% CI 1.22, 1.64); however, this effect was attenuated as the number of baseline antihypertensive classes increased. The 10 most frequently prescribed regimens accounted for only 40% of all antihypertensive regimens.Among patients with stage 2 hypertension, a prior stage 2 BP, a systolic BP ≥ 165, and fewer office visits were strong predictors of failure to achieve BP control. Increasing to dual-class antihypertensive therapy was significantly associated with achieving BP control. There is broad heterogeneity in the antihypertensive regimens prescribed.

Published
2014

10. Transfusions for Jehovah's Witnesses

Author

Ivy Purkey, John Cuddeback, Linda Orsine, and Richard F. Kaplan

Subjects
medicine.medical_specialty, Blood Transfusion, Autologous, Anesthesiology and Pain Medicine, business.industry, General surgery, Religion and Medicine, medicine, Humans, business, Christianity
Published
1983

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