M. Segar, Kershaw V. Patel, A. Hellkamp, M. Vaduganathan, Y. Lokhnygina, Jennifer B. Green, S. Wan, A. Kolkailah, R. Holman, E. Peterson, V. Kannan, D. Willett, D. McGuire, A. Pandey
{"title":"WATCH - DM和TRS - HFDM风险评分预测成人2型糖尿病心力衰竭住院风险的验证:一项多队列分析","authors":"M. Segar, Kershaw V. Patel, A. Hellkamp, M. Vaduganathan, Y. Lokhnygina, Jennifer B. Green, S. Wan, A. Kolkailah, R. Holman, E. Peterson, V. Kannan, D. Willett, D. McGuire, A. Pandey","doi":"10.1161/JAHA.121.024094","DOIUrl":null,"url":null,"abstract":"Background The WATCH‐DM (weight [body mass index], age, hypertension, creatinine, high‐density lipoprotein cholesterol, diabetes control [fasting plasma glucose], ECG QRS duration, myocardial infarction, and coronary artery bypass grafting) and TRS‐HFDM (Thrombolysis in Myocardial Infarction [TIMI] risk score for heart failure in diabetes) risk scores were developed to predict risk of heart failure (HF) among individuals with type 2 diabetes. WATCH‐DM was developed to predict incident HF, whereas TRS‐HFDM predicts HF hospitalization among patients with and without a prior HF history. We evaluated the model performance of both scores to predict incident HF events among patients with type 2 diabetes and no history of HF hospitalization across different cohorts and clinical settings with varying baseline risk. Methods and Results Incident HF risk was estimated by the integer‐based WATCH‐DM and TRS‐HFDM scores in participants with type 2 diabetes free of baseline HF from 2 randomized clinical trials (TECOS [Trial Evaluating Cardiovascular Outcomes With Sitagliptin], N=12 028; and Look AHEAD [Look Action for Health in Diabetes] trial, N=4867). The integer‐based WATCH‐DM score was also validated in electronic health record data from a single large health care system (N=7475). Model discrimination was assessed by the Harrell concordance index and calibration by the Greenwood‐Nam‐D’Agostino statistic. HF incidence rate was 7.5, 3.9, and 4.1 per 1000 person‐years in the TECOS, Look AHEAD trial, and electronic health record cohorts, respectively. Integer‐based WATCH‐DM and TRS‐HFDM scores had similar discrimination and calibration for predicting 5‐year HF risk in the Look AHEAD trial cohort (concordance indexes=0.70; Greenwood‐Nam‐D’Agostino P>0.30 for both). Both scores had lower discrimination and underpredicted HF risk in the TECOS cohort (concordance indexes=0.65 and 0.66, respectively; Greenwood‐Nam‐D’Agostino P<0.001 for both). In the electronic health record cohort, the integer‐based WATCH‐DM score demonstrated a concordance index of 0.73 with adequate calibration (Greenwood‐Nam‐D’Agostino P=0.96). TRS‐HFDM score could not be validated in the electronic health record because of unavailability of data on urine albumin/creatinine ratio in most patients in the contemporary clinical practice. Conclusions The WATCH‐DM and TRS‐HFDM risk scores can discriminate risk of HF among intermediate‐risk populations with type 2 diabetes.","PeriodicalId":17189,"journal":{"name":"Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Validation of the WATCH‐DM and TRS‐HFDM Risk Scores to Predict the Risk of Incident Hospitalization for Heart Failure Among Adults With Type 2 Diabetes: A Multicohort Analysis\",\"authors\":\"M. Segar, Kershaw V. Patel, A. Hellkamp, M. Vaduganathan, Y. Lokhnygina, Jennifer B. Green, S. Wan, A. Kolkailah, R. Holman, E. Peterson, V. Kannan, D. Willett, D. McGuire, A. Pandey\",\"doi\":\"10.1161/JAHA.121.024094\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background The WATCH‐DM (weight [body mass index], age, hypertension, creatinine, high‐density lipoprotein cholesterol, diabetes control [fasting plasma glucose], ECG QRS duration, myocardial infarction, and coronary artery bypass grafting) and TRS‐HFDM (Thrombolysis in Myocardial Infarction [TIMI] risk score for heart failure in diabetes) risk scores were developed to predict risk of heart failure (HF) among individuals with type 2 diabetes. WATCH‐DM was developed to predict incident HF, whereas TRS‐HFDM predicts HF hospitalization among patients with and without a prior HF history. We evaluated the model performance of both scores to predict incident HF events among patients with type 2 diabetes and no history of HF hospitalization across different cohorts and clinical settings with varying baseline risk. Methods and Results Incident HF risk was estimated by the integer‐based WATCH‐DM and TRS‐HFDM scores in participants with type 2 diabetes free of baseline HF from 2 randomized clinical trials (TECOS [Trial Evaluating Cardiovascular Outcomes With Sitagliptin], N=12 028; and Look AHEAD [Look Action for Health in Diabetes] trial, N=4867). The integer‐based WATCH‐DM score was also validated in electronic health record data from a single large health care system (N=7475). Model discrimination was assessed by the Harrell concordance index and calibration by the Greenwood‐Nam‐D’Agostino statistic. HF incidence rate was 7.5, 3.9, and 4.1 per 1000 person‐years in the TECOS, Look AHEAD trial, and electronic health record cohorts, respectively. Integer‐based WATCH‐DM and TRS‐HFDM scores had similar discrimination and calibration for predicting 5‐year HF risk in the Look AHEAD trial cohort (concordance indexes=0.70; Greenwood‐Nam‐D’Agostino P>0.30 for both). Both scores had lower discrimination and underpredicted HF risk in the TECOS cohort (concordance indexes=0.65 and 0.66, respectively; Greenwood‐Nam‐D’Agostino P<0.001 for both). In the electronic health record cohort, the integer‐based WATCH‐DM score demonstrated a concordance index of 0.73 with adequate calibration (Greenwood‐Nam‐D’Agostino P=0.96). TRS‐HFDM score could not be validated in the electronic health record because of unavailability of data on urine albumin/creatinine ratio in most patients in the contemporary clinical practice. Conclusions The WATCH‐DM and TRS‐HFDM risk scores can discriminate risk of HF among intermediate‐risk populations with type 2 diabetes.\",\"PeriodicalId\":17189,\"journal\":{\"name\":\"Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1161/JAHA.121.024094\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1161/JAHA.121.024094","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Validation of the WATCH‐DM and TRS‐HFDM Risk Scores to Predict the Risk of Incident Hospitalization for Heart Failure Among Adults With Type 2 Diabetes: A Multicohort Analysis
Background The WATCH‐DM (weight [body mass index], age, hypertension, creatinine, high‐density lipoprotein cholesterol, diabetes control [fasting plasma glucose], ECG QRS duration, myocardial infarction, and coronary artery bypass grafting) and TRS‐HFDM (Thrombolysis in Myocardial Infarction [TIMI] risk score for heart failure in diabetes) risk scores were developed to predict risk of heart failure (HF) among individuals with type 2 diabetes. WATCH‐DM was developed to predict incident HF, whereas TRS‐HFDM predicts HF hospitalization among patients with and without a prior HF history. We evaluated the model performance of both scores to predict incident HF events among patients with type 2 diabetes and no history of HF hospitalization across different cohorts and clinical settings with varying baseline risk. Methods and Results Incident HF risk was estimated by the integer‐based WATCH‐DM and TRS‐HFDM scores in participants with type 2 diabetes free of baseline HF from 2 randomized clinical trials (TECOS [Trial Evaluating Cardiovascular Outcomes With Sitagliptin], N=12 028; and Look AHEAD [Look Action for Health in Diabetes] trial, N=4867). The integer‐based WATCH‐DM score was also validated in electronic health record data from a single large health care system (N=7475). Model discrimination was assessed by the Harrell concordance index and calibration by the Greenwood‐Nam‐D’Agostino statistic. HF incidence rate was 7.5, 3.9, and 4.1 per 1000 person‐years in the TECOS, Look AHEAD trial, and electronic health record cohorts, respectively. Integer‐based WATCH‐DM and TRS‐HFDM scores had similar discrimination and calibration for predicting 5‐year HF risk in the Look AHEAD trial cohort (concordance indexes=0.70; Greenwood‐Nam‐D’Agostino P>0.30 for both). Both scores had lower discrimination and underpredicted HF risk in the TECOS cohort (concordance indexes=0.65 and 0.66, respectively; Greenwood‐Nam‐D’Agostino P<0.001 for both). In the electronic health record cohort, the integer‐based WATCH‐DM score demonstrated a concordance index of 0.73 with adequate calibration (Greenwood‐Nam‐D’Agostino P=0.96). TRS‐HFDM score could not be validated in the electronic health record because of unavailability of data on urine albumin/creatinine ratio in most patients in the contemporary clinical practice. Conclusions The WATCH‐DM and TRS‐HFDM risk scores can discriminate risk of HF among intermediate‐risk populations with type 2 diabetes.