Matthew W Segar1,2, Muhammad Shahzeb Khan3, Kershaw V Patel4, Muthiah Vaduganathan5, Vaishnavi Kannan6, Duwayne Willett1,6, Eric Peterson1, W H Wilson Tang7, Javed Butler3, Brendan M Everett5, Gregg C Fonarow8, Thomas J Wang1, Darren K McGuire1, Ambarish Pandey1. 1. Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA. 2. Department of Cardiology, Texas Heart Institute, Houston, TX, USA. 3. Division of Cardiology, Duke University School of Medicine, Durham, NC, USA. 4. Department of Cardiology, Houston Methodist DeBakey Heart and Vascular Center, Houston, TX, USA. 5. Brigham and Women's Hospital Heart and Vascular Center, Department of Medicine, Harvard Medical School, Boston, MA, USA. 6. Clinical Informatics Center, University of Texas Southwestern Medical Center, Dallas, TX, USA. 7. Department of Cardiovascular Medicine, Cleveland Clinic, Cleveland, OH, USA. 8. Division of Cardiology, Ronald Reagan UCLA Medical Center, Ahmanson-UCLA Cardiomyopathy Center, Los Angeles, CA, USA.
Abstract
AIMS: To evaluate the performance of the WATCH-DM risk score, a clinical risk score for heart failure (HF), in patients with dysglycaemia and in combination with natriuretic peptides (NPs). METHODS AND RESULTS: Adults with diabetes/pre-diabetes free of HF at baseline from four cohort studies (ARIC, CHS, FHS, and MESA) were included. The machine learning- [WATCH-DM(ml)] and integer-based [WATCH-DM(i)] scores were used to estimate the 5-year risk of incident HF. Discrimination was assessed by Harrell's concordance index (C-index) and calibration by the Greenwood-Nam-D'Agostino (GND) statistic. Improvement in model performance with the addition of NP levels was assessed by C-index and continuous net reclassification improvement (NRI). Of the 8938 participants included, 3554 (39.8%) had diabetes and 432 (4.8%) developed HF within 5 years. The WATCH-DM(ml) and WATCH-DM(i) scores demonstrated high discrimination for predicting HF risk among individuals with dysglycaemia (C-indices = 0.80 and 0.71, respectively), with no evidence of miscalibration (GND P ≥0.10). The C-index of elevated NP levels alone for predicting incident HF among individuals with dysglycaemia was significantly higher among participants with low/intermediate (<13) vs. high (≥13) WATCH-DM(i) scores [0.71 (95% confidence interval 0.68-0.74) vs. 0.64 (95% confidence interval 0.61-0.66)]. When NP levels were combined with the WATCH-DM(i) score, HF risk discrimination improvement and NRI varied across the spectrum of risk with greater improvement observed at low/intermediate risk [WATCH-DM(i) <13] vs. high risk [WATCH-DM(i) ≥13] (C-index = 0.73 vs. 0.71; NRI = 0.45 vs. 0.17). CONCLUSION: The WATCH-DM risk score can accurately predict incident HF risk in community-based individuals with dysglycaemia. The addition of NP levels is associated with greater improvement in the HF risk prediction performance among individuals with low/intermediate risk than those with high risk.
AIMS: To evaluate the performance of the WATCH-DM risk score, a clinical risk score for heart failure (HF), in patients with dysglycaemia and in combination with natriuretic peptides (NPs). METHODS AND RESULTS: Adults with diabetes/pre-diabetes free of HF at baseline from four cohort studies (ARIC, CHS, FHS, and MESA) were included. The machine learning- [WATCH-DM(ml)] and integer-based [WATCH-DM(i)] scores were used to estimate the 5-year risk of incident HF. Discrimination was assessed by Harrell's concordance index (C-index) and calibration by the Greenwood-Nam-D'Agostino (GND) statistic. Improvement in model performance with the addition of NP levels was assessed by C-index and continuous net reclassification improvement (NRI). Of the 8938 participants included, 3554 (39.8%) had diabetes and 432 (4.8%) developed HF within 5 years. The WATCH-DM(ml) and WATCH-DM(i) scores demonstrated high discrimination for predicting HF risk among individuals with dysglycaemia (C-indices = 0.80 and 0.71, respectively), with no evidence of miscalibration (GND P ≥0.10). The C-index of elevated NP levels alone for predicting incident HF among individuals with dysglycaemia was significantly higher among participants with low/intermediate (<13) vs. high (≥13) WATCH-DM(i) scores [0.71 (95% confidence interval 0.68-0.74) vs. 0.64 (95% confidence interval 0.61-0.66)]. When NP levels were combined with the WATCH-DM(i) score, HF risk discrimination improvement and NRI varied across the spectrum of risk with greater improvement observed at low/intermediate risk [WATCH-DM(i) <13] vs. high risk [WATCH-DM(i) ≥13] (C-index = 0.73 vs. 0.71; NRI = 0.45 vs. 0.17). CONCLUSION: The WATCH-DM risk score can accurately predict incident HF risk in community-based individuals with dysglycaemia. The addition of NP levels is associated with greater improvement in the HF risk prediction performance among individuals with low/intermediate risk than those with high risk.
Authors: Andrew L Masica; Ferdinand Velasco; Tanna L Nelson; Richard J Medford; Amy E Hughes; Ambarish Pandey; Eric D Peterson; Christoph U Lehmann Journal: Learn Health Syst Date: 2022-09-04
Authors: Matthew W Segar; Kershaw V Patel; Anne S Hellkamp; Muthiah Vaduganathan; Yuliya Lokhnygina; Jennifer B Green; Siu-Hin Wan; Ahmed A Kolkailah; Rury R Holman; Eric D Peterson; Vaishnavi Kannan; Duwayne L Willett; Darren K McGuire; Ambarish Pandey Journal: J Am Heart Assoc Date: 2022-06-03 Impact factor: 6.106