Impact of Residential Social Deprivation on Prediction of Heart Failure in Patients With Type 2 Diabetes: External Validation and Recalibration of the WATCH-DM Score Using Real World Data

Author:

Deo Salil V.123ORCID,Al-Kindi Sadeer4ORCID,Motairek Issam5ORCID,McAllister David3ORCID,Shah Anoop S.V.6ORCID,Elgudin Yakov E.12ORCID,Gorodeski Eiran Z.5ORCID,Virani Salim78ORCID,Petrie Mark C.910ORCID,Rajagopalan Sanjay5ORCID,Sattar Naveed9ORCID

Affiliation:

1. Surgical Services, Louis Stokes Cleveland VA Medical Center, Cleveland, OH (S.V.D., Y.E.E.).

2. Case School of Medicine, Case Western Reserve University School of Medicine, Cleveland, OH (S.V.D., Y.E.E., E.Z.G., S.R.).

3. School of Health and Wellbeing (S.V.D., D.M.), University of Glasgow, United Kingdom.

4. Division of Cardiovascular Prevention and Wellness, DeBakey Heart and Vascular Center, Houston Methodist, Houston, TX (S.A.-K.).

5. Harrington Heart and Vascular Institute, University Hospitals, Cleveland, OH (I.M., E.Z.G., S.R.).

6. London School of Hygiene and Tropical Medicine, London, United Kingdom (A.S.V.S.).

7. The Aga Khan University, Karachi, Pakistan (S.V.).

8. Division of Cardiology, Baylor School of Medicine, Houston, TX (S.V.).

9. BHF Cardiovascular Research Center, School of Cardiovascular and Metabolic Health (M.C.P., N.S.), University of Glasgow, United Kingdom.

10. Robertson Center for Biostatistics (M.C.P.), University of Glasgow, United Kingdom.

Abstract

BACKGROUND: Patients with type 2 diabetes are at risk of heart failure hospitalization. As social determinants of health are rarely included in risk models, we validated and recalibrated the WATCH-DM score in a diverse patient-group using their social deprivation index (SDI). METHODS: We identified US Veterans with type 2 diabetes without heart failure that received outpatient care during 2010 at Veterans Affairs medical centers nationwide, linked them to their SDI using residential ZIP codes and grouped them as SDI <20%, 21% to 40%, 41% to 60%, 61% to 80%, and >80% (higher values represent increased deprivation). Accounting for all-cause mortality, we obtained the incidence for heart failure hospitalization at 5 years follow-up; overall and in each SDI group. We evaluated the WATCH-DM score using the C statistic, the Greenwood Nam D’Agostino test χ 2 test and calibration plots and further recalibrated the WATCH-DM score for each SDI group using a statistical correction factor. RESULTS: In 1 065 691 studied patients (mean age 67 years, 25% Black and 6% Hispanic patients), the 5-year incidence of heart failure hospitalization was 5.39%. In SDI group 1 (least deprived) and 5 (most deprived), the 5-year heart failure hospitalization was 3.18% and 11%, respectively. The score C statistic was 0.62; WATCH-DM systematically overestimated heart failure risk in SDI groups 1 to 2 (expected/observed ratios, 1.38 and 1.36, respectively) and underestimated the heart failure risk in groups 4 to 5 (expected/observed ratios, 0.95 and 0.80, respectively). Graphical evaluation demonstrated that the recalibration of WATCH-DM using an SDI group-based correction factor improved predictive capabilities as supported by reduction in the χ 2 test results (801–27 in SDI groups I; 623–23 in SDI group V). CONCLUSIONS: Including social determinants of health to recalibrate the WATCH-DM score improved risk prediction highlighting the importance of including social determinants in future clinical risk prediction models.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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