Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Department of Cardiology, Texas Heart Institute, Houston, TX, USA.
Eur J Heart Fail. 2022 Jan;24(1):169-180. doi: 10.1002/ejhf.2375. Epub 2021 Nov 23.
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).
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).
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.
评估 WATCH-DM 风险评分(一种用于心力衰竭(HF)的临床风险评分)在血糖异常患者中的表现,并与利钠肽(NPs)联合使用。
本研究纳入了四项队列研究(ARIC、CHS、FHS 和 MESA)中基线时无 HF 的糖尿病/糖尿病前期成年人。使用基于机器学习的 [WATCH-DM(ml)] 和基于整数的 [WATCH-DM(i)] 评分来估计 5 年内发生 HF 的风险。通过 Harrell 一致性指数(C 指数)评估判别能力,并通过 Greenwood-Nam-D'Agostino(GND)统计量评估校准情况。通过 C 指数和连续净重新分类改善(NRI)评估添加 NP 水平对模型性能的改善情况。在纳入的 8938 名参与者中,3554 名(39.8%)患有糖尿病,432 名(4.8%)在 5 年内发生 HF。WATCH-DM(ml)和 WATCH-DM(i)评分在预测血糖异常个体的 HF 风险方面表现出较高的判别能力(C 指数分别为 0.80 和 0.71),且没有校准不当的证据(GND P≥0.10)。在血糖异常个体中,单独升高 NP 水平对预测 HF 事件的 C 指数在低/中(<13)与高(≥13)WATCH-DM(i)评分之间存在显著差异[0.71(95%置信区间 0.68-0.74)与 0.64(95%置信区间 0.61-0.66)]。当 NP 水平与 WATCH-DM(i)评分相结合时,HF 风险判别改善和 NRI 随风险谱变化而变化,在低/中风险(WATCH-DM(i)<13)中观察到更大的改善,而在高风险(WATCH-DM(i)≥13)中则改善较小[C 指数=0.73 比 0.71;NRI=0.45 比 0.17]。
WATCH-DM 风险评分可准确预测社区人群中血糖异常个体的 HF 事件风险。NP 水平的增加与低/中风险个体的 HF 风险预测性能的改善相关,而与高风险个体的改善相关。