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将利钠肽与临床风险评分相结合,以预测伴不同血糖水平人群的心力衰竭。

Incorporation of natriuretic peptides with clinical risk scores to predict heart failure among individuals with dysglycaemia.

机构信息

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.

出版信息

Eur J Heart Fail. 2022 Jan;24(1):169-180. doi: 10.1002/ejhf.2375. Epub 2021 Nov 23.

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.

摘要

目的

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。

方法和结果

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]。

结论

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。

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