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当前用于预测心力衰竭患者死亡率的风险分层模型的性能:系统评价和荟萃分析。

Performance of current risk stratification models for predicting mortality in patients with heart failure: a systematic review and meta-analysis.

机构信息

Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA.

Department of Medicine, DOW University of Health Sciences, Karachi, Pakistan.

出版信息

Eur J Prev Cardiol. 2022 Nov 8;29(15):2027-2048. doi: 10.1093/eurjpc/zwac148.

Abstract

AIMS

There are several risk scores designed to predict mortality in patients with heart failure (HF). This study aimed to assess performance of risk scores validated for mortality prediction in patients with acute HF (AHF) and chronic HF.

METHODS AND RESULTS

MEDLINE and Scopus were searched from January 2015 to January 2021 for studies which internally or externally validated risk models for predicting all-cause mortality in patients with AHF and chronic HF. Discrimination data were analysed using C-statistics, and pooled using generic inverse-variance random-effects model. Nineteen studies (n = 494 156 patients; AHF: 24 762; chronic HF mid-term mortality: 62 000; chronic HF long-term mortality: 452 097) and 11 risk scores were included. Overall, discrimination of risk scores was good across the three subgroups: AHF mortality [C-statistic: 0.76 (0.68-0.83)], chronic HF mid-term mortality [1 year; C-statistic: 0.74 (0.68-0.79)], and chronic HF long-term mortality [≥2 years; C-statistic: 0.71 (0.69-0.73)]. MEESSI-AHF [C-statistic: 0.81 (0.80-0.83)] and MARKER-HF [C-statistic: 0.85 (0.80-0.89)] had an excellent discrimination for AHF and chronic HF mid-term mortality, respectively, whereas MECKI had good discrimination [C-statistic: 0.78 (0.73-0.83)] for chronic HF long-term mortality relative to other models. Overall, risk scores predicting short-term mortality in patients with AHF did not have evidence of poor calibration (Hosmer-Lemeshow P > 0.05). However, risk models predicting mid-term and long-term mortality in patients with chronic HF varied in calibration performance.

CONCLUSIONS

The majority of recently validated risk scores showed good discrimination for mortality in patients with HF. MEESSI-AHF demonstrated excellent discrimination in patients with AHF, and MARKER-HF and MECKI displayed an excellent discrimination in patients with chronic HF. However, modest reporting of calibration and lack of head-to-head comparisons in same populations warrant future studies.

摘要

目的

有几种风险评分旨在预测心力衰竭(HF)患者的死亡率。本研究旨在评估针对急性 HF(AHF)和慢性 HF 患者死亡率预测进行内部或外部验证的风险评分的性能。

方法和结果

从 2015 年 1 月至 2021 年 1 月,使用 MEDLINE 和 Scopus 检索了旨在预测 AHF 和慢性 HF 患者全因死亡率的风险模型的内部或外部验证研究。使用 C 统计量分析判别数据,并使用通用逆方差随机效应模型进行汇总。纳入了 19 项研究(n=494156 例患者;AHF:24762 例;慢性 HF 中期死亡率:62000 例;慢性 HF 长期死亡率:452097 例)和 11 个风险评分。总体而言,风险评分在三个亚组中的判别能力均较好:AHF 死亡率[C 统计量:0.76(0.68-0.83)]、慢性 HF 中期死亡率(1 年;C 统计量:0.74(0.68-0.79)]和慢性 HF 长期死亡率(≥2 年;C 统计量:0.71(0.69-0.73)]。MEESSI-AHF[C 统计量:0.81(0.80-0.83)]和 MARKER-HF[C 统计量:0.85(0.80-0.89)]对 AHF 和慢性 HF 中期死亡率具有出色的判别能力,而 MECKI 具有良好的判别能力[C 统计量:0.78(0.73-0.83)]。与其他模型相比,用于预测慢性 HF 长期死亡率的风险评分。总体而言,预测 AHF 患者短期死亡率的风险评分没有证据表明校准不良(Hosmer-Lemeshow P>0.05)。然而,预测慢性 HF 患者中期和长期死亡率的风险模型在校准性能方面存在差异。

结论

最近验证的风险评分中的大多数都显示出对 HF 患者死亡率的良好判别能力。MEESSI-AHF 在 AHF 患者中显示出出色的判别能力,MARKER-HF 和 MECKI 在慢性 HF 患者中显示出出色的判别能力。然而,在同一人群中,校准的适度报告和缺乏头对头比较需要进一步的研究。

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