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使用个体化风险分层策略预测心力衰竭事件恶化和全因死亡率。

Prediction of worsening heart failure events and all-cause mortality using an individualized risk stratification strategy.

作者信息

Zile Michael R, Koehler Jodi, Sarkar Shantanu, Butler Javed

机构信息

Medical University of South Carolina and the Ralph H. Johnson Department of Veterans Affairs Medical Center, Charleston, SC, USA.

Medtronic Inc., Minneapolis, MN, USA.

出版信息

ESC Heart Fail. 2020 Dec;7(6):4277-4289. doi: 10.1002/ehf2.13077. Epub 2020 Oct 28.

Abstract

AIMS

This study aimed to examine the clinical utility of a multisensor, remote, ambulatory diagnostic risk score, TriageHF™, in a real-world, unselected, large patient sample to predict heart failure events (HFEs) and all-cause mortality.

METHODS AND RESULTS

TriageHF risk score was calculated in patients in the Optum database who had Medtronic implantable cardiac defibrillator device from 2007 to 2016. Patients were categorized into three risk groups based on probability for having an HFE within 6 months (low risk <5.4%, medium risk ≥5.4 < 20%, and high risk ≥20%). Data were analysed using three strategies: (i) scheduled monthly data download; (ii) alert-triggered data download; and (iii) daily data download. Study population consisted of 22 901 patients followed for 1.8 ± 1.3 years. Using monthly downloads, HFE risk over 30 days incrementally increased across risk categories (odds ratio: 2.8, 95% confidence interval: 2.5-3.2 for HFE, P < 0.001, low vs. medium risk, and odds ratio: 9.2, 95% confidence interval: 8.1-10.3, P < 0.001, medium vs. high risk). Findings were similar using the other two analytic strategies. Using a receiver operating characteristic curve analysis, sensitivity for predicting HFE over 30 days using high-risk score was 47% (alert triggered) and 51% (daily download) vs. 0.5 per patient year unexplained detection rate. TriageHF risk score also predicted all-cause mortality risk over 4 years. All-cause mortality risk was 14% in low risk, 20% in medium risk, and 38% in high risk.

CONCLUSIONS

TriageHF risk score provides a multisensor remote, ambulatory diagnostic method that predicts both HFEs and all-cause mortality.

摘要

目的

本研究旨在检验一种多传感器、远程、动态诊断风险评分系统TriageHF™在真实世界、未经过筛选的大型患者样本中预测心力衰竭事件(HFEs)和全因死亡率的临床实用性。

方法与结果

对2007年至2016年在Optum数据库中植入美敦力植入式心脏除颤器的患者计算TriageHF风险评分。根据6个月内发生HFE的概率将患者分为三个风险组(低风险<5.4%,中风险≥5.4%<20%,高风险≥20%)。使用三种策略分析数据:(i)每月定期下载数据;(ii)警报触发数据下载;(iii)每日数据下载。研究人群包括22901名患者,随访时间为1.8±1.3年。使用每月下载的数据,30天内HFE风险在各风险类别中逐渐增加(优势比:2.8,95%置信区间:2.5 - 3.2用于HFE,P<0.001,低风险与中风险相比;优势比:9.2,95%置信区间:8.1 - 10.3,P<0.001)。使用其他两种分析策略的结果相似。使用受试者工作特征曲线分析,使用高风险评分预测30天内HFE的敏感性在警报触发时为47%,每日下载时为51%,而每位患者每年无法解释的检测率为0.5。TriageHF风险评分还预测了4年内的全因死亡风险。低风险组全因死亡风险为14%,中风险组为20%,高风险组为38%。

结论

TriageHF风险评分提供了一种多传感器远程动态诊断方法,可预测HFEs和全因死亡率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3db7/7754961/ad7e039312c3/EHF2-7-4277-g001.jpg

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