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声学生物标志物与心力衰竭患者的住院和死亡相关。

Vocal Biomarker Is Associated With Hospitalization and Mortality Among Heart Failure Patients.

机构信息

Chaim Sheba Medical Center Tel Hashomer Israel.

Sackler School of Medicine Tel Aviv University Tel Aviv Israel.

出版信息

J Am Heart Assoc. 2020 Apr 7;9(7):e013359. doi: 10.1161/JAHA.119.013359. Epub 2020 Apr 1.

Abstract

Background The purpose of this article is to evaluate the association of voice signal analysis with adverse outcome among patients with congestive heart failure (CHF). Methods and Results The study cohort included 10 583 patients who were registered to a call center of patients who had chronic conditions including CHF in Israel between 2013 and 2018. A total of 223 acoustic features were extracted from 20 s of speech for each patient. A biomarker was developed based on a training cohort of non-CHF patients (N=8316). The biomarker was tested on a mutually exclusive CHF study cohort (N=2267) and was evaluated as a continuous and ordinal (4 quartiles) variable. Median age of the CHF study population was 77 (interquartile range 68-83) and 63% were men. During a median follow-up of 20 months (interquartile range 9-34), 824 (36%) patients died. Kaplan-Meier survival analysis showed higher cumulative probability of death with increasing quartiles (23%, 29%, 38%, and 54%; <0.001). Survival analysis with adjustment to known predictors of poor survival demonstrated that each SD increase in the biomarker was associated with a significant 32% increased risk of death during follow-up (95% CI, 1.24-1.41, <0.001) and that compared with the lowest quartile, patients in the highest quartile were 96% more likely to die (95% CI, 1.59-2.42, <0.001). The model consistently demonstrated an independent association of the biomarker with hospitalizations during follow-up (<0.001). Conclusions Noninvasive vocal biomarker is associated with adverse outcome among CHF patients, suggesting a possible role for voice analysis in telemedicine and CHF patient care.

摘要

背景

本文旨在评估充血性心力衰竭(CHF)患者的语音信号分析与不良预后的相关性。

方法和结果

研究队列纳入了 2013 年至 2018 年间在以色列登记的患有慢性疾病(包括 CHF)的患者呼叫中心的 10583 名患者。为每位患者从 20 秒的语音中提取了 223 个声学特征。基于非 CHF 患者(N=8316)的训练队列开发了一种生物标志物。在相互排斥的 CHF 研究队列(N=2267)上测试了该生物标志物,并将其评估为连续和有序(4 个四分位数)变量。CHF 研究人群的中位年龄为 77 岁(四分位距 68-83),63%为男性。在中位随访 20 个月(四分位距 9-34)期间,824 名(36%)患者死亡。Kaplan-Meier 生存分析显示,随着四分位的增加,死亡的累积概率逐渐升高(23%、29%、38%和 54%;<0.001)。对已知不良预后预测因素进行调整后的生存分析表明,生物标志物每增加一个标准差,与随访期间死亡风险显著增加 32%相关(95%CI,1.24-1.41,<0.001),与最低四分位相比,最高四分位患者死亡的可能性增加了 96%(95%CI,1.59-2.42,<0.001)。该模型一致表明,生物标志物与随访期间的住院治疗存在独立关联(<0.001)。

结论

非侵入性语音生物标志物与 CHF 患者的不良预后相关,表明语音分析在远程医疗和 CHF 患者护理中可能发挥作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/74b4/7428646/d6344bd570ff/JAH3-9-e013359-g001.jpg

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