Digital cough monitoring - A potential predictive acoustic biomarker of clinical outcomes in hospitalized COVID-19 patients.
Digital cough monitoring - A potential predictive acoustic biomarker of clinical outcomes in hospitalized COVID-19 patients.
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DOI：
10.1016/j.jbi.2023.104283
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发表时间：
2023-03
影响因子：
4.5
通讯作者：
Lapierre, Simon Grandjean
中科院分区：
文献类型：
--
作者：
Altshuler, Ellery;Tannir, Bouchra;Jolicoeur, Gisele;Rudd, Matthew;Saleem, Cyrus;Cherabuddi, Kartikeya;Dore, Dominique Helene;Nagarsheth, Parav;Brew, Joe;Small, Peter M.;Morris, J. Glenn;Lapierre, Simon Grandjean
人工智能和声学领域的最新发展使得在临床和门诊环境中客观地监测咳嗽成为可能。我们假设，COVID-19患者客观测量的咳嗽时间模式可以预测临床预后，并有助于快速识别插管或死亡风险高的患者。佛罗里达大学健康尚兹医院和蒙特利尔大学中心医院共招募了123名COVID-19住院患者。患者的咳嗽与疾病的临床严重程度一起沿着数字化连续监测，直到出院、插管或死亡。描述了住院COVID-19疾病的咳嗽自然史，并使用拟合咳嗽时间模式的logistic模型预测临床结局。在这两个队列中，早期咳嗽率较高与更有利的临床结局相关。预测不良结局的过渡性咳嗽率或每小时最大咳嗽率为3.40，预测不良结局的咳嗽频率AUC为0.761。入组后最初6 h（0.792）和24 h（0.719）的观察期证实了这种关联，并显示出相似的预测值。数字咳嗽监测可用作预后生物标志物，以预测COVID-19疾病的不利临床结果。由于早期采样期显示出良好的预测价值，这种数字生物标志物可以与临床和临床旁评估相结合，并且非常适合在不堪重负或资源有限的健康计划中对患者进行分类。
Recent developments in the field of artificial intelligence and acoustics have made it possible to objectively monitor cough in clinical and ambulatory settings. We hypothesized that time patterns of objectively measured cough in COVID-19 patients could predict clinical prognosis and help rapidly identify patients at high risk of intubation or death. One hundred and twenty-three patients hospitalized with COVID-19 were enrolled at University of Florida Health Shands and the Centre Hospitalier de l’Université de Montréal. Patients’ cough was continuously monitored digitally along with clinical severity of disease until hospital discharge, intubation, or death. The natural history of cough in hospitalized COVID-19 disease was described and logistic models fitted on cough time patterns were used to predict clinical outcomes. In both cohorts, higher early coughing rates were associated with more favorable clinical outcomes. The transitional cough rate, or maximum cough per hour rate predicting unfavorable outcomes, was 3·40 and the AUC for cough frequency as a predictor of unfavorable outcomes was 0·761. The initial 6 h (0·792) and 24 h (0·719) post-enrolment observation periods confirmed this association and showed similar predictive value. Digital cough monitoring could be used as a prognosis biomarker to predict unfavorable clinical outcomes in COVID-19 disease. With early sampling periods showing good predictive value, this digital biomarker could be combined with clinical and paraclinical evaluation and is well adapted for triaging patients in overwhelmed or resources-limited health programs.
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DOI：
10.1109/ojemb.2020.3026928
发表时间：
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影响因子：
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作者：
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