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无监督机器学习显示 TAPSE/PASP 比值在住院 COVID-19 患者中的预后价值。

Unsupervised machine learning demonstrates the prognostic value of TAPSE/PASP ratio among hospitalized patients with COVID-19.

机构信息

Division of Cardiology, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.

出版信息

Echocardiography. 2022 Sep;39(9):1198-1208. doi: 10.1111/echo.15432. Epub 2022 Jul 30.

DOI:10.1111/echo.15432
PMID:35907784
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10687738/
Abstract

BACKGROUND

The ratio of tricuspid annular plane systolic excursion (TAPSE) to pulmonary artery systolic pressure (PASP) is a validated index of right ventricular-pulmonary arterial (RV-PA) coupling with prognostic value. We determined the predictive value of TAPSE/PASP ratio and adverse clinical outcomes in hospitalized patients with COVID-19.

METHODS

Two hundred and twenty-nine consecutive hospitalized racially/ethnically diverse adults (≥18 years of age) admitted with COVID-19 between March and June 2020 with clinically indicated transthoracic echocardiograms (TTE) that included adequate tricuspid regurgitation (TR) velocities for calculation of PASP were studied. The exposure of interest was impaired RV-PA coupling as assessed by TAPSE/PASP ratio. The primary outcome was in-hospital mortality. Secondary endpoints comprised of ICU admission, incident acute respiratory distress syndrome (ARDS), and systolic heart failure.

RESULTS

One hundred and seventy-six patients had both technically adequate TAPSE measurements and measurable TR velocities for analysis. After adjustment for age, sex, BMI, race/ethnicity, diabetes mellitus, and smoking status, log(TAPSE/PASP) had a significantly inverse association with ICU admission (p = 0.015) and death (p = 0.038). ROC analysis showed the optimal cutoff for TAPSE/PASP for death was 0.51 mm mmHg (AUC = 0.68). Unsupervised machine learning identified two groups of echocardiographic function. Of all echocardiographic measures included, TAPSE/PASP ratio was the most significant in predicting in-hospital mortality, further supporting its significance in this cohort.

CONCLUSION

Impaired RV-PA coupling, assessed noninvasively via the TAPSE/PASP ratio, was predictive of need for ICU level care and in-hospital mortality in hospitalized patients with COVID-19 suggesting utility of TAPSE/PASP in identification of poor clinical outcomes in this population both by traditional statistical and unsupervised machine learning based methods.

摘要

背景

三尖瓣环平面收缩期位移(TAPSE)与肺动脉收缩压(PASP)的比值是评估右心室-肺动脉(RV-PA)耦联的有效指标,具有预后价值。我们确定了 TAPSE/PASP 比值与 COVID-19 住院患者不良临床结局的预测价值。

方法

研究了 2020 年 3 月至 6 月期间因 COVID-19 住院的 229 例连续住院的、种族/民族多样化的成年人(≥18 岁),这些患者接受了临床指征明确的经胸超声心动图(TTE)检查,其中包括足够的三尖瓣反流(TR)速度,以计算 PASP。感兴趣的暴露是通过 TAPSE/PASP 比值评估的 RV-PA 偶联受损。主要结局是院内死亡率。次要终点包括 ICU 入院、新发急性呼吸窘迫综合征(ARDS)和收缩性心力衰竭。

结果

176 例患者均有技术上足够的 TAPSE 测量值和可测量的 TR 速度进行分析。在校正年龄、性别、BMI、种族/民族、糖尿病和吸烟状况后,log(TAPSE/PASP)与 ICU 入院(p=0.015)和死亡(p=0.038)呈显著负相关。ROC 分析显示 TAPSE/PASP 预测死亡的最佳截断值为 0.51 mm mmHg(AUC=0.68)。无监督机器学习确定了两组超声心动图功能。在所有纳入的超声心动图指标中,TAPSE/PASP 比值是预测院内死亡率的最显著指标,进一步支持其在该队列中的意义。

结论

通过 TAPSE/PASP 比值评估的 RV-PA 偶联受损可预测 COVID-19 住院患者需要 ICU 级护理和院内死亡,表明 TAPSE/PASP 可通过传统统计学和无监督机器学习方法识别该人群的不良临床结局。

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