Unsupervised machine learning demonstrates the prognostic value of TAPSE/PASP ratio among hospitalized patients with COVID-19.
Unsupervised machine learning demonstrates the prognostic value of TAPSE/PASP ratio among hospitalized patients with COVID-19.
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DOI：
10.1111/echo.15432
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发表时间：
2022-09
影响因子：
1.5
通讯作者：
Mukherjee, Monica
中科院分区：
文献类型：
--
作者：
Jani, Vivek;Kapoor, Karan;Meyer, Joseph;Lu, Jim;Goerlich, Erin;Metkus, Thomas S.;Madrazo, Jose A.;Michos, Erin;Wu, Katherine;Bavaro, Nicole;Kutty, Shelby;Hays, Allison G.;Mukherjee, Monica
三尖瓣环平面收缩期离散度(TAPSE)与肺动脉收缩压(PASP)的比值是右室-肺动脉(RV-PA)偶联的有效指标，具有一定的预后价值。我们确定了TAPSE/PASP比值对新冠肺炎住院患者不良临床结局的预测价值。对2020年3月至6月连续229名因种族/民族不同而因新冠肺炎入院的成年人(年龄18岁)进行经胸超声心动图检查，其中包括足够的三尖瓣返流速度以计算≥。根据Tapse/PASP比率，感兴趣的暴露是RV-PA偶联受损。主要结果是住院死亡率。次要终点包括ICU入院、急性呼吸窘迫综合征(ARDS)和收缩性心力衰竭。176名患者既有技术上足够的TAPSE测量，又有可测量的TR速度进行分析。在调整了年龄、性别、体重指数、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分析表明，TAPSE/PASP的最佳死亡界值为0.51 mm Hg−1(AUC=0.68)。无监督机器学习识别了两组超声心动图功能。在包括的所有超声心动图测量中，TAPSE/PASP比率在预测住院死亡率方面是最显著的，进一步支持了它在该队列中的重要性。通过TAPSE/PASP比率无创地评估RV-PA偶联受损，可以预测新冠肺炎住院患者是否需要ICU水平的护理和住院死亡率，这表明TAPSE/PASP在通过传统统计和基于无监督机器学习的方法识别该人群中不良临床结果方面具有实用价值。
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. 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. 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−1 (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. 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.
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DOI：
10.1186/s13054-020-03385-5
发表时间：
2020-11-30
期刊：
Critical care (London, England)
影响因子：
--
作者：
D'Alto M;Marra AM;Severino S;Salzano A;Romeo E;De Rosa R;Stagnaro FM;Pagnano G;Verde R;Murino P;Farro A;Ciccarelli G;Vargas M;Fiorentino G;Servillo G;Gentile I;Corcione A;Cittadini A;Naeije R;Golino P
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Golino P
影响因子：
6.2
作者：
Lang, Roberto M.;Badano, Luigi P.;Voigt, Jens-Uwe
通讯作者：
Voigt, Jens-Uwe
影响因子：
2.7
作者：
Kawai, Masataka;Jin, Jian-Ping
通讯作者：
Jin, Jian-Ping
影响因子：
24
作者：
Brener, Michael, I;Lurz, Philipp;Hahn, Rebecca T.
通讯作者：
Hahn, Rebecca T.
影响因子：
18.2
作者：
Ghio, Stefano;Guazzi, Marco;Dini, Frank Lloyd
通讯作者：
Dini, Frank Lloyd