Evidence map›Paper›PMID 35907784›Full record

ArticleEchocardiography (Mount Kisco, N.Y.)2022

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

Vivek Jani, Karan Kapoor, Joseph Meyer, Jim Lu, Erin Goerlich, Thomas S Metkus, Jose A Madrazo, Erin Michos, Katherine Wu, Nicole Bavaro and 3 more

Abstract read
In one paragraph

Article in Echocardiography (Mount Kisco, N.Y.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Refining Risk Prediction in Systemic Sclerosis-Associated Pulmonary Arterial Hypertension.Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography · 2025
    Article
  3. Right-sided heart failure in acute respiratory distress syndrome.European respiratory review : an official journal of the European Respiratory Society · 2025
    Review
  4. Article
  5. Prognostic Value of Echocardiographic Coupling Metrics in Systemic Sclerosis-Associated Pulmonary Vascular Disease.Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography · 2025
    Article
  6. Review
  7. Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Vivek JaniDivision of Cardiology, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Karan KapoorDivision of Cardiology, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Joseph MeyerDivision of Cardiology, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Jim LuDivision of Cardiology, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Erin GoerlichDivision of Cardiology, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Thomas S MetkusDivision of Cardiology, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Jose A MadrazoDivision of Cardiology, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Erin MichosDivision of Cardiology, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Katherine WuDivision of Cardiology, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Nicole BavaroDivision of Cardiology, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Shelby KuttyDivision of Cardiology, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Allison G HaysDivision of Cardiology, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Monica MukherjeeDivision of Cardiology, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.

Funding

Early Detection of Right Ventricular Dysfunction and Emerging Pulmonary Hypertension in Systemic SclerosisR01HL162851 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI Monica Mukherjee · 2023 to 2026
$2.5M
Emerging factors in the pathophysiology of endothelial dysfunction in HIV+ womenR01HL147660 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI HAYS, ALLISON G · 2019 to 2023
$1.4M
NHLBI NIH HHS R01 HL147660NHLBI NIH HHS R01 HL162851
6 · The paper itself

Abstract

backgroundThe 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.

methodsTwo 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.

resultsOne 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

conclusionImpaired 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.

Indexed as

COVID-19Ventricular Dysfunction, RightAdultEchocardiography, DopplerHumansPrognosisProspective StudiesUnsupervised Machine LearningVentricular Function, RightCOVID-19echocardiographyright ventricular failure

Identifiers

PMID35907784
PMCPMC10687738

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.