Evidence map›Paper›PMID 42252486›Full record

ArticleEcho research and practice2026

Reporting changes in right ventricular systolic pressure: insights from Classification and Regression Tree (CART) analysis.

Shadi P Bagherzadeh, Kartik S Malunjkar, Neha M Mantri, Bettia E Celestin, Roham T Zamanian, Paul Heidenreich, Ingela Schnittger, Michael Salerno, David Oxborough, Daniel Augustine and 3 more

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Article in Echo research and practice, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Shadi P Bagherzadeh *Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Palo Alto, CA, USA. shadi.bagherzadeh@mountsinai.org.
Kartik S Malunjkar *Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Palo Alto, CA, USA.
Neha M MantriDivision of Cardiovascular Medicine, Department of Medicine, Stanford University, Palo Alto, CA, USA.
Bettia E CelestinDivision of Cardiovascular Medicine, Department of Medicine, Stanford University, Palo Alto, CA, USA.
Roham T ZamanianStanford Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, Stanford University, Palo Alto, CA, USA.
Paul HeidenreichDivision of Cardiovascular Medicine, Department of Medicine, Stanford University, Palo Alto, CA, USA.
Ingela SchnittgerDivision of Cardiovascular Medicine, Department of Medicine, Stanford University, Palo Alto, CA, USA.
Michael SalernoDivision of Cardiovascular Medicine, Department of Medicine, Stanford University, Palo Alto, CA, USA.
David OxboroughLiverpool John Moores University, Liverpool, UK.
Daniel AugustineRoyal United Hospital, Bath, UK.
Raymond BenzaMount Sinai Health Systems, New York, NY, USA.
Everton J SantanaStanford Cardiovascular Institute, Palo Alto, CA, USA.
Francois HaddadDivision of Cardiovascular Medicine, Department of Medicine, Stanford University, Palo Alto, CA, USA. fhaddad@stanford.edu.

Funding

Computational Medicine in the Heart, Integrated Training ProgramT32HL166155 · NHLBI · STANFORD UNIVERSITY · PI Alison L Marsden, Sanjiv M Narayan · 2023 to 2026
$2.0M
NHLBI NIH HHS T32 HL166155NIH, NHLBI Computational Medicine in the Heart Integrated Training Program (CHIP T32) T32HL166155
6 · The paper itself

Abstract

backgroundRight ventricular systolic pressure (RVSP) is an echocardiographic metric to monitor pulmonary hypertension (PH). However, there is no recommendation on what constitutes a meaningful change. In this study, we aimed to gain insight into how physicians at our institution report significant changes in RVSP. We then aimed to quantify the analytic variability of reported RVSP using duplicate analysis.

methodsWe utilized the Stanford CardioShare Registry to identify 5,934 patients with 32,656 echocardiogram pairs with reported RVSP. Natural Language Processing was employed to categorize pairs into decrease, increase, no change, and no direct mention. Classification and Regression Tree (CART) analysis was applied to these groups to identify reporting thresholds among physicians. To assess the performance of the CART model, accuracy, precision, recall, and F1-score were reported using a stratified cross-validation method. In a separate cohort comprising 210 healthy volunteers and 208 patients with PH, two blinded core laboratory cardiologists measured the peak tricuspid regurgitation velocity. We employed a duplicate analysis method to model bias and a robust precision method for reporting RVSP and assessing analytical variability.

resultsOf the total pairs of echocardiographic studies, RVSP was reported as stable in 48.9%, increased in 12.5%, decreased in 9.9% while 28.7% did not have a direct reference to RVSP change. CART analysis revealed that physicians most commonly determine change based on an absolute threshold of 8 mmHg and whether the change occurred within or outside the reference range. On cross-validation, the accuracy and F1-score were 83% and 79% for the increase and 81% and 74% for the decrease algorithms. In the duplicate analysis cohort, the analytic precision was 8-10% with worst relative precision at lower values of RVSP. This translates into a 15% reference change value, assuming a 4-5% biological variation.

conclusionThe study provides insights on real world practice of physician reporting in RVSP and provides directions for future recommendations regarding report changes.

Indexed as

Analytical variabilityCART analysisPulmonary hypertensionReference changeRight ventricular systolic pressure

Identifiers

PMID42252486
PMCPMC13244848

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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.