Evidence map›Paper›PMID 39937766›Full record

ArticlePloS one2025

CT imaging biomarkers to predict severity and prognosis of pulmonary hypertension.

Do Won Yoon, Yeonyee E Yoon, In Chang Hwang, Wonjae Lee, Ki-Yeal Lee, Eun Ju Chun

Abstract read
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Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers 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

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Do Won YoonDepartment of Radiology, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, South Korea.
Yeonyee E YoonDivision of Cardiology, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, South Korea.
In Chang HwangDivision of Cardiology, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, South Korea.ORCID 0000-0003-4966-3924
Wonjae LeeDivision of Cardiology, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, South Korea.
Ki-Yeal LeeDepartment of Radiology, Korea University Kuro Hospital, Korea University College of Medicine, Seoul, South Korea.
Eun Ju ChunDepartment of Radiology, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, South Korea.ORCID 0000-0002-1041-8035

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo explore whether there are computed tomography (CT) imaging biomarkers that can stratify the severity of patients with pulmonary hypertension (PH).

methodsWe retrospectively enrolled 144 consecutive patients with suspected PH who underwent CT pulmonary angiography and right heart catheterization (RHC). CT findings were analyzed by two observers for large vessel size [ascending aorta (A), pulmonary artery (P), inferior vena cava (IVC)], each chamber size, and septal angle. We investigated the associations between CT imaging parameters and the mean pulmonary artery pressure (mPAP) from RHC. During a median follow-up of 36 months, we observed major adverse cardiovascular events (MACE; all-cause mortality and hospitalization for PH worsening). Univariate and multivariate Cox regression models were used with hazard ratios (HR) and 95% confidence intervals (95% CI) to determine independent predictors of MACE in patients with PH.

resultsOf 144 patients, 116 (80.2%) were diagnosed with PH based on an mPAP of 20 mmHg. Among CT parameters, P, P/A ratio, right ventricle (RV), and RV/left ventricle (LV) ratio were strongly correlated with mPAP values (Pearson's correlation coefficient, all r < 0.001). During the follow-up period, 44 (30.6%) patients developed MACE (14 deaths and 30 hospitalizations). Using multivariate Cox regression analysis, the RV/LV ratio (HR 2.32; 95% CI: 1.17-4.59) was the best predictor of MACE, followed by age (HR 1.03, 95% CI;1.00-1.05) (all p < 0.05). Among various CT parameters, A, P, and P/A ratio showed excellent reliability with intraclass correlation coefficient ≥ 0.95.

conclusionAmong CT parameters, the RV/LV ratio was the most robust predictor of MACE in patients with PH, while the P and P/A ratios served as reliable indicators reflecting mPAP levels.

Indexed as

Hypertension, PulmonaryTomography, X-Ray ComputedAdultAgedBiomarkersCardiac CatheterizationFemaleHumansMaleMiddle AgedPrognosisPulmonary ArteryRetrospective StudiesSeverity of Illness IndexBiomarkers

Identifiers

PMID39937766
PMCPMC11819466

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