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Table 5_Non-invasive PECS model for detection of combined post-capillary pulmonary hypertension.docx

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NIAID Data Ecosystem2026-05-10 收录
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https://figshare.com/articles/dataset/Table_5_Non-invasive_PECS_model_for_detection_of_combined_post-capillary_pulmonary_hypertension_docx/30414271
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BackgroundCombined post-capillary pulmonary hypertension (Cpc-PH) is a severe form of pulmonary hypertension associated with high morbidity and mortality. Early identification and intervention are crucial but challenging due to the invasive right heart catheterization (RHC). This study aimed to develop and validate a non-invasive diagnostic model, the Predictive Echocardiography Cpc-PH Score (PECS), using echocardiographic parameters to facilitate detection of Cpc-PH. MethodsA retrospective analysis encompassing 198 patients with suspected PH-LHD, admitted from July 2010 through December 2023, was executed. Patients were divided into Cpc-PH and Ipc-PH/No-PH groups based on RHC in accordance with the 7th World Symposium on Pulmonary Hypertension criteria for PECS model construction. Chi-square and L1-regularized backward elimination refined predictive indicators. Model efficacy and stability were appraised via receiver operating characteristic and 5-fold cross-validation. ResultsThe PECS model, incorporating a suite of indicators including valvular heart disease, left atrial systolic diameter, interventricular septal thickness, mitral valve E/Em ratio, left ventricular fractional shortening, and tricuspid regurgitation velocity, demonstrated good predictive performance, achieving an area under characteristic (AUC) of 0.761 (95% CI: 0.692–0.823, P < 0.001). It demonstrated a sensitivity of 66.7%, specificity of 72.0%, a positive predictive value of 72.9%, a negative predictive value of 65.7%, and an overall accuracy of 69.2%. A total of 5-fold cross-validation confirmed these findings, yielding an AUC of 0.752 ± 0.070. ConclusionThe PECS model provides a non-invasive and precise approach to diagnosing Cpc-PH, potentially acting as a practical screening tool.
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