Abstract Background Previous research identifies residual pulmonary vascular obstruction (RPVO) as an independent risk factor for venous thromboembolism (VTE) recurrence and a predictor of poor outcomes, yet its risk factors and prognostic impact remain unclear. Purpose This study developed predictive models combining clinical and metabolic biomarkers to identify high-risk RPVO patients, offering clinically actionable guidance for optimizing anticoagulation therapy. Patients and Methods This retrospective study analyzed 363 acute pulmonary embolism (APE) patients (2018.1-2024.12) with ≥3-month follow-up. We developed comprehensive and simplified RPVO predictive models by identifying risk factors and assessing long-term outcomes. The models, incorporating metabolomic biomarkers from baseline blood samples, were validated in a prospective APE cohort (2024.12-2025.2). Results Multivariable analysis identified five independent RPVO predictors: 1) affected lobes on V/Q scan, 2) sPESI score, 3) pulmonary artery pressure, 4) recent surgery/immobilization, and 5) active cancer. Both the comprehensive and simplified predictive models showed excellent discrimination (kappa 0.6) in training, validation, and prospective cohorts. Metabolomic analysis revealed azelaic acid and L-3-phenyl lactate as key differentiating metabolites, whose inclusion enhanced model performance. Notably, RPVO presence and extensive lung involvement (≥6 lobes) independently predicted adverse outcomes (recurrent VTE, cardiopulmonary failure, or mortality). Conclusion We developed comprehensive and simplified RPVO prediction models incorporating five clinical predictors and two metabolic biomarkers (azelaic acid and L-3-phenyl lactic acid), significantly improving model performance. RPVO independently predicted adverse outcomes, highlighting the clinical value of combined clinical and molecular profiling.
Xu et al. (Sat,) studied this question.