Abstract
BACKGROUND: Currently, simplified methods based on computed tomography pulmonary angiography (CTPA) to predict clinical deterioration in patients with acute pulmonary embolism (PE) are lacking. We developed a simplified imaging model with good clinical accessibility to predict this outcome. STUDY DESIGN AND METHODS: Patients with acute pulmonary embolism from 2008 to 2019 were retrospectively enrolled from two medical centers to form a study cohort and a validation cohort. Seven models of pulmonary artery obstruction index (PAOI) were developed based on the location and degree of obstruction. The outcome of interest was clinical deterioration during hospitalization. Logistic regression analysis was used to assess the association between different models and clinical deterioration. The category-free net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were used to quantify improvements in predictability. RESULTS: The study group included 210 patients (mean age: 65 ± 16 years; male: 40 %) and the external validation group included 109 patients (mean age: 64 ± 17 years; male: 43 %). Calculating the nearly total obstruction of 20 peripheral arteries demonstrated good predictive ability (AUC: 0.77). Total obstruction of six peripheral arteries did not increase the odds of clinical deterioration, while total obstruction of ten peripheral arteries nearly doubled the risk of deterioration. Combining PAOI with the simplified pulmonary embolism severity index (sPESI) improved the predictive ability for clinical deterioration compared to using sPESI alone (NRI: 0.09-0.12; IDI: 0.05-0.09). CONCLUSION: Calculating totally obstructed pulmonary arteries simplifies the prediction of clinical deterioration. The combination of PAOI and sPESI enhances the ability to predict clinical deterioration in patients with acute PE.