Predictive Model For Pulmonary Embolism In Patients With Deep Vein Thrombosis

Abstract Objective To develop and verify a risk predictive model/scoring system for pulmonary embolism (PE) among hospitalized patients with deep venous thrombosis of the lower extremities (LDVT). Methods 776 patients with LDVT were enrolled in a case-control study between January 2016 and June 2017 from the Vascular Surgery Department of Shanxi Dayi Hospital, China. They were randomly divided into development (543 patients, 70%) and validation (233 patients, 30%) databases. Based on the results of pulmonary computed tomography arteriography (PCTA), patients were divided into two categories; those with PE were designated as the case group while those without comprised the controls. A logistic regression model and scoring system for PE in patients with LDVT was established in the development database and verified in the validation database. Scoring system (Shanxi Dayi Hospital score - SDH score) was tabulated as follows: right lower extremity or bilateral lower extremities, 1; surgery or immobilization, 1; malignant tumor, 1; history of VTE, 2; D-dimer>1000 ng/mL, 2; and unprovoked, 2. Calibration and discrimination of the model were assessed by Hosmer-Lemeshow good-of-fit test and the area under the receiver operating characteristic curve (AUC). Wells score, the Revised Geneva score and the SDH score for predictive value of PE by AUC in the validation database, were compared. Results 776 patients with LDVT were divided into 2 risk categories based on the scores from the risk model, as follows: PE-unlikely (score 0.05 and the AUC was 0.705 (95% CI: 0.634∼0.776, P Conclusions Our logistic regression model and the SDH score based on 7 risk factors as right lower extremity, bilateral lower extremities, unprovoked, surgery or immobilization, malignant tumor, history of VTE, and D-dimer>1000 ng/ml, showed good calibration and discriminative power for the assessment of PE risk in patients with LDVT. The SDH score is more specific for PE prediction in the Chinese population, compared with the Wells score and the Revised Geneva score.