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      Derivation and validation of a prognostic model for pulmonary embolism.

      American journal of respiratory and critical care medicine
      Acute Disease, Aged, Cause of Death, Comorbidity, Decision Support Techniques, Discriminant Analysis, Female, France, epidemiology, Hospitals, University, Humans, Logistic Models, Male, Pennsylvania, Predictive Value of Tests, Prognosis, Pulmonary Embolism, classification, complications, diagnosis, mortality, therapy, ROC Curve, Risk Assessment, organization & administration, Risk Factors, Severity of Illness Index, Switzerland

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          Abstract

          An objective and simple prognostic model for patients with pulmonary embolism could be helpful in guiding initial intensity of treatment. To develop a clinical prediction rule that accurately classifies patients with pulmonary embolism into categories of increasing risk of mortality and other adverse medical outcomes. We randomly allocated 15,531 inpatient discharges with pulmonary embolism from 186 Pennsylvania hospitals to derivation (67%) and internal validation (33%) samples. We derived our prediction rule using logistic regression with 30-day mortality as the primary outcome, and patient demographic and clinical data routinely available at presentation as potential predictor variables. We externally validated the rule in 221 inpatients with pulmonary embolism from Switzerland and France. We compared mortality and nonfatal adverse medical outcomes across the derivation and two validation samples. The prediction rule is based on 11 simple patient characteristics that were independently associated with mortality and stratifies patients with pulmonary embolism into five severity classes, with 30-day mortality rates of 0-1.6% in class I, 1.7-3.5% in class II, 3.2-7.1% in class III, 4.0-11.4% in class IV, and 10.0-24.5% in class V across the derivation and validation samples. Inpatient death and nonfatal complications were

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