title: Derivation and validation of the In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) prediction rule.
abstract: BACKGROUND
  Existing prediction rules for prospectively prognosticating early mortality following pulmonary embolism (PE) require clinical and/or laboratory data, and are rarely suitable for claims database analyses. We sought to develop a claims-based prediction rule that retrospectively classifies PE patients into low- or higher-risk in-hospital mortality categories.
  
  
  METHODS
  We randomly assigned MarketScan database patient admitted for PE between April 2010 and September 2013 into derivation (80%) and validation (20%) cohorts. A prediction rule (In-hospital Mortality for PulmonAry embolism using Claims daTa or IMPACT) was derived using multivariable logistic regression, with in-hospital mortality as the dependent variable and demographic/comorbidity data available in claims databases as independent variables. In-hospital mortality rates for low- and higher-risk patients were compared across the derivation and validation cohorts, and prediction rule performance was assessed by evaluating sensitivity and specificity estimates.
  
  
  RESULTS
  A total of 27,833 patients admitted for PE were included. The IMPACT rule consisted of 12 risk factors, and categorized 46% of patients as low-risk in both cohorts. Patients classified as low-risk by IMPACT (defined as an estimated in-hospital mortality risk ≤1.5%) had average in-hospital mortality rates of 0.81% (95% confidence interval [CI], 0.65-1.00) in the derivation and 0.77% (95% CI, 0.50-1.18) in the validation cohort. Higher-risk patients had average in-hospital mortality rates of 4.61% (95% CI, 4.25-5.01) and 5.02% (95% CI, 4.30-5.85), respectively. The IMPACT rule had high sensitivity for classifying in-hospital mortality risk (0.87 in both cohorts), but moderate specificity (0.47 for both cohorts).
  
  
  CONCLUSIONS
  We were unable to assess 30 day mortality as an endpoint. IMPACT was only validated in an internal sample.
  
  
  CONCLUSIONS
  The IMPACT prediction rule may be able to retrospectively classify PE patients' in-hospital mortality risk with high sensitivity and moderate specificity.
authors.affiliation: a a University of Connecticut School of Pharmacy, Department of Pharmacy Practice , Storrs , CT , USA.
authors.forename: Craig I
authors.initials: CI
authors.lastname: Coleman
authors.forename: Christine G
authors.initials: CG
authors.lastname: Kohn
authors.forename: Thomas J
authors.initials: TJ
authors.lastname: Bunz
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D005260:Female; D017052:Hospital Mortality; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011655:Pulmonary Embolism / Q000401:mortality*; D012189:Retrospective Studies
keywords: Claims analysis; Clinical prediction rule; Pulmonary embolism; Sensitivity and specificity