Key result
The IMPACT prediction rule identified low-risk PE patients with an in-hospital mortality of 0.77% vs 5.02% in higher-risk patients, demonstrating high sensitivity (0.87) and moderate specificity (0.47).
Observational (n=27,833)
Yes
The IMPACT prediction rule can retrospectively classify in-hospital mortality risk for pulmonary embolism patients using claims data with high sensitivity but moderate specificity.
Supports retrospective PE risk stratification in claims data; leaves open prospective validation before clinical adoption.
INTRODUCTION: 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. MATERIALS AND 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). LIMITATIONS: 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.
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Coleman et al. (2015) conducted an observational in Pulmonary embolism (n=27,833). IMPACT prediction rule low-risk classification vs. Higher-risk classification was evaluated on In-hospital mortality. The IMPACT prediction rule identified low-risk PE patients with an in-hospital mortality of 0.77% vs 5.02% in higher-risk patients, demonstrating high sensitivity (0.87) and moderate specificity (0.47).
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