Derivation and validation of the In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) prediction rule

Abstract

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.

Keywords: :

• Claims analysis
• Clinical prediction rule
• Pulmonary embolism
• Sensitivity and specificity

Transparency

Declaration of funding

This research was supported by a grant from Janssen Scientific Affairs LLC, Raritan, NJ, USA.

Author contributions: Study concept and design: C.I.C., C.G.K., T.J.B. Acquisition of data: C.I.C., C.G.K., T.J.B. Analysis and interpretation of data: C.I.C., C.G.K., T.J.B. Drafting of the manuscript: C.I.C., T.J.B. Critical revision of the manuscript for important intellectual content: C.I.C., C.G.K., T.J.B. Administrative, technical, or material support: C.I.C. Study supervision: C.I.C. C.I.C. had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. All authors read and approved the final manuscript. The authors meet criteria for authorship as recommended by the International Committee of Medical Journal Editors (ICJME) and were fully responsible for all content and editorial decisions, and were involved in all stages of manuscript development.

Declaration of financial/other relationships

C.I.C. has disclosed that he has received grant funding from Janssen Scientific Affairs and Boehringer-Ingelheim Pharmaceuticals. C.G.K. and T.J.B. have disclosed that they have no significant relationships with or financial interests in any commercial companies related to this study or article.

CMRO peer reviewers on this manuscript have received an honorarium from CMRO for their review work, but have no relevant financial or other relationships to disclose.