One‐Year All‐Cause Mortality After Stroke: A Prediction Model. Issue 6 (7th November 2013)

• Record Type: Journal Article
• Authors: Bates, Barbara E.; Xie, Dawei; Kwong, Pui L.; Kurichi, Jibby E.; Ripley, Diane Cowper; Stineman, Margaret G.
• Is Part Of: PM&R. Volume 6:Issue 6(2014)
• Page Start: 473
• Page End: 483
• Publication Date: 2013-11-07
• Subjects: Medical rehabilitation -- Periodicals; Physical therapy -- Periodicals; Physical Therapy Modalities -- Periodicals; 615.5
• DOI: 10.1016/j.pmrj.2013.11.006
• Languages: English
• ISSNs: 1934-1482

Abstract

Abstract : Objective: By using data from Department of Veterans Affairs (VA) national databases, this article presents and internally validates a 1‐year all‐cause mortality prediction index after hospitalization for acute stroke. Design: An observational cohort. Setting: VA medical centers. Participants: Veterans with a diagnosis of a new stroke who were discharged between October 1, 2006, and September 30, 2008. Main Outcome Measure: Death due to any cause that occurred between the index hospital discharge date and the 1‐year anniversary of that date. Results: Within 1‐year after discharge, 1542 (12.3%) of the total 12, 565 patients had died. Seventeen risk factors known at the point of hospital discharge remained in the predictive model of 1‐year postdischarge mortality after backward selection, including advanced age, admission from extended care, type of stroke, 8 comorbid conditions, 4 types of procedures that occurred during the index hospitalization, hospital length of stay (longer than 3 weeks), and discharge location. We assigned a score to each variable in the final model and a risk score was determined for each patient by adding up the points for all risk factors present. According to these risk scores, the patients were divided into approximate quartiles that yielded low, moderate, high, and highest mortality likelihood strata. The risk of 1‐year mortality ranged from 2.24% in the lowest quartile to 29.50% in the highest quartile in the derivation cohort and from 2.11%‐30.77% in the validation cohort. Model discrimination demonstrated an area under the receiver operating characteristic curve of 0.785 in the derivation cohort and 0.787 in the validation cohort. The Hosmer‐Lemeshow goodness of fit indicated that the model fit was adequate ( P = .69). Conclusion: When using readily available data, a simple index that stratifies stroke patients at hospital discharge according to low, moderate, high, and highest likelihood of all‐cause 1‐year mortality is feasible and can inform the postdischarge planning process, depending on level of risk.