Barbara E Bates1, Dawei Xie2, Pui L Kwong3, Jibby E Kurichi4, Diane Cowper Ripley5, Margaret G Stineman6. 1. Veterans Affairs Medical Center, Albany, NY; Physical Medicine and Rehabilitation, Albany Medical College, VAMC (117), 113 Holland Avenue, Albany, NY 12208(∗). Electronic address: barbara.bates@va.gov. 2. Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA(†). 3. Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA(‡). 4. Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA(§). 5. Veterans Affairs Medical Center Gainesville, FL, Division of Health Policy and Outcomes Research, Department of Epidemiology and Health Policy Research, University of Florida, Gainesville, FL(‖). 6. Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, Department of Physical Medicine and Rehabilitation, University of Pennsylvania, Philadelphia, PA(¶).
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.
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 strokepatients 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.
Authors: Yanting Guo; Gang Zheng; Tianyun Fu; Xuefeng Bruce Ling; Shiying Hao; Chengyin Ye; Le Zheng; Modi Liu; Minjie Xia; Bo Jin; Chunqing Zhu; Oliver Wang; Qian Wu; Devore S Culver; Shaun T Alfreds; Frank Stearns; Laura Kanov; Ajay Bhatia; Karl G Sylvester; Eric Widen; Doff B McElhinney Journal: J Med Internet Res Date: 2018-06-04 Impact factor: 5.428