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Volume 89, Issue 7, Pages 1276-1283 (July 2008)


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Validation of the Charlson Comorbidity Index for Predicting Functional Outcome of Stroke

Annie Tessier, MPHaCorresponding Author Informationemail address, Lois Finch, PhDa, Stella S. Daskalopoulou, MD, PhDb, Nancy E. Mayo, PhDab

Abstract 

Tessier A, Finch L, Daskalopoulou SS, Mayo NE. Validation of the Charlson Comorbidity Index for predicting functional outcome of stroke.

Objective

To determine whether a separate comorbidity index is needed to predict functional outcome after stroke, we compared the predictability of the Charlson Comorbidity Index (CMI) and the Functional Comorbidity Index (FCI) to that of a stroke-specific comorbidity index with function quantified with a measure developed with a Rasch model as outcome.

Design

Two prospective inception cohort studies, in 1996 through 1998 and in 2002 through 2005, with up to 9 months of follow-up.

Setting

Participants enrolled in 2 studies were recruited from acute care hospitals in the Montreal area.

Participants

For study one, 1027 persons with a first stroke discharged into the community were eligible; the 437 who were interviewed a second time at 6 months were included in the analysis. In study two, 235 of 262 patients with stroke were enrolled.

Interventions

Not applicable.

Main Outcome Measures

To predict recovery, we developed 3 stroke-specific comorbidity algorithms based on the estimated strength of association between comorbidities and stroke function. The various indices were compared on the basis of their predictive ability with a c statistic.

Results

In study 1, the c statistics were .758, .763, .766, and .763 for the stroke-specific algorithms 1, 2, and 3 and the CMI, respectively. In study 2, the c statistics were .680, .700, .704, .714, and .714 for the algorithms 1, 2, and 3, the CMI, and the FCI, respectively.

Conclusions

For purposes of case-mix adjustment, the CMI seems to be more than adequate.

a School of Physical and Occupational Therapy, Faculty of Medicine, McGill University, Montreal, QC, Canada

b Department of Epidemiology and Biostatistics and Occupational Health, Faculty of Medicine, McGill University, Montreal, QC, Canada.

Corresponding Author InformationReprint requests to Annie Tessier, MPH, Royal Victoria Hospital, Div of Clinical Epidemiology, 687 Pine Ave W, Ross 4:00, Montreal, QC H3A 1A1, Canada

 No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit upon the authors or upon any organization with which the authors are associated.

PII: S0003-9993(08)00274-8

doi:10.1016/j.apmr.2007.11.049


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