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Validation of the Charlson Comorbidity Index for predicting functional outcome of stroke
Annie Tessier1, Lois Finch, Stella S Daskalopoulou
1School of Physical and Occupational Therapy, Faculty of Medicine, McGill University, Montreal, QC, Canada. annie.tessier@mail.mcgill.ca
Insights
The Charlson Comorbidity Index (CMI) adequately predicts functional outcomes after stroke. A separate stroke-specific index is not necessary for case-mix adjustment in stroke recovery prediction.
Area of Science:
- Neurology
- Rehabilitation Medicine
- Medical Statistics
Background:
- Predicting functional outcomes after stroke is crucial for patient care and resource allocation.
- Existing comorbidity indices may not fully capture stroke-specific complexities.
- Evaluating the utility of different comorbidity indices is essential for accurate prognostication.
Purpose of the Study:
- To compare the predictive accuracy of the Charlson Comorbidity Index (CMI) and the Functional Comorbidity Index (FCI) against stroke-specific comorbidity algorithms.
- To determine if a dedicated stroke-specific comorbidity index is required for predicting functional recovery post-stroke.
Main Methods:
- Two prospective inception cohort studies involving patients with first-time stroke were conducted.
- Participants were recruited from acute care hospitals in Montreal.
- Three stroke-specific comorbidity algorithms were developed and compared with CMI and FCI using c-statistics for predictive ability.
Main Results:
- In the first study, CMI (c=.763) showed comparable predictive ability to stroke-specific algorithms (c=.758-.766) for functional outcome.
- In the second study, CMI (c=.714) and FCI (c=.714) demonstrated similar predictive performance to stroke-specific algorithms (c=.680-.704).
Conclusions:
- The Charlson Comorbidity Index (CMI) appears sufficiently accurate for case-mix adjustment in stroke research.
- A separate, stroke-specific comorbidity index may not be necessary for predicting functional outcomes after 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.