New Index for Multiple Chronic Conditions Predicts Functional Outcome in Ischemic Stroke
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Published on: July 14, 2023
Xiaqing Jiang1, Lu Wang1, Lewis B Morgenstern1
1From the Departments of Epidemiology (X.J., L.B.M., L.D.L.) and Biostatistics (L.W.), School of Public Health, University of Michigan; Stroke Program (L.B.M., E.S.C., L.D.L.), Department of Family Medicine (C.T.C.), Department of Internal Medicine (C.T.C.), and Ann Arbor Healthcare System, Department of Physical Medicine and Rehabilitation (E.S.C.), University of Michigan Medical School; and VA Geriatric Research Education and Clinical Center (C.T.C.), Ann Arbor, MI.
Insights
A new index for multiple chronic conditions (MCCs) effectively predicts functional outcome after ischemic stroke. This tool identifies key predictors and synergistic effects for better patient prognostication.
Area of Science:
- Neurology
- Biostatistics
- Public Health
Background:
- Multiple chronic conditions (MCCs) complicate stroke recovery and influence functional outcomes.
- Predictive models for post-stroke functional outcome often lack precision in accounting for complex comorbidities.
Purpose of the Study:
- To develop and internally validate a novel index for MCCs to predict functional outcome (FO) in patients with ischemic stroke.
- To identify key chronic conditions and their synergistic interactions that impact post-stroke recovery.
Main Methods:
- A prospective cohort of ischemic stroke patients (2008-2017) was assessed at baseline and 90 days.
- Functional outcome was measured using activities of daily living (ADL)/instrumental ADL (IADL) items.
- Machine learning techniques were employed to develop and weight predictors for the MCC index.
Main Results:
- The novel MCC index incorporated prestroke modified Rankin Scale (mRS) score, age, congestive heart failure, weight loss, diabetes, other neurologic disorders, and synergistic effects.
- The index alone explained 31% of the variability in FO and demonstrated good calibration (p=0.41).
- It accurately predicted unfavorable FO (AUC 0.81) and outperformed the modified Charlson Comorbidity Index.
Conclusions:
- A new MCC index was successfully developed and validated for predicting post-stroke functional outcome.
- The index identified novel predictors and synergistic interactions, enhancing prognostic accuracy for ischemic stroke patients.
Objective:
To determine whether a new index for multiple chronic conditions (MCCs) predicts poststroke functional outcome (FO), we developed and internally validated the new MCC index in patients with ischemic stroke.
Methods:
A prospective cohort of patients with ischemic stroke (2008-2017) was interviewed at baseline and 90 days in the Brain Attack Surveillance in Corpus Christi Project. An average of 22 activities of daily living (ADL)/instrumental ADL (IADL) items measured the FO score (range 1-4) at 90 days. A FO score >3 (representing a lot of difficulty with ADL/IADLs) was considered unfavorable FO. A new index was developed using machine learning techniques to select and weight conditions and prestroke impairments.
Results:
Prestroke modified Rankin Scale (mRS) score, age, congestive heart failure (CHF), weight loss, diabetes, other neurologic disorders, and synergistic effects (dementia × age, CHF × renal failure, and prestroke mRS × prior stroke/TIA) were identified as important predictors in the MCC index. In the validation dataset, the index alone explained 31% of the variability in the FO score, was well-calibrated (p = 0.41), predicted unfavorable FO well (area under the receiver operating characteristic curve 0.81), and outperformed the modified Charlson Comorbidity Index in predicting the FO score and poststroke mRS.
Conclusions:
A new MCC index was developed and internally validated to improve the prediction of poststroke FO. Novel predictors and synergistic interactions were identified.
Classification Of Evidence:
This study provides Class II evidence that in patients with ischemic stroke, an index for MCC predicts FO at 90 days.
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