Outcome Prediction for Patients With Ischemic Stroke in Acute Care: New Three-Level Model by Eating and Bladder Functions
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Objective To develop a new prediction model by combining independence in eating and bladder management functions, and to assess its utility in an acute care setting. Methods Patients with ischemic stroke who were admitted in our acute stroke care unit (n=250) were enrolled in this study. Functional Independence Measure (FIM) scores for eating and bladder management on the initial day of rehabilitative treatment (median, 3 days) were collected as predictive variables. These scores were divided into low (<5) and high (≥5) and categorized as values 0 and 1, respectively. From the simple summation of these two-level model values, we derived a three-level model that categorized the scores as values 0, 1, and 2. The FIMmotor scores at discharge (median, 14 days) were collected as outcome measurements. The three-level model was assessed by observing the distribution patterns of the outcome FIM-motor scores and logistic regression analyses. Results The median outcome FIM-motor score was 19 (interquartile range [IQR],13.8–45.3) for the value 0 category (n=14), 66.5 (IQR, 59.5–81.8) for the value 1 category (n=16), and 84 (IQR, 77–89) for the value 2 category (n=95) in the three-level model. Data fitting by logistic regression for FIM-motor scores of 41.3 and 61.4 reached 50% probability of values 1 and 2, respectively. Conclusion Despite the simplicity of the three-level model, it may be useful for predicting outcomes of patients with ischemic stroke in acute care.
Abstract
Objective To develop a new prediction model by combining independence in eating and bladder management functions, and to assess its utility in an acute care setting. Methods Patients with ischemic stroke who were admitted in our acute stroke care unit (n=250) were enrolled in this study. Functional Independence Measure (FIM) scores for eating and bladder management on the initial day of rehabilitative treatment (median, 3 days) were collected as predictive variables. These scores were divided into low (<5) and high (≥5) and categorized as values 0 and 1, respectively. From the simple summation of these two-level model values, we derived a three-level model that categorized the scores as values 0, 1, and 2. The FIMmotor scores at discharge (median, 14 days) were collected as outcome measurements. The three-level model was assessed by observing the distribution patterns of the outcome FIM-motor scores and logistic regression analyses. Results The median outcome FIM-motor score was 19 (interquartile range [IQR],13.8–45.3) for the value 0 category (n=14), 66.5 (IQR, 59.5–81.8) for the value 1 category (n=16), and 84 (IQR, 77–89) for the value 2 category (n=95) in the three-level model. Data fitting by logistic regression for FIM-motor scores of 41.3 and 61.4 reached 50% probability of values 1 and 2, respectively. Conclusion Despite the simplicity of the three-level model, it may be useful for predicting outcomes of patients with ischemic stroke in acute care.
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