fig3

Comparison of outcome prediction models post-stroke for a population-based registry with clinical variables collected at admission <i>vs</i>. discharge

Figure 3. The coefficients of selected clinical variables. The variables shown were selected 100/100 times, and the coefficients were calculated in the LR models. The higher number of the coefficient indicated the degree of importance in predicting the functional outcome; for example, age at onset and functional assessments were higher than those of other clinical variables. In addition, the sign (+ or -) were indicative of positive or negative impacts on the prediction outcomes. The variables in the blank rectangle were not included (i.e., not available) in the model assessed. LR: logistic regression

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ISSN 2574-1209 (Online)
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