fig3
![Comparison of outcome prediction models post-stroke for a population-based registry with clinical variables collected at admission <i>vs</i>. discharge](https://image.oaes.cc/6c8ffb77-0c29-4a92-ad00-b29ddd448d4e/3873.fig.3.jpg)
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