Objectives: To develop an accurate and easy-to-use predictive tool of short-term functional outcome for ischemic stroke patients treated with thrombolysis in the rural setting. Methods: This multicenter retrospective study involved the Southern Illinois Healthcare rural stroke network registry as derivative cohort, and the University of Oklahoma Health Sciences Center stroke database as validation cohort. Demographics, clinical, laboratory, and radiographic data were collected. Short-term outcome at 30 days was divided in good (mRS ≤2) bad (mRS ≥5). A backward logistic regression analysis was developed by clinical significance of the dependent variables and a 5-point predictive score system was developed based on clinical plausibility and practicality. Calibration curve was designed. The score was tested on the validation cohort. P value was set at 0.05 for all statistical analyses. Results: Of 222 patients included in the derivation cohort, 35 (16%) had poor short-term outcome. In a backward logistic regression model, baseline mRS (OR: 1.511, 95% CI: 1.047-2.182, P =0.02), and NIHSS (OR: 1.136, 95% CI: 1.063-1.214, P 75, cardiac disease, baseline mRS >2, NIHSS ≥20, and GFR <40. The c-statistic of the model was 0.79, 95% CI: 0.71-0.87. In the validation cohort of 200 patients, the model performed with a c-statistic of 0.75, 95% CI: 0.64-0.86. Good outcome was predicted with a c-statistic of 0.71, 95% CI: 0.64-0.77 in the derivation cohort, and 0.69, 95% CI: 0.62-0.76 in the validation cohort. Conclusions: This predictive score is an accurate and easy-to-use tool to help providers in the rural settings facilitate early conversations with stroke patients and their families. Providing rural settings with affordable and accurate prognostic tools is a crucial step in bridging the gap in stroke care between urban and rural settings.
Loggini et al. (Thu,) studied this question.