Background. The telestroke technology provides sustainable approaches to improve the use of thrombolysis therapy. How this is achieved is not fully understood. We developed a new computational model to predict inclusion for thrombolysis for hypertensive stroke patients.
Methods. Clinical risk factors associated with inclusion or exclusion for thrombolysis in the telestroke and non telestroke were identified using multiple regression analysis. Associations between variables and thrombolysis in the regression models were determined using variance inflation factors while the fitness of each model was determined using the ROC curve to predict the power of each logistic regression model.
Results. The non telestroke admitted more patients (62% vs 38%), when compared with the telestroke. Although the telestroke admitted fewer patients, it excluded 11% and administered thrombolysis therapy to 89% of stroke patients with hypertension. In the non telestroke group, adjusted odd ratios showed significant associations of NIH stroke scale score (OR= 1.059, 95% CI, 1.025 - 1.093, P<0.001) and coronary artery disease (OR= 2.003, 95% CI, 1.16 - 3.457, P=0.013) with thrombolysis. In the telestroke, only direct admission to the telestroke was associated with thrombolysis (OR= 4.083, 95% CI, 1.322 - 12.611, P=0.014).
Conclusion: The direct admission of hypertensive stroke patients to the telestroke network was the only factor associated with inclusion for thrombolysis therapy even after adjustment for baseline variables. The telestroke technology provides less restrictive criteria for clinical risk factors associated with the inclusion of hypertensive stroke patients for thrombolysis.