A simple scoring system for outcome prediction of ischemic stroke

Area of Science:

• Neurology
• Clinical Medicine
• Biostatistics

Background:

• Existing stroke outcome prediction models often require complex calculations or computer assistance.
• There is a need for a simple, reliable prognostic tool for ischemic stroke patients.

Purpose of the Study:

• To develop and validate a straightforward prognostic scale for predicting ischemic stroke outcomes.
• To create a tool that does not rely on computational analysis.

Main Methods:

• The Bologna Outcome Algorithm for Stroke (BOAS) scale was developed using data from 221 ischemic stroke patients.
• The scale was validated in an independent group of 100 patients, assessing outcomes at 9 months using the modified Rankin scale (mRS).

Main Results:

• A multivariable model identified five key risk factors: NIH Stroke Scale score ≥10, age ≥78, urinary catheter use, oxygen administration, and persistent upper limb paralysis.
• Patients with ≥2 risk factors had a 91% rate of dependency or death (mRS > 2), versus 24% for those with 0-1 risk factor.
• The scale demonstrated high predictive accuracy (83.9% overall, AUC 0.891 in the derivation group; 79.0% accuracy, AUC 0.839 in the validation group).

Conclusions:

• The BOAS scale effectively predicts dependency or death after ischemic stroke using five simple clinical variables.
• This prognostic tool offers a reliable, non-computerized method for assessing stroke outcomes.
• Key predictors include stroke severity, advanced age, need for catheterization, oxygen support, and limb paralysis persistence.