Clinical Validation of an Artificial Intelligence-Based Scoring System for the Modified Rankin Scale (mRS) in Patients With Stroke

This is a prospective, multicenter, observational study designed to validate the diagnostic performance of an AI-based automated scoring system for the Modified Rankin Scale (mRS) in patients with stroke. The primary objective is to evaluate the agreement between AI-generated mRS scores and standardized manual assessments conducted by trained clinicians. Secondary endpoints include the system's sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) in classifying functional outcomes.

Inclusion criteria

• Age ≥ 18 years, male or female.
• Clinically diagnosed with stroke, and confirmed by cranial CT/MRI to have stroke.
• Clinically stable, with basic communication ability at discharge or outpatient visit. The patient or a fixed family caregiver is able to cooperate with telephone follow-up at 1 week after discharge or outpatient visit.
• Signed informed consent by the patient or their legally authorized representative.

Exclusion criteria

• Neurological deficits caused by non-stroke etiologies (e.g., brain tumor, traumatic brain injury, encephalitis).
• Presence of severe disturbance of consciousness, severe cognitive impairment, psychiatric disorders, or global aphasia at discharge/outpatient visit, preventing effective communication; neither the patient nor family can cooperate with follow-up or assessment.
• Combined with severe multi-organ failure (e.g., cardiac, hepatic, renal, respiratory), with an expected survival of less than 1 month, making completion of the 1-week follow-up impossible.
• Long-term bedridden without a fixed caregiver, with no confirmed contact for follow-up, or refusal to participate in telephone follow-up and mRS assessment.
• Incomplete clinical data, preventing baseline data collection.