Clinical Validation of an Artificial Intelligence-Based Scoring System for the Modified Rankin Scale (mRS) in Patients With Stroke
Study Overview
Status
Status
Conditions
Conditions
Detailed Description
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Qingfeng Ma, MD
- Phone Number: +8613601069493
- Email: m.qingfeng@163.com
Study Contact Backup
- Name: Zixin Wang, MD Candidate
- Phone Number: +8615031041048
- Email: wzx15031041048@163.com
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
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.
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
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AI-first interview group
Participants first receive telephone assessment by AI, followed by telephone assessment by human assessors.
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Human-first group
Participants first receive telephone assessment by human assessors, followed by telephone assessment by AI.
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Agreement Between Artificial Intelligence (AI)-Based and Manual Modified Rankin Scale (mRS) Assessments
Time Frame: 7 days post-discharge or post-outpatient visit, ± 2 days
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The weighted kappa coefficient quantifies the level of agreement between the Artificial Intelligence (AI)-generated Modified Rankin Scale (mRS) scores and the standardized manual mRS assessments performed by trained clinicians
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7 days post-discharge or post-outpatient visit, ± 2 days
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Agreement Between AI-based and Manual Assessments of Dichotomized Modified Rankin Scale (mRS)
Time Frame: 7 days post-discharge or post-outpatient visit, ± 2 days
|
The simple kappa coefficient quantifies the level of agreement between the Artificial Intelligence (AI)-generated dichotomized Modified Rankin Scale (mRS) scores (0-2 vs. 3-6) and the standardized manual mRS assessments performed by trained clinicians
|
7 days post-discharge or post-outpatient visit, ± 2 days
|
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Bland-Altman Limits of Agreement Between AI and Manual Modified Rankin Scale (mRS) Scores
Time Frame: 7 days post-discharge or post-outpatient visit, ± 2 days
|
The Bland-Altman limits of agreement analysis evaluates the consistency between the Artificial Intelligence (AI)-generated and manually assessed Modified Rankin Scale (mRS) scores.
The difference between manual and AI scores will be plotted on the y-axis against their mean on the x-axis, with limits of agreement (mean difference ± 1.96 × standard deviation) calculated.
The analysis aims to visually assess how agreement varies across the range of mRS scores and identify any proportional bias, such as greater disagreement in patients with severe disability.
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7 days post-discharge or post-outpatient visit, ± 2 days
|
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Diagnostic Performance of AI-Based vs. Manual Modified Rankin Scale (mRS) Dichotomization
Time Frame: 7 days post-discharge or post-outpatient visit, ± 2 days
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The diagnostic performance analysis evaluates the ability of the Artificial Intelligence (AI)-based Modified Rankin Scale (mRS) scoring system to classify functional outcomes, using manual assessment as the reference standard.
A 2×2 contingency table will be constructed for the dichotomized mRS categories (good outcome: 0-2 vs. poor outcome: 3-6).
The analysis will calculate sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and Youden's index.
A receiver operating characteristic (ROC) curve will be plotted, and the area under the curve (AUC) will be computed.
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7 days post-discharge or post-outpatient visit, ± 2 days
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Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Investigators
Investigators
- Study Chair: Qingfeng Ma, MD, Xuanwu Hospital, Beijing
Study record dates
Study Major Dates
Study Start (Estimated)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- qingfeng ma AI mRS
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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