Patient Relevance of the Modified Rankin Scale in Subarachnoid Hemorrhage Research
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: There is significant heterogeneity in the reporting of outcome measures in aneurysmal subarachnoid hemorrhage (aSAH) research. The modified Rankin scale (mRS) is the most commonly reported functional outcome measure. The mRS focuses on physical disability; however, many aSAH survivors experience sequalae in other domains, and the mRS may therefore not capture outcomes important to aSAH survivors. The objective of this study was to assess the clinical relevance of the mRS as a research outcome measure to people with lived aSAH experience. METHODS: We conducted an international cross-sectional survey of 355 aSAH survivors, family members, and caregivers to evaluate patient-perceived outcomes in relation to the mRS. The mRS was assessed using a previously validated web-based tool. RESULTS: Response rate was 60%; respondents from 7 continents were composed of 86% aSAH survivors and 14% family members/caregivers. Agreement between self-assessed outcome and the mRS was poor (Kappa 0.26 [CI 0.14-0.39]). Of the 172 respondents who self-assessed as having had a good aSAH outcome, 122 (71%) had a score of 0-2 on the mRS. Approximately 19% of respondents with a good outcome, based on a measured mRS score of 0-2, self-assessed as having had a poor aSAH outcome. When the mRS score was dichotomized as 0-3 corresponding to a good outcome, agreement between the score and self-assessed outcome remained poor with a Kappa score of 0.40 (CI 0.20-0.60). Approximately 30% of respondents believed that the mRS should not be used as an outcome measure in future aSAH trials. DISCUSSION: The findings suggest that there is poor agreement between aSAH survivors' self-assessed outcome, their actual mRS score, and the dichotomization of the mRS score into good/poor outcomes. Patient-centered and patient-informed outcome measurement tools are needed to guide the aSAH research agenda.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.060 | 0.185 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".