Prognostic Factors of Functional Outcome Assessed by Using the Modified Rankin Scale in Subacute Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND: Most stroke survivors spent their lifetime with disability which not only affects the clients themselves and the family but also brings economic cost to the country. Therefore, this retrospective cohort study aimed to identify independent prognostic determinants associated with functional recovery in ischemic stroke within 6 months after onset. METHODS: Data from all first-onset ischemic stroke patients admitted to the acute stroke unit of the tertiary, university hospital were reviewed for 5 years consecutively. The functional outcome of the patients was recorded during 6-month follow-up by using the modified Rankin Scale (mRS). Baseline characteristics, motor assessment and all stroke-related variables were assessed during first week after stroke and 6-month follow-up. In order to derive clinical predictors, the backward stepwise multivariable risk regression analyses were used with the generalized linear model. RESULTS: The result revealed that in the 358 patients recruited into this study, 255 (71.2%) were in the functional recovery group (mRS score of 1 - 3) within 6 months after onset. The final model of multivariable risk regression analysis, with generalized linear model, demonstrated that the independent variables of functional recovery were leg score with a risk ratio (RR = 1.92, 95% confidence interval (CI): 1.14 - 3.21, P = 0.013), arm score (RR = 1.75, 95% CI: 1.02 - 3.01, P = 0.042) and age older than 75 years (RR = 1.36, 95% CI: 1.04 - 1.77, P = 0.025). CONCLUSIONS: Achieving functional recovery during 6 months post stroke was related to age and motor improvement. With limited resources, continuity of rehabilitation training in the community system or allocation of caregiver training should be a part of discharge planning to promote recovery.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".