Functional rehabilitation in intensive care units for post craniotomy patients: study protocol
Bibliographic record
Abstract
INTRODUCTION: Craniotomy makes insight and approach towards the brain easier but accompanies ailments. Intensive care units are equipped with trained professional physical therapists working over these deleterious after-effects of this surgical program, but a progressive, defined, and evidence-supported protocol for such patients is lacking. OBJECTIVE: To assess the feasibility of a Neuro-rehabilitation protocol devised for post-craniotomy patients within their stay in the Intensive Care Unit (ICU) to improve their functional outcomes and reduce their length of stay (LOS). MATERIALS AND METHODS: It will be a single group pre-test post-test quasi feasibility trial. Fifteen patients undergoing craniotomy will be recruited for the trial and will be rendered with Neuro-rehabilitation protocol for 60 minutes from the first day of surgery up to 15 days of surgery. The primary outcome will be the Early Functional Abilities (EFA) Scale to measure functional outcomes like conscious level, sensorimotor abilities, cognitive-perceptual abilities, and oro-motor abilities of patients, which will be assessed first-day post craniotomy. Secondary outcomes will include Glasgow Coma Scale (GCS), Coma Recovery Scale-Revised (CRS-R), Sensory Modality Assessment Rehabilitation Technique (SMART), Modified Ashworth Scale (mMAS), Montreal Cognitive Assessment Score (MoCA), and Medical Research Council Scale (MRC). Assessments will be taken on the first and fifteenth days post-surgery. PERSPECTIVES: It is expected that this protocol might improve functional outcomes and may reduce the occurrence of comorbidities in patients after Craniotomy in ICUs.
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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 | 0.029 | 0.019 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.039 | 0.009 |
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".