Post-stroke cognition with the Oxford Cognitive Screen vs Montreal Cognitive Assessment: a multi-site randomized controlled study (OCS-CARE)
Bibliographic record
Abstract
Background: Cognitive impairment is common following stroke. The Oxford Cognitive Screen (OCS) was designed to assess focal post-stroke cognitive deficits in five domains. Here, we investigated whether results generated by the OCS vs the domain-general Montreal Cognitive Assessment (MoCA) at baseline impacted patient outcomes at 6 months follow-up. Methods: Patients <2 months post-stroke were randomized to receive either the OCS and corresponding information leaflet or standard care with the MoCA at baseline. After 6 months, patients received both the OCS and MoCA. The primary registered outcome measures were the Stroke Impact Scale (SIS) and change in stroke severity (National Institutes of Health Stroke Scale; NIHSS) at 6 months. The secondary outcome was change in cognitive performance from baseline to 6-month follow-up. The relationship between scores from the two cognitive screens at follow-up was also explored. Results: A total of 821 patients from 37 different hospital or rehabilitation sites (England, UK) were recruited to the OCS-CARE study, with 467 completing 6-month follow-up. Patient outcomes defined by overall SIS scores and changes in NIHSS did not differ between the OCS or MoCA groups. There were high accordance rates between the OCS and MoCA at 6 months, with severity of cognitive impairment reflected in both screening tools. Cognitive performance in both groups over the 6-month follow-up declined in 22% of patients. A larger proportion of OCS group patients demonstrated improvements in cognitive scores (49% vs 40% in MoCA). Conclusions: The type of cognitive screening test did not impact broad stroke outcome measures, and the two screening tools showed a high overall accordance. The results suggest that more of the domain-specific deficits in OCS recover subacutely, providing a more granular picture of cognitive recovery as well as decline. Registration: ISRCTN50857950 ; registered on 27/03/2014.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".