Oxford Cognitive Screen – Brazilian Portuguese version (OCS-Br): assessment of vascular cognitive impairment
Bibliographic record
Abstract
Cognitive impairment is prevalent in stroke patients and is rarely diagnosed. Cognitive deficits involving language functions, praxis, visuospatial and visuoconstructive skills, as well as memory, are prominent. The cognitive assessment tests available do not address some specific characteristics of stroke patients and present essential limitations concerning the most compromised cognitive domains.To determine the performance profile of the Oxford Cognitive Screen - Brazilian Portuguese version (OCS-Br) in cognitively-healthy individuals and to evaluate its ability to screen for cognitive impairment in individuals after ischemic stroke.We conducted an observational and descriptive study with cognitively-healthy individuals and patients with a history of stroke. The healthy individuals were recruited at the Neurology Clinic of the Outpatient Center of Universidade de São Caetano do Sul and the João Castaldelli Integrated Center for Health and Education for the Elderly, in the city of São Caetano do Sul, state of São Paulo. The stroke patients were recruited at the same Neurology Clinic and among subjects referred from Hospital Municipal de Emergências Albert Sabin and admitted to the Stroke Unit of Hospital Santa Marcelina, in the city of São Paulo, from September 2021 to July 2023.The study included 108 participants, 50 (46.3%) in the stroke group and 58 (53.7%) in the healthy group. When comparing the OCS-Br scores between the groups, we found a significant difference in writing tasks, executive functions (attention, change of strategy), and memory.Our results show the need for adequate monitoring and rehabilitation of poststroke patients. The advantages of the OCS-Br are: its focus on specific cognitive aspects of stroke, such as visual inattention and visual field testing; the assessment of patients with aphasia and visual impairment; and its prognostic value to predict long-term functioning.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".