Validation of the OCS-plus in comparison to the MoCA in patients with mild cognitive Impairment in an ambulant setting
Bibliographic record
Abstract
Mild Cognitive Impairment (MCI) represents an intermediate stage between normal ageing and dementia and may progress to dementia. Early identification and intervention are therefore crucial to slow disease progression. New therapeutic approaches such as amyloid-beta–directed antibodies show promising effects. There are still no standardized diagnostic criteria or test batteries for MCI. Common screening tools include the Mini Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA). However, the MMSE has been shown to have limitations in detecting MCI, whereas the MoCA provides higher sensitivity but is not age-normed and only provides an overall score. Comprehensive test batteries such as the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) require trained personnel and more time, limiting their use in daily clinical practice. The tablet-based Oxford Cognitive Screen-Plus (OCS-Plus) was developed to assess subtle cognitive impairments in various domains. It provides automated scoring, reducing examiner bias, and can be performed in any quiet environment, making it well-suited for an ambulant setting. This study investigated the validity and feasibility of the OCS-Plus in an ambulant setting. Patients with suspected cognitive impairment, but without prior testing, completed both the OCS-Plus and the MoCA in a single session. In total, 38 participants were assessed, and data were analyzed using Spearman’s rank correlation. Subgroup analyses were conducted for participants younger and older than 70 years. Significant correlations between OCS-Plus and MoCA subtasks were found for orientation, memory, executive function, and attention, indicating good construct validity. All participants completed testing successfully, confirming feasibility without specialist neuropsychological staff. In summary, the OCS-Plus proved to be a valid, reliable, and practical tool for detecting cognitive decline, particularly MCI, in ambulant setting.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".