Prevalence of Poststroke Neurocognitive Disorders Using National Institute of Neurological Disorders and Stroke-Canadian Stroke Network, VASCOG Criteria (Vascular Behavioral and Cognitive Disorders), and Optimized Criteria of Cognitive Deficit
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The prevalence of poststroke neurocognitive disorder (NCD) has yet to be accurately determined. The primary objective of the present study was to optimize operationalization of the criterion for NCD by using an external validity criterion. METHODS: The GRECOG-VASC cohort (Groupe de Réflexion pour l'Évaluation Cognitive Vasculaire) of 404 stroke patients with cerebral infarct (91.3%) or hemorrhage (18.7%) was assessed 6 months poststroke and 1003 healthy controls, with the National Institute of Neurological Disorders and Stroke-Canadian Stroke Network standardized battery. Three dimensions of the criterion for cognitive impairment were systematically examined by using the false-positive rate as an external validity criterion. Diagnosis of mild and major NCD was based on the VASCOG criteria (Vascular Behavioral and Cognitive Disorders). The mechanisms of functional decline were systematically assessed. RESULTS: =0.0001) corrected true-positive rate (43.5%) and a false-positive rate ≤5%. Using this criterion, the mean (95% confidence interval) prevalence of poststroke NCD was 49.5% (44.6-54.4), most of which corresponded to mild NCD (39.1%; 95% confidence interval, 34.4-43.9) rather than dementia (10.4%; 95% confidence interval, 7.4-13.4). CONCLUSIONS: This study is the first to have optimized the operationalization of the criterion for poststroke cognitive impairment. It documented the prevalence of poststroke NCD in the GRECOG-VASC cohort and showed that mild cognitive impairment accounts for 80% of the affected patients. Finally, the method developed in the present study offers a means of harmonizing the diagnosis of NCD. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov. Unique identifier: NCT01339195.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".