Evaluation of Vascular Cognitive Impairment Using the ICMR-Neuro Cognitive Tool Box (ICMR-NCTB) in a Stroke Cohort from India
Bibliographic record
Abstract
Background and Purpose: Vascular cognitive impairment (VCI) presents with a spectrum of cognitive impairment due to stroke and poses a huge socioeconomic burden especially in low middle-income countries. There is a critical need for early recognition and identification of VCI patients. Therefore, we developed and validated culturally appropriate neuropsychological instruments, the ICMR-Neuro Cognitive Tool-Box (ICMR-NCTB) and Montreal Cognitive Assessment (MoCA) to diagnose vascular MCI and dementia in the Indian context. Methods: A total of 181 participants: 59 normal cognition, 25 stroke with normal cognition, 46 vascular MCI (VaMCI) and 51 vascular dementia (VaD) were recruited for the study. The ICMR-NCTB and MoCA were administered to patients with VCI and major cognitive domains were evaluated. Results: The ICMR-NCTB was found to have good internal reliability in VaMCI and VaD. The sensitivity of the ICMR-NCTB to detect VaMCI and VaD ranged from 70.8% to 72.9% and 75.9% to 79.7%, respectively, and the specificity for VaMCI and VaD ranged from 84.8% to 86.1% and 82.5% to 85.2%, respectively. The MoCA had excellent sensitivity and specificity to detect VaMCI and VaD at ideal cut-off scores. Conclusion: The ICMR-NCTB is a valid neuropsychological toolbox that can be used for comprehensive cognitive assessment and diagnosis of VCI in India. In addition, the Indian version of MoCA is more adept as a screening instrument to detect VCI due to its high sensitivity. The ICMR-NCTB will aid in early detection and management of many patients, thereby reducing the burden of vascular MCI and dementia in India.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".