The value of montreal cognitive assessment in evaluation of mild cognitive impairment in patients with transient ischemic attack
Bibliographic record
Abstract
Objective To explore the value of montreal cognitive assessment (MoCA) in evaluation of mild cognitive impairment(MCI)in patients with transient ischemic attack (TIA).Methods Seventy-six patients with TIA were divided into patients with MIC group (group A) or patients without MIC group (group B).Thirty-eight healthy individuals were as control (group C).Results The scores of MoCA (19.51 ± 3.96) and the latency period of P300(367.05 ± 36.03ms)in group A were significantly higher than group B and group C (P 0.01).The area under ROC curve of MoCA was 0.935 (95% credible interval 0.879 ～ 0.992).Score of optimal cut-off-point of the MoCA in evaluating TIA patients was 25 in ROC curve analyses as well as the largest Youden`s index? which accords with the diagnosis by clinical golden standard.Kappa value was 0.698.Sensitivity and specificity were found to be 85.45% and 90.48% respectively.Efficiency of MoCA for the diagnosis of TIA patients with cognitive impairment was superior to that of latency period of P300.Conclusion The score of optimal cut-off-point of MoCA was 25.in screening MCI.MoCA could be a good tool in screening MCI from the patients with TIA.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".