Assessment of cognitive dysfunction using the Montreal Cognitive Assessment test: rate, severity and comparison with the Clock test alone in a population of patients referred for TAVI
Bibliographic record
Abstract
Abstract Background Although not recommended in routine practice, the detection and quantification of Cognitive Dysfunction (CD) in older patients might have an impact on clinical decisions. We assessed the rate and severity of CD in an unselected population of patients referred for Transcatheter Aortic Valve Implantation (TAVI) using the Montreal Cognitive Assessment (MoCA) and using the Clock Drawing Test (ClockT) alone. Methods The MoCA was performed before TAVI by an experienced operator. The ClockT was scored out of 10 points according to the Rouleau rating scale. CD was defined according to the MoCA score: No CD if score ≥26, mild CD if score 18–25, moderate if 10–17 and severe if <10. Inter-observer reliability of scoring on the ClockT was estimated with the Bland-Altman method. Agreement between MoCA scores and the ClockT for ruling out and for detecting CD were measured with the Kappa coefficient. Results MoCA was performed in 83 consecutive patients referred for TAVI, median age 85 years. The mean time required for assessment was 11±2 min for the MoCA and 3±2 min for the ClockT. The mean MoCA score was 21±4.5: CD was excluded in 17 (20%) pts, mild CD was found in 50 (60%), moderate in 15 (18%) and severe in one (1%). The median ClockT score was 8 (interquartile 6; 9), with excellent inter-observer concordance (Kappa= 0.84). Overall, 51% of the variance of the MoCA score was explained by the ClockT alone according to multiple regression. A ClockT <7 detected a group with significantly lower MoCA score, compared to pts with higher ClockT scores (figure). Conclusion Among patients referred for TAVI, CD can be excluded using the MoCA test in 20%, while moderate or severe CD is observed in 18%. The ClockT alone is faster to implement, reliable to interpret and enabled detection of patients with moderate CD when Rouleau scoring was <7. Funding Acknowledgement Type of funding sources: None.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".