Comparative Analysis of Alzheimer Questionnaire and Montreal Cognitive Assessment Tool for Cognitive Impairment Screening among the Elderly Population
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction: Alzheimer Questionnaire (AQ) and Montreal Cognitive Assessment (MoCA) are tools for assessment of cognitive impairment. MoCA is a common tool for screening of cognitive impairment but it requires trained personnel. AQ questionnaire is informant-based, simple and less time consuming with or without the involvement of trained personnel. Aim: To estimate the prevalence of cognitive impairment and to find out the accuracy of AQ compared to MoCA in Cognitive Impairment screening among elderly population in an urban area of West Bengal. Materials and Methods: The Prospective cross-sectional study was conducted in urban field practice area of All India Institute of Hygiene and Public Health, Kolkata among 140 randomly selected elderly population from June to September 2019. Accuracy of AQ with MoCA tool as gold standard in screening cognitive impairment was analysed by Cohen’s Kappa, Receiver Operating Characteristics (ROC) Curve, Spearman rho Coefficient along with sensitivity, specificity, predictive values and likelihood ratio was obtained. Results: Prevalence of cognitive impairment using MoCA and AQ was 40% (95% CI=31.8-48.6) and 36.4% (95% CI=28.5-45.0), respectively. AQ and MoCA showed good agreement (Cohen’s kappa, κ=0.834; 95% CI=0.739-0.928). The AQ and MoCA showed a strong negative correlation (spearman’s Rho=-0.709; 95%CI=0.764-0.884, p-value <0.001). Considering MoCA as gold standard, AQ showed sensitivity of 85.7% (95% CI=74.2-92.6), specificity of 96.4% (95% CI=89.9-98.7) for cognitive impairment screening and the Positive predictive value of this tool was 94.1% (95% CI=84.0-97.9%). The Youden index of 0.821 showed highest sum of sensitivity and specificity of AQ tool at 4.5 score to anticipate cognitive impairment. Conclusion: AQ is equally effective as MoCA to screen cognitive impairment among elderly at the community level. AQ can be used even by grass root level health workers without involvement of trained personnel. So, community level screening of elderly for cognitive dysfunction can be made even in resource poor settings. Early identification and referral of elderly with cognitive dysfunction will help them in better living.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it