Validation of a short cognitive tool for the screening of dementia in elderly people with low educational level
Bibliographic record
Abstract
AIM: To validate the 'Prueba Cognitiva de Leganés' (PCL) as a screening tool for cognitive impairment in elderly people with little formal education. METHODS: The PCL is a simple cognitive test with 32 items that includes two scores of orientation and memory and a global score of 0-32 points. It was applied to a population sample of 527 elderly people over 70 with low educational level, who were independently diagnosed by consensus between two neurologists as having normal cognitive function, age associated cognitive decline (AACD, IPA-OMS criteria) or dementia (DSM-IV criteria). Individuals with severe visual or hearing defects and those who rejected the exam were excluded from the study. The PCL was validated in a sample of 375 individuals: 300 normal, 42 with AACD and 33 with dementia. The sensitivity, specificity, accuracy and likelihood ratios, as well as the ROC curves for dementia and for AACD-dementia, were calculated. The confounding effect of sociodemographic variables was assessed by logistic regression analysis and convergent validity by partial correlations of the PCL with other cognitive tests. Inter-rater reliability was evaluated with the intraclass correlation coefficient. RESULTS: The PCL identified dementia (cut-off < or =22) and AACD-dementia (cut-off < or =26), with the following diagnostic parameters, respectively: sensitivity 93.9%-80%, specificity 94.7%-84.3%, positive likelihood ratio 17.8-5.1, negative likelihood ratio 0.06-0.24, and accuracy 94.6%-83.4%. The areas under the ROC curve were 0.985 (95% Confidence Intervals (CI) 0.967-0.995) and 0.904 (95% CI: 0.870-0.932) respectively. The intraclass correlation coefficient was 0.79 (0.74-0.83). CONCLUSION: The PCL is a simple instrument, which is both valid and reliable, for the screening of dementia in population samples of individuals with low educational level. This instrument could be useful in primary health care.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".