Validation of the Cognitive Telephone Screening Instrument (COGTEL) for detecting mild cognitive impairment and dementia due to Alzheimer's disease (AD)
Bibliographic record
Abstract
Abstract Background Cognitive assessment is necessary for diagnosing cognitive impairment. In epidemiologic surveys and genetic family studies cognitive tests that can be administered over the telephone are valuable tools. The Cognitive Telephone Screening Instrument (COGTEL) is a brief instrument for capturing interindividual differences in cognitive functioning, with the advantage of covering more cognitive domains than traditional screening tools such as the Mini‐mental State Examination (MMSE), as well as differentiating between individual performance levels in healthy older adults. Here, we report first evidence of the utility of the COGTEL in detecting mild cognitive impairment (MCI) and dementia due to Alzheimer’s disease (AD). Method The COGTEL was translated into Greek. Thereafter a bilingual expert not familiar with the original COGTEL made a back translation into English. The new version was very similar to the original one. The study refers to 30 and 22 patients with MCI and dementia due to AD, respectively. They fulfilled the international NIA‐AA diagnostic criteria. The study included 45 cognitively normal elderly individuals, too. The COGTEL was compared to the conventional modified Mini Mental State Examination (3MS). They were validated against an expert diagnosis based on a comprehensive diagnostic workup which included the Montreal Cognitive Assessment (MoCA). Statistical analysis was performed using the receiver‐operator‐characteristics (ROC) method. Result The COGTEL outperformed the 3MS in the distinction between cognitively unimpaired individuals and patients with MCI (Area under the curve, AUC: 0.94 vs. 0.89), whilst both instruments were excellent in identifying patients suffering from dementia due to AD (AUC in both cases 0.99). Conclusion The COGTEL is a short, practical and reliable telephone test for the identification of both MCI and dementia due to AD. It can serve as a useful instrument in studying normal cognition and cognitive impairment in aging in both clinical diagnostics and research projects. The lack of difference between COGTEL and 3MS in their capacity to detect dementia due to AD is probably attributable to the fact that healthy aging can in most cases be unambiguously distinguished from dementia due AD, while the distinction between MCI and healthy aging is more ambitious.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".