Accuracy of cognitive and functional screening tests to Clinical Dementia Rating in an Outpatient Memory Clinic
Bibliographic record
Abstract
BACKGROUND: Short screening tools designed to detect cognitive impairment are important for clinical and research. The Clinical Dementia Rating (CDR) is the main used categorization system, which classifies from no dementia, to questionable dementia/mild cognitive impairment (MCI) and three severities of dementia. OBJECTIVE: To conduct an accuracy analysis of different short screening tests to predict CDR scores on a cohort of a Memory Clinic. METHODS: This is a cross-sectional study, using data from the Cog-Aging cohort study in 2023. Participants go through a comprehensive clinical, neuropsychological and neuroimaging assessment to determine the diagnosis and CDR. Eighty participants were recruited: 11 controls, 43 MCI, and 26 Dementia. Mini Mental State Examination (MMSE), Figure Memory Test's delayed recall in the Brief Cognitive Screening Battery (FMT-BCSB), The Consortium to Establish a Registry for Alzheimer's Disease's word list delayed recall (DR-CERAD) and Short-version of the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) were used to distinguish the CDR scores. Participants were classified based on CDR (0; 0.5; and 1-2). We performed a Receiver Operating Characteristic (ROC) curve and cut-off values defined by Youden's J statistic comparing: CDR 0 x CDR 0,5; CDR 0,5 x CDR 1-2; CDR 0 x CDR 1-2. This study was approved by the ethics committee of UFMG. RESULTS: Participants had a mean age of 77.7 yr. (SD 6.9) and median 6.1 years of education (IQR 5.25). The DR-CERAD had the best area under the curve (AUC) (0.863) to distinguish CDR 0 to 0.5, with 88% sensitivity with cut-off points of 5 / 6. Comparing CDR 0.5 to 1-2, IQCODE had the largest AUC (0,884) with 92% sensitivity with cut-off ≥ 3,78. Comparing CDR 0 to 1-2, the DR-CERAD had the largest AUC (0.987), with 88% sensitivity with cut-off points of 3 / 4. CONCLUSION: These findings suggest that DR-CERAD is the most accurate to distinguish MCI to normal cognition, and normal cognition to dementia in this sample. IQCODE presented as the best to distinguish MCI to dementia. These are preliminary results and more studies with years of education and a larger sample are necessary.
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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 | 0.023 |
| 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".