Dual-stage cognitive assessment: a two-stage screening for cognitive impairment in primary care
Bibliographic record
Abstract
BACKGROUND: Aging population has led to an increased proportion of older adults and cognitively impaired. We designed a brief and flexible two-stage cognitive screening scale, the Dual-Stage Cognitive Assessment (DuCA), for cognitive screening in primary care settings. METHOD: In total, 1,772 community-dwelling participants were recruited, including those with normal cognition (NC, n = 1,008), mild cognitive impairment (MCI, n = 633), and Alzheimer's disease (AD, n = 131), and administered a neuropsychological test battery and the DuCA. To improve performance, the DuCA combines visual and auditory memory tests for an enhanced memory function test. RESULTS: The correlation coefficient between DuCA-part 1 and DuCA-total was 0.84 (P < 0.001). The correlation coefficients of DuCA-part 1 with Addenbrooke's Cognitive Examination III (ACE-III) and Montreal Cognitive Assessment Basic (MoCA-B) were 0.66 (P < 0.001) and 0.85 (P < 0.001), respectively. The correlation coefficients of DuCA-total with ACE-III and MoCA-B were 0.78 (P < 0.001) and 0.83 (P < 0.001), respectively. DuCA-Part 1 showed a similar discrimination ability for MCI from NC (area under curve [AUC] = 0.87, 95%CI 0.848-0.883) as ACE III (AUC = 0.86, 95%CI 0.838-0.874) and MoCA-B (AUC = 0.85, 95%CI 0.830-0.868). DuCA-total had a higher AUC (0.93, 95%CI: 0.917-0.942). At different education levels, the AUC was 0.83-0.84 for DuCA-part 1, and 0.89-0.94 for DuCA-total. DuCA-part 1 and DuCA-total's ability to discriminate AD from MCI was 0.84 and 0.93, respectively. CONCLUSION: DuCA-Part 1 would aid rapid screening and supplemented with the second part for a complete assessment. DuCA is suited for large-scale cognitive screening in primary care, saving time and eliminating the need for extensively training assessors.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".