A novel digital clock drawing test as a screening tool for perioperative neurocognitive disorders: A feasibility study
Bibliographic record
Abstract
BACKGROUND: We developed a digital clock drawing test (dCDT), an adaptation of the original pen and paper clock test, that may be advantageous over previous dCDTs in the perioperative environment. We trialed our dCDT on a tablet device in the preoperative period to determine the feasibility of administration in this setting. To assess the clinical utility of this test, we examined the relationship between the performance on the test and compared derived digital clock measures with the 4 A's Test (4AT), a delirium and cognition screening tool. METHODS: We recruited a sample of 102 adults aged 65 years and over presenting for elective surgery in a single tertiary hospital. Participants completed the 4AT, followed by both command and copy clock conditions of the dCDT. We recorded time-based clock-drawing metrics, alongside clock replications scored using the Montreal Cognitive Assessment (MoCA) clock scoring criteria. RESULTS: The dCDT had an acceptance rate of 99%. After controlling for demographic variables and prior tablet use, regression analyses showed higher 4AT scores were associated with greater dCDT time (seconds) for both command (β = 8.2, P = .020) and copy clocks (β = 12, P = .005) and lower MoCA-based clock scores in both command (OR = 0.19, P = .001) and copy conditions (OR = 0.14, P = .012). CONCLUSION: The digital clock drawing test is feasible to administer and is highly acceptable to older adults in a preoperative setting. We demonstrated a significant association between both the dCDT time and clock score metrics, with the established 4AT. Our results provide convergent validity of the dCDT in the preoperative setting.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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 | 0.000 |
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".