Clock‐Drawing Test as a Bedside Assessment of Post‐operative Delirium Risk in Elderly Patients with Accidental Hip Fracture
Bibliographic record
Abstract
BACKGROUND: Currently applied cognitive tests for assessing the risk of post-operative delirium require time and specialised medical staff, in addition to the patients' mental strain. We investigated the four-point scoring Clock-Drawing Test (CDT-4) as a preoperative independent predictor for post-operative delirium. METHODS: A total of 100 consecutive patients aged over 65 years admitted for accidental hip fracture were assessed for delirium using the Confusion Assessment Method Scale. The cognitive function was rated with mini-mental state examination, Montreal Cognitive Assessment Scale (MoCA), and CDT-4. Descriptive statistics were performed, and a logistic regression model for post-operative delirium was applied. RESULTS: Out of the 100 enrolled patients 98 underwent hip repair surgery and 65 (66%) had post-operative delirium, with 24 (42%) incident cases. The median (IQR) ages were 78 (72-83) and 84 (80-87) years for the non-delirium and post-operative delirium groups, respectively. The logistic regression concluded with age and CDT-4 as independent preoperative predictors, while controlling for gender, pre-surgery delirium, MoCA visual, and MoCA attention: OR 1.32 [95% CI (1.099-1.585); p = 0.003] for age; OR 0.153 [95% CI (0.033-0.719); p = 0.017] for CDT-4. CONCLUSIONS: Employing CDT-4 as a bedside assessment of delirium risk may help to preoperatively stratify and prioritise the patients for preventive perioperative care in a timely manner.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".