Assessing the feasibility of using the Dalhousie Computerized Attention Battery to measure postoperative cognitive dysfunction in older patients
Bibliographic record
Abstract
Purpose Postoperative cognitive dysfunction is difficult to predict and diagnose, and can have severe consequences in the long term. The purpose of this study was to examine the feasibility of using a computerised test battery, the Dalhousie Computerized Assessment Battery in the perioperative clinic to detect cognitive changes after surgery. Methods Fifty patients were recruited for this study. Patients completed the Dalhousie Computerized Assessment Battery and tests of general cognition, mood and pain at baseline and at three months postoperatively. Results This pilot study had a screening rate (85.4%) and low attrition rate (12%). At baseline, patients exhibited no significant cognitive differences compared to a normative dataset. Postoperative cognitive dysfunction incidence was 2.7% on Montreal Cognitive Assessment, 13.6% with Dalhousie Computerized Assessment Battery and 36.3% based on subjective reports. Conclusion Computerised cognitive testing in the perioperative setting proved feasible. Deficits in spatial working memory and dual tasks may be most compromised by surgically related variables.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".