91PROSPECTIVE COHORT STUDY OF DELIRIUM IN ELDERLY UNDERGOING CARDIOTHORACIC SURGERY
Bibliographic record
Abstract
Introduction: Delirium is common in the post-operative cardiothoracic surgery setting especially in older age. Delirium is associated with poor post-operative outcomes. The aims of this study were to review predictors of delirium, demographics and outcomes in those over 70 years undergoing cardio- thoracic surgery who had delirium compared with those without delirium. Methods: Prospective cohort study including those over 70 years undergoing cardiothoracic surgery. Data collected preoperatively included age, gender, supports, mobility, Charlson comorbidity index, living status, MMSE, number of delirium risk factors and Edmonton Frailty score. Outcome data included discharge destination, code blacks, nurse special, falls, early mortality, return to theatre and length of stay. If delirium present type identified. Statistical software used SAS 9.4. Tests included Wilcoxon Rank Sum test and Fisher’s Exact test. Ethics approval CALHN R20160219. Results: N = 39 participants included in cohort. The mean age was 76.64 years (SD = 4.6). 35.9% female. Preoperatively 64.1% had home supports, 20.5% required walking aids and 28.2% lived alone. Mean MMSE 28/30(SD = 2.1), mean number of delirium risk factors 3(SD = 0.9), mean Charlson comorbidity index 3(SD = 1.4) and mean Edmonton Frailty Scale 5/17(SD = 1.7). Postoperatively prevalence of delirium 46%. Types of delirium comprised 55.6% hypoactive, 16.7% mixed and 27.8% hyperactive. Average length of stay total 11 days and 4.9 in ICU. Outcomes 7.7 % mortality and 58.9% discharged directly home. 2.6% had a code black and nurse special, 7.9% had falls and 12.8% returned to theatre. Those who developed delirium had significant association with preoperative lower MMSE (p = 0.03), higher Edmonton Frailty Score (p = 0.01) and living with others (p = 0.04). Conclusion: Delirium is common in the older cardiothoracic patient. Statistically significant preoperative predictors of delirium included lower MMSE, higher Edmonton Frailty score and living with others. Preoperative assessment of the elderly in preparation for cardio thoracic surgery can allow those who are at risk of delirium to be identified, given education regarding delirium and interventions to reduce post-operative delirium and therefore improve surgical outcomes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".