Incidence and predictors of postoperative delirium in the older acute care surgery population: a prospective study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Among older inpatients, the highest incidence of delirium is within the surgical population. Limited data are available regarding postoperative delirium risk in the acute care surgical population. The purpose of our study was to establish the incidence of and risk factors for delirium in an older acute care surgery population. Methods: Patients aged 65 years or more who had undergone acute care surgery between April 2014 and September 2015 at 2 university-affiliated hospitals in Alberta were followed prospectively and screened for delirium by means of a validated chart review method. Delirium duration was recorded. We used separate multivariable logistic regression models to identify independent predictors for overall delirium and longer episodes of delirium (duration ≥ 48 h). Results: Of the 322 patients included, 73 (22.7%) were identified as having experienced delirium, with 49 (15.2%) experiencing longer episodes of delirium. Postoperative delirium risk factors included Foley catheter use, intestinal surgery, gallbladder surgery, appendix surgery, intensive care unit (ICU) admission and mild to moderate frailty. Risk factors for prolonged postoperative delirium included Foley catheter use and mild to moderate frailty. Surgical approach (open v. laparoscopic) and overall operative time were not found to be significant. Conclusion: In keeping with the literature, our study identified Foley catheter use, frailty and ICU admission as risk factors for delirium in older acute care surgical patients. We also identified an association between delirium risk and the specific surgical procedure performed. Understanding these risk factors can assist in prevention and directed interventions for this high-risk population.
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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 | 0.003 |
| 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 | 0.000 |
| 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 it