Role of perceived stress in postoperative delirium: an investigation among elderly patients
Bibliographic record
Abstract
Objectives: This study examined levels of perceived stress (PS), postoperative delirium (POD) and associated factors among Thai elderly patients undergoing elective noncardiac surgery.Background and aims: Preoperative PS and change after operation have not been widely studied. Moreover, psychological factors associated with PS and POD has been poorly investigated.Materials and Methods: In total, 429 elderly patients were recruited at a university hospital. The preoperative evaluation included sociodemographic data, health behaviors at risk, Perceived Stress Scale (PSS-10), Neuroticism Inventory (NI), Mental State Examination T10 (MSET10), Montreal Cognitive Assessment (MoCA) and Geriatric Depression Scale (GDS-15). Three-day postoperative evaluation included PSS-10 and Confusion Assessment Method Algorithm (CAM) or CAM-ICU for Delirium. Multiple regression and logistic regression analysis were performed to determine potential predictors.Results: Females were 58.97%, and the mean age was 69.93 ± 6.87 years. Mean pre- and postoperative PS were 12.77 ± 5.41 and 13.39 ± 5.26, respectively (P < 0.05). Multiple regression revealed that neuroticism, depression, and BMI predicted PS significantly. None of the independent variables was found to predict postoperative PS except for preoperative PS (p <.001). POD at the recovery room was predicted by preoperative PS (odds ratio = 1.181, 95% CI = 1.019–1.369), whereas overall POD was predicted by MoCA (odds ratio = .864, 95% CI = .771 -.968).Conclusion: Preoperative PS was significant in that it was associated with postoperative PS and POD. A careful assessment of preoperative PS as well as providing brief interventions for patients with high levels of this condition may reduce the risk of POD.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 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".