Psychological Distress After Inpatient Noncardiac Surgery
Bibliographic record
Abstract
OBJECTIVE: To describe the incidence and natural progression of psychological distress after major surgery. BACKGROUND: The recovery process after surgery imposes physical and mental burdens that put patients at risk of psychological distress. Understanding the natural course of psychological distress after surgery is critical to supporting the timely and tailored management of high-risk individuals. METHODS: We conducted a secondary analysis of the "Measurement of Exercise Tolerance before Surgery" multicentre cohort study (Canada, Australia, New Zealand, and the UK). Measurement of Exercise Tolerance before Surgery recruited adult participants (≥40 years) undergoing elective inpatient noncardiac surgery and followed them for 1 year. The primary outcome was the severity of psychological distress measured using the anxiety-depression item of EQ-5D-3L. We used cumulative link mixed models to characterize the time trajectory of psychological distress among relevant patient subgroups. We also explored potential predictors of severe and/or worsened psychological distress at 1 year using multivariable logistic regression models. RESULTS: Of 1546 participants, moderate-to-severe psychological distress was reported by 32.6% of participants before surgery, 27.3% at 30 days after surgery, and 26.2% at 1 year after surgery. Psychological distress appeared to improve over time among females [odds ratio (OR): 0.80, 95% CI: 0.65-0.95] and patients undergoing orthopedic procedures (OR: 0.73, 95% CI: 0.55-0.91), but not among males (OR: 0.87, 95% CI: 0.87-1.07) or patients undergoing nonorthopedic procedures (OR: 0.95, 95% CI: 0.87-1.04). Among the average middle-aged adult, there were no time-related changes (OR: 0.94, 97% CI: 0.75-1.13), whereas the young-old (OR: 0.89, 95% CI: 0.79-0.99) and middle-old (OR: 0.87, 95% CI: 0.73-1.01) had small improvements. Predictors of severe and/or worsened psychological distress at 1 year were younger age, poor self-reported functional capacity, smoking history, and undergoing open surgery. CONCLUSIONS: One-third of adults experience moderate to severe psychological distress before major elective noncardiac surgery. This distress tends to persist or worsen over time among select patient subgroups.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".