Anxiety and depression in non-cardiac surgical patients and associations with adverse outcomes: A systematic review and meta-analysis
Bibliographic record
Abstract
Background: Mental health disorders such as anxiety and depression are associated with advanced disease at presentation, reduced treatment uptake, and worse postoperative outcomes. Despite this, preoperative screening remains underutilized. This systematic review and meta-analysis aimed to characterize the prevalence of preoperative anxiety and depression in non-cardiac surgery patients and assess their associations with adverse postoperative outcomes. Methods: The protocol was registered with PROSPERO (CRD42024578357) and followed PRISMA guidelines. MEDLINE, Embase, PsycINFO, Cochrane Database of Systematic Reviews, and CENTRAL were searched. All studies included were prospective cohorts that enrolled a minimum of 100 adults undergoing non-cardiac surgery, used validated preoperative mental health screening tools, and reported postoperative outcomes. Studies involving cardiac, neurosurgical, or bariatric procedures were excluded. Random-effects meta-analysis generated pooled prevalence, mean difference (MD), and odds ratios (OR) with 95 % confidence intervals (CI) and 95 % prediction intervals (PI). Results: Forty-six studies (n = 23,628; mean age 58.5 ± 19.2 years; 61 % female) met inclusion criteria. Pooled prevalence of anxiety was 26 % (95 % CI, 21 %-31 %; 95 % PI, 20 %-33 %; I² = 95 %) while depression was 23 % (95 % CI, 14 %-31 %; 95 % PI, 14 %-36 %; I² = 100 %). The prevalence of anxiety ranged from 19 % in orthopedic to 29 % in cancer surgery. It was associated with a greater hospital length of stay (MD 0.55 days; 95 % CI, 0.29-0.82; 95 % PI, -0.04-1.14; I² = 0 %). The prevalence of depression ranged from 17 % in orthopedic to 30 % in cancer surgery and 24 % in mixed surgery. Preoperative depression was associated with increased odds of postoperative delirium (OR 2.33; 95 % CI, 1.74-3.11; 95 % PI, 1.5-3.5; I² = 0 %). Conclusions: Anxiety and depression affect one-fifth of non-cardiac surgical patients, with highest prevalence in cancer surgery. Preoperative anxiety was associated with a greater hospital length of stay, while preoperative depression was associated with twofold risk of postoperative delirium. Therefore, routine preoperative mental health screening could identify high-risk patients and enable targeted perioperative interventions to reduce adverse 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 | 0.012 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.040 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".