Preoperative predictors of poor acute postoperative pain control: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVES: Inadequate postoperative pain control is common and is associated with poor clinical outcomes. This study aimed to identify preoperative predictors of poor postoperative pain control in adults undergoing inpatient surgery. DESIGN: Systematic review and meta-analysis DATA SOURCES: MEDLINE, Embase, CINAHL and PsycINFO were searched through October 2017. ELIGIBILITY CRITERIA: Studies in any language were included if they evaluated postoperative pain using a validated instrument in adults (≥18 years) and reported a measure of association between poor postoperative pain control (defined by study authors) and at least one preoperative predictor during the hospital stay. DATA EXTRACTION AND SYNTHESIS: Two reviewers screened articles, extracted data and assessed study quality. Measures of association for each preoperative predictor were pooled using random effects models. RESULTS: Thirty-three studies representing 53 362 patients were included in this review. Significant preoperative predictors of poor postoperative pain control included younger age (OR 1.18 [95% CI 1.05 to 1.32], number of studies, n=14), female sex (OR 1.29 [95% CI 1.17 to 1.43], n=20), smoking (OR 1.33 [95% CI 1.09 to 1.61], n=9), history of depressive symptoms (OR 1.71 [95% CI 1.32 to 2.22], n=8), history of anxiety symptoms (OR 1.22 [95% CI 1.09 to 1.36], n=10), sleep difficulties (OR 2.32 [95% CI 1.46 to 3.69], n=2), higher body mass index (OR 1.02 [95% CI 1.01 to 1.03], n=2), presence of preoperative pain (OR 1.21 [95% CI 1.10 to 1.32], n=13) and use of preoperative analgesia (OR 1.54 [95% CI 1.18 to 2.03], n=6). Pain catastrophising, American Society of Anesthesiologists status, chronic pain, marital status, socioeconomic status, education, surgical history, preoperative pressure pain tolerance and orthopaedic surgery (vs abdominal surgery) were not associated with increased odds of poor pain control. Study quality was generally high, although appropriate blinding of predictor during outcome ascertainment was often limited. CONCLUSIONS: Nine predictors of poor postoperative pain control were identified. These should be recognised as potentially important factors when developing discipline-specific clinical care pathways to improve pain outcomes and to guide future surgical pain research. PROSPERO REGISTRATION NUMBER: CRD42017080682.
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 | 0.015 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.037 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 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".