A prospective cohort study of chronic postsurgical pain after ambulatory surgeries
Bibliographic record
Abstract
OBJECTIVE: The incidence and factors associated with chronic postsurgical pain (CPSP) after ambulatory surgeries have not been well studied. Our primary objective was to determine the incidence of CPSP and secondary objectives included assessment of intensity of CPSP, incidence of moderate-to-severe CPSP, and exploration of factors associated with CPSP. METHODS: This is a prospective cohort study of ambulatory surgery patients having procedures with a potential to cause moderate-to-severe postoperative pain. All patients had participated in a randomized controlled trial (RCT) showing no difference in achieving satisfactory analgesia in a recovery unit with either morphine or hydromorphone. CPSP was defined as chronic pain that developed or increased in intensity after the surgical procedure and is localized to the surgical field or within the innervation territory of a nerve in the surgical field, and has persisted for 3 months post-surgery, with the exclusion of other causes of pain. Incidences of CPSP were reported as rate (%) with 95% CI, and intensity using a 0-10 numerical rating scale (95% CI). We used logistic regression to explore factors associated with CPSP adjusting for baseline catastrophizing and depression. RESULTS: Among 402 RCT patients, 208 provided data for the 3-month outcome. Incidence of CPSP was 18.8% (39/208), 95% CI = 13.7%-24.7% and 78% (28/39) of them had moderate-to-severe CPSP. Average CPSP intensity was 5.5, 95% CI = 4.7-6.4. Every unit increase in pain over the first 24 h was significantly associated with increased odds of moderate-to-severe CPSP at 3 months; odds ratio = 1.28, 95% CI = 1.04-1.58. CONCLUSIONS: Nearly one in five patients develop CPSP after ambulatory surgeries with the majority of them having moderate-to-severe pain. Considering that acute pain after discharge is associated with CPSP and that there are no formal care pathways to address this need, studies need to focus on evaluating feasible strategies to provide continuing care.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".