Contribution of preoperative and acute postoperative pain on the onset and intensity of chronic pain at three months following breast cancer surgery: A prospective cohort study
Bibliographic record
Abstract
Aim: The overall aim of this 3-month prospective cohort study was to determine the contribution of preoperative and acute postoperative pain on the onset and intensity of CPBCS following surgery, regardless of painful comorbidities, age, psychological factors, type of cancer, and breast cancer treatment. We also determined the contribution of preoperative pain on the onset and intensity of acute postoperative pain before transitioning into CPBCS.Methods: One hundred and sixty-two female participants, scheduled to undergo their first breast cancer surgery were recruited from the Jewish General Hospital, Montreal, Quebec. Data on preoperative pain and covariates, such as age, psychological factors, painful comorbidities, type of cancer and tumour size were collected before surgery. Telephone follow-up interviews were conducted at seven days and three months after surgery to assess acute pain and CPBCS, respectively, using a brief pain inventory scale. Intra and postoperative data on covariates such as the type of surgery, axillary status, infiltration, duration of surgery, radiotherapy, and chemotherapy were assessed from physicians' chart (Chart Maxx). Multivariable logistic and linear regression analyses were performed to determine the contribution of preoperative and acute postoperative pain on CPBCS risk and intensity, regardless of pre, intra, and postoperative covariates. In addition, the same analyses, as previously described, were performed to assess the contribution of preoperative pain on the onset and intensity of acute postoperative pain at seven days following surgery. Results: One hundred and thirty-eight participants completed the three months follow-up. The principal findings in the multivariable analysis showed that acute postoperative pain was positively associated with CPBCS risk (OR = 2.59, P< 0.05) and CPBCS intensity (β = 9.13, P< 0.05), adjusted for other covariates. In addition, preoperative pain intensity at baseline was related to acute pain risk (OR = 1.31, P< 0.05) and intensity (β = 5.47, P< 0.05), adjusted for other covariates. Predictors, such as depression and ALND, were positively related to the onset of CPBCS, whereas adjunctive therapies and depression were associated with CPBCS intensity. Moreover, young age, duration of surgery, invasiveness of cancer and surgery were positively related to the risk of acute pain at seven days following surgery. Conclusion: These results demonstrated that pre operative pain contributes to acute pain risk and severity, but not to CPBCS. Further, acute postoperative pain contributes to CPBCS risk and its intensity at three months following surgery. Such knowledge may result in designing more efficient and early interventions to prevent CPBCS.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".