Disparity between High Satisfaction and Severe Pain in Patients after Caesarean Section: A Prospective Observational-Controlled Investigation
Bibliographic record
Abstract
Objectives. Recent advances in the treatment of postoperative pain (POP) have increased the quality of life in surgical patients. The aim of this study was to examine the quality of POP management in patients after CS in comparison with patients after comparable surgical procedures. Methods. This was a prospective observational analysis in patients after CS in comparison with the patients of the same age, who underwent comparable abdominal gynaecological surgeries (GS group) at the university hospital. A standardised questionnaire including pain intensity on the Verbal Rating Scale (VRS-11), incidence of analgesia-related side effects, and incidence of pain interference with the items of quality of life and patients’ satisfaction with the treatment of POP was used. Results. Sixty-four patients after CS reported more pain on movement than the patients after GS ( N=63 ): mean 6.1 versus 3.6 (VRS-11; P<0.001 ). The patients after CS reported less nausea (8 versus 41%) and vomiting (3 versus 21%; P<0.001 ) and demonstrated better satisfaction with POP treatment than the patients after GS: 1.4 (0.7) versus 1.7 (0.7) (mean (SD); VRS-5; P=0.02 ). Conclusion. The disparity between the high level of pain and excellent satisfaction with POP treatment raises the ethical and biomedical considerations of restrictive pharmacological therapy of post-CS pain.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".