Pain after cesarean section: do we have reliable predictors? Scoping review
Bibliographic record
Abstract
BACKGROUND: Every year, the number of publications devoted to the study of various tools for predicting the intensity of pain after cesarean section is growing, which necessitated the generalization and systematization of these data. OBJECTIVE: Our aim was to identify factors contributing to high-intensity pain after cesarean section (CS). MATERIALS AND METHODS: a scoping review based on the PRISMA for Scoping Reviews (PRISMA-ScR) guidelines was conducted using PubMed, Cochrane Database of Systematic Reviews, and Google Scholar. The search was performed using the following keywords: “predictors” OR “prediction” OR “forecasting” AND “cesarean section” AND “pain”) in Russian and English, last search date November 30, 2022. The inclusion criteria for the review were formulated using the PICOD method: (P) population: postpartum women; (I) intervention: CS surgery; (C) comparison: surgical approach, anesthesia method, psychological status, pain threshold, genetic characteristics; (O) outcomes: pain intensity scores, analgesic requirements; (D) study design: prospective/retrospective cohort studies. Exclusion criteria were as follows: lack of sufficient data or outcome of interest; duplicate publication; chronic pain; publications devoted to pain relief during childbirth or pain after other surgical interventions; lack of full-text version; reviews and meta-analyses. The quality of selected non-randomized cohort studies was assessed using the Newcastle-Ottawa Scale (NOS). RESULTS: 30 cohort studies were selected, involving 11,063 patients. Most studies were assigned an NOS score of 6 to 8, which was considered good quality. Two groups of factors were identified as predictors of the intensity of postoperative pain: factors associated with the characteristics of the patient (physical status, psychological status, individual pain threshold and pain tolerance, genetic characteristics) and factors associated with the characteristics of the operation and anesthesia. CONCLUSION: the scoping review allowed us to identify reliable factors predicting high-intensity pain after CS, which should be taken into account when planning anesthesiological care for patients.
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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 | 0.031 | 0.235 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.022 | 0.024 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".