Perineal Assessment and Repair Longitudinal Study (PEARLS): a matched-pair cluster randomized trial
Bibliographic record
Abstract
BACKGROUND: Perineal trauma during childbirth affects millions of women worldwide every year. The aim of the Perineal Assessment and Repair Longitudinal Study (PEARLS) was to improve maternal clinical outcomes following childbirth through an enhanced cascaded multiprofessional training program to support implementation of evidence-based perineal management. METHODS: This was a pragmatic matched-pair cluster randomized controlled trial (RCT) that enrolled women (n = 3681) sustaining a second-degree perineal tear in one of 22 UK maternity units (clusters), organized in 11 matched pairs. Units in each matched pair were randomized to receive the training intervention either early (group A) or late (group B). Outcomes within each cluster were assessed prior to any training intervention (phase 1), and then after the training intervention was given to group A (phase 2) and group B (phase 3). Focusing on phase 2, the primary outcome was the percentage of women who had pain on sitting or walking at 10 to 12 days post-natal. Secondary outcomes included use of pain relief at 10 to 12 days post-natal, need for suture removal, uptake and duration of exclusive breastfeeding, and perineal wound infection. Practice-based measures included implementation of evidence into practice to promote effective clinical management of perineal trauma. Cluster-level paired t-tests were used to compare groups A and B. RESULTS: There was no significant difference between the clusters in phase 2 of the study in the average percentage of women reporting perineal pain on sitting and walking at 10 to 12 days (mean difference 0.7%; 95% CI -10.1% to 11.4%; P = 0.89). The intervention significantly improved overall use of evidence-based practice in the clinical management of perineal trauma. Following the training intervention, group A clusters had a significant reduction in mean percentages of women reporting perineal wound infections and of women needing sutures removed. CONCLUSION: PEARLS is the first RCT to assess the effects of a 'training package on implementation of evidence-based perineal trauma management. The intervention did not significantly improve the primary outcome but did significantly improve evidence-based practice and some of the relevant secondary clinical outcomes for women. TRIAL REGISTRATIONS: ISRCTN28960026 NIHR UKCRN portfolio no: 4785.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".