Short‐Term Effects in the Treatment of Episiotomy Dehiscence in Physiotherapy: A Novel Approach in a Case Series Report
Bibliographic record
Abstract
ABSTRACT Background and Aims Dehiscence is defined as the appearance of a hole or gap between the sutured edges of the episiotomy of more than 0.5 cm. Episiotomy is a technique in which an incision is made in the perineum to reduce the incidence of severe perineal tears. The two most used are the midline in the USA and Canada and the postero‐lateral incision in Europe. In cases where the mother's BMI exceeds 35 kg/m 2 , the risk of infection and dehiscence increases. Reoperation is the usual choice and may be accompanied by other symptoms such as purulent discharge in 22.2%, perineal pain in 23.6% and 26.2% suffering from both. Radiofrequency and magnetotherapy are common treatments in physiotherapy that have been shown to have positive effects on tissue regeneration with indications for scarring processes. Methods/Results The following case series report proposes a detailed treatment protocol for episiotomy dehiscence with excellent results and no adverse effects in all cases. All patients had a 50% pain relief and total recovery in 1 week. Conclusions This is a novel treatment which needs future clinical trials to evaluate, analyze, and determine its effectiveness.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".