The effects of perineal management techniques on labor complications.
Bibliographic record
Abstract
BACKGROUND: Many women suffer from perineal trauma during the normal vaginal delivery. Perineal trauma is mainly associated with pain and complications after the childbirth. Perineal management techniques can play a significant role in perineal trauma reduction. This study aimed to compare the effects of perineal management techniques (hands-off technique, Ritgen maneuver and perineal massage using a lubricant during delivery) on the labor complications. MATERIALS AND METHODS: This quasi-experimental clinical trial was conducted on 99 primiparous women who referred to Daran Hospital, Isfahan, Iran for normal vaginal delivery in 2009. The subjects were selected using a convenient method and randomly assigned to three groups of Ritgen maneuver, hands-off technique and perineal massage with lubricant. A questionnaire was used to determine the demographic characteristics of the participants and complications after birth. The short form of McGill Pain Questionnaire and the visual analogue scale for pain were also employed. The incidence and degree of perineal tears were evaluated immediately after delivery. Moreover, the incidence and severity of perineal pain were assessed 24 hours and also 6 weeks after delivery. FINDINGS: In the Ritgen maneuver group, the frequency of tears, the relative frequency of tear degrees, the severity of perineal pain 24 hours after delivery and the frequency of pain and perineal pain severity 6 weeks after delivery were significantly different from the other two methods. CONCLUSIONS: Hands-off technique during parturition of the neonate's head was associated with fewer complications after delivery. It was even better than perineal massage during the parturition.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".