Study of Factors Associated with Postoperative Pain Following Episiotomy in Primiparous Women at Mashhad Omalbanin Hospital in 2012
Bibliographic record
Abstract
Background & aim: Episiotomy is a common medical procedure for widening the perineum. In fact, perineal pain is the most common complaint after episiotomy. Therefore, it is important to determine factors associated with postoperative pain following episiotomy in order to provide comfort for women after delivery. This study aimed to investigate factors associated with postoperative pain following episiotomy in primiparous women. Methods:This analytical, descriptive study was conducted on 119 eligible mothers, selected via convenience sampling, referring to Mashhad Omolbanin Hospital. Childbirth-related information was collected using a questionnaire. Neonates and mothers were also evaluated using Redness, Edema, Ecchymosis, Discharge, and Approximation (REEDA) scale and McGill Pain Questionnaire for perineal pain on days 1, 7, 10, and 14after delivery. Kolmogorov-Smirnov, one-way ANOVA, Spearman’s test, and Pearson’s correlation were performed, using SPSS version 16. P-value ≤ 0.05 was considered statistically significant. Results: A significant direct relationship was found between the severity of episiotomy pain on day 7 and length of wound cut (P=0.034), neonatal weight (P=0.040), and number of sutures (P=0.028). There was also a significant relationship between the severity of episiotomy pain on day 10 and the duration of active phase during the second stage of labor (P=0.047), duration of sitting position (P=0.011), and number of sutures (P=0.020). However, a reverse significant correlation was found between the severity of postoperative pain following episiotomy and wound recovery on days 7 (P=0.015) and 10 (P=0.035). Conclusion: Perineal pain was related to factors such as long perineal cut, slow wound recovery, prolonged active phase in the second stage of labor, neonatal overweight, and mother’s prolonged sitting position. Therefore, it is recommended to train health care providers and mothers about these factors.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".