Suture Closure versus Non-Closure of Subcutaneous Fat and Cosmetic Outcome after Cesarean Section: A Randomized Controlled Trial
Bibliographic record
Abstract
INTRODUCTION: To investigate the effect of subcutaneous fat suture closure versus non-closure at cesarean section (CS) on long-term cosmetic outcome. MATERIAL AND METHODS: Women undergoing planned or unplanned CS were randomized to either subcutaneous fat suture closure or non-closure using a 1∶1 allocation algorithm. Participants and outcome assessors were blinded to group allocation. Scar evaluation was performed after two and six months. Primary outcome measures were Patient and Observer Scar Assessment Scale (POSAS) summary scores six months after surgery. Secondary outcome measures were Vancouver Scar Scale (VSS) summary scores, retraction of the scar below the level of the surrounding skin, duration of surgery, and development of hematoma, seroma, surgical site infection (SSI) or wound disruption. Data were analyzed according to the intention to treat principle. RESULTS: A total of 116 women were randomized and 91 participants, 47 in the closure and 44 in the non-closure group, completed the trial and were analyzed. There were no differences in patient morphometrics or surgery indications between groups. At two and six months no significant differences were found with respect to POSAS or VSS scores between groups. After two months significantly more women in the non-closure group described their scar as being retracted below the level of the skin (36% vs. 15%, p = 0.02) whereas no difference was observed at six months. There were significantly more hematomas in the non-closure (25%) compared to the closure group (4%) (p = 0.005). There was no difference in duration of surgery, SSI, seroma formation or wound disruption between groups. CONCLUSIONS: Suture closure of the subcutaneous fat at CS does not affect long-term cosmetic outcome. (Level I evidence). TRIAL REGISTRATION: ClinicalTrials.gov NCT01542346.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.009 | 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".