Efficacy and safety of umbilical cord mesenchymal stem cells in treatment of cesarean section skin scars: a randomized clinical trial
Bibliographic record
Abstract
BACKGROUND: Pathological skin scars, caused by cesarean section, affected younger mothers esthetically and psychosocially and to some extent frustrated obstetricians and dermatologists. Umbilical cord mesenchymal stem cells (UC-MSCs), as a population of multipotent cells, are abundant in human tissues, providing several possibilities for their effects on skin scar tissues. Herein, we performed a randomized, double-blind, placebo-controlled, three-arm clinical trial, aiming to assess the efficacy and safety of UC-MSCs in the treatment of cesarean section skin scars among primiparous singleton pregnant women. METHODS: cells) transdermal hydrogel UC-MSCs on the surface of the skin incision. The primary outcome was cesarean section skin scars followed after the sixth month, assessed by the Vancouver Scar Scale (VSS). RESULTS: All the participants completed their trial of the primary outcome according to the protocol. The mean score of estimated total VSS was 5.52 in all participants at the sixth-month follow-up, with 6.43 in the placebo group, 5.18 in the low-dose group, and 4.71 in the high-dose group, respectively. No significant difference was found between-group in the mean scores for VSS at the sixth month. Additional prespecified secondary outcomes were not found with significant differences among groups either. No obvious side effects or adverse effects were reported in any of the three arms. CONCLUSION: This randomized clinical trial showed that UC-MSCs did not demonstrate the effects of improvement of cesarean section skin scars. TRIAL REGISTRATION: ClinicalTrials.gov identifier, NCT02772289. Registered on 13 May 2016.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".