Comparison of tissue adhesive (N-butyl-2-cyanoacrylate) versus conventional suturing in umbilical hernia surgeries
Bibliographic record
Abstract
Background: Umbilical hernia is a common problem encountered mostly in women. Conventional suturing is used as a traditional method for closure of skin in umbilical hernia surgeries. N-butyl-2-cyanoacrylate glue can be used as an alternative where tissue loss is minimal, minimal scarring, no significant bacterial infection and less postoperative pain. The aim of this study was to determine the effectiveness of tissue adhesive in the closure of umbilical skin incisions compared to conventional sutures.Methods: A prospective study was conducted including 30 patients with umbilical hernia. Patients were allocated into two groups using odd and even method: group A and B. Patients of group A underwent skin closure with topical tissue adhesive and that of group B underwent skin closure with conventional sutures. Skin closure time, postoperative pain, scar assessment using Vancouver scar scale and surgical site infection were recorded. IBS-statistical package for the social sciences (SPSS) 22 version was used to analyse the data.Results: 57% females and 43% males were included in the study. The age of the patients ranged between 18 and 60 years in both the groups. All patients had chief complaint of swelling in the umbilical area. Group A (tissue adhesive) patients had lesser skin closure time and cosmetically better scar than group B (conventional suturing) patients. Surgical site infection was seen in 2 patients in group B and 1 patient in group A.Conclusions: Tissue adhesive is superior as compared to conventional suture in terms of skin closure time, cosmesis, postoperative pain and postoperative surgical complications.
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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 | 0.000 |
| 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 | 0.000 |
| 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".