In Search of an Ideal Closure Method: A Randomized, Controlled Trial of Octyl-2-Cyanoacrylate and Adhesive Mesh versus Subcuticular Suture in Reduction Mammaplasty
Bibliographic record
Abstract
BACKGROUND: An ideal wound closure system is one that is effective, consistent, and efficient. Recent studies have demonstrated the efficacy of octyl-2-cyanoacrylate and mesh (Dermabond Prineo) in the closure of surgical wounds. This study compared the use of Prineo to use of subcuticular suture closure in reduction mammaplasty. METHODS: A prospective, randomized, controlled, single-blind study of patients undergoing bilateral reduction mammaplasty was performed. Each breast per patient was randomized to layered closure with Prineo or subcuticular sutures. Incisions were assessed at 2 weeks, 6 weeks, 6 months, and 1 year. Subjects completed the Patient and Observer Scar Assessment Scale for each breast, and two blinded plastic surgeons evaluated scar quality using the Vancouver Scar Scale at each time point. RESULTS: Twenty-one patients participated in the study. On average, Prineo closure took 58.38 seconds (2.50 seconds/cm) and subcuticular closure took 444.76 seconds (18.94 seconds/cm). Prineo closure was approximately 6.8 times faster (p < 0.001) than subcuticular closure, saving an average of 6.4 minutes per incision. Vancouver Scar Scale scores were significantly better in patients with Prineo closure at 2 weeks (p = 0.026), although there was no difference in Patient and Observer Scar Assessment Scale and Vancouver Scar Scale scores at all other time points. CONCLUSIONS: In reduction mammaplasty, Prineo closure results in similar scar quality and lower operative cost without increased complications when compared to subcuticular closure. Prineo is faster than subcuticular closure and represents an effective, consistent, and efficient alternative to subcuticular suture techniques. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, II.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".