65 Conservative Management of Wound Dehiscence Following Inguinal Lymph Node Dissection Using Topical Metronidazole Gel Compared to Simple Wound Packing - a Cohort Study
Bibliographic record
Abstract
Abstract Aim The aim of this study is to determine the effect of simple packing against topical metronidazole in the management of wound dehiscence following inguinal lymph node dissection. Method This is a retrospective cohort study of all adult patients who underwent groin dissection between 2014 and 2020 at the Queen Elizabeth Hospital Birmingham. Patients who had flaps or grafts for wound closure, and those with incomplete follow up records were excluded. Patients who developed wound dehiscence were treated with either topical metronidazole or simple packing and were followed up regularly by specialist wound care nurses. Data was collected from electronic medical records from the date of procedure to the latest follow up and analysed in SPSS. The two groups were compared for the time taken for the wound to heal in days as the primary outcome. Results From the 157 patients that had groin dissection, 76 (48.4%) developed wound dehiscence. Eight of them were still unhealed at the time of data collection. Among the 68 healed patients, 32 (47%) had been treated with metronidazole-soaked packing, and 44 (53%) had received packing without metronidazole. The two groups were comparable in terms of age, sex, indication for groin dissection and wound size. The mean time to healing for patients treated with topical metronidazole was 63.7±40 days, compared to 45 ±24.7 days in the non-metronidazole group. The difference is significant with a p value of 0.02. Conclusions Simple packing of dehisced wounds following groin dissection leads to significantly shorter healing times compared to topical metronidazole.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".