Immediate versus delayed closure of facial dog-bite wounds: Retrospective analysis and nursing care experience
Bibliographic record
Abstract
Facial dog-bite injuries present a complex surgical challenge, balancing infection prevention with optimal cosmetic outcomes. While delayed primary closure (DPC) has traditionally been preferred to mitigate infection risk, immediate primary closure (IPC) may enhance healing and aesthetic results. However, IPC remains underutilized due to concerns about surgical site infection (SSI), particularly in contaminated wounds. A retrospective cohort study was conducted at a tertiary center in Western China from 2020 to 2024. A total of 212 patients presenting within 24 hours of facial dog-bite injury were included. Patients received either IPC (n = 120) or DPC (n = 92) following standardized debridement and antibiotic protocols. The primary outcome was SSI within 7 days. Secondary outcomes included time to epithelialization, scar quality at 3 months, and pain scores. Multivariate logistic regression was used to identify independent predictors of infection. The overall SSI rate was 12.7%, with no significant difference between IPC (12.5%) and DPC (13.0%) groups (P = .92). Multivariate analysis identified wound area as the sole independent predictor of SSI (odds ratio 1.53 per cm2; P = .005). IPC was associated with faster epithelialization (median 18 vs 20 days; P = .02) and superior cosmetic outcomes, with lower Vancouver scar scale and higher modified Stony Brook scar evaluation scale scores at 3 months (P < .001). IPC of facial dog-bite wounds, when performed with rigorous debridement and structured nursing care, is safe and yields better cosmetic outcomes than DPC. Wound size should guide closure decisions and infection risk stratification.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".