Primary Repair of Facial Dog Bite Injuries in Children
Bibliographic record
Abstract
OBJECTIVES: The management of dog bite wounds is controversial, and current data on risk of infection are variable and inconsistent. Furthermore, the use of prophylactic or empiric antibiotics for the treatment of these wounds is debatable. We investigate the rate of wound infections and other complications after primary repair of pediatric facial dog bite injuries. METHODS: We reviewed 87 consecutive patients aged 18 years or younger who had facial dog bite injuries from January 2003 to December 2008. Variables examined were age, sex, setting of repair, number of sutures used for repair, whether surgical drains were used, and antibiotic administration. End points measured were incidence of wound infection, need for scar revision, and any wound complications. RESULTS: The mean age of patients was 6.8 years, and the majority were women (53%). All facial injuries were primarily repaired at the time of presentation either in the emergency department (ED; 46%), operating room (OR; 51%), or an outpatient setting (3%). All patients received an antibiotic course, none of the patients developed wound infection, and no subsequent scar revisions were performed. Three patients repaired in the OR underwent placement of a total of 4 closed-suction drains. The mean (SD) age of patients repaired in the OR was significantly younger than those repaired in the ED (5.7 [3.9] vs 8.0 [4.5] years, respectively; P < 0.01). The number of sutures used were greater for patients repaired in the OR than in the ED (66.4 [39.6] vs 21.7 [12.5], respectively; P < 0.01). CONCLUSIONS: Intuitively, younger patients and patients with greater severity injuries are more likely to undergo repair in the OR, and this was supported by our data. Overall, we found that primary repair of pediatric facial dog bite injuries, including complex soft-tissue injuries, is safe when performed in conjunction with antibiotic administration; however, further cross-specialty studies are needed to fully characterize these end points in a larger population.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".