Prospective Surgical Site Infection Surveillance in Dogs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To 1) describe the incidence of surgical site infections (SSI) in dogs undergoing surgery at the Ontario Veterinary College Health Sciences Centre; 2) describe and compare procedure-specific SSI rates; and 3) identify factors associated with development of SSI. STUDY DESIGN: Prospective, cohort study ANIMALS: Dogs (n = 846) undergoing surgery during 45 weeks (September 2010-July 2011). METHODS: Follow-up telephone conversation with dog owners was performed 30 days postoperatively, with additional 1-year follow-up performed for cases with surgical implants. A standardized questionnaire was administered to detect and characterize SSI. RESULTS: SSI were identified in 26 (3.0%) dogs; 11 (42%) were classified as superficial SSI, whereas 13 were deep, and 2 were organ/space. Of the confirmed SSI, only 17 (65%) were documented in the medical records. Hypotension (P = .011), class of surgery (P = .029), and use of an implant (P = .001) increased the risk of SSI. Microbial cultures were submitted for 19 cases (73%) and of those, 74% were staphylococci. CONCLUSIONS: SSI can result in devastating consequences in dogs and understanding risk factors is critical to target prevention practices. Whereas some risk factors such as hypotension are modifiable, others such as class of surgery are not. When possible, active surveillance should be used as part of a hospital infection control program.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it