Assessment of laboratory and biosafety practices associated with bacterial culture in veterinary clinics
Bibliographic record
Abstract
OBJECTIVE: To investigate bacterial culture practices in veterinary clinics, with an emphasis on laboratory biosafety and on quality of laboratory practices. DESIGN: Survey-based prospective study. SAMPLE POPULATION: 166 veterinarians. PROCEDURES: Veterinarians were recruited through the Veterinary Information Network (an Internet-based network restricted to veterinary personnel). All Network-registered veterinarians were eligible to participate. A standardized questionnaire regarding bacterial culture practices in veterinary clinics was completed electronically by study participants. RESULTS: 720 veterinarians completed the survey; 166 (23%) indicated that bacterial culture was performed in his or her clinic. Clinic practices ranged from preliminary aerobic bacterial culture only with submission of isolates to a diagnostic laboratory for further testing (93/160 [58%]) to bacterial culture, identification, and antimicrobial susceptibility testing (19/160 [12%]). Most commonly, urine samples were cultured (151/162 [93%] clinics). Several problematic practices were identified regarding quality and quality control, including inadequate facilities, equipment, supervision, interpretation of data, and culture methods. Biosafety infractions were also common, including inadequate laboratory location, lack of biosafety protocols, and dangerous disposal practices. Ninety-four percent of respondents stated that continuing education regarding culture practices and laboratory safety would be useful. CONCLUSIONS AND CLINICAL RELEVANCE: Data confirmed that bacterial culture was commonly performed in clinics, but that major deficiencies in laboratory methods were widespread. These could result in negative effects on testing quality and increased risk of laboratory-acquired infections among clinic personnel. Veterinary practices in which bacterial cultures are performed must ensure that adequate equipment, facilities, personnel, and training are provided to enable accurate and safe sample testing.
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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 | 0.006 | 0.041 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".