Northeastern Section of the American Urological Association 64(th) Annual Meeting, Niagara Falls, Ontario Scientific Program.
Bibliographic record
Abstract
BACKGROUND: : Infections following prostate biopsy can be associated with significant morbidity and occasional mortality. Studies have suggested an increased incidence in post-biopsy sepsis. The purpose of this study was to determine the effect of a bacteria sensitivity adapted antimicrobial prophylactic strategy on the incidence of sepsis post prostate biopsy. METHODS: : In October 2008, based on the prevalence of ciprofloxacin-resistant E.coli in the region, our institution modified the prophylactic regimen for prostate biopsy from oral ciprofloxacin alone to a combination of single-dose ciprofloxacin and trimethoprim/sulfamethoxazole. If patients had a history of urosepsis, bacterial prostatitis, organ transplant, or fluoroquinolone use in the preceding 12 months, intramuscular ceftriaxone was administered for prophylaxis. Patients with penicillin allergy received gentamicin. We determined the incidence of ciprofloxacin-resistant bacteremia 16 months before and 16 months after the change in antibiotic protocol. RESULTS: : Between June 2007 and September 2008, 9 of 847 (1.06%) patients were admitted with prostate biopsy induced bacteremia secondary to ciprofloxacin-resistant E. coli. In the 16 months following introduction of the described prophylactic regimen, 1 of 989 (0.10%) patients suffered ciprofloxacin-resistant sepsis. The absolute reduction in E. coli sepsis was 0.96% (95%CI 0.2% to 1.7%; p=0.007). The number needed to treat is 104. CONCLUSIONS: : Bacterial susceptibility to antimicrobial agents is in evolution. Using a regional bacteria sensitivity based approach to biopsy prophylaxis, we have significantly decreased ciprofloxacin-resistant E. coli sepsis in our patients. Regional bacteria sensitivity based protocols may decrease the incidence at other centers and warrants further study.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.313 | 0.073 |
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".