Clinical and Bacterial Risk Factors for Development of Post-Prostate Biopsy Infections.
Bibliographic record
Abstract
PURPOSE: To research on clinical and bacterial risk factors and their relationship with post-prostate biopsy infection (PBI). MATERIALS AND METHODS: In this prospective cohort study, rectal swabs were collected from 158 men prior to prostate biopsy and cultured selectively for identify ciprofloxacin-resistant (FQ-R) gram-negative bacteria. The patient characteristics, phylogenetic background, sequence typing and pulsed field gel electrophoresis (PFGE) pattern were compared in two groups of FQ-R E. coli rectal and clinical isolates. RESULTS: In total, PBI was observed in 20 (12.5%) cases; the most of these subjects were FQ-R-colonized. (17/73 [24%] vs 3/85 [3.5%]; P < 0.001). FQ-R colonization, diabetes, hospitalization and UTI were independent risk factors (95% CI: 1.1-20.1, OR = 4.73; 95% CI: 1.7-25.3, OR = 6.57; 95% CI: 1.9-27.5, OR = 7.22; and 95% CI: 1.2-14.3, OR = 4.05; respectively), that increased the rate of PBI (All P < 0.05). Despite the increase in infections among patients colonized with strains of E. coli ST131, its prevalence was near significance between colonized and infected groups (P = 0.07). The PFGE patterns and antimicrobial susceptibility profiles of rectal and clinical isolates in 13 patients were similar which is remarkably important and informative. CONCLUSIONS: The most PBIs originate from FQ-R E. coli rectal colonization. Rectal culture screening and assessment of clinical risk factors can predict the incidence of PBI in patients.
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".