Comparison of three different antibiotic protocols in transurethral resection of bladder tumour and the possible infectious risk factors: A non-randomized, prospective study
Bibliographic record
Abstract
INTRODUCTION: We sought to investigate three different antibiotic protocols in transurethral resection of a bladder tumour (TURBT), and the possible infectious risk factors of this surgery. METHODS: We conducted a non-randomized, prospective study, gathering cases of patients in whom TURBT had been performed. The sample was divided into three groups based on those who received antibiotics as: a single preoperative dose (Group A); a preoperative dose, plus a long protocol during the hospitalization (Group B); a preoperative dose, plus a long protocol during the hospitalization, plus five days at home (Group C). Intra- and postoperative data that could be relevant to infections was gathered. RESULTS: A total of 219 patients were included. In the multivariate analysis, it was observed that the patients in Group A were more prone to re-hospitalization due to fever than were those from Group C (odds ratio [OR] 11.13; p=0.03). Furthermore, the cases with tumour necrosis and those who entered surgery with a urinary catheter were more prone to have a temperature above 37.5°C (OR6.74; p=0.02 and OR6.4; p=0.04, respectively), as well as have an increased risk per every additional tumour in the cystoscopy (OR 1.32; p=0.01). Those who received mitomycin had a lower chance of a positive urine culture (OR 0.29; p=0.01), contrary to those patients with over two days of hospitalization (OR 4.11; p<0.01) and those who entered surgery with a urinary catheter (OR 12.35; p=0.02). CONCLUSIONS: Those patients that only received a single dose of antibiotic before TURBT may have an increased risk of re-hospitalization due to fever in comparison to those who received prolonged antibiotic protocols. In addition, there are perioperative factors in this surgery that predict the risk of infectious complications.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".