Antibiotic prophylaxis in transurethral resection of bladder tumours: study protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background The necessity of antibiotic prophylaxis for postoperative urinary tract infections (UTIs) after transurethral resection of bladder tumours is controversial. This potentially leads to the overuse of antibiotic prophylaxis and rising antimicrobial resistance rates. The objective of this systematic review and meta-analysis is to compare the impact of different antimicrobial prophylaxis schemes versus placebo on the prevention of postoperative UTI and asymptomatic bacteriuria. Methods We designed and registered a study protocol for a systematic review and meta-analysis of randomized controlled trials and non-randomized (e.g. cohort, case-control) studies examining any form of antibiotic prophylaxis in patients with transurethral resection of bladder tumours. Literature searches will be conducted in several electronic databases (from inception onwards), including MEDLINE (Ovid), EMBASE (Ovid), and the Cochrane Central Register of Controlled Trials (CENTRAL). Grey literature will be identified through searching conference abstracts. The primary outcome will be postoperative urinary tract infections. The secondary outcome will be asymptomatic bacteriuria. Two reviewers will independently screen all citations, full-text articles, and abstract data. Potential conflicts will be resolved through discussion. The study methodological quality (or bias) will be appraised using appropriate tools (e.g. Risk of Bias 2.0 tool and Newcastle-Ottawa Scale). If feasible, we will conduct random-effects meta-analysis of outcome data. Additional analyses will be conducted to explore the potential sources of heterogeneity (e.g. study design, publication year, the setting of the study, and antibiotics regimen). We will also search, identify, and discuss potential risk factors for urinary tract infections following transurethral resection of bladder tumours. This may serve as basis for a scoping review. Discussion In times of rising antimicrobial resistance rates, sound evidence on the necessity of antibiotic prophylaxis is essential for implementation into guideline recommendations and for decision-making in clinical practice. Systematic review registration PROSPERO, CRD42019131733
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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 | 0.053 | 0.093 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.024 | 0.029 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.049 | 0.005 |
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".