Best practice policy statement on urodynamic antibiotic prophylaxis in the non‐index patient
Bibliographic record
Abstract
AIMS: Antibiotic prophylaxis before urodynamic testing (UDS) is widely utilized to prevent urinary tract infection (UTI) with only limited guidance. The Society of Urodynamics, Female Pelvic Medicine, and Urogenital Reconstruction (SUFU) convened a Best Practice Policy Panel to formulate recommendations on the urodynamic antibiotic prophylaxis in the non-index patient. METHODS: Recommendations are based on a literature review and the Panel's expert opinion, with all recommendations graded using the Oxford grading system. RESULTS: All patients should be screened for symptoms of UTI and undergo dipstick urinalysis. If the clinician suspects a UTI, the UDS should be postponed until it has been treated. The first choice for prophylaxis is a single oral dose of trimethoprim-sulfamethoxazole before UDS, with alternative antibiotics chosen in case of allergy or intolerance. Individuals who do NOT require routine antibiotic prophylaxis include those without known relevant genitourinary anomalies, diabetics, those with prior genitourinary surgery, a history of recurrent UTI, post-menopausal women, recently hospitalized patients, patients with cardiac valvular disease, nutritional deficiencies or obesity. Identified risk factors that increase the potential for UTI following UDS and for which the panel recommends peri-procedure antibiotics include: known relevant neurogenic lower urinary tract dysfunction, elevated PVR, asymptomatic bacteriuria, immunosuppression, age over 70, and patients with any indwelling catheter, external urinary collection device, or performing intermittent catheterization. Patients with orthopedic implants have a separate risk stratification. CONCLUSIONS: These recommendations can assist urodynamic providers in the appropriate use of antibiotics for UDS testing. Clinical judgment of the provider must always be considered.
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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 | 0.037 | 0.116 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.048 | 0.027 |
| Insufficient payload (model declined to judge) | 0.021 | 0.015 |
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".