Updates to Microhematuria: AUA/SUFU Guideline (2025)
Bibliographic record
Abstract
PURPOSE: In 2023 the AUA in collaboration with the Society for Urodynamics, Female Pelvic Medicine & Urogenital Reconstruction (SUFU) requested an Update Literature Review to incorporate new evidence generated since the 2020 publication of this Guideline. The resulting 2025 Microhematuria Guideline Amendment addresses updated recommendations to provide a clinical framework for the diagnosis, evaluation, and follow-up of microhematuria. MATERIALS AND METHODS: In 2024, this Guideline was reviewed via the AUA Update Literature Review process, which identified 82 studies for full-text review that were published between December 2019 and June 7, 2024. Of those 82 studies, 23 met inclusion criteria for qualitative synthesis. The subsequent amendment is based on data released since the initial 2020 publication of this Guideline. RESULTS: The Panel developed evidence- and consensus-based statements based on an updated review to provide guidance on evaluation and management of microhematuria. These updates are detailed herein. CONCLUSIONS: This update provides several new insights, including a revised risk stratification system, updated information regarding use of urine-based tumor markers and cytology, and new guidance on diagnosis and surveillance. This Guideline will require further review as the diagnostic and treatment options in this space continue to evolve.
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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 | 0.011 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".