A contemporary review about the management of radiation-induced hemorrhagic cystitis
Bibliographic record
Abstract
PURPOSE OF REVIEW: There are various specific therapeutic intervention available to treat hemorrhagic cystitis, once emergency treatment has been carried out. The lack of prospective studies, because of the relative rarity of this condition, makes it difficult to hierarchize the therapeutic sequence. The present review presents and summarizes the literature published on radiation-induced hemorrhagic cystitis from April 2015, date of a precedent exhaustive review, to March 2018. RECENT FINDINGS: During our period of interest, 13 clinical studies and two new clinical trials protocols were published. Most of the clinical studies were retrospective and presented data about hyperbaric oxygen (HBO) therapy, comforting its place as a well tolerated and effective first-line treatment. Other studies reported the outcomes of treatments with alum, formalin, silver nitrate, fulguration with laser or definitive surgery. SUMMARY: Although authors seem to agree that formalin and surgery have their role as effective but potentially morbid last-line treatments, there is no consensus on primary approach to management of radiation-induced hemorrhagic cystitis beyond symptomatic measures. Several treatments have proven excellent response rates and few side effects. The results of on-going prospective studies on mesenchymal stromal cells or tacrolimus instillations are awaited, but the main discriminating factor to choose between treatments remains local availability.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".