Rodent models of ketamine‐induced cystitis
Bibliographic record
Abstract
AIMS: Long-term or recreational use of ketamine affects the urinary system and can result in ketamine-induced cystitis (KIC). Rodent models of KIC are important to study KIC pathophysiology and are paramount to the future development of therapies for this painful condition. This review aims to provide a summary of rodent models of KIC, focusing on disease induction, experimental methods, and pathological features of the model. METHOD: A literature search was performed using the National Center for Biotechnology Information (NCBI) Pubmed database up to March 2021. 20 articles met the inclusion criteria and were finally selected. RESULTS: There are considerable variations in the rodent models used for studying KIC in terms of the strain of the animal being used; dose, duration, and route of ketamine administration to induce KIC, and assessment of pathological features. CONCLUSION: KIC remains difficult to fully recapitulate in humans. Improved characterization of KIC models and the experimental parameters and meticulous discussion on translational limitations are required to improve the translational value of research using rodent models of KIC.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".