2025 iCatCare consensus guidelines on the diagnosis and management of lower urinary tract diseases in cats
Bibliographic record
Abstract
PRACTICAL RELEVANCE: Lower urinary tract signs (LUTS) such as dysuria, haematuria, periuria, pollakiuria and stranguria can occur as the result of a variety of underlying conditions and diagnostic investigation is required to uncover the underlying cause and select appropriate treatment. AIM: The '2025 iCatCare consensus guidelines on the diagnosis and management of lower urinary tract diseases in cats' provide an overview of the common presenting signs caused by underlying feline lower urinary tract (LUT) diseases in cats, which often are indistinguishable between different underlying causes. The Guidelines set out a diagnostic approach to affected cats before focusing on the most common causes of LUTS: feline idiopathic cystitis (FIC), urolithiasis, urinary tract infection and urethral obstruction. The aim is to provide practitioners with practical information on these problematic conditions. CLINICAL CHALLENGES: The fact that LUTS are similar despite different underlying causes creates a diagnostic challenge. The most common cause of LUTS, FIC, is challenging to manage due to a complex pathogenesis involving organs outside the LUT. Urethral obstruction is a life-threatening complication of various underlying LUT diseases and recurrent LUTS can lead to relinquishment or euthanasia of affected cats. EVIDENCE BASE: These Guidelines have been created by a panel of experts brought together by International Cat Care (iCatCare) Veterinary Society (formerly the International Society of Feline Medicine [ISFM]). Information is based on the available literature, expert opinion and the panel members' experience.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.011 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.012 |
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".