International collaborative study to assess cardiovascular risk and evaluate long-term health in cats with preclinical hypertrophic cardiomyopathy and apparently healthy cats: The REVEAL Study
Bibliographic record
Abstract
BACKGROUND: Hypertrophic cardiomyopathy is the most prevalent heart disorder in cats and principal cause of cardiovascular morbidity and mortality. Yet, the impact of preclinical disease is unresolved. HYPOTHESIS/OBJECTIVES: Observational study to characterize cardiovascular morbidity and survival in cats with preclinical nonobstructive (HCM) and obstructive (HOCM) hypertrophic cardiomyopathy and in apparently healthy cats (AH). ANIMALS: One thousand seven hundred and thirty client-owned cats (430 preclinical HCM; 578 preclinical HOCM; 722 AH). METHODS: Retrospective multicenter, longitudinal, cohort study. Cats from 21 countries were followed through medical record review and owner or referring veterinarian interviews. Data were analyzed to compare long-term outcomes, incidence, and risk for congestive heart failure (CHF), arterial thromboembolism (ATE), and cardiovascular death. RESULTS: During the study period, CHF, ATE, or both occurred in 30.5% and cardiovascular death in 27.9% of 1008 HCM/HOCM cats. Risk assessed at 1, 5, and 10 years after study entry was 7.0%/3.5%, 19.9%/9.7%, and 23.9%/11.3% for CHF/ATE, and 6.7%, 22.8%, and 28.3% for cardiovascular death, respectively. There were no statistically significant differences between HOCM compared with HCM for cardiovascular morbidity or mortality, time from diagnosis to development of morbidity, or cardiovascular survival. Cats that developed cardiovascular morbidity had short survival (mean ± standard deviation, 1.3 ± 1.7 years). Overall, prolonged longevity was recorded in a minority of preclinical HCM/HOCM cats with 10% reaching 9-15 years. CONCLUSIONS AND CLINICAL IMPORTANCE: Preclinical HCM/HOCM is a global health problem of cats that carries substantial risk for CHF, ATE, and cardiovascular death. This finding underscores the need to identify therapies and monitoring strategies that decrease morbidity and mortality.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".