Risk factors for duration of equine rhinitis A virus respiratory disease
Bibliographic record
Abstract
BACKGROUND: Infectious respiratory disease is common in young horses and can impact athletic performance and long-term health. Significant variation in the duration of clinical disease has been observed, even in the absence of secondary complications. The determination of factors associated with disease chronicity may facilitate clinical decision-making and the development of improved biosecurity protocols. OBJECTIVE: To investigate contact network characteristics, and demographic variables associated with time to clinical recovery from Equine Rhinitis A virus respiratory disease. STUDY DESIGN: Prospective cohort study. METHODS: Yearling Standardbred racehorses (n = 58) housed in a multi-barn training facility in Southern Ontario were included. Horses were monitored daily for clinical signs of acute respiratory disease over a 41-day period in Autumn 2017. Contact patterns between horses, including older racehorses, were determined through use of proximity loggers attached to halters during the initial 7-day of the study. Associations between duration of disease, demographic factors (birth month, gait, sex and yearling sale), serologic titres and network metrics (degree, betweenness and Eigenvector centrality) were investigated using a Cox proportional hazard model. RESULTS: Yearling attack rate for infectious respiratory disease was 87.9% (n = 51). Median time to recovery was 6 days (IQR = 1-32) and 17 horses were censored due to early withdrawal or failure to recover during the study period. In those yearlings born February-May, birth month was significant in the Cox proportional hazard model (Hazard Ratio 0.7, 95% CI 0.49-1, P = 0.05). MAIN LIMITATION: Probability of censoring was not independent of outcome which necessitated use of sensitivity analysis. CONCLUSIONS: These findings suggest late born foals are less likely to recover quickly from infectious respiratory disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".