Tracheobronchoscopic Assessment of Exercise-Induced Pulmonary Hemorrhage and Airway Inflammation in Barrel Racing Horses
Bibliographic record
Abstract
BACKGROUND: Poor performance is often suspected to be associated with EIPH in barrel racing horses; however, there are no published reports of EIPH for this discipline. The prevalence of EIPH in barrel racing horses is also unknown. OBJECTIVES: This study was performed to determine the prevalence of EIPH and signs of airway inflammation in barrel racing horses under normal racing conditions in Alberta. ANIMALS: About 170 barrel racing horses. METHODS: Observational cross-sectional study. Tracheobronchoscopic examinations were performed at least 30 minutes postrace. Video recordings were scored off-site independently by two observers for EIPH and tracheal mucus accumulation (TMA). Horses with an EIPH score ≥2 were not assessed for TMA. Interobserver agreement was calculated by weighted κ statistics. Run times, environmental variables, and clinical information were also recorded for analysis. RESULTS: 77/170 (45.3%) of horses examined showed evidence of EIPH (grade ≥ 1). Interobserver agreement was 0.94. 140/141 (99.3%) of horses assessed for TMA showed evidence of tracheal mucus accumulation (grade ≥ 1) with 104/141 (73.8%) having a TMA score ≥ 2. Interobserver agreement was 0.73. A weak positive association was found between EIPH scores and average run speed, the presence of cough at rest reported by the riders, increased recovery time, exercise intolerance, and outdoor pattern. CONCLUSIONS AND CLINICAL IMPORTANCE: The high prevalence of EIPH observed in the sampled population indicates that barrel racing induces substantial stress on the lungs. The presence of EIPH did not impact negatively on performance. Factors such as environmental dust and frequent traveling might have contributed to the high prevalence of TMA observed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".