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Record W4311762480 · doi:10.1016/j.jevs.2022.104182

Free Swimming and Exercise-Induced Pulmonary Hemorrhage in Endurance Horses: A Preliminary Study

2022· article· en· W4311762480 on OpenAlexaff
Tatiana Vinardell, Florent David, Angelica M. Galezowski, Mohammad Javed Ali, Muhammad Qasim, Shannon Massie, Persephone McCrae, Silvio Filho, Renaud Léguillette

Bibliographic record

VenueJournal of Equine Veterinary Science · 2022
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Equine Medical Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineBronchoalveolar lavageInterquartile rangeHorseAnesthesiaPhysical therapyInternal medicineLungBiology

Abstract

fetched live from OpenAlex

Swimming is used for rehabilitation of musculoskeletal injuries and for conditioning to improve equine fitness. However, there are anecdotal reports that suggest that tethered swimming can induce epistaxis, likely secondary to exercise-induced pulmonary hemorrhage (EIPH). The objective of this observational, prospective study was to investigate if EIPH occurs during intensive free-swimming training sessions (5 × 70m) using 15 endurance horses. On tracheo-bronchoscopic evaluations following swimming, low grade mucus scores were observed, but no tracheal blood was observed. Bronchoalveolar lavage fluid analysis revealed a low cellularity, and the median red blood cell count (RBCs) was 271 cells/μL (interquartile range 150-363 cells/μL), which is much lower than the threshold of RBCs >1,000 cells/μL for horses to be considered positive for EIPH. Therefore, free swimming does not seem to predispose endurance horses to EIPH following a typical free-swimming training session.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.100
GPT teacher head0.383
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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