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Record W4401555082 · doi:10.1111/evj.14206

Differences in pulmonary function measured by oscillometry between horses with mild–moderate equine asthma and healthy controls

2024· article· en· W4401555082 on OpenAlexaff
Chiara Maria Lo Feudo, Francesco Ferrucci, Davide Bizzotto, Raffaele L. Dellacá, Jean‐Pierre Lavoie, Luca Stucchi

Bibliographic record

VenueEquine Veterinary Journal · 2024
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Equine Medical Research
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineBronchoalveolar lavagePulmonary function testingBonferroni correctionAsthmaHorseInternal medicineReceiver operating characteristicAnesthesiaLung

Abstract

fetched live from OpenAlex

Abstract Background The diagnosis of mild–moderate equine asthma (MEA) can be confirmed by airway endoscopy, bronchoalveolar lavage fluid (BALf) cytology, and lung function evaluation by indirect pleural pressure measurement. Oscillometry is a promising pulmonary function test method, but its ability to detect subclinical airway obstruction has been questioned. Objective s To evaluate the differences in lung function measured by oscillometry between healthy and MEA‐affected horses. Study design Prospective case–control clinical study. Methods Thirty‐seven horses were divided into healthy and MEA groups, based on history and clinical score; the diagnosis of MEA was confirmed by airway endoscopy and BALf cytology. Horses underwent oscillometry at frequencies ranging from 2 to 6 Hz. Obtained parameters included whole‐breath, inspiratory, expiratory, and the difference between inspiratory and expiratory resistance (Rrs) and reactance (Xrs). Differences between oscillometry parameters at different frequencies were evaluated within and between groups by repeated‐measures two‐way ANOVA and post hoc tests with Bonferroni correction. Frequency dependence was compared between groups by t test. For significant parameters, a receiver operating characteristics curve was designed, cut‐off values were identified and their sensitivity and specificity were calculated. Statistical significance was set at p < 0.05. Results No significant differences in Xrs and Rrs were observed between groups. The frequency dependence of whole‐breath and inspiratory Xrs significantly differed between healthy (respectively, −0.03 ± 0.02 and −0.05 ± 0.02 cmH 2 O/L/s) and MEA (−0.1 ± 0.03 and −0.2 ± 0.02 cmH 2 O/L/s) groups ( p < 0.05 and p < 0.01). For inspiratory Xrs frequency dependence, a cut‐off value of −0.06 cmH 2 O/L/s was identified, with 86.4% (95% CI: 66.7%–95.3%) sensitivity and 66.7% (95% CI: 41.7%–84.8%) specificity. Main limitations Sample size, no BALf cytology in some healthy horses. Conclusions Oscillometry can represent a useful non‐invasive tool for the diagnosis of MEA. Specifically, the evaluation of the frequency dependence of Xrs may be of special interest.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.682
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.120
GPT teacher head0.368
Teacher spread0.248 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations2
Published2024
Admission routes1
Has abstractyes

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