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Record W2791694668 · doi:10.5326/jaaha-ms-6626

Preliminary Assessment of a Novel 14-Day Electrocardiographic Adhesive Patch Monitor in Dogs

2018· article· en· W2791694668 on OpenAlexaff
Jonathan Lichtenberger, Kathryn M. Meurs, Étienne Côté

Bibliographic record

VenueJournal of the American Animal Hospital Association · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Effects of Exercise
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsMedicineAmbulatory ECGElectrocardiographyCardiologyAmbulatoryArtifact (error)Thorax (insect anatomy)Holter monitorAnesthesiaInternal medicineAnatomy

Abstract

fetched live from OpenAlex

Cardiac arrhythmias often are transient and might not be detected using conventional electrocardiographic (ECG) techniques. The adhesive patch monitor (APM) is a single-lead, lightweight, up to 14-day continuous ambulatory ECG monitor. This study aimed to prospectively assess its usability in four boxer dogs considered either to be healthy or to have arrhythmogenic right ventricular cardiomyopathy. Optimal recording was obtained by placing the APM on the left side of the animal's thorax, at the fifth intercostal space, slightly dorsal to the costochondral junction, and oriented either vertically or parallel to the long axis of the heart. In three dogs, the APM remained attached for 14 days. One dog removed the APM after 59 hr. Skin irritation was documented in all dogs and resolved spontaneously after removal of the APM. The analyzable time was >93% of the total wear time and recordings provided an unambiguous rhythm diagnosis at rest. Walking, running, or playing caused intermittent motion artifact that could impair ECG interpretation. APM results were comparable to those obtained with 24-hr Holter monitoring. Extended continuous ECG monitoring with the APM is feasible in boxer dogs and provides interpretable recordings.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.038
Threshold uncertainty score0.470

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.005
GPT teacher head0.267
Teacher spread0.262 · 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.

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

Citations3
Published2018
Admission routes1
Has abstractyes

Explore more

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