Evidence map›Paper›PMID 30592089›Full record

ArticleJournal of veterinary internal medicine2019

Comparison of smartphone-based and standard base-apex electrocardiography in healthy dairy cows.

Francesca Bonelli, Tommaso Vezzosi, Mireille Meylan, Irene Nocera, Vincenzo Ferrulli, Carlotta Buralli, Valentina Meucci, Rosalba Tognetti

Open access · goldAbstract readComparative Study
In one paragraph

Article in Journal of veterinary internal medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
2.4field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 36 citations in OpenAlex.

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  7. Convolutional Neural Network-Based ECG-Assisted Diagnosis for Coal Workers.International journal of environmental research and public health · 2022
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  11. Comparison between a fitness tracker (EquimetreFrontiers in veterinary science · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 2 countries.

Francesca BonelliDepartment of Veterinary Sciences, University of Pisa, Pisa, Italy.ORCID https://orcid.org/0000-0002-4119-7781
Tommaso VezzosiDepartment of Veterinary Sciences, University of Pisa, Pisa, Italy.ORCID https://orcid.org/0000-0001-8301-6582
Mireille MeylanThe Clinic for Ruminants, Vetsuisse-Faculty, University of Bern, Bern, Switzerland.ORCID https://orcid.org/0000-0003-0191-5686
Irene NoceraDepartment of Veterinary Sciences, University of Pisa, Pisa, Italy.
Vincenzo FerrulliDepartment of Veterinary Sciences, University of Pisa, Pisa, Italy.
Carlotta BuralliDepartment of Veterinary Sciences, University of Pisa, Pisa, Italy.
Valentina MeucciDepartment of Veterinary Sciences, University of Pisa, Pisa, Italy.
Rosalba TognettiDepartment of Veterinary Sciences, University of Pisa, Pisa, Italy.
University of Pisa · ITUniversity of Bern · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is good diagnostic accuracy of smartphone-based ECG in the evaluation of heart rate (HR), heart rhythm, and ECG values for humans, horses, dogs, and cats.

objectivesAssess feasibility and reliability of a smartphone ECG device to evaluate HR expressed as beats per minute and ECG values in cows. ANIMALS: Fifty-five healthy Holstein Friesian cows.

methodsProspective observational study. A standard base-apex ECG was acquired for 60 seconds in each cow. A smartphone ECG tracing was recorded simultaneously using a single-lead bipolar ECG recorder. All ECGs were reviewed by 1 blinded investigator. The following ECG variables were assessed: HR, P wave duration, PR interval, QRS complex and QT interval (milliseconds), P wave, and QRS complex polarity. Agreement between standard and smartphone ECG was evaluated by Cohen's k test and the Bland-Altman test.

resultsSmartphone ECG tracings were interpretable in 89% of the recordings. Minimal differences of no clinical relevance were found between standard and smartphone ECG tracings regarding HR and duration of ECG waves and interval. Good agreement found in the evaluation of QRS complex polarity (85%) but not for P wave polarity (k = 0.006). Artifacts were rare but of significantly higher frequency in smartphone ECG compared to standard ECG tracings (22% versus 0%; P = .005). CONCLUSIONS AND CLINICAL IMPORTANCE: Good quality single-lead ECG tracings can be recorded by smartphone device in healthy cows. Smartphone tracings are reliable for evaluation of HR and selective ECG variables. Smartphone ECG can represent an additional tool for ECG screening in cows.

Indexed as

Heart RateSmartphoneAnimalsArrhythmias, CardiacCattleCattle DiseasesElectrocardiographyFemaleProspective StudiesSensitivity and SpecificitySingle-Blind MethodcowECGiPhonemobilevalidation

Identifiers

PMID30592089
PMCPMC6430901
OpenAlexW2907309979

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.