Evidence map›Paper›PMID 38587231›Full record

ArticleClinical cardiology2024

The diagnostic efficiency of artificial intelligence based 2 hours Holter monitoring in premature ventricular and supraventricular contractions detection.

Qiong Huang, Yuansheng Fan, Jialin Wang, Zhiyang Xu, Linfeng Yang, Junhong Wang, Yiyang Zhan, Xiangqing Kong, Ningtian Zhou

Open access · goldAbstract read
In one paragraph

Article in Clinical cardiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
4.0field-weighted citation impact, top 6% 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

2 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
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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

9 authors at 2 institutions in 1 country.

Qiong HuangDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
Yuansheng FanDepartment of Cardiac Surgery, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
Jialin WangDepartment of General Practice, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
Zhiyang XuDepartment of Geriatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
Linfeng YangDepartment of General Practice, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
Junhong WangDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.ORCID http://orcid.org/0000-0003-2314-1810
Yiyang ZhanDepartment of Geriatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
Xiangqing KongDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
Ningtian ZhouDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.ORCID http://orcid.org/0000-0003-0515-7341
Jiangsu Province Hospital · CNSecond Affiliated Hospital of Nanjing Medical University · CN

Funding

National Natural Science Foundation of China 81441011National Natural Science Foundation of China 81570328National Natural Science Foundation of China 81670328
6 · The paper itself

Abstract

backgroundElectrocardiography (ECG) and 24 hours Holter monitoring (24 h-Holter) provided valuable information for premature ventricular and supraventricular contractions (PVC and PSVC). Currently, artificial intelligence (AI) based 2 hours single-lead Holter (2 h-Holter) monitoring may provide an improved strategy for PSVC/PVC diagnosis. HYPOTHESIS: AI combined with single-lead Holter monitoring improves PSVC/PVC detection.

methodsIn total, 170 patients were enrolled between August 2022 and 2023. All patients wore both devices simultaneously; then, we compared diagnostic efficiency, including the sensitivity/specificity/positive predictive-value (PPV) and negative predictive-value (NPV) in detecting PSVC/PVC by 24 h-Holter and 2 h-Holter.

resultsThe PPV and NPV in patients underwent 2 h-Holter were 76.00%/87.50% and 96.35%/98.55, respectively, and the sensitivity and specificity were 79.17%/91.30%, and 95.65%/97.84% in PSVC/PVC detection compared with 24 h-Holter. The areas under the ROC curves (AUCs) for PSVC and PVC were 0.885 and 0.741, respectively (p < .0001).

conclusionsThe potential advantages of the 2 h-Holter were shortened wearing period, improved convenience, and excellent consistency of diagnosis.

Indexed as

Electrocardiography, AmbulatoryVentricular Premature ComplexesArtificial IntelligenceElectrocardiographyHumansPredictive Value of Testsarrythmiaartificial intelligencediagnostic efficiencyHolter monitoring

Identifiers

PMID38587231
PMCPMC11000269
OpenAlexW4394578417

What OpenQuestion holds

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Registered trials

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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.