Evidence map›Paper›PMID 36560238›Full record

ArticleSensors (Basel, Switzerland)2022

An Effective Method of Detecting Characteristic Points of Impedance Cardiogram Verified in the Clinical Pilot Study.

Ilona Karpiel, Monika Richter-Laskowska, Daniel Feige, Adam Gacek, Aleksander Sobotnicki

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. 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
–field-weighted citation impact
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.

  1. Article
  2. Current and Future Use of Artificial Intelligence in Electrocardiography.Journal of cardiovascular development and disease · 2023
    Review
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

5 authors.

Ilona KarpielŁukasiewicz Research Network, Institute of Medical Technology and Equipment, Roosevelt 118, 41-800 Zabrze, Poland.ORCID 0000-0002-2104-7997
Monika Richter-LaskowskaŁukasiewicz Research Network, Institute of Medical Technology and Equipment, Roosevelt 118, 41-800 Zabrze, Poland.ORCID 0000-0002-6591-5944
Daniel FeigeŁukasiewicz Research Network, Institute of Medical Technology and Equipment, Roosevelt 118, 41-800 Zabrze, Poland.ORCID 0000-0001-6840-0965
Adam GacekŁukasiewicz Research Network, Institute of Medical Technology and Equipment, Roosevelt 118, 41-800 Zabrze, Poland.
Aleksander SobotnickiŁukasiewicz Research Network, Institute of Medical Technology and Equipment, Roosevelt 118, 41-800 Zabrze, Poland.

Funding

National Centre for Research STRATEGMED3/305274/8/NCBR/2017SYBIOZ CŁ/631/2021/DF/DW
6 · The paper itself

Abstract

Accurate and reliable determination of the characteristic points of the impedance cardiogram (ICG) is an important research problem with a growing range of applications in the cardiological diagnostics of patients with heart failure (HF). The shapes of the characteristic waves of the ICG signal and the temporal location of the characteristic points B, C, and X provide significant diagnostic information. On this basis, essential diagnostic cardiological parameters can be determined, such as, e.g., cardiac output (CO) or stroke volume (SV). Although the importance of this problem is obvious, we face many challenges, including noisy signals and the big variability in the morphology, which altogether make the accurate identification of the characteristic points quite difficult. The paper presents an effective method of ICG points identification intended for conducting experimental research in the field of impedance cardiography. Its effectiveness is confirmed in clinical pilot studies.

Indexed as

Heart FailureCardiac OutputCardiography, ImpedanceElectric ImpedanceHumansPilot ProjectsStroke Volumecardiaccardiac functionheartheart failurehemodynamicsimpedance cardiographyremote monitoring

Identifiers

PMID36560238
PMCPMC9782651

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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.