Evidence map›Paper›PMID 36949420›Full record

ArticleBMC cardiovascular disorders2023

Performance of heart rate adjusted heart rate variability for risk stratification of sudden cardiac death.

Su-Peng Yan, Xin Song, Liang Wei, Yu-Shun Gong, Hou-Yuan Hu, Yong-Qin Li

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Article in BMC cardiovascular disorders, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

6 authors.

Su-Peng YanDepartment of Biomedical Engineering and Imaging Medicine, Army Medical University, 30 Gaotanyan Main Street, Chongqing, 400038, China.
Xin SongDepartment of Biomedical Engineering and Imaging Medicine, Army Medical University, 30 Gaotanyan Main Street, Chongqing, 400038, China.
Liang WeiDepartment of Biomedical Engineering and Imaging Medicine, Army Medical University, 30 Gaotanyan Main Street, Chongqing, 400038, China.
Yu-Shun GongDepartment of Biomedical Engineering and Imaging Medicine, Army Medical University, 30 Gaotanyan Main Street, Chongqing, 400038, China.
Hou-Yuan HuDepartment of Cardiology, Southwest Hospital, Army Medical University, Chongqing, 400038, China.
Yong-Qin LiDepartment of Biomedical Engineering and Imaging Medicine, Army Medical University, 30 Gaotanyan Main Street, Chongqing, 400038, China. leeoken@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeAs a non-invasive tool for the assessment of cardiovascular autonomic function, the predictive value of heart rate variability (HRV) for sudden cardiac death (SCD) risk stratification remains unclear. In this study, we investigated the performance of the individualized heart rate (HR) adjusted HRV (HRV

methodsA total of 11 commonly used HRV metrics were analyzed in 192 subjects, including 88 healthy controls (low risk group), 82 hypertrophic cardiomyopathy (HCM) patients (medium risk group), and 22 SCD victims (high risk group). The relationship between HRV metrics and HR was examined with long-term and short-term analysis. The performance HRV

resultsMost of the HRV metrics were exponentially decayed with the increase of HR, while the exponential power coefficients were significantly different among groups. The HRV

conclusionsSubjects with diverse risks of SCD had similar exponential decay relationship between HRV metrics and HR, but with different decaying rates. HRV

Indexed as

Cardiomyopathy, HypertrophicDeath, Sudden, CardiacHeartHeart RateHumansRisk AssessmentRisk FactorsHeart rateHeart rate variabilityHypertrophic cardiomyopathyRisk stratificationSudden cardiac death

Identifiers

PMID36949420
PMCPMC10032001

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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.