Evidence map›Paper›PMID 33398130›Full record

ArticleHypertension research : official journal of the Japanese Society of Hypertension2021

Electrocardiogram findings at the initiation of hemodialysis and types of subsequent cardiovascular events.

Satoshi Yamaguchi, Takayuki Hamano, Tatsufumi Oka, Yohei Doi, Sachio Kajimoto, Seiichi Yasuda, Karin Shimada, Ayumi Matsumoto, Yusuke Sakaguchi, Kazunori Inoue and 3 more

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in Hypertension research : official journal of the Japanese Society of Hypertension, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 29% 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

4 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. 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

13 authors at 2 institutions in 1 country.

Satoshi YamaguchiDepartment of Nephrology, Osaka University Graduate School of Medicine, Suita, Japan.
Takayuki HamanoDepartment of Nephrology, Osaka University Graduate School of Medicine, Suita, Japan. hamatea@kid.med.osaka-u.ac.jp.
Tatsufumi OkaDepartment of Nephrology, Osaka University Graduate School of Medicine, Suita, Japan.
Yohei DoiDepartment of Nephrology, Osaka University Graduate School of Medicine, Suita, Japan.
Sachio KajimotoDepartment of Nephrology, Osaka University Graduate School of Medicine, Suita, Japan.
Seiichi YasudaDepartment of Nephrology, Osaka University Graduate School of Medicine, Suita, Japan.
Karin ShimadaDepartment of Nephrology, Osaka University Graduate School of Medicine, Suita, Japan.
Ayumi MatsumotoDepartment of Nephrology, Osaka University Graduate School of Medicine, Suita, Japan.
Yusuke SakaguchiDepartment of Inter-Organ Communication Research in Kidney Disease, Osaka University Graduate School of Medicine, Suita, Japan.
Kazunori InoueDepartment of Nephrology, Osaka University Graduate School of Medicine, Suita, Japan.
Isao MatsuiDepartment of Nephrology, Osaka University Graduate School of Medicine, Suita, Japan.
Akira SuzukiDepartment of Internal Medicine, Japan Community Health care Organization Osaka Hospital, Osaka, Japan.
Yoshitaka IsakaDepartment of Nephrology, Osaka University Graduate School of Medicine, Suita, Japan.
Osaka University · JPJapan Community Healthcare Organization · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The prognostic value of electrocardiograms (ECGs) has been reported in predialysis patients but not in incident hemodialysis patients with overhydration and electrolyte disturbances, both of which potentially affect ECG results. We performed a retrospective multicenter cohort study involving incident hemodialysis patients and examined whether ECG parameters immediately before hemodialysis initiation can predict subsequent cardiovascular disease (CVD) using Cox proportional hazards models. We explored potential effect modifications by several electrolytes on the predictive power of ECG abnormalities. Among the 618 enrolled patients, 16%, 10%, 46%, and 22% showed a PR interval ≥ 200 ms, QRS interval ≥120 ms, QTc interval ≥ 450/460 ms (male/female), and left ventricular hypertrophy (LVH) by voltage criteria, respectively. Over a median 3-year follow-up, 19% and 16% of the patients developed atherosclerotic and nonatherosclerotic CVD, respectively. The Cox regression model results revealed that the sum of the number of abnormalities in PR, QRS, and QT intervals was a significant risk factor for nonatherosclerotic CVD (hazard ratios (HRs) [95% confidence interval (CI)]: 1.58 [1.24-2.01] per number of abnormalities). The predictive value of LVH for atherosclerotic CVD was attenuated over time. At up to 36 months, although the proportional hazards assumption was met, LVH was significantly associated with atherosclerotic CVD (HR [95% CI]: 1.89 [1.15-3.11]). The adjusted HR was particularly high (HR [95% CI]: 4.02 [1.68-9.60]) among patients who were in the lowest tertile of serum magnesium levels (P for interaction = 0.04). PR, QRS, and QT prolongation additively predicted nonatherosclerotic CVD, while LVH predicted atherosclerotic CVD in the short term.

Indexed as

Cardiovascular DiseasesHypertrophy, Left VentricularRenal DialysisElectrocardiographyFemaleHumansMaleProportional Hazards ModelsRetrospective StudiesRisk Factorsleft ventricular hypertrophyPR prolongationQRS prolongationQT prolongation

Identifiers

PMID33398130
OpenAlexW3120801339

What OpenQuestion holds

Textmetadata
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.