Evidence map›Paper›PMID 35607309›Full record

ArticleBioMed research international2022

Left Heart Failure Caused by Capacity Overload in Peritoneal Dialysis Patients.

Lin Zhang, Xiaocui Zhang, Song Xue

RetractedOpen access · hybridAbstract readRetracted Publication
In one paragraph

Article in BioMed research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 32% 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, 5 citations in OpenAlex.

  1. Article
  2. Observational
  3. Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Lin ZhangDepartment of Nephrology, Municipal Hospital Affiliated to Xuzhou Medical University, Xuzhou First People's Hospital, Xuzhou, China.ORCID https://orcid.org/0000-0001-6895-4589
Xiaocui ZhangDepartment of Pediatrics, East Hospital of the Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.
Song XueDepartment of Cardiology, Affiliated Huaihai Hospital of Xuzhou Medical University, Xuzhou, China.
Xuzhou Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study sets out to investigate the incidence of acute left ventricular failure in peritoneal dialysis patients with different volume loads and to analyze the related risk factors for LVF in these patients. Methods: This study involved patients who received peritoneal dialysis in our hospital between September 2018 and January 2021. The demographic data and biochemical indicators of the patients were collected. The bioimpedance analysis method was used to determine the volume overload [overhydration (OH)] level of patients, and cardiac color Doppler ultrasound was used to detect changes in their cardiac structure. According to the LVF diagnostic criteria of symptoms and laboratory tests, the patients were divided into the LVF and non-LVF groups and then divided according to their OH level into the normal volume (OH ≤1.1 L) and volume overload (OH >1.1 L) groups. The incidence of LVF in was analyzed in patients with different volume loads, and logistic regression was used to identify the risk factors for LVF. Results: Among the 226 peritoneal dialysis patients enrolled in this study, 125 patients (55.3%) had LVF. The normal volume group ( Conclusions: LVF has a high incidence in peritoneal dialysis patients, especially those with volume overload. A high OH level and low hemoglobin level are independent risk factors for LVF.

Indexed as

Heart FailureKidney Failure, ChronicPeritoneal DialysisHeartHemoglobinsHumansRisk FactorsHemoglobins

Identifiers

PMID35607309
PMCPMC9124112
OpenAlexW4280646066

What OpenQuestion holds

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LicenceCC BY
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.