Evidence map›Paper›PMID 32787649›Full record

ArticleRenal failure2020

Serum Sphingosine-1-phosphate level and peritonitis in peritoneal dialysis patients.

Qiong Bai, Hong-Xia Guo, Chun-Yan Su, Qing-Feng Han, Tao Wang, Wen Tang

Open access · goldAbstract read
In one paragraph

Article in Renal failure, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
0.4field-weighted citation impact, top 37% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
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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 at 2 institutions in 1 country.

Qiong BaiDepartment of Nephrology, Peking University Third Hospital, Beijing, China.
Hong-Xia GuoDepartment of Nephrology, Peking University Third Hospital, Beijing, China.
Chun-Yan SuDepartment of Nephrology, Peking University Third Hospital, Beijing, China.
Qing-Feng HanDepartment of Nephrology, Peking University Third Hospital, Beijing, China.
Tao WangDepartment of Nephrology, Peking University Third Hospital, Beijing, China.
Wen TangDepartment of Nephrology, Peking University Third Hospital, Beijing, China.
Peking University · CNPeking University Third Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGiven the important role of Sphingosine-1-phosphate (S1P) in maintaining the hemostasis in intestinal barrier function and regulation of inflammation and immune, we hypothesize that S1P might be a biomarker to predict peritonitis in peritoneal dialysis (PD) patients.

methodsIn this case-control study, 78 stable, continuous ambulatory peritoneal dialysis patients were enrolled and followed for the episode of PD associated peritonitis. Patients were divided into two groups by whether or not they had peritonitis during follow-up: non-peritonitis (

resultsPatients with peritonitis had a lower level of S1P than that of patients without peritonitis (1.3 ng/mL IQ 0.8, 3.6 ng/mL vs. 2.8 ng/mL IQ 1.5, 5.4 ng/mL,

conclusionOur study showed that S1P was an independent determinant of subsequent peritonitis in PD patients. S1P might serve as a biomarker to predict peritonitis in PD patients.

Indexed as

AgedBiomarkersCase-Control StudiesFemaleHumansLeukocyte CountLogistic ModelsLysophospholipidsMaleMiddle AgedPeritoneal Dialysis, Continuous AmbulatoryPeritonitisRisk FactorsSerum AlbuminSphingosineBiomarkersLysophospholipidsSerum AlbuminSphingosinesphingosine 1-phosphateintestinal barrierperitoneal dialysisperitonitisSphingosine-1-phosphate

Identifiers

PMID32787649
PMCPMC7472472
OpenAlexW3049200012

What OpenQuestion holds

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LicenceCC BY
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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.