Evidence map›Paper›PMID 32769935›Full record

SynthesisMedicine2020

Diagnostic value of mean platelet volume for neonatal sepsis: A systematic review and meta-analysis.

Jingjing Wang, Zhen Wang, Min Zhang, Zhenshuai Lou, Jiaxiang Deng, Qian Li

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 2 pooled it
4.0field-weighted citation impact, top 6% 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

19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 35 citations in OpenAlex.

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  12. Group BAntibiotics (Basel, Switzerland) · 2023
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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 1 institution in 2 countries.

Jingjing WangDepartment of Emergency Internal Medicine.ORCID 0000-0003-4383-2264
Zhen WangDepartment of Critical Care Medicine.
Min ZhangDepartment of Emergency Internal Medicine.
Zhenshuai LouDepartment of Emergency Internal Medicine.
Jiaxiang DengDepartment of Emergency Intensive Care Unit, The First Affiliated Hospital of Wannan Medical College, Yijishan Hospital, Wuhu, Anhui, China.
Qian LiDepartment of Emergency Internal Medicine.
Weatherford College · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAn increasing number of studies in recent years have identified mean platelet volume (MPV) as a predictive marker for neonatal sepsis. However, most of these studies focused on single regions, and therefore, the findings remain inconclusive. We, in this study, aimed to evaluate the potential of MPV as a biological indicator of neonatal sepsis through a systematic review and meta-analysis.

methodsWe searched PubMed, the Cochrane Library, Embase, and WanFang database for articles on MPV and neonatal sepsis, published from January 1, 1990 to December 31, 2018. We included 11 studies on 932 neonates with sepsis in this meta-analysis.

resultsThe overall meta-analysis showed that MPV was significantly higher in patients with neonatal sepsis compared with healthy controls. Subgroup analysis revealed that the type of diagnostic criteria, analyzer, analyte, and controls used in the studies affected the difference in MPV between patients and healthy controls.

conclusionMPV was significantly higher in the neonatal sepsis group compared to the control group. Therefore, in clinical practice, MPV could be used as an indicator for the early diagnosis of neonatal sepsis.

Indexed as

PrognosisBiomarkersChi-Square DistributionHumansInfant, NewbornMean Platelet VolumeNeonatal SepsisPredictive Value of TestsBiomarkers

Identifiers

PMID32769935
PMCPMC7593009
OpenAlexW3047540181

What OpenQuestion holds

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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.