Evidence map›Paper›PMID 34266524›Full record

ArticleZhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics2021

[A clinical analysis of sepsis in very low birth weight infants].

Xiao-Shan Hu, Jin-Gai Zhu, Cheng-Yao Jiang, Xiao-Hui Chen, Zhang-Bin Yu, Shu-Ping Han

Open access · greenAbstract read
In one paragraph

Article in Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 42% 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

3 citing papers in PubMed, 2 citations in OpenAlex.

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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 1 country.

Xiao-Shan HuDepartment of Pediatrics, Maternity Hospital Affiliated to Nanjing Medical University/Nanjing Maternal and Child Health Hospital, Nanjing 210004, China.
Jin-Gai ZhuDepartment of Pediatrics, Maternity Hospital Affiliated to Nanjing Medical University/Nanjing Maternal and Child Health Hospital, Nanjing 210004, China.
Cheng-Yao JiangDepartment of Pediatrics, Maternity Hospital Affiliated to Nanjing Medical University/Nanjing Maternal and Child Health Hospital, Nanjing 210004, China.
Xiao-Hui ChenDepartment of Pediatrics, Maternity Hospital Affiliated to Nanjing Medical University/Nanjing Maternal and Child Health Hospital, Nanjing 210004, China.
Zhang-Bin YuDepartment of Pediatrics, Maternity Hospital Affiliated to Nanjing Medical University/Nanjing Maternal and Child Health Hospital, Nanjing 210004, China.
Shu-Ping HanDepartment of Pediatrics, Maternity Hospital Affiliated to Nanjing Medical University/Nanjing Maternal and Child Health Hospital, Nanjing 210004, China.
Nanjing Maternity and Child Health Care Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo study the incidence and clinical features of sepsis in very low birth weight (VLBW) infants.

methodsThe clinical data were collected from VLBW infants, with a birth weight of < 1 500 g, who were admitted to the Department of Neonatology, Maternity Hospital Affiliated to Nanjing Medical University, from January 2019 to June 2020. The incidence of sepsis, distribution of pathogenic bacteria, and risk factors for sepsis were analyzed.

resultsA total of 369 infants were enrolled, and 138 infants had sepsis, among whom 84 had early-onset sepsis (EOS) and 54 had late-onset sepsis (LOS).

conclusions

Indexed as

Infant, Very Low Birth WeightSepsisBirth WeightFemaleGestational AgeHumansIncidenceInfantInfant, NewbornPregnancyRisk Factors

Identifiers

PMID34266524
PMCPMC8292651
OpenAlexW3181519000

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.