Evidence map›Paper›PMID 35501095›Full record

ArticleBMJ open2022

Chinese Neonatal Network: a national protocol for collaborative research and quality improvement in neonatal care.

Mingyan Hei, Xiaoying Li, Yuan Shi, Yun Cao, Jianhua Sun, Hui Wu, Siyuan Jiang, Xiaolu Ma, Yanchen Wang, Huiqing Sun and 6 more

Abstract read
In one paragraph

Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
–field-weighted citation impact
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

24 citing papers in PubMed.

  1. Article
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  4. Article
  5. Observational
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  7. Observational
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  9. Article
  10. Article
  11. The role of QI collaboratives in neonatology.Journal of perinatology : official journal of the California Perinatal Association · 2025
    Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Observational
  18. Article
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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

16 authors.

Mingyan HeiNeonatal Center, Beijing Children's Hospital Capital Medical University, Beijing, China.ORCID 0000-0001-5810-605X
Xiaoying LiDepartment of Neonatology, Qilu Children's Hospital of Shandong University, Jinan, Shandong, China.
Yuan ShiDepartment of Neonatology, Children's Hospital of Chongqing Medical University, Chongqing, China.
Yun CaoNeonatology, Children's Hospital of Fudan University, Shanghai, China.
Jianhua SunDepartment of Neonatology, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Hui WuNeonatology, The First Bethune Hospital of Jilin University, Changchun, Jilin, China.ORCID 0000-0002-7649-4575
Siyuan JiangNeonatology, Children's Hospital of Fudan University, Shanghai, China.
Xiaolu MaNeonatology, The Children's Hospital Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Yanchen WangNeonatology, Children's Hospital of Fudan University, Shanghai, China.
Huiqing SunDivision of Neonatology, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, China.
Huayan ZhangDivision of Neonatology and Center for Newborn Care, Guangzhou Women and Children's Medical Center, Guangzhou, Guangdong, China.
Li-Zhong DuThe Children's Hospital Zhejiang University School of Medicine, Hangzhou, China.
Wenhao ZhouNeonatology, Children's Hospital of Fudan University, Shanghai, China.
Shoo K LeeDepartment of Pediatrics, University of Toronto, Toronto, Ontario, Canada.
Chao ChenNeonatology, Children's Hospital of Fudan University, Shanghai, China chaochen6010@163.com.
Chinese Neonatal Network (CHNN)*

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe objective of the Chinese Neonatal Network (CHNN) is to provide a platform for collaborative research, outcomes evaluation and quality improvement for preterm infants with gestational age less than 32 weeks in China. The CHNN is the first national neonatal network and has the largest geographically representative cohort from neonatal intensive care units (NICUs) in China. METHODS AND ANALYSIS: Individual-level data from participating NICUs will be collected using a unique database developed by the CHNN on an ongoing basis from January 2019. Data will be prospectively collected from all infants <32 weeks gestation or <1500 g birth weight at 58 participating NICUs. Infant outcomes and inter-institutional variations in outcomes will be examined and used to inform quality improvement measures aimed at improving outcomes. Information about NICU environmental and human resource factors and processes of neonatal care will also be collected and analysed for association with outcomes. Clinical studies, including randomised controlled trials will be conducted using the CHNN data platform. ETHICS AND DISSEMINATION: This study was approved by the ethics review board of Children's Hospital of Fudan University, which was recognised by all participating hospitals. Waiver of consent were granted at all sites. Only non-identifiable patient level data will be transmitted and only aggregate data will be reported in CHNN reports and publications.

Indexed as

Infant HealthInformation ServicesQuality ImprovementChildChinaDatabases, FactualHumansInfantInfant, NewbornInfant, PrematureInfant, Very Low Birth WeightIntensive Care Units, Neonatalneonatal intensive & critical careneonatologyperinatologyprotocols & guidelinesqualitative research

Identifiers

PMID35501095
PMCPMC9062799

What OpenQuestion holds

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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.