Evidence map›Paper›PMID 37670960›Full record

ArticleInternational journal of population data science2023

Study protocol: Generation Victoria (GenV) special care nursery registry.

Jing Wang, Yanhong Jessika Hu, Lana Collins, Anna Fedyukova, Varnika Aggarwal, Fiona Mensah, Jeanie L Y Cheong, Melissa Wake, GenV Newborns Working Group

Abstract read
In one paragraph

Article in International journal of population data science, 2023. 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
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

9 authors.

Jing WangMurdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria, Australia.
Yanhong Jessika HuMurdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria, Australia.
Lana CollinsFaculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Victoria, Australia.
Anna FedyukovaMurdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria, Australia.
Varnika AggarwalMurdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria, Australia.
Fiona MensahMurdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria, Australia.
Jeanie L Y CheongMurdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria, Australia.
Melissa WakeMurdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria, Australia.
GenV Newborns Working Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Newborn babies who require admission for specialist care can experience immediate and sometimes lasting impacts. For babies admitted to special care nurseries (SCN), there is no dataset comparable to that of the Australian and New Zealand Neonatal Network (ANZNN), which has helped improve the quality and consistency of neonatal intensive care through standardised data collection. Objectives: We aim to establish a proof-of-concept, Victoria-wide registry of babies admitted to SCN, embedded within the whole-of-Victoria Generation Victoria (GenV) cohort. Methods: This prototype registry is a depth sub-cohort nested within GenV, targeting all babies born in Victoria from Oct-2021 to Oct-2023. Infants admitted to SCN are eligible. The minimum dataset will be harmonised with ANZNN for common constructs but also include SCN-only items, and will cover maternal, antenatal, newborn, respiratory/respiratory support, cardiac, infection, nutrition, feeding, cerebral and other items. As well as the dataset, this protocol outlines the anticipated cohort, timeline for this registry, and how this will serve as a resource for longitudinal research through its integration with the GenV longitudinal cohort and linked datasets. Conclusion: The registry will provide the opportunity to better understand the health and future outcomes of the large and growing cohort of children that require specialist care after birth. The data would generate translatable evidence and could lay the groundwork for a stand-alone ongoing clinical quality registry post-GenV.

Indexed as

FamilyNymphaeaceaeAustraliaChildData CollectionFemaleHeartHumansInfantInfant, NewbornPregnancyRegistriesclinical quality registryprotocolsick newbornsspecial care nursery

Identifiers

PMID37670960
PMCPMC10476699

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.