ArticleFrontiers in genetics2023
A data management plan for the NESHIE observational study.
Article in Frontiers in genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Neonatal encephalopathy due to suspected hypoxic-ischaemic encephalopathy.World journal of pediatrics : WJP · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With regard to the use and transfer of research participants' personal information, samples and other data nationally and internationally, it is necessary to construct a data management plan. One of the key objectives of a data management plan is to explain the governance of clinical, biochemical, laboratory, molecular and other sources of data according to the regulations and policies of all relevant stakeholders. It also seeks to describe the processes involved in protecting the personal information of research participants, especially those from vulnerable populations. In most data management plans, the framework therefore consists of describing the collection, organization, use, storage, contextualization, preservation, sharing and access of/to research data and/or samples. It may also include a description of data management resources, including those associated with analyzed samples, and identifies responsible parties for the establishment, implementation and overall management of the data management strategy. Importantly, the data management plan serves to highlight potential problems with the collection, sharing, and preservation of research data. However, there are different forms of data management plans and requirements may vary due to funder guidelines and the nature of the study under consideration. This paper leverages the detailed data management plans constructed for the 'NESHIE study' and is a first attempt at providing a comprehensive template applicable to research focused on vulnerable populations, particularly those within LMICs, that includes a multi-omics approach to achieve the study aims. More particularly, this template, available for download as a supplementary document, provides a modifiable outline for future projects that involve similar sensitivities, whether in clinical research or clinical trials. It includes a description of the management not only of the data generated through standard clinical practice, but also that which is generated through the analysis of a variety of samples being collected from research participants and analyzed using multi-omics approaches.
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Registered trials
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.