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Record W4405853389 · doi:10.1136/bmjopen-2024-087653

Assessing the impact of different donor milk treatments on infant health and growth: a systematic review protocol

2024· review· en· W4405853389 on OpenAlexaboutno aff
Daniel Klotz, Agnieszka Bzikowska‐Jura, Marzia Giribaldi, Tanya Cassidy, Laura Cavallarin, Serena Gandino, Karolina Karcz, Chiara Peila, Carolyn Smith, Bartłomiej Walczak, Aleksandra Wesołowska

Bibliographic record

VenueBMJ Open · 2024
Typereview
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsnot available
FundersWorld Health Organization
KeywordsMedicineCINAHLProtocol (science)MEDLINEClinical trialPopulationFamily medicineEuropean unionClinical study designInclusion (mineral)Alternative medicinePediatricsEnvironmental healthPsychological interventionPathologyNursing

Abstract

fetched live from OpenAlex

INTRODUCTION: Donor human milk (DHM) is the first alternative if mother's own milk is unavailable or contraindicated. Much DHM research has focused on its nutritional, immunological and biochemical composition in response to various maternal variables, standard human milk banking procedures and storage protocols. The current systematic review protocol, however, aims to systematically gather and analyse existing data pertaining to the impact of these aforementioned factors on the clinical, health-related and developmental outcomes observed in infants fed with DHM. METHODS AND ANALYSIS: We will apply a predefined search strategy including Cochrane Central Register of Controlled Trials, Global Index Medicus, CINAHL on Ebscohost, Medline, Embase, Emcare, Pubmed, Global Health on OVID, Google Scholar, clinicaltrials.gov, the WHO International Trials Registry and Platform and the European Union/European Economic Area Clinical Trials Register. No setting, patient population, date or language restrictions will be applied. The search strategy will consist of search words on the key concepts of 'donated human milk' and 'effect on infants'. Published or unpublished primary research studies are eligible for inclusion if there is an abstract available in English. Conference proceedings, animal studies and publications with no original data will be excluded.Authors of unpublished or partially published studies will be contacted and eligible data added if provided. Risk of bias will be evaluated according to CASP using appropriate tools depending on study type (RoB 2, ROBINS-I, Newcastle Ottawa Scale). Data will be synthesised in a quantitative format describing significant results as well as presenting the results of the quality assessment of studies. ETHICS AND DISSEMINATION: This systematic review does not require ethical approval, as we will not collect primary data. The review will be published in a peer-reviewed journal and disseminated electronically and in print. PROSPERO REGISTRATION NUMBER: CRD42024522015.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.066
metaresearch head score (Gemma)0.075
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.066
Threshold uncertainty score0.351

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0660.075
Meta-epidemiology (narrow)0.0050.005
Meta-epidemiology (broad)0.0220.016
Bibliometrics0.0170.013
Science and technology studies0.0030.005
Scholarly communication0.0080.010
Open science0.0060.006
Research integrity0.0070.004
Insufficient payload (model declined to judge)0.0640.007

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.221
GPT teacher head0.578
Teacher spread0.357 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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