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Record W2986768741 · doi:10.1111/ajd.13186

Systematic review and meta‐analysis on the use of probiotic supplementation in pregnant mother, breastfeeding mother and infant for the prevention of atopic dermatitis in children

2019· review· en· W2986768741 on OpenAlexaboutno aff
Nasya Amalia, David Orchard, Kate Francis, Emma King

Bibliographic record

VenueAustralasian Journal of Dermatology · 2019
Typereview
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBreastfeedingAtopic dermatitisProbioticMeta-analysisCochrane LibraryRelative riskRandomized controlled trialPediatricsSystematic reviewIncidence (geometry)Breast feedingMEDLINEConfidence intervalInternal medicineImmunology

Abstract

fetched live from OpenAlex

Probiotic supplementation may decrease the risk of allergic disease; however, there are differences between studies, such as the type of probiotic, the route or the duration of supplementation. Therefore, determining the most effective probiotic strain/s, route of administration and duration for clinical recommendation has been difficult. An electronic systematic literature search was undertaken between using Ovid MEDLINE, Embase, PubMed and Cochrane. Risk ratio (RR) and 95% confidence interval (CI) are presented for the studies. PEDro scale and Newcastle-Ottawa Scale were used to assess the quality of the included studies. A total of 21 studies met the inclusion criteria. Strain-specific sub-meta-analyses indicated that single strains are not as effective as probiotic mixtures and administration to a combination of pregnant mothers, breastfeeding mothers and infants had a reduced risk in the onset of atopic dermatitis in children. Our systematic review and meta-analysis showed that a mixture of probiotic supplementation given to the mother in pregnancy and continuing while breastfeeding and also to the infant in children classified as high-risk for atopic dermatitis and non-high-risk groups is the most efficacious in reducing the risk of incidence of atopic dermatitis in children.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.704
Threshold uncertainty score0.470

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.061
GPT teacher head0.342
Teacher spread0.282 · 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 teacher head, not a consensus.

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

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

Citations49
Published2019
Admission routes1
Has abstractyes

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