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Record W3039926729 · doi:10.1371/journal.pone.0235332

Association between vitamin D level and bronchopulmonary dysplasia: A systematic review and meta-analysis

2020· review· en· W3039926729 on OpenAlexaboutno aff
Hye Won Park, Gina Lim, Yong-Mean Park, Misoo Chang, Jae Sung Son, Ran Lee

Bibliographic record

VenuePLoS ONE · 2020
Typereview
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsnot available
Fundersnot available
KeywordsBronchopulmonary dysplasiaMedicineMeta-analysisvitamin D deficiencyVitamin D and neurologyInternal medicineVitaminPediatricsGestational agePregnancyBiology

Abstract

fetched live from OpenAlex

Neonatal vitamin D deficiency is common and is associated with development of pulmonary disease in children and adults. While the role of vitamin D in normal lung development is well established, the association between vitamin D deficiency and bronchopulmonary dysplasia (BPD) remains unclear. The present meta-analysis was conducted to evaluate the relationship between vitamin D and BPD. We identified relevant studies (n = 8) using the PubMed, EMBASE, Cochrane Library, and KoreaMed databases and applied the Newcastle-Ottawa Scale to assess the methodological components of each study, and used I2 statistic to evaluate heterogeneity. Comprehensive Meta-Analysis software version 3.3 was used for the statistical analysis. A total of 909 infants were included, of whom 251 (27.6%) were diagnosed with BPD. We found that both vitamin D deficiency at birth (four studies; OR 2.405; 95% CI 1.269 to 4.560; p = 0.007) and low levels of vitamin D at birth (four studies; standardized mean difference -1.463; 95% CI -2.900 to -0.027; p = 0.046) were associated with BPD. The compiled data suggest that antenatal vitamin D deficiency and low vitamin D levels are associated with neonatal BPD.

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)0.009
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.021
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0160.030
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.393
GPT teacher head0.411
Teacher spread0.017 · 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 designMeta-analysis
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

Citations51
Published2020
Admission routes1
Has abstractyes

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Same venuePLoS ONESame topicNeonatal Respiratory Health ResearchFrench-language works237,207