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Association of LEPR Gln223Arg Polymorphism with Obstructive Sleep Apnea Syndrome: A Meta-Analysis

2019· review· en· W2925169924 on OpenAlexaboutno aff
Mei Zhu, Xue Bai

Bibliographic record

VenueCritical Reviews in Eukaryotic Gene Expression · 2019
Typereview
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineObstructive sleep apneaOdds ratioMeta-analysisPolymorphism (computer science)Internal medicineConfidence intervalLeptin receptorObesityGenotypeLeptinGeneticsGeneBiology

Abstract

fetched live from OpenAlex

Previous studies examining the association of leptin receptor (LEPR) Gln223Arg polymorphism with obstructive sleep apnea-hypopnea syndrome (OSAHS) risk have yielded controversial outcomes. We aimed to clarify whether LEPR Gln223Arg polymorphism was critically involved in the development of OSAHS. We thoroughly searched PubMed as well as CNKI datasets for collection of relevant studies, followed by analysis of odds ratios (ORs) with corresponding 95% confidence intervals (CIs). Of the seven case-control studies we enrolled, there was insignificant correlation of the LEPR Gln223Arg polymorphism with OSAHS risk. However, subgroup analysis by Newcastle-Ottawa scale (NOS) scores revealed that, LEPR Gln223Arg polymorphism was significantly related to OSAHS risk in high-quality studies. In addition, we found no publication bias. Our findings suggest that LEPR Gln223Arg polymorphism might contribute to the risk of OSAHS. Well-designed studies with more subjects are needed for further validation of these results.

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)0.007
metaresearch head score (Gemma)0.014
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 score0.012
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.014
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0120.020
Bibliometrics0.0040.006
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.109
GPT teacher head0.392
Teacher spread0.283 · 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

Citations6
Published2019
Admission routes1
Has abstractyes

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