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Record W2955278014 · doi:10.1097/md.0000000000015963

Tumor necrosis factor-α-308 polymorphism is not associated with Kawasaki disease

2019· review· en· W2955278014 on OpenAlexaboutno aff
Ye Yuan, Jinhua Piao, Na Lu

Bibliographic record

VenueMedicine · 2019
Typereview
Languageen
FieldMedicine
TopicKawasaki Disease and Coronary Complications
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMeta-analysisPublication biasOdds ratioCochrane LibraryFunnel plotConfidence intervalInternal medicineStudy heterogeneityRandom effects modelOncology

Abstract

fetched live from OpenAlex

BACKGROUND: Genetic factors in the pathogenesis of Kawasaki disease (KD) have received a lot of attention during the past decade. Some studies have reported that tumor necrosis factor (TNF)-α-308 polymorphism has been associated with KD. However, there have been inconsonant results among different studies. To increase the power for clarifying the influence of TNF on KD, a meta-analysis of case-control studies were performed. METHODS: The following databases were searched to identify related studies: PubMed, Embase, Cochrane Library, CNKI, Wanfang, and VIP databases according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Search terms included "Kawasaki disease" or "KD," "tumor necrosis factor-alpha" or "TNF-α," and "polymorphism" or "mutation." Two reviewers independently extracted data and assessed study quality using Newcastle-Ottawa Scale. Odds ratios (ORs) with corresponding 95% confidence intervals (CI) were used to assess the strength of the association. Accounting for heterogeneity, a fixed or random effects model was respectively adopted. Heterogeneity was checked using the Q test and the I statistic. A cumulative meta-analysis was conducted to estimate the tendency of pooled OR. Funnel plots and Egger tests were performed to test for possible publication bias and sensitivity analyses were done to ensure authenticity of the outcome. RESULTS: Eleven separate studies were suitable for the inclusion criterion. The selected studies contained 2582 participants, including 841 in KD group and 1741controls. The pooled odds ratio of G versus A with the random effect model was 1.09 (95% CI = 0.69-1.70, P = .72) and the genotype effects for GG versus GA+AA was 1.14 (95% CI = 0.68-1.90, P = .62) in the whole population separately. Unfortunately, no significant association was detected between the TNF-α-308 polymorphism and KD risk under allele and genotype model. CONCLUSION: No association between the TNF-α-308 polymorphism and KD was found in our meta-analysis and further studies with larger sample size and more ethnicities are expected to be conducted in the future to validate the 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)0.013
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.045
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.008
Bibliometrics0.0030.005
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
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 head0.117
GPT teacher head0.359
Teacher spread0.243 · 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 designObservational
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

Citations2
Published2019
Admission routes1
Has abstractyes

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