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Record W4247183051 · doi:10.3889/oamjms.2019.027

Evaluation of Serum Interleukin-6 Levels in the Renal Transplant Recipients: A Systematic Review and Meta-Analysis of Case-Control Studies

2019· review· en· W4247183051 on OpenAlexaboutno aff
Hamidreza Omrani, Seyed Vahid Jasemi, Masoud Sadeghi, Sima Golmohamadi

Bibliographic record

VenueOpen Access Macedonian Journal of Medical Sciences · 2019
Typereview
Languageen
FieldMedicine
TopicInflammatory Biomarkers in Disease Prognosis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMeta-analysisRenal transplantCochrane LibraryInternal medicineConfidence intervalTransplantationGastroenterology

Abstract

fetched live from OpenAlex

AIM: The purpose of this meta-analysis was the assessment of the serum IL-6 levels in the renal transplant recipients compared to the healthy controls. MATERIAL AND METHODS: Four databases including PubMed, Web of Science, Scopus, and Cochrane Library were searched up to July 2018 without language restriction. The quality of studies was evaluated using the Newcastle-Ottawa scale (NOS). A continuous random-effects meta-analysis was used by RevMan 5.3 using the mean difference (MD) and 95% confidence intervals (CIs). Also, a regression model was done by Comprehensive Meta-Analysis version 2 (CMA v2). RESULTS: Out of 615 studies identified in the databases, 15 studies included and analysed in the meta-analysis. The studies were reported from 1994 to 2018. The meta-analysis included 1035 renal transplant recipients and 682 healthy controls. The pooled MD of the serum IL-6 levels in the transplant recipients compared to the healthy controls was 3.25 pg/mL [95%CI: 2.17, 4.32; P < 0.00001; I2 = 98% (P < 0.00001)]. Meta-regression analysis showed that one of the reasons of heterogeneity is the year of publication (Correlation coefficient (r) = 0.208, p-value = 0.00002). CONCLUSION: An elevated serum IL-6 level in the renal transplant recipients compared to the healthy controls showed that the serum level of this marker could be used for the evaluation of inflammation in ESRD patients undergoing renal transplantation.

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)0.079
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.508
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0790.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0100.002
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0040.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.565
GPT teacher head0.567
Teacher spread0.002 · 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.

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

Citations11
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueOpen Access Macedonian Journal of Medical SciencesSame topicInflammatory Biomarkers in Disease PrognosisFrench-language works237,207