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Record W2985901957 · doi:10.1177/2474126419880391

Changes in Aqueous and Vitreous Inflammatory Cytokine Levels in Retinal Vein Occlusion: A Systematic Review and Meta-analysis

2019· review· en· W2985901957 on OpenAlexaff
Samuel A. Minaker, Ryan H. Mason, Motaz Bamakrid, Yung Lee, Rajeev H. Muni

Bibliographic record

VenueJournal of VitreoRetinal Diseases · 2019
Typereview
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsKensington HealthUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineAqueous humourCytokineRetinal VeinOphthalmologyProinflammatory cytokinePathogenesisMonocyteAqueous humorAqueous solutionRetinalInflammationInternal medicineGastroenterologyChemistry

Abstract

fetched live from OpenAlex

Purpose: Evidence suggests that inflammatory cytokines not only play a role in the pathogenesis of retinal vein occlusion (RVO) but also may be useful as biomarkers to predict disease severity and response to treatment. We aimed to quantitatively summarize data on inflammatory cytokines associated with RVO. Methods: A systematic search of peer-reviewed English-language articles was performed without year limitation up to August 19, 2019. Studies were included if they provided data on aqueous or vitreous cytokine concentrations in patients with RVO. Data were extracted from 116 studies that encompassed 3242 study eyes with RVO and 1402 control eyes. Effect sizes were generated as standardized mean differences (SMDs) of cytokine concentrations between patients with RVO vs controls. Results: Among the 4644 eyes in 116 studies, aqueous and vitreous concentrations (SMD, 95% CI, and P value) of interleukin (IL)-6 (aqueous: 1.23, 0.65 to 1.81, P < .001 vitreous: 0.70, 0.49 to 0.90, P < .001), IL-8 (aqueous: 1.11, 0.73 to 1.49, P < .001; vitreous: 1.19, 0.73 to 1.65, P < .001), monocyte chemoattractant protein 1(aqueous: 1.22, 0.72 to 1.72, P < .001; vitreous 1.42, 0.92 to 1.91, P < .001), vascular endothelial growth factor (VEGF) (aqueous: 1.52, 1.09 to 1.94, P < .001; vitreous: 0.99, 0.78 to 1.21, P < .001) were significantly higher in patients with RVO than in healthy controls. Only aqueous concentrations of IL-10 (0.81, 0.45 to 1.18, P < .001), angiopoietin 4 (1.96, 0.92 to 3.00, P < .001), and platelet-derived growth factor (PDGF)-AA (0.82, 0.35 to 1.30, P < .001) were significantly higher in patients with RVO than in healthy controls. Only the vitreous concentration of soluble intercellular adhesion molecule-1 (sICAM-1) (1.23, 0.83 to 1.63, P < .001) was significantly higher in patients with RVO. No differences, failed sensitivity analyses, or insufficient data were found between patients with RVO and healthy controls for the concentrations of the remaining cytokines. Conclusions: Several cytokines in addition to VEGF have the potential to be useful biomarkers and therapeutic targets in RVO.

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)0.011
metaresearch head score (Gemma)0.027
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 score0.017
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.027
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0170.029
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.001
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 head0.060
GPT teacher head0.357
Teacher spread0.297 · 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

Citations15
Published2019
Admission routes1
Has abstractyes

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