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Record W4281679108 · doi:10.1016/j.eclinm.2022.101498

Bidirectional association between glaucoma and chronic kidney disease: A systematic review and meta-analysis

2022· review· en· W4281679108 on OpenAlexaboutno aff
Faye Yu Ci Ng, Harris Jun Jie Muhammad Danial Song, Benjamin Kye Jyn Tan, Chong Boon Teo, Emmett Tsz Yeung Wong, Pui Yi Boey, Ching‐Yu Cheng

Bibliographic record

VenueEClinicalMedicine · 2022
Typereview
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsnot available
FundersNational Medical Research CouncilMedical Research CouncilSingapore Eye Research InstituteMinistry of Health -Singapore
KeywordsMedicineOdds ratioMeta-analysisInternal medicineKidney diseaseCochrane LibraryGlaucomaSubgroup analysisConfidence intervalCohort studyOphthalmology

Abstract

fetched live from OpenAlex

Background Glaucoma and chronic kidney disease (CKD) are prevalent and debilitating conditions, with common pathogenic pathways like oxidative stress and fluid dysregulation. We evaluated if there is a bidirectional association between them, as previous studies have yielded conflicting results. Methods In this systematic review and meta-analysis, we searched PubMed, Embase and Cochrane Library from inception until 15 June 2021, including full-length English articles published in peer-reviewed journals reporting on glaucoma and CKD as either exposure or outcome, among participants aged ≥18 years. We pooled overall summary estimates of odds ratios using random-effect meta-analysis and conducted subgroup meta-analyses and univariate meta regression. We assessed risk of bias using the Newcastle-Ottawa Scale (NOS) and quality of evidence using the GRADE framework. Our article is PROSPERO-registered and adherent to both PRISMA and MOOSE guidelines. This review is registered with PROSPERO (CRD42021262846). Findings We identified 14 articles comprising of 3 retrospective cohort studies and 12 cross-sectional studies from 2,428 records, including 1,978,254 participants. Risk of bias was low to moderate. Participants with CKD at baseline had higher pooled odds of glaucoma (odds ratio[OR]=1.18, 95% confidence interval[CI]=1.04-1.33, I 2 =66%, N=12) compared to participants without CKD. The association remained significant in subgroups of longitudinal studies, participants with diabetes, East Asian studies and primary open-angle glaucoma. In the reverse direction, participants with glaucoma at baseline had over three-fold higher odds of incident CKD compared to participants without glaucoma after 10-15 years of follow-up in longitudinal studies (OR=3.67, 95% CI=2.16-6.24, I 2 =75%, N=2). All studies adjusted for age and sex, while most studies adjusted for comorbidities such as diabetes and hypertension. Meta-regression identified ethnicity (East Asians vs Non-East Asians) as a significant effect moderator. Associations were robust to trim-and-fill adjustment for publication bias, single-study influence and cumulative meta-analyses. Interpretation Our meta-analysis suggests a bidirectional relationship between glaucoma and CKD, particularly among East Asians. Further studies are required to elucidate underlying mechanisms and account for differential association by ethnicity. Funding Ching-Yu Cheng is supported by Clinician Scientist Award (NMRC/CSA-SI/0012/2017) of the Singapore Ministry of Health's National Medical Research Council.

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)0.017
metaresearch head score (Gemma)0.040
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 score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.040
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0170.045
Bibliometrics0.0070.008
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.083
GPT teacher head0.388
Teacher spread0.305 · 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

Citations21
Published2022
Admission routes1
Has abstractyes

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