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Record W4401889233 · doi:10.2196/57168

Association Between Fatty Liver Index and Incidence of Cataract Surgery in Individuals Aged 50 Years and Older Based on the Korean National Health Insurance Service-Health Screening Cohort (NHIS-HEALS) Data: Longitudinal Retrospective Cohort Study

2024· article· en· W4401889233 on OpenAlexvenueno aff
Yonghwan Kim, Kim Jeongsook, Eoi Jong Seo, Kyung Tae Kim, Jae‐woo Lee, Joungyoun Kim, Hee‐Taik Kang

Bibliographic record

VenueJMIR Public Health and Surveillance · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnexins and lens biology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIncidence (geometry)Hazard ratioCataract surgeryNonalcoholic fatty liver diseaseCohortConfoundingProportional hazards modelCohort studyInternal medicineFatty liverSurgeryDiseaseConfidence interval

Abstract

fetched live from OpenAlex

Background: Cataract is a leading cause of vision impairment. Obesity-related risk factors, including insulin resistance, increase the risk of cataract. The fatty liver index (FLI) is a biomarker for noninvasive fat layer prediction of nonalcoholic fatty liver disease. The FLI has been used to evaluate the metabolic contribution in other organs besides the eye. However, no study exists on the FLI and eye disease. Objective: This retrospective cohort study for the association between the FLI and incidence of cataract surgery in individuals older than 50 years was designed to show that a higher FLI is associated with an increased incidence of cataract surgery in individuals aged 50 years and older. Methods: This study was retrospectively designed based on the Korean National Health Insurance Service-Health Screening Cohort (NHIS-HEALS) cohort (median follow-up of 9.8 years). Participants were assigned to 1 of 3 groups based on the FLI: low (FLI<30), intermediate (FLI 30-59), or high (FLI≥60). Kaplan-Meier survival analysis was performed on the cumulative incidence of all-cataract and senile-cataract surgery. Multivariable Cox proportional hazards regression models were used to study the association between the FLI group and cataract surgery after adjusting for potential confounders. Results: Of the 138,347 included participants, the incidence of cataract surgery was 12.49% (4779/38,274), 13.95% (6680/47,875), and 14.16% (7496/52,930) in the low, intermediate, and high FLI groups, respectively. After adjusting for all confounding factors, hazard ratios (HRs; 95% CIs) in the high FLI group for all-cataract surgery were 1.111 (1.028-1.199) and 1.184 (1.101-1.274) in men and women, respectively, when compared with the low FLI group. HRs (95% CIs) in the high FLI group for senile-cataract surgery were 1.106 (1.022-1.197) and 1.147 (1.065-1.237) in men and women, respectively, when compared with the low FLI group. The project was conducted between August 2023 and February 2024 without donations from external bodies. Conclusions: Individuals with a higher FLI had a higher risk of all-cataract surgery. This association was maintained even after limiting the analyses to senile-cataract surgery.

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)0.001
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.043
GPT teacher head0.322
Teacher spread0.279 · 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
GenreEmpirical

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

Citations3
Published2024
Admission routes1
Has abstractyes

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