Bone Lead Levels and Risk of Incident Primary Open-Angle Glaucoma: The VA Normative Aging Study
Bibliographic record
Abstract
Abstract Background: Oxidative stress may play an important role in the etiology of primary open-angle glaucoma (POAG). The association between risk of POAG and lead exposure, which is an environmental source of oxidative stress, has not been fully investigated yet. Objective: Our objective was to determine the association between bone lead—a biomarker of cumulative lead dose (tibia lead) or an endogenous source of stored lead (patella lead)—and incident POAG. Methods: We examined a prospective cohort of 634 POAG-free men [mean baseline age=66.8 y of age (SD=6.7)] from the Normative Aging Study (NAS) who had tibia and patella K X-ray fluorescence lead measurements between 1 January 1991 and 31 December 1999. They also had standard ocular evaluations by NAS optometrists until 31 December 2014. POAG cases were identified by consistent reports of enlarged or asymmetric cup-to-disc ratio together with visual field defect or existence of disc hemorrhage. We used Cox proportional hazards regressions to estimate hazard ratios (HRs) of incident POAG and adjusted survival curves to examine changes in the risk of POAG during follow-up according to bone lead quartiles. Results: We identified 44 incident cases of POAG by the end of follow-up (incidence rate=74 per 10,000 person-years; median follow-up=10.6 y). In fully adjusted models, 10-fold increases in patella lead and tibia lead were associated with HRs of 5.06 (95% CI: 1.61, 15.88, p=0.005) and 3.07 (95% CI: 0.94, 10.0, p=0.06), respectively. The HRs comparing participants in the third and fourth quartiles with the lowest quartile were 3.41 (95% CI: 1.34, 8.66) and 3.24 (95% CI: 1.22, 8.62) for patella lead (p-for-trend=0.01), and 3.84 (95% CI: 1.54, 9.55) and 2.61 (95% CI: 0.95, 7.21) for tibia lead (p-for-trend=0.02). Conclusions: Our study provides longitudinal evidence that bone lead may be an important risk factor for POAG in the U.S. population. https://doi.org/10.1289/EHP3442
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".