Association between glaucoma and the risk of Alzheimer's disease: A systematic review of observational studies
Bibliographic record
Abstract
Abstract To address inconsistency as well as investigate the relationship between glaucoma and the risk of Alzheimer's disease ( AD ). We systematically conducted this meta‐analysis based on observational studies published up to 15 January 2018, identified from PubMed and Web of Science. Two team members independently extracted the data and assessed the quality of each included study. Summary relative risk ( RR ) and 95% confidence intervals ( CI s) were calculated using a random‐effects model. Eight observational studies with 6870 AD cases were included. The majority of these studies (n = 6) were graded as low risk according to the Newcastle‐Ottawa Quality Assessment Scale. Individuals diagnosed with glaucoma, compared to those who were not, had an increased risk of AD ( RR = 1.52; 95% CI : 1.41–1.63; I 2 = 97%, p < 0.001). A significant finding was also observed for primary open‐angle glaucoma ( RR = 1.52; 95% CI : 1.41–1.63; I 2 = 97%, p < 0.001). However, when stratified by study design, only the case–control studies ( RR = 1.08; 95% CI : 0.89–1.31; I 2 = 37.3%, p = 0.207) yielded significant results, while the cohort studies did not ( RR = 1.08; 95% CI : 0.89–1.31; I 2 = 97.7%, p < 0.001). Of note, our meta‐regression analysis suggested that study design might be a source of heterogeneity (p = 0.009). Additionally, a significantly positive association was observed when the analyses were restricted to Asia ( RR = 2.03; 95% CI : 1.02–4.07). There was no significant publication bias in these analyses. Recent evidence suggests that glaucoma may increase the risk of AD . Additional cohort studies are needed to confirm these findings and to have improved knowledge on the true nature of this association.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".