Comparison of Serum Biochemical and Haematological Analyses in Patients with Age-Related Macular Degeneration and Diabetic Retinopathy
Bibliographic record
Abstract
We evaluated biochemical analysis results with the aim of discovering serum levels that have possible effects and differences on age-related macular degeneration (AMD) and diabetic retinopathy (DRP). A retrospective case-control study was conducted between January 2017 and January 2018 on a total of 114 patients (84 DRP, 30 AMD) and 24 age and sex-matched control individuals. Four groups were created; 52 patients with proliferative DRP (PDR), 32 patients with nonproliferative PDR (non-PDR), 30 patients with wet AMD and 24 control individuals. Serum biochemical (HbA1C, fasting glucose, AST, ALT, C-reactive protein, albumin, total protein, uric acid, triglyceride, HDL, LDL, total cholesterol, Na, K, urine albumin) and complete blood count (CBC) analyses were performed at the time of diagnosis. Descriptive statistics, one-way ANOVA and Kruskal-Wallis tests were performed using SPSS to analyse data (Version 22.0). The mean age of patients was 63.3 years ± 6.4 (49-91year), and that of control individuals was 65.3 years ± 9.3 (50-88 year). Post hoc analysis showed statistically significant differences in HbA1c and fasting glucose levels among PDR-AMD, PDR-control, non-PDR-AMD, and non-PDR-control groups (whole, P
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".