Malondialdehyde levels in diabetic retinopathy patients: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: It remains unclear whether circulating malondialdehyde (MDA) levels change in people with diabetic retinopathy (DR). This systematic review compared circulating MDA levels in diabetic people with and without DR. METHODS: PubMed, Medline (Ovid), Embase (Ovid), and Web of Science were searched for case-control studies conducted before May 2022 in English that compared circulating MDA levels in people with and without DR. The following MeSH search terms were used: ("malondialdehyde" or "thiobarbituric acid reactive substances [TBARS]" or "lipid peroxidation" or "oxidative stress") and "diabetic retinopathy." Newcastle-Ottawa Quality Assessment Scale was used to evaluate the quality of the included studies. Random-effects pairwise meta-analysis pooled the effect size with standardized mean difference (SMD) and 95% confidence intervals (CIs). RESULTS: This meta-analysis included 29 case-control studies with 1680 people with DR and 1799 people with diabetes but not DR. Compared to people without DR, the circulating MDA levels were higher in those with DR (SMD, 0.897; 95% CI, 0.631 to 1.162; P < 0.001). The study did not identify credible subgroup effects or publication bias and the sensitivity analysis confirmed the robustness of the study. CONCLUSIONS: Circulating MDA levels are higher in people with DR compared to those without. Future comparative studies that use more specific methods are required to draw firm conclusions. REGISTRATION: PROSPERO; https://www.crd.york.ac.uk/PROSPERO/ ; No. CRD42022352640.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.035 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".