Association between cystatin C and diabetic retinopathy among type 2 diabetic patients in China: a Meta-analysis
Bibliographic record
Abstract
AIM: To explore the correlation between cystatin C (Cys-C) and diabetic retinopathy (DR) in those patients with type 2 diabetes mellitus (DM) in China. METHODS: Articles were collected from China National Knowledge Infrastructure (CNKI), Wanfang, VIP, PubMed, EMBASE, Cochrane Library, Clinical Trials.gov, and Google Scholar. Quality and risk of bias within included studies was assessed using the Newcastle-Ottawa scale (NOS). Heterogeneity was determined by using Cochran’s Q-test and Higgins I2 statistics. Mean differences (MDs) and 95% confidence intervals (CIs) of Cys-C within the diabetes without retinopathy (DWR) and DR, DWR and non-proliferative diabetic retinopathy (NPDR), NPDR and proliferative diabetic retinopathy (PDR) were collected by using random-effects model because of high heterogeneity. Meta-analysis was conducted based on 23 articles of 2331 DR including NPDR and PDR patients and 2023 DWR patients through Review Manager 5.3. Subgroup analyses were also performed according to DM duration, body mass index (BMI), total cholesterol (TC), total triglycerides (TG), low-density lipoprotein C (LDL-C), and high-density lipoprotein C (HDL-C), sample origins and methods. Publication bias was assessed by the funnel plot. RESULTS: Cys-C level in DR patients was increased compared with that of DWR (total MD: 0.69, 95%CI: 0.41 to 0.97, Z=4.79, P<0.01). Besides, the synthesized results of the studies showed the similar findings in the DWR vs NPDR group (total MD: 0.29, 95%CI 0.20 to 0.39, Z=6.02, P<0.01) and the NPDR vs PDR group (total MD: 0.63, 95%CI 0.43 to 0.82, Z=6.33, P<0.01). Heterogeneity of most of the subgroup analyses was still obvious (I2?≥?50%, P?<?0.1). Forest plots of different subgroups indicated that there was a slight increase of Cys-C during the period between DWR and DR, DWR and NPDR, NPDR and PDR. Funnel plot showed that there was no significant publication bias. CONCLUSION: The elevated Cys-C is closely related with DR and probably plays a critical role in its progression.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.035 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".