Relationship between Serum Asymmetric Dimethylarginine Level and Microvascular Complications in Diabetes Mellitus: A Meta-Analysis
Bibliographic record
Abstract
Objective. The purpose of the meta-analysis was to evaluate the relationship between serum asymmetric dimethylarginine (ADMA) level and microvascular complications in diabetes mellitus (DM) including diabetic retinopathy (DR), diabetic neuropathy (DN), and diabetic nephropathy. Methods. Studies were comprehensively identified by searching Web of Science, Embase, and PubMed databases up to August 30, 2018. The meta-analysis was carried out to compare the difference of serum ADMA concentrations of DR, DN, and diabetic nephropathy patients with healthy controls. The Newcastle-Ottawa Scale and the Agency for Healthcare Research and Quality were applied to assess the methodological quality. Chi-squared Q test and I2 statistics were applied to evaluate statistical heterogeneity. Subgroup analyses were conducted and publication bias was assessed by Egger’s test. Result. Ten studies were finally entered in the meta-analysis. Statistically significant heterogeneity was observed across these studies ( I2 = 77.0%, p < 0.001). Compared with DM without microvascular complications, circulating level of ADMA was significantly higher in DM with microvascular complications (all p < 0.05). Sensitivity analysis suggested that the results of this meta-analysis were shown to be stable. There was no significant publication bias (P=0.823). Conclusion. Elevated ADMA levels correlate with diabetic microangiopathies such as DR and diabetic nephropathy. ADMA may play an important role in the pathobiology of microvascular complications of diabetes.
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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 | 0.015 | 0.024 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.068 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".