Comparison of the usefulness of plasma levels of oxidatively modified forms of albumin in estimating kidney dysfunction in diabetic patients
Bibliographic record
Abstract
PURPOSE: Advanced oxidation protein products (AOPP) and ischemia-modified albumin (IMA) are forms of oxidatidatively modified albumin and have recently been investigated as indicators of oxidative stress. They are increased in different disorders, including diabetes mellitus, as a result of hyperglycaemia, oxidative stress and hypoxia. The usefulness of the plasma levels of these two parameters in estimating kidney dysfunction in type 2 diabetic patients (T2DM) was compared in this study. METHODS: Plasma levels of AOPP and IMA were determined spectrophotometrically in 218 individuals, 153 patients with T2DM and 65 healthy people.. The urinary albumin/creatinine ratio (UACR) was used as the reference to define the stage of kidney dysfunction by the assessment of the degree of albuminuria. RESULTS: Receiver Operating Characteristic (ROC) curve analysis, likelihood ratio (LR), and Youden's index (J) revealed that AOPP and IMA had acceptable sensitivities and specificities in individuals with different degrees of albuminuria; however, AOPP had higher values of the area under the curve (AUC: 0.934) than IMA, as well as 100% sensitivity and 77.01% specificity for distinguishing patients with micro- and macroalbuminuria. CONCLUSIONS: Both AOPP and IMA may be helpful clinical markers for estimating kidney dysfunction, but AOPP is better able to identify diabetic patients with nephropathy. We suggest that AOPP is almost ideal for discriminating between T2DM patients with micro- and macroalbuminuria.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".