Evaluation of the Urinary Kidney Injury Molecule-1 Levels in Patients With Diabetic Nephropathy
Bibliographic record
Abstract
PURPOSE: Kidney Injury Molecule-1 is a protein that increases in urine following tubular damage. Kidney Injury Molecule-1 levels were correlated with the level of chronic kidney disease secondary to diabetic nephropathy in patients with type 2 Diabetes Mellitus. METHODS: Clinical and laboratory findings of 142 patients with diabetic nephropathy and 34 control subjects were analysed. Creatinine and HbA1c levels in blood samples and albumin, creatinine and Kidney Injury Molecule-1 levels in urine samples were assessed. RESULTS: Urinary Kidney Injury Molecule-1 levels were significantly increased both in subgroups of diabetic nephropathy (normo-/micro-/macro-albuminuria) and in chronic kidney disease (stage 2-4) compared with controls. Urinary Kidney Injury Molecule-1 levels in stage 2 chronic kidney disease patients were significantly higher than those of the patients with stage 3-4 chronic kidney disease. Urinary Kidney Injury Molecule-1 levels, along with urinary albumin excretion and the duration of diabetes, were found to be independent risk factors associated with low glomerular filtration rates. CONCLUSION: Urinary Kidney Injury Molecule-1 levels seems to predict renal injury secondary to diabetic nephropathy in early period independent of albuminuria, because urinary Kidney Injury Molecule-1 was elevated despite normal urinary albumin excretion in the normoalbuminuric subgroup. Urinary Kidney Injury Molecule-1 levels, which are elevated in primarily in stage 2, shows a gradual decrease in patients with chronic kidney disease stages 3 and 4; thus, urinary Kidney Injury Molecule-1 levels may be useful in tracking the progression of kidney disease.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".