Exploring the Correlates of Hematological Parameters With Early Diabetic Nephropathy in Type 2 Diabetes Mellitus
Bibliographic record
Abstract
BACKGROUND: Type 2 diabetes mellitus (DM) with nephropathy is a common complication in poorly controlled diabetes. Uncontrolled DM leads to intraglomerular vascular changes that cause physical injury to capillary walls, causing a profibrotic response in kidneys. The present study aimed to determine the association of hematological markers with microalbuminuria in early diabetic nephropathy. METHODS: A single-center, cross-sectional study was conducted over the period of two years at the Department of Medicine of Pradyumna Bal Memorial Hospital, Kalinga Institute of Medical Sciences. A total of 90 patients diagnosed with type 2 DM were classified into two groups (group A and group B) according to microalbuminuria; there were 45 patients in each group. Levels of hematological markers, i.e., neutrophil-to-lymphocyte ratio (NLR) and red cell distribution width (RDW), between the study groups were examined and compared. RESULTS: A significant difference in NLR was found between groups A and B (p = 0.001). A statistically significant difference in RDW was found between the groups (p = 0.015). Receiver operating characteristic curve analysis of inflammatory markers and microalbuminuria prediction showed an area under the curve of 0.814 for NLR and 0.656 for RDW. CONCLUSION: Hematological parameters like NLR and RDW are elevated in early diabetic nephropathy patients. NLR is found to be a better marker than RDW in predicting early nephropathy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".