Diagnosis and Management of Diabetes and the Relationship of dGlucose to Kidney Function
Bibliographic record
Abstract
This article reviews different glycemic parameters and is aimed to clarify the most dependable glycemic parameter that predicts renal preservation. Glycosylated hemoglobin (HbA1c) and fasting blood glucose (FBG) are the most commonly ordered tests for the diagnosis of diabetes and are also used to indicate prevention of microvascular complications associated with diabetes. Some experts have concluded that HbA1c remains the only test that can predict microvascular complications but HbA1c is misleading with anemia. Other experts have reported that elevation of 2 hour postprandial glucose (2hPPG) or postprandial hyperglycemia is critical for the development of diabetic complications Measurement of parameters under fasting conditions is convenient in both clinical and research settings and are used to establish clinical guidelines for diabetes management and for rating efficacy of management. Despite the use of these diagnostic markers and a plethora of oral antidiabetic agents to treat diabetes, diabetic complications namely; cardiovascular disorders (CVD), end stage renal disease (ESRD) and amputation are on the rise. Although affirmative data on many of the complications are not available, the United States Renal Data System on ESRD is a testimonial to poor diabetes care. We have innovated dglucose (2hPPG-FBG) and found that dglucose relates significantly to renal function change measured by serum creatinine levels or estimated glomerular filtration rate. Our current study on dglucose confirms our previous finding and validates the importance of dglucose to aid in the management of diabetes and prevents diabetic complications. In conclusion, the new finding in this study is dglucose (2h-postprandial glucose-Fasting glucose) which convincingly relates to renal function changes. Since dglucose is a product of 2hPP glucose, keeping 2hPPG under tight control with intensive insulin therapy is fundamentally important. Further blood pressure control avoiding the use of renin-angiotensin inhibitor therapy is additive to renal protection in 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 | 0.001 | 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".