Cystatin C and Chronic Complications of Diabetes Mellitus in a Subsaharian Population
Bibliographic record
Abstract
Background: Type 2 diabetes (T2D) is a chronic and progressive condition whose early management is crucial in preventing the occurrence of its chronic degenerative complications. Cystatin C (CysC) is a biomarker that may have a beneficial interest in the early detection of microvascular and macrovascular complications of T2D. Methods: We carried out a cross-sectional analytic study at the National Obesity Center of the Yaounde Central Hospital. We recruited 135 patients with T2D and performed a neurologic physical exam using the Toronto clinical score, a fundoscopy, ECG, ABI, and the following paraclinicals: dosage of serum levels of Cystatin C, lipid profile (with determination of Atherogenic indexes), Creatinine (with calculation of glomerular filtration rate using CKD-EPI formula) and hs-CRP. Results: Prevalences of diabetic retinopathy, nephropathy, neuropathy and PAD were 3.0%, 8.9%, 38.5%, 28.1% respectively. Electrocardiographic signs of myocardial ischemia were present in 5.9 % of the participants. We found 0.3[0.5-0.3] mg/l as median levels of the HDL-cholesterol and 0.9[1.2-0.7] mg/l for LDL-cholesterol. The median value of GFR was 105.7[119,0-85.7] ml/min/1.73m². The median serum CysC level was 0.8[0.9-0.6]mg/l and varied with age (p=0.01), A1C (p=0.016) and high blood pressure (HBP) (p=0.006). There was a relationship between serum CysC and diabetic nephropathy (p=0.01) and neuropathy (p=0.025). There was no significant relationship with diabetic retinopathy (p=0.225), PAD (p=0.169) and ECG signs of myocardial ischemia (p=0.669). Conclusion: Chronic microvascular and macrovascular complications of type 2 diabetes are common and in our study are predominantly represented by diabetic neuropathy and PAD. Serum CysC can be useful in the diagnosis of chronic complications of T2D.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| 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".