Association of Whole Blood Viscosity With Metabolic Syndrome in Type 2 Diabetic Patients: Independent Association With Post-Breakfast Triglyceridemia
Bibliographic record
Abstract
Background: Associations of whole blood viscosity (WBV) with metabolic syndrome (MS) have not been extensively studied in patients with type 2 diabetes. Methods: Intrapersonal means of 12 measurements of waist circumference, blood pressure (BP) and high-density lipoprotein cholesterol and those of six measurements of fasting and post-breakfast triglycerides (TG) during 12 months were calculated in a cohort of 168 patients with type 2 diabetes. Based on these means, MS was diagnosed according to the modified National Cholesterol Education Program Adult Treatment Panel III criteria with the Asian definition of abdominal obesity. WBV was calculated from hematocrit and total serum protein concentrations by a validated formula. Results: Diabetes patients with MS (n = 77) had higher WBV as compared to those without MS (6.38 ± 0.06 vs. 6.10 ± 0.07 cP, P = 0.004). As the number of MS components increased, WBV increased (component number 1: 6.12 ± 0.10, 2: 6.09 ± 0.10, 3: 6.37 ± 0.08, 4: 6.42 ± 0.10, 5: 6.30 ± 0.15 cP, P for trends = 0.001). Multiple regression analysis revealed that male gender, diastolic BP and post-breakfast TG were determinants of WBV independent of fasting TG, body mass index (BMI) and waist circumference (R 2 = 0.258). Conclusions: Both the presence of MS and the number of MS components were associated with higher WBV in patients with type 2 diabetes. Physicians need to perform a close follow-up of type 2 diabetes patients with MS on inhibitors of sodium-glucose co-transporters 2, which may increase stroke risk associated with an increase in hematocrit and therefore blood viscosity. Post-breakfast TG was an independent determinant of WBV. Elevated WBV may represent an important confounder of the relationship between MS, postprandial hyperlipidemia and elevated cardiovascular risk in this population. J Clin Med Res. 2017;9(4):332-338 doi: https://doi.org/10.14740/jocmr2885w
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".