Rate of Glucose Utilization by Blood Cells in Serum and Plasma Specimens With or Without Using Preservative
Bibliographic record
Abstract
Objective: This study aims to estimate and compare the time-course change in blood glucose levels by blood cells in serum, and plasma with or without preservatives, which may reflect the rate of glucose utilization by blood cells.Method: This laboratory-based cross-sectional study was carried out using a blood specimen of 28 participants among which 14 were diagnosed with diabetes and 14 were non-diabetic.Fasting blood specimen was collected in a plain tube, Ethylene Diamine Tetra Acetic Acid (EDTA) tube, and EDTA+ Sodium Fluoride (NaF) tube.The test was performed by hourly estimation of glucose for 24 hours.Time-course changes in glucose levels in serum and plasma with or without NaF preservative were statistically compared using ANOVA test.Result: Serum and EDTA plasma glucose levels decreased gradually after the 3rd hour to 24th hour in comparison to EDTA+NaF plasma (p<0.05).The rate of glucose utilization by blood cells was significantly higher in clotted blood and anticoagulated blood (EDTA) specimens in comparison with anticoagulated blood (EDTA) containing preservative (NaF) ((p<0.05).In addition, decreased rate of glucose utilization was observed in hyperglycemic specimens compared to that of normoglycemic blood.Conclusion: Higher rate of glucose utilization by blood cells observed in serum and EDTA plasma represents a pre-analytical error in a long-standing specimen.The use of preservative NaF with EDTA significantly prevents cellular glucose utilization and stabilize plasma glucose level.In contrast, this study also shows further insight into the reduced cellular metabolic rate of glucose utilization in diabetes mellitus.
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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) | 0.001 | 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 | 0.000 | 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".