Definition of Norma / Prediabetes Cut-off Point for Fasting Glycaemia on the Basis of Glucose Tolerance Test and HbA1c Interrelationships
Bibliographic record
Abstract
Abstract Unification of the approach to the diagnosis of prediabetes (PD) is hardly in doubt. The borderline between PD and diabetes is recognized by all, as well as the upper and lower bounds of PD according to the results of glycemia 120 minutes after 75 g glucose loading (GL120). There are still ambiguities regarding glycohemoglobin (HbA1c) and fasting glycemia (FG). For determination of the Norma/PD cut-off point for FG, we analyzed 85 nondiabetic glucose tolerance test results (75.0 glucose; Samples of fasting blood, and 30, 60, 90, 120 minutes after glucose loading) by using correlation and regression analysis. Glycemic values were measured in mg/dl, HbA1c values were measured in %. The fact of identifying the relationship between FG and Gl120 (r=+0.52 [95%CI +0.346, +0.659]; p<0.001), as well as between FG and HbA1c (r=+0.59 [95%CI +0.432, +0.713]; p<0.001) were the basis of this study. As a result of using regression analysis, multiple regression equations were obtained. GL0 =-4.2439 + 0.1927 * GL120 + 15.462 * HbA1c If GL120 is equal to 139 mg/dl (in accordance with all recommendations), and HbA1c is equal to 5.9% (in accordance with the recommendations of NICE, Canadian Diabetes Association, Australian Diabetes Association, et al.), the maximal normal value for FG should be equal to 114 mg/dl. If GL120 is 139 mg/dl and HbA1c is 5.6% (as recommended by the American Diabetes Association), the maximum normal value of FG should be 109 mg/dl. The optimal upper limit of normal carbohydrate metabolism is levels of GL120 equal to 139 mg/dl, HbA1c - equal to 5.6%, and FG - equal to 109 mg/dl. Values above these and below diabetic levels (200 mg/dl, 6.5%, and 126 mg/dl, respectively) can be considered as prediabetes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".