Interpretation of A1C measurement in sub-Saharan Africa beyond the global A1C-Derived Average Glucose (ADAG) equation
Bibliographic record
Abstract
Introduction: optimal metabolic control is crucial for prevention of diabetes associated complications. HbA1c is a correlate of chronic hyperglycemia and is associated with long-term diabetes complications. We investigate the relationship between A1C and estimated average blood glucose (eAG) from the multicenter A1C-Derived Average Glucose (ADAG) study, in a sub-Saharan African population. Methods: forty-seven patients with diabetes mellitus and ten normoglycemic individuals were consecutively recruited from a tertiary reference hospital in Cameroon. This observational study was conducted in the framework of the ADAG study. eAG was derived from single values obtained from self-monitored blood glucose (SMBG) and from continuous glucose monitoring (CGM). Spearman correlation coefficient was used to examine the relationship between eAG and A1C levels. Results: there was a strong linear relationship between eAG using SMBG with A1C level; eAG (mmol/l) =1.22 x A1C (%) - 0.25; R2 = 0.58; p<0.001. This suggests that a one percent increase in A1C corresponds to a 1.22 mmol/l increment of eAG. A similar relationship was found between A1C level and eAG from the continuous glucose monitoring (CGM) measurements albeit with a smaller accretion; eAG (mmol/l) =0.95 x A1C (%) + 1.52; R2 = 0.52; p<0.001. The bias of the global ADAG equation was lower than 5% below A1C level of 7% and progressively increased with higher values of A1C. Conclusion: consistent with previous reports, using a population specific equation, A1C can be better derived from eAG in individuals from sub-Saharan African origin.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".