Higher HbA1c variability is associated with increased arterial stiffness in individuals with type 1 diabetes
Bibliographic record
Abstract
Abstract Background Both long-term glycaemic variability and arterial stiffness have been recognized as cardiovascular risk factors. This study aims to investigate whether an association between these phenomena exists in individuals with type 1 diabetes. Methods This cross-sectional study included 673 adults (305 men, 368 women) with type 1 diabetes and combined available retrospective laboratory data on HbA 1c from the preceding 10 years with outcome data on arterial stiffness and clinical variables from a comprehensive study visit. HbA 1c variability was calculated as adjusted standard deviation (adj-HbA 1c -SD), coefficient of variation (HbA 1c -CV) and average real variability (HbA 1c -ARV). As measures of arterial stiffness, carotid-femoral pulse wave velocity (cfPWV; n = 335) and augmentation index (AIx; n = 653) were assessed using applanation tonometry. Results The study population had a mean age of 47.1 (± 12.0) years and a median duration of diabetes of 31.2 (21.2–41.3) years. The median number of HbA 1c assessments per individual was 17 (12–26). All three indices of HbA 1c variability were significantly correlated with both cfPWV and AIx after adjustment for sex and age ( p < 0.001). In separate multivariable linear regression models, adj-HbA 1c -SD and HbA 1c -CV were significantly associated with cfPWV ( p = 0.032 and p = 0.046, respectively) and AIx ( p = 0.028 and p = 0.049, respectively), even after adjustment for HbA 1c -mean. HbA 1c -ARV was not associated with cfPWV or AIx in the fully adjusted models. Conclusions An association independent of HbA 1c -mean was found between HbA 1c variability and arterial stiffness, suggesting a need to consider multiple HbA 1c metrics in studies assessing cardiovascular risk in type 1 diabetes. Longitudinal and interventional studies are needed to confirm any causal relationship and to find strategies for reducing long-term glycaemic variability.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| 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".