Association between HbA<sub>1c</sub> and the development of cystic fibrosis‐related diabetes
Bibliographic record
Abstract
Abstract Aims To examine HbA1c as a predictor of risk for future development of cystic fibrosis‐related diabetes and to assess the association with the development of retinopathy in people with cystic fibrosis‐related diabetes. Methods A 7‐year retrospective longitudinal study was conducted in 50 adults with cystic fibrosis, comparing oral glucose tolerance test results with HbA1c values in predicting the development of cystic fibrosis‐related diabetes. Retinal screening data were also compared with HbA1c measurements to assess microvascular outcome. Results An HbA1c value ≥37 mmol/mol (5.5%; hazard ratio 3.49, CI 1.5–8.1) was significantly associated with the development of dysglycaemia, as defined by the oral glucose tolerance test over a 7‐year period. Severity of diabetic retinopathy was associated with a higher HbA1c and longer duration of cystic fibrosis‐related diabetes. Conclusion There is a link between HbA1c level and the future development of dysglycaemia in cystic fibrosis based on oral glucose tolerance test, as well as microvascular outcomes. Although current guidance does not advocate the use of HbA1c as a diagnostic tool in cystic fibrosis‐related diabetes, it may be of clinical use in determining individuals at risk of future development of cystic fibrosis‐related diabetes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".