Gender, diabetes education, and psychosocial factors are associated with persistent poor glycemic control in patients with type 2 diabetes in the <scp>J</scp>oint <scp>A</scp>sia <scp>D</scp>iabetes <scp>E</scp>valuation (<scp>JADE</scp>) program
Bibliographic record
Abstract
BACKGROUND: Factors associated with persistent poor glycemic control were explored in patients with type 2 diabetes under the Joint Asia Diabetes Evaluation (JADE) program. METHODS: Chinese adults enrolled in JADE with HbA1c ≥8% at initial comprehensive assessment (CA1) and repeat assessment were analyzed. The improved group was defined as those with a ≥1% absolute reduction in HbA1c, and the unimproved group was those with <1% reduction at the repeat CA (CA2). RESULTS: Of 4458 enrolled patients with HbA1c ≥8% at baseline, 1450 underwent repeat CA. After a median interval of 1.7 years (interquartile range[IQR] 1.1-2.2) between CA1 and CA2, the unimproved group (n = 677) had a mean 0.4% (95% confidence interval [CI] 0.3%, 0.5%) increase in HbA1c compared with a mean 2.8% reduction (95% CI -2.9, -2.6%) in the improved group (n = 773). The unimproved group had a female preponderance with lower education level, and was more likely to be insulin treated. Patients in the improved group received more diabetes education between CAs with improved self-care behaviors, whereas the unimproved group had worsening of health-related quality of life at CA2. Apart from female gender, long disease duration, low educational level, obesity, retinopathy, history of hypoglycemia, and insulin use, lack of education from diabetes nurses between CAs had the strongest association for persistent poor glycemic control. CONCLUSIONS: These results highlight the multidimensional nature of glycemic control, and the importance of diabetes education and optimizing diabetes care by considering psychosocial factors.
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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".