Exploring diabetes distress and its relationship to glycemic control in hospitalized patients
Bibliographic record
Abstract
Introduction: Diabetes distress (DD) influences diabetes management and glycemic control. Although widely studied internationally, its prevalence and association with HbA1c remain underexplored in France. Method: This single-center cross-sectional study included 66 patients with type 1 or type 2 diabetes hospitalized in a diabetology department. DD was assessed using the DDS17 scale, measuring a total score and subscores (emotional burden, diet and treatment, interpersonal relationships, and physician-related distress). HbA1c levels were used to assess glycemic control. Univariate tests were employed for analyses. Results: The prevalence of clinically significant DD (≥ 2) was 72.73%. The emotional burden (85.39%) and diet and treatment (65.15%) subscales had the highest scores. A moderate correlation was observed between the total DD score and HbA1c (r = 0.333, p < 0.01), with the diet and treatment subscale showing the strongest correlation (r = 0.442, p < 0.001). Discussion: The results emphasize the relationship between DD and glycemic control. Limitations include the small sample size and the lack of formal validation of the French version of the DDS17.This study highlights the importance of integrating DD assessment into the care of diabetic patients. Multicenter studies are needed.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".