The effect of free diabetes care on metabolic control and on health-related quality of life among youths with type 1 diabetes in Cameroon
Bibliographic record
Abstract
OBJECTIVE: To assess the effect of free diabetes care on metabolic control and on health-related quality of life (HRQoL) of youths living with type 1 diabetes in Cameroon. RESEARCH DESIGN AND METHODS: We conducted a clinical audit of a multicenter prospective cohort, performed in three of the nine clinics of the 'Changing Diabetes in Children' (CDiC) project in Cameroon. We collected data on demography, glycemic control, diabetes acute complications, and patients' HRQoL at baseline and after 1 year of follow-up. RESULTS: One hundred and four patients (51 female) were included. The mean age was 16±2 years (min-max: 9-18), the mean duration of diabetes was 5±3 years, and the mean HbA1C level was 11.4%±2.7%. A significant reduction in HbA1c (11.4%±2.7% vs 8.7±2.4%), episodes of severe hypoglycemia (27/104 vs 15/104), and episodes of ketoacidosis (31/104 vs 7/104) were observed after 1 year (p<0.05). We did not observe any significant difference in the total HRQoL score (p=0.66). However, we observed a significant decrease in diabetes-associated symptoms (p<0.05). Age, level of education, duration of diabetes, glycemic control, and the presence or absence of diabetes complications did not significantly affect the total HRQoL score. CONCLUSIONS: One year after free diabetes care offered through the CDiC project, a significant improvement was observed in glycemic control and acute complications of diabetes, but not in the total score of HRQoL of youths living with type 1 diabetes enrolled in the project.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".