Continuous Glucose Monitoring Among Patients With Type 1 Diabetes in Rwanda (CAPT1D) Phase I: Prospective Observational Feasibility Study
Bibliographic record
Abstract
BACKGROUND: The development of minimally invasive continuous glucose monitoring systems (CGMs) has transformed diabetes management. CGMs have shown clinical significance by improving time in the euglycemic range, decreasing rates of hypoglycemia, and improving HbA1c. In Rwanda, CGMs are currently not in routine use, and no clinical studies of CGM use were identified in the literature. OBJECTIVE: To determine impact and feasibility of real-time CGM use among people living with T1D in Rwanda, through assessment of sensor usage, time in range, rates of hypo-and-hyperglycemia, HbA1c and rates of diabetes-related hospitalizations over time. METHODS: The Continuous Glucose Monitoring Among Patients with Type 1 Diabetes in Rwanda (CAPT1D) study is a single-arm prospective observational study conducted at the Rwandan Diabetes Association (RDA) clinic in Kigali, Rwanda, aiming to assess the impact and feasibility of CGM use in Rwanda. A cohort of 50 participants diagnosed with T1D were enrolled. Participants were at least 21 years old, undergoing multiple daily insulin therapy, and not currently pregnant. Phase I of the study was conducted over 12 months, using the Dexcom G6 CGM. Phase II and Phase III extended CGM use for an additional 6 months respectively, using the next generation, Dexcom G7 CGM. Here we report the quantitative results of the Phase I study. RESULTS: Participants used the sensor for >80% of the time throughout the study period. A significant increase in time in range was observed within 3 months, and sustained over 12 months. HbA1c decreased significantly in 3 months and stayed lower throughout the 12-month period. Mean HbA1c levels decreased by 2.8% at 6 months (p<0.01) and 3.2% at 12 months (p<0.01) A total of 12 diabetes-related hospitalizations were reported during the study period. No cases of DKA or episodes of severe hypoglycemia occurred. CONCLUSIONS: Significant and meaningful improvements in key glycemic indices indicate the potential feasibility and impact of CGM among people living with T1D in Rwanda. Future studies could be designed to include pre- and post-intervention analysis to determine the effectiveness in terms of complications and costs.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".