Pilot Study of a Prototype Integrated Diabetes Management System and the Relationship of Use to Diabetes Management Behaviors and HbA1c Among Type 2 Diabetes Patients
Bibliographic record
Abstract
Background Type 2 diabetes (T2D) is the seventh leading cause of death (2017) in the United States, and by 2030 it is estimated that it will affect 439 million globally. Effective glycemic control can be challenging for patients. A tool to guide patients’ in their self-management behaviors and share this data with their physician may improve insulin adherence leading to lower HbA1c. We examined an integrated diabetes management (IDM) system that utilizes a Bluetooth-enabled insulin event capture device, a Bluetooth-enabled glucometer, and an Android smartphone app. IDM data can be viewed by clinicians in the electronic medical record (EMR). Objective The primary aim of this study is to describe how app use is related to insulin adherence, blood glucose measurements, meal snapshots, and step count. Secondarily, we assessed the impact on HbA1c levels over a 3- and 6-month period. Methods Thirty-five participants were enrolled from Boston-area hospitals in this single-arm pilot study. Use of the IDM system was defined as the number of days per week participants logged into the app and moved past the home screen. Three app use groups were created: low app use (0.33-2.46 days per week), medium app use (2.54-5.08 days per week), and high app use (>5.4 days per week). Adherence to insulin, blood glucose measurements, and meal snapshots were defined as a ratio of actual weekly events recorded by participants’ app use divided by their physician’s recommendation. Step count was defined as the total weekly steps for each participant. Daily app-generated data on app use and indicators of diabetes management were collected. HbA1c levels were assessed via blood test at enrollment, 3-months, and 6-months. Using a hierarchical linear mixed model, we examined changes in outcome measures while accounting for random intercepts and slopes to control for variation in individual outcomes over the study. Results Overall app use (average unique days using the app per week) declined from 6.19 days to 3.00 days (at 1 and 24 weeks, respectively). Participants with high app use had significant improvement in bolus and basal insulin adherence per week (0.009 P=.041 [95% CI 0.0004 to 0.018] and 0.016 P<.001 [95% CI 0.0079 to 0.023], respectively), but participants had no significant improvements in blood glucose and meal snapshot adherence or absolute step count. HbA1c significantly decreased per week (coefficient –0.025 [95% CI –0.044 to –0.007], P=.007) with an overall change of 0.6. Participants with high app use significantly improved their HbA1c per week (–0.037 P=.016 [–0.066 to –0.0067]) compared to participants with medium and low app use, yielding a total improvement of 0.88 over 24 weeks. Conclusions Results show that bolus and basal insulin may have increased with higher app use. HbA1c significantly improved over the course of the study, along with significantly greater improvement in HbA1c among participants with higher app use compared to participants in the middle or low app use groups. This study is not designed or intended to evaluate efficacy but provides results to guide the future design and development of this prototype IDM system.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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; a candidate call from one teacher head, 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".