Advanced Meter Features Improve Postprandial and Paired Self-Monitoring of Blood Glucose in Individuals with Diabetes: Results of the Actions with the CONTOUR Blood Glucose Meter and Behaviors in Frequent Testers (ACT) Study
Bibliographic record
Abstract
BACKGROUND: This study evaluated whether education and use of the advanced meter features of the CONTOUR(®) (Bayer HealthCare LLC, Diabetes Care, Tarrytown, NY) blood glucose monitoring system (BGMS) affect the frequency and pattern of blood glucose testing in insulin-using subjects with diabetes who routinely perform self-monitoring of blood glucose (SMBG). SUBJECTS AND METHODS: Insulin-using subjects with type 1 or type 2 diabetes were enrolled in this 6-month, multicenter, prospective study and randomized to one of two groups. The basic meter features group (BMF group) received basic instruction in the use of the BGMS, whereas the advanced meter features group (AMF group) also received training in the use of advanced features, including the meal marker and audible reminder, and were instructed to use these features. Both groups received education on the importance of postprandial testing. RESULTS: The AMF group (n=105) had significantly greater average weekly postprandial blood glucose testing than the BMF group (n=106) at each follow-up visit (P<0.001) and significantly increased the frequency of paired blood glucose testing (P<0.001) as well. In both groups, glycated hemoglobin decreased significantly as postprandial testing frequency increased (P<0.05). Subject reports indicated that use of advanced features made postmeal SMBG considerably easier to remember, helped them better understand how to make decisions on their own, and increased their confidence in meal choices. CONCLUSIONS: Study findings showed that advanced features of the CONTOUR BGMS increased structured testing as measured by postprandial and paired SMBG and were perceived as useful by patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".