Effect of low-frequency blood glucose self-monitoring on glycosylated hemoglobin levels among older adults with type 2 diabetes mellitus
Bibliographic record
Abstract
Background: Reducing the frequency of self-monitoring of blood sugar, due to needle phobia, pain, stress, and costs associated with the procedure, can improve patient compliance and quality of life, provided that adequate blood sugar control is maintained. This study aimed to evaluate the effect of low-frequency blood glucose self-monitoring (LFBGSM) on glycosylated hemoglobin (HbA1 C ) levels among older adults living with type 2 diabetes mellitus (T2DM), treated with or without insulin. Materials and Methods: This randomized controlled trial with a parallel design was conducted on 121 older adults with T2DM in Sabzevar, Iran, between 2018 and 2020. Initially, subjects were stratified based on the type of treatment (with or without insulin) and then randomly assigned to intervention (LFBGSM) and control (no blood glucose self-monitoring [no-BGSM]) groups. HbA1 C levels were measured at the beginning of the study and 3 months later for all study groups. Results: The mean age of participants treated with and without insulin was 64.3 ± 9.60 and 64.7 ± 5.01 years, respectively. The ANCOVA test revealed a significant difference in the mean HbA1 C levels among the four groups 3 months postintervention ( P < 0.001). The HbA1 C scores significantly decreased in the LFBGSM groups and increased in the no-BGSM groups at 3 months postintervention (insulin/LFBGSM, insulin/no-BGSM, noninsulin/LFBGSM, and noninsulin/no-BGSM: 7.74 ± 0.76, 8.34 ± 1.53, 7.70 ± 0.75, and 8.14 ± 1.11, respectively) compared to baseline (8.25 ± 0.67, 8.03 ± 0.64, 8.08 ± 0.69, and 7.83 ± 0.74, respectively). The least significant difference post hoc tests showed significant differences between specific groups, emphasizing subtle responses to interventions ( P values ranging from 0.001 to 0.929). Conclusion: Findings suggest a significant reduction in HbA1 C scores within the LFBGSM groups, while a discernible increase is observed in the no-BGSM groups over the 3 months. These findings underscore the efficacy of the interventions and emphasize the crucial role of personalized approaches in optimizing glycemic control for individuals with diabetes.
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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 | 0.011 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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".