Web-Based, Algorithm-Guided Insulin Titration in Insulin-Treated Type 2 Diabetes: Pre-Post Intervention Study
Abstract BackgroundSelf-monitoring of blood glucose (SMBG) using web-based diabetes management platforms has demonstrated promise in managing type 2 diabetes (T2D). However, the effectiveness of such systems incorporating algorithm-guided insulin titration has not been extensi...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
JMIR Publications
2025-02-01
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| Series: | JMIR Formative Research |
| Online Access: | https://formative.jmir.org/2025/1/e68914 |
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| Summary: | Abstract
BackgroundSelf-monitoring of blood glucose (SMBG) using web-based diabetes management platforms has demonstrated promise in managing type 2 diabetes (T2D). However, the effectiveness of such systems incorporating algorithm-guided insulin titration has not been extensively studied in Asian populations.
ObjectiveThis study evaluates the efficacy and safety of the ALRT telehealth solution—a US Food and Drug Administration–cleared, web-based platform that integrates SMBG with algorithm-driven insulin dose adjustments—in improving glycemia in insulin-treated T2D.
MethodsThis 24-week, pre-post intervention study enrolled 25 adults with T2D (mean age 58.9, SD 7.0 y; n=14, 56% male) on twice-daily premixed insulin. Inclusion criteria included a baseline hemoglobin A1c1c1c
ResultsParticipants achieved significant reductions in HbA1cPPPP
ConclusionsIn conclusion, patients with insulin-treated T2D initiated on a web-based glucose monitoring system with algorithm-guided dosing recommendations showed significant improvement in glycemic control compared to baseline. High adherence rates underscore the feasibility of integrating algorithm-guided insulin titration into routine care. While hypoglycemia incidence rose slightly, episodes were predominantly mild, and no severe events occurred. This intervention shows promise for broader adoption in T2D management, particularly in resource-constrained settings. |
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| ISSN: | 2561-326X |