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<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/"><rdf:Description rdf:about="https://dirros.openscience.si/IzpisGradiva.php?id=31854"><dc:title>Insulin delivery characteristics and glycemic control in older adults with type 1 diabetes using the Minimed™ 780G system</dc:title><dc:creator>Volčanšek,	Špela	(Avtor)
	</dc:creator><dc:creator>Vidmar,	Petra	(Avtor)
	</dc:creator><dc:creator>Janež,	Andrej	(Avtor)
	</dc:creator><dc:creator>Skvarča,	Aleš	(Avtor)
	</dc:creator><dc:subject>type 1 diabetes</dc:subject><dc:subject>automated insulin delivery</dc:subject><dc:subject>advanced technologies</dc:subject><dc:description>Introduction: Diabetes self-management in older adults with type 1 diabetes (T1D) presents a unique clinical challenge, since maintaining tight glycemic control must be carefully weighed against age-related vulnerabilities. This study aimed to analyze glycemic control through the effects of customized algorithm settings in a cohort of older adults with T1D using an automated insulin delivery (AID) system. Methods: This retrospective real-world data analysis included users of the MiniMed™ 780G AID system, aged ≥60 years. Continuous glucose monitoring (CGM) data including time in range (TIR; 70–180 mg/dL; 3.9–10.0 mmol/L), time in tight range (TITR; 70–140 mg/dL; 3.9–7.8 mmol/L), time below range (TBR; &lt;70 mg/dL; &lt;3.9 mmol/L), level 2 TBR (&lt;54 mg/dL; &lt;3.0 mmol/L) and time above range (TAR; &gt;180 mg/dL; &gt;10.0 mmol/L) were analyzed alongside algorithm settings and daily insulin use. Group comparisons utilized standard parametric and non-parametric statistical tests. A multivariable logistic regression model identified independent clinical predictors of high glycemic performance (TITR ≥50%). Results: The cohort comprised 97 AID users (70.1% female, mean age 67.9 ± 6.7; range 60–90 years). Overall glycemic control was good, with mean TIR 76.1%, TITR 51.1% and TBR 1.1%. Fourteen participants (14.4%) used the manufacturer’s recommended optimal settings (ROS); i.e., target glucose of 5.5 mmol/L and active insulin time of 2 hours. CGM metrics did not differ between ROS and non-ROS users for TIR, TITR and TBR. When stratifying the cohort by glycemic performance, 55 participants (56.7%) reached TITR ≥50%; however, the adoption of ROS in high (≥50%) TITR and lower (&lt;50%) TITR subgroups was similar (16.4% vs 11.9%; Fisher p=0.58). When compared to the lower TITR subgroup, participants in the high TITR subgroup delivered less auto-correction insulin (14.2% vs 20.6%, p&lt;0.001) and a higher proportion of manual bolus insulin (46.1% vs 35.2%, p&lt;0.001), which remained a significant predictor of high TITR after multivariable adjustment. TBR was significantly higher in the high (≥50%) TITR subgroup, although it remained low in absolute terms (1.5% vs. 0.8%; p=0.017). Conclusion: While the MiniMed™ 780G AID system use is associated with low CGM-derived hypoglycemia exposure and highly effective glycemic control, regardless of customized settings, superior glycemic control is associated with a higher proportion of user-initiated manual boluses. The algorithm supports, but cannot replace, user engagement.</dc:description><dc:date>2026</dc:date><dc:date>2026-08-12 09:08:44</dc:date><dc:type>Neznano</dc:type><dc:identifier>31854</dc:identifier><dc:language>sl</dc:language></rdf:Description></rdf:RDF>
