Diabetes & Metabolism Journal

Zhenqi Liu (Liu Z)

2 Articles

Technology/Device
Efficacy and Safety of Automated Insulin Delivery Systems in Patients with Type 1 Diabetes Mellitus: A Systematic Review and Meta-Analysis: Wenqi Fan, Chao Deng, Ruoyao Xu, Zhenqi Liu, Richard David Leslie, Zhiguang Zhou, Xia Li; Diabetes Metab J. 2025;49(2):235-251. Published online November 13, 2024; DOI: https://doi.org/10.4093/dmj.2024.0130

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Abstract PDF Supplementary Material PubReader ePub

Background
Automated insulin delivery (AID) systems studies are upsurging, half of which were published in the last 5 years. We aimed to evaluate the efficacy and safety of AID systems in patients with type 1 diabetes mellitus (T1DM).
Methods
We searched PubMed, Embase, Cochrane Library, Web of Science, and ClinicalTrials.gov until August 31, 2023. Randomized clinical trials that compared AID systems with other insulin-based treatments in patients with T1DM were considered eligible. Studies characteristics and glycemic metrics was extracted by three researchers independently.
Results
Sixty-five trials (3,623 patients) were included. The percentage of time in range (TIR) was 11.74% (95% confidence interval [CI], 9.37 to 14.12; P<0.001) higher with AID systems compared with control treatments. Patients on AID systems had more pronounced improvement of time below range when diabetes duration was more than 20 years (–1.80% vs. –0.86%, P=0.031) and baseline glycosylated hemoglobin lower than 7.5% (–1.93% vs. –0.87%, P=0.033). Dual-hormone full closed-loop systems revealed a greater improvement in TIR compared with hybrid closed-loop systems (–19.64% vs. –10.87%). Notably, glycemia risk index (GRI) (–3.74; 95% CI, –6.34 to –1.14; P<0.01) was also improved with AID therapy.
Conclusion
AID systems showed significant advantages compared to other insulin-based treatments in improving glucose control represented by TIR and GRI in patients with T1DM, with more favorable effect in euglycemia by dual-hormone full closedloop systems as well as less hypoglycemia for patients who are within target for glycemic control and have longer diabetes duration.

Citations

Citations to this article as recorded by

Transitioning between automated insulin delivery systems: A focus on personalisation
Pilar Isabel Beato-Víbora, Ana Chico, Jesus Moreno-Fernandez, Sharona Azriel-Mira, Lia Nattero-Chávez, Rosario Vallejo Mora, Núria Alonso-Carril, Olga Simó-Servat, Eva Aguilera-Hurtado, Luz María Reyes Céspedes, Marisol Ruiz de Adana, Marta Domínguez, Ros
Diabetes Research and Clinical Practice.2025; 222: 112070. CrossRef
Advances in Continuous Glucose Monitoring: Clinical Applications
So Yoon Kwon, Jun Sung Moon
Endocrinology and Metabolism.2025; 40(2): 161. CrossRef

Regulation of Muscle Microcirculation in Health and Diabetes: Zhenqi Liu, Seung-Hyun Ko, Weidong Chai, Wenhong Cao; Diabetes Metab J. 2012;36(2):83-89. Published online April 17, 2012; DOI: https://doi.org/10.4093/dmj.2012.36.2.83

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32 Download
7 Crossref

Abstract PDF PubReader

Insulin increases microvascular perfusion and substrate exchange surface area in muscle, which is pivotal for hormone action and substrate exchange, by activating insulin signaling cascade in the endothelial cells to produce nitric oxide. This action of insulin is closely coupled with its metabolic action and type 2 diabetes is associated with both metabolic and microvascular insulin resistance. Muscle microvascular perfusion/volume can be assessed by 1-methylxanthine metabolism, contrast-enhanced ultrasound and positron emission tomography. In addition to insulin, several factors have been shown to recruit muscle microvasculature, including exercise or muscle contraction, mixed meals, glucagon-like peptide 1 and angiotensin II type 1 receptor (AT₁R) blocker. On the other hand, factors that cause metabolic insulin resistance, such as inflammatory cytokines, free fatty acids, and selective activation of the AT₁R, are capable of causing microvascular insulin resistance. Therapies targeting microvascular insulin resistance may help prevent or control diabetes and decrease the associated cardiovascular morbidity and mortality.

Citations

Citations to this article as recorded by

Cardiovascular aging and the microcirculation of skeletal muscle: using contrast-enhanced ultrasound
Emily C. Dunford, Jason S. Au, Michaela C. Devries, Stuart M. Phillips, Maureen J. MacDonald
American Journal of Physiology-Heart and Circulatory Physiology.2018; 315(5): H1194. CrossRef
Direct Activation of Angiotensin II Type 2 Receptors Enhances Muscle Microvascular Perfusion, Oxygenation, and Insulin Delivery in Male Rats
Fei Yan, Zhaoshun Yuan, Nasui Wang, Robert M Carey, Kevin W Aylor, Li Chen, Xinmin Zhou, Zhenqi Liu
Endocrinology.2018; 159(2): 685. CrossRef
Long-term high-fat diet induces hippocampal microvascular insulin resistance and cognitive dysfunction
Zhuo Fu, Jing Wu, Tanseli Nesil, Ming D. Li, Kevin W. Aylor, Zhenqi Liu
American Journal of Physiology-Endocrinology and Metabolism.2017; 312(2): E89. CrossRef
GLP-1 Receptor Agonist Exenatide Increases Capillary Perfusion Independent of Nitric Oxide in Healthy Overweight Men
Mark M. Smits, Marcel H.A. Muskiet, Lennart Tonneijck, Mark H.H. Kramer, Michaela Diamant, Daniël H. van Raalte, Erik H. Serné
Arteriosclerosis, Thrombosis, and Vascular Biology.2015; 35(6): 1538. CrossRef
New insights into insulin action and resistance in the vasculature
Camila Manrique, Guido Lastra, James R. Sowers
Annals of the New York Academy of Sciences.2014; 1311(1): 138. CrossRef
Angiotensin-(1–7) Recruits Muscle Microvasculature and Enhances Insulin’s Metabolic Action via Mas Receptor
Zhuo Fu, Lina Zhao, Kevin W. Aylor, Robert M. Carey, Eugene J. Barrett, Zhenqi Liu
Hypertension.2014; 63(6): 1219. CrossRef
Insulin Resistance and Skeletal Muscle Vasculature: Significance, Assessment and Therapeutic Modulators
Camila Manrique, James R. Sowers
Cardiorenal Medicine.2014; 4(3-4): 244. CrossRef

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