1.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 & Metabolism Journal 2025;49(2):235-251
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.
3.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 & Metabolism Journal 2025;49(2):235-251
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.
5.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 & Metabolism Journal 2025;49(2):235-251
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.
7.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 & Metabolism Journal 2025;49(2):235-251
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.
9.Potential utility of albumin-bilirubin and body mass index-based logistic model to predict survival outcome in non-small cell lung cancer with liver metastasis treated with immune checkpoint inhibitors.
Lianxi SONG ; Qinqin XU ; Ting ZHONG ; Wenhuan GUO ; Shaoding LIN ; Wenjuan JIANG ; Zhan WANG ; Li DENG ; Zhe HUANG ; Haoyue QIN ; Huan YAN ; Xing ZHANG ; Fan TONG ; Ruiguang ZHANG ; Zhaoyi LIU ; Lin ZHANG ; Xiaorong DONG ; Ting LI ; Chao FANG ; Xue CHEN ; Jun DENG ; Jing WANG ; Nong YANG ; Liang ZENG ; Yongchang ZHANG
Chinese Medical Journal 2025;138(4):478-480
10.Intestinal metabolites in colitis-associated carcinogenesis: Building a bridge between host and microbiome.
Yating FAN ; Yang LI ; Xiangshuai GU ; Na CHEN ; Ye CHEN ; Chao FANG ; Ziqiang WANG ; Yuan YIN ; Hongxin DENG ; Lei DAI
Chinese Medical Journal 2025;138(16):1961-1972
Microbial-derived metabolites are important mediators of host-microbial interactions. In recent years, the role of intestinal microbial metabolites in colorectal cancer has attracted considerable attention. These metabolites, which can be derived from bacterial metabolism of dietary substrates, modification of host molecules such as bile acids, or directly from bacteria, strongly influence the progression of colitis-associated cancer (CAC) by regulating inflammation and immune response. Here, we review how microbiome metabolites short-chain fatty acids (SCFAs), secondary bile acids, polyamines, microbial tryptophan metabolites, and polyphenols are involved in the tumorigenesis and development of CAC through inflammation and immunity. Given the heated debate on the metabolites of microbiota in maintaining gut homeostasis, serving as tumor molecular markers, and affecting the efficacy of immune checkpoint inhibitors in recent years, strategies for the prevention and treatment of CAC by targeting intestinal microbial metabolites are also discussed in this review.
Humans
;
Gastrointestinal Microbiome/physiology*
;
Animals
;
Carcinogenesis/metabolism*
;
Colitis-Associated Neoplasms/microbiology*
;
Fatty Acids, Volatile/metabolism*
;
Bile Acids and Salts/metabolism*
;
Colitis/microbiology*

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