Suppr超能文献

夜间预测性低血糖暂停系统对1型糖尿病青少年和成人低血糖风险因素的疗效

Efficacy of an Overnight Predictive Low-Glucose Suspend System in Relation to Hypoglycemia Risk Factors in Youth and Adults With Type 1 Diabetes.

作者信息

Calhoun Peter M, Buckingham Bruce A, Maahs David M, Hramiak Irene, Wilson Darrell M, Aye Tandy, Clinton Paula, Chase Peter, Messer Laurel, Kollman Craig, Beck Roy W, Lum John

机构信息

Jaeb Center for Health Research, Tampa, FL, USA.

Department of Pediatrics, Division of Pediatric Endocrinology and Diabetes, Stanford University School of Medicine, Stanford, CA, USA.

出版信息

J Diabetes Sci Technol. 2016 Nov 1;10(6):1216-1221. doi: 10.1177/1932296816645119. Print 2016 Nov.

Abstract

BACKGROUND

We developed a system to suspend insulin pump delivery overnight when the glucose trend predicts hypoglycemia. This predictive low-glucose suspend (PLGS) system substantially reduces nocturnal hypoglycemia without an increase in morning ketosis. Evaluation of hypoglycemia risk factors that could potentially influence the efficacy of the system remains critical for understanding possible problems with the system and identifying patients that may have the greatest benefit when using the system.

METHODS

The at-home randomized trial consisted of 127 study participants with hemoglobin A1c (A1C) of ≤8.5% (mmol/mol) for patients aged 4-14 years and ≤8.0% for patient aged 15-45 years. Factors assessed included age, gender, A1C, diabetes duration, daily percentage basal insulin, total daily dose of insulin (units/kg-day), bedtime BG, bedtime snack, insulin on board, continuous glucose monitor (CGM) rate of change (ROC), day of the week, time system activated, daytime exercise intensity, and daytime CGM-measured hypoglycemia.

RESULTS

The PLGS system was effective in preventing hypoglycemia for each factor subgroup. There was no evidence that the PLGS system was more or less effective in preventing hypoglycemia in any one subgroup compared with the other subgroups based on that factor. In addition, the effect of the system on overnight hyperglycemia did not differ in subgroups.

CONCLUSIONS

The PLGS system tested in this study effectively reduced hypoglycemia without a meaningful increase in hyperglycemia across a variety of factors.

摘要

背景

我们开发了一种系统,当血糖趋势预测会发生低血糖时,该系统会在夜间暂停胰岛素泵输注。这种预测性低血糖暂停(PLGS)系统可大幅降低夜间低血糖的发生率,且不会增加晨起酮症。评估可能影响该系统疗效的低血糖风险因素,对于理解该系统可能存在的问题以及确定使用该系统可能获益最大的患者仍然至关重要。

方法

这项居家随机试验纳入了127名研究参与者,4至14岁患者的糖化血红蛋白(A1C)≤8.5%(mmol/mol),15至45岁患者的A1C≤8.0%。评估的因素包括年龄、性别、A1C、糖尿病病程、每日基础胰岛素百分比、胰岛素每日总剂量(单位/千克·天)、睡前血糖、睡前加餐、体内胰岛素量、连续血糖监测仪(CGM)的变化率(ROC)、一周中的日期、系统激活时间、白天运动强度以及白天CGM测量的低血糖情况。

结果

PLGS系统对每个因素亚组预防低血糖均有效。没有证据表明基于该因素,PLGS系统在任何一个亚组中预防低血糖的效果比其他亚组更好或更差。此外,该系统对夜间高血糖的影响在各亚组中并无差异。

结论

本研究中测试的PLGS系统有效降低了低血糖发生率,且在各种因素下高血糖均无显著增加。

相似文献

1
Efficacy of an Overnight Predictive Low-Glucose Suspend System in Relation to Hypoglycemia Risk Factors in Youth and Adults With Type 1 Diabetes.
J Diabetes Sci Technol. 2016 Nov 1;10(6):1216-1221. doi: 10.1177/1932296816645119. Print 2016 Nov.
5
In-Clinic Evaluation of the MiniMed 670G System "Suspend Before Low" Feature in Children with Type 1 Diabetes.
Diabetes Technol Ther. 2018 Nov;20(11):731-737. doi: 10.1089/dia.2018.0209. Epub 2018 Oct 6.
8
Factors associated with nocturnal hypoglycemia in at-risk adolescents and young adults with type 1 diabetes.
Diabetes Technol Ther. 2015 Jun;17(6):385-91. doi: 10.1089/dia.2014.0342. Epub 2015 Mar 11.
9
A randomized trial of a home system to reduce nocturnal hypoglycemia in type 1 diabetes.
Diabetes Care. 2014 Jul;37(7):1885-91. doi: 10.2337/dc13-2159. Epub 2014 May 7.
10
A Review of Predictive Low Glucose Suspend and Its Effectiveness in Preventing Nocturnal Hypoglycemia.
Diabetes Technol Ther. 2019 Oct;21(10):602-609. doi: 10.1089/dia.2019.0119.

引用本文的文献

1
2025 Clinical Practice Guidelines for Diabetes Management in Korea: Recommendation of the Korean Diabetes Association.
Diabetes Metab J. 2025 Jul;49(4):582-783. doi: 10.4093/dmj.2025.0469. Epub 2025 Jul 1.
2
Perioperative use and accuracy of continuous glucose monitoring: A systematic review.
Diabetes Obes Metab. 2025 Oct;27(10):5393-5408. doi: 10.1111/dom.16583. Epub 2025 Jul 4.
3
4
An automatic deep reinforcement learning bolus calculator for automated insulin delivery systems.
Sci Rep. 2024 Jul 2;14(1):15245. doi: 10.1038/s41598-024-62912-4.
5
Utility and precision evidence of technology in the treatment of type 1 diabetes: a systematic review.
Commun Med (Lond). 2023 Oct 5;3(1):132. doi: 10.1038/s43856-023-00358-x.
7
Recreational diving in persons with type 1 and type 2 diabetes: Advancing capabilities and recommendations.
Diving Hyperb Med. 2020 Jun 30;50(2):135-143. doi: 10.28920/dhm50.2.135-143.
8
Artificial Intelligence in Decision Support Systems for Type 1 Diabetes.
Sensors (Basel). 2020 Jun 5;20(11):3214. doi: 10.3390/s20113214.
9
Modern diabetes devices in the school setting: Perspectives from school nurses.
Pediatr Diabetes. 2020 Aug;21(5):832-840. doi: 10.1111/pedi.13015. Epub 2020 Apr 22.

本文引用的文献

2
Factors associated with nocturnal hypoglycemia in at-risk adolescents and young adults with type 1 diabetes.
Diabetes Technol Ther. 2015 Jun;17(6):385-91. doi: 10.1089/dia.2014.0342. Epub 2015 Mar 11.
3
A novel method to detect pressure-induced sensor attenuations (PISA) in an artificial pancreas.
J Diabetes Sci Technol. 2014 Nov;8(6):1091-6. doi: 10.1177/1932296814553267. Epub 2014 Oct 14.
4
A randomized trial of a home system to reduce nocturnal hypoglycemia in type 1 diabetes.
Diabetes Care. 2014 Jul;37(7):1885-91. doi: 10.2337/dc13-2159. Epub 2014 May 7.
7
Threshold-based insulin-pump interruption for reduction of hypoglycemia.
N Engl J Med. 2013 Jul 18;369(3):224-32. doi: 10.1056/NEJMoa1303576. Epub 2013 Jun 22.
8
Nocturnal glucose control with an artificial pancreas at a diabetes camp.
N Engl J Med. 2013 Feb 28;368(9):824-33. doi: 10.1056/NEJMoa1206881.
9
Factors influencing the effectiveness of glucagon for preventing hypoglycemia.
J Diabetes Sci Technol. 2010 Nov 1;4(6):1305-10. doi: 10.1177/193229681000400603.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验