Delivery of Guideline Directed Care for Inpatient Glycemic Management: Quality Improvement Implementation [0.03%]
基于指南的住院患者血糖管理质量改进实施研究
Felicia A Mendelsohn Curanaj,Mangala Rajan,Jessica Snead et al.
Felicia A Mendelsohn Curanaj et al.
Background: Effective glucose management of hospitalized individuals is essential for improving outcomes such as wound healing and reducing complications including hypoglycemia. There are many models of effective manageme...
In Support of Venous Glucose as a Reference Matrix for Evaluating Continuous Glucose Monitoring Accuracy [0.03%]
支持使用静脉血血糖作为连续葡萄糖监测准确性的参考矩阵言论
David C Klonoff,Timothy S Bailey,Tadej Battelino et al.
David C Klonoff et al.
Systematic Review of Continuous Glucose Monitor Accuracy in the Hypoglycemia Range for Non-Critical Care Ward Hospitalized People Living With Diabetes [0.03%]
连续血糖监测仪在非重症监护病房糖尿病患者低血糖范围内的准确性系统评价
Nicole Prince,Timothy Ramsay,Risa Shorr et al.
Nicole Prince et al.
In-hospital standard of care for people living with diabetes (PLWD) is based on capillary blood glucose to activate hypoglycemia treatment protocols. PLWD on non-critical care wards often prefer to keep their continuous glucose monitor (CGM...
Mudassir M Rashid,Laurie Quinn,Ali Cinar
Mudassir M Rashid
Factors Associated With Time to Automated Insulin Delivery System Initiation in Adults With Type 1 Diabetes on Multiple Daily Injections [0.03%]
与1型糖尿病患者从多次每日注射转用自动化胰岛素输注系统相关的因素
Yllka Valdez,Neha Parimi,Yoohee Claire Kim et al.
Yllka Valdez et al.
Introduction: Automated insulin delivery (AID) systems for type 1 diabetes (T1D) improve HbA1C, increase time-in-range, and reduce hypoglycemia. However, starting AID systems involves multiple steps, from decision to init...
Insulin Bolus Patterns in Newly Diagnosed Youth With Type 1 Diabetes Using a Hybrid Closed-Loop Insulin Delivery System [0.03%]
新诊断的1型糖尿病青少年使用混合闭环胰岛素输注系统的大剂量注射模式
Chloë Royston,Julia Ware,Janet M Allen et al.
Chloë Royston et al.
Background: This study aimed to investigate the decline over time in the proportion of total daily insulin delivered as boluses in newly diagnosed youth with type 1 diabetes using a hybrid closed-loop system. ...
Tight Glycemic Control Can Be Achieved in Adult ICU Patients Safely: Results From a 5-Year Single-Center Observational Study Using the STAR Glycemic Control Framework [0.03%]
使用STAR血糖控制框架的安全方法可以实现成人ICU患者的严格血糖控制：一项为期五年的单中心观察性研究的结果
Marie Seret,Vincent Uyttendaele,J Geoffrey Chase et al.
Marie Seret et al.
Background: Glycemic control (GC) is hard to implement safely in intensive care due to patient variability. GC has been wrongly blamed for increased hypoglycemic risk instead of protocol design, limiting its adoption. Sto...
Automated Insulin Delivery Systems Are Safe During Prolonged Religious Jewish Fasting Among Adolescents and Young Adults With Type 1 Diabetes [0.03%]
automated insulin delivery系统在宗教斋戒期间安全有效地用于1型糖尿病青少年患者
Eliyahu M Heifetz,Adi Auerbach,Carmit Avnon-Ziv et al.
Eliyahu M Heifetz et al.
Aims: To evaluate the outcomes of prolonged religious Jewish fasting in individuals with type 1 diabetes using automated insulin delivery (AID) systems. M...
Efficacy of an AI-Enabled Low Glucose Prediction: A Pooled Performance Analysis With Capillary Blood Glucose as Ground Truth [0.03%]
基于毛细血管血糖的AI驱动低血糖预警效能：真实世界数据分析
Timor Glatzer,Ajandek Peak,Eemeli Leppäaho et al.
Timor Glatzer et al.
Background: Hypoglycemia is a critical challenge for insulin-dependent people with diabetes using multiple daily injections (MDI), who rely on reactive responses to continuous glucose monitoring (CGM) alerts. To meet the ...
Continuous Glucose Monitoring-Based Machine Learning Identification of Diurnal Glycemic Patterns and Diabetes Distress in Type 2 Diabetes [0.03%]
基于连续葡萄糖监测的机器学习识别2型糖尿病昼夜血糖模式和糖尿病心理压力
Minjung Lee,Soohyun Nam
Minjung Lee
Background: To identify diurnal glycemic patterns in adults with type 2 diabetes (T2D) using continuous glucose monitoring (CGM)-based machine learning and examine their association with diabetes distress, a key psychosoc...