Suppr超能文献

iDECIDE:一款使用基于证据的方程式来考虑患者偏好的胰岛素剂量计算移动应用程序。

iDECIDE: A Mobile Application for Insulin Dosing Using an Evidence Based Equation to Account for Patient Preferences.

作者信息

Lloyd Buffy, Groat Danielle, Cook Curtiss B, Kaufman David, Grando Adela

机构信息

Arizona State University Department of Biomedical Informatics, AZ.

出版信息

Stud Health Technol Inform. 2015;216:93-7.

Abstract

Diabetes is a complex disease affecting 29.1 million (9.3%) US citizens [1]. It is a chronic illness that needs continual medical care and ongoing patient self-management, education, and support [2]. There is no cure for diabetes, requiring patients to conduct frequent self-monitoring of blood glucose and dosing of insulin in many cases. Evidence has shown that patients are more adherent to their diabetes management plan when they incorporate personal lifestyle choices [3]. To address the challenge of empowering patients to better manage their diabetes, we have developed a novel mobile application prototype, iDECIDE, that refines rapid-acting insulin dose calculations by incorporating two important patient variables in addition to carbohydrates consumed that are not a part of standard insulin dose calculation algorithms: exercise and alcohol intake [4, 5]. A retrospective analysis for the calibration and evaluation of iDECIDE is underway by comparing recommendations made by the application against dosing recommendations made by insulin pumps.

摘要

糖尿病是一种复杂的疾病,影响着2910万(9.3%)美国公民[1]。它是一种慢性病,需要持续的医疗护理以及患者持续的自我管理、教育和支持[2]。糖尿病无法治愈,在许多情况下,患者需要频繁进行血糖自我监测并注射胰岛素。有证据表明,当患者将个人生活方式选择纳入其中时,他们会更严格地遵守糖尿病管理计划[3]。为应对帮助患者更好地管理糖尿病这一挑战,我们开发了一款新型移动应用程序原型iDECIDE,除了消耗的碳水化合物外,该应用程序还纳入了两个重要的患者变量(这两个变量并非标准胰岛素剂量计算算法的一部分):运动和酒精摄入量,从而优化速效胰岛素剂量计算[4,5]。目前正在通过将该应用程序给出的建议与胰岛素泵给出的给药建议进行比较,对iDECIDE进行校准和评估的回顾性分析。

相似文献

2
Post-prandial plasma glucose prediction in type I diabetes based on Impulse Response Models.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:1324-7. doi: 10.1109/IEMBS.2010.5626386.
3
A Mobile Application Guiding Patients With Type 1 Diabetes Using Sensor-Augmented Insulin Pump Therapy.
J Diabetes Sci Technol. 2016 Jun 28;10(4):985-6. doi: 10.1177/1932296816633486. Print 2016 Jul.
5
A novel adaptive basal therapy based on the value and rate of change of blood glucose.
J Diabetes Sci Technol. 2009 Sep 1;3(5):1099-108. doi: 10.1177/193229680900300513.
6
Model-based blood glucose control for Type 1 diabetes via parametric programming.
IEEE Trans Biomed Eng. 2006 Aug;53(8):1478-91. doi: 10.1109/TBME.2006.878075.
7
A communication and information technology infrastructure for real time monitoring and management of type 1 diabetes patients.
Annu Int Conf IEEE Eng Med Biol Soc. 2007;2007:3685-8. doi: 10.1109/IEMBS.2007.4353131.
9
Insulin algorithms in the self-management of insulin-dependent diabetes: the interactive 'Apple Juice' program.
Med Inform (Lond). 1996 Oct-Dec;21(4):327-44. doi: 10.3109/14639239608999293.
10
Characterization of Exercise and Alcohol Self-Management Behaviors of Type 1 Diabetes Patients on Insulin Pump Therapy.
J Diabetes Sci Technol. 2017 Mar;11(2):240-246. doi: 10.1177/1932296816663746. Epub 2016 Sep 25.

引用本文的文献

1
Practical applications of methods to incorporate patient preferences into medical decision models: a scoping review.
BMC Med Inform Decis Mak. 2025 Mar 3;25(1):109. doi: 10.1186/s12911-025-02945-5.
2
Issues and Ideas in Bolus Advisor Research With Commentary on "A Methodology to Compare Insulin Dosing Algorithms in Real-Life Settings".
J Diabetes Sci Technol. 2017 Nov;11(6):1183-1186. doi: 10.1177/1932296817719907. Epub 2017 Jul 6.
3
A Methodology to Compare Insulin Dosing Recommendations in Real-Life Settings.
J Diabetes Sci Technol. 2017 Nov;11(6):1174-1182. doi: 10.1177/1932296817704444. Epub 2017 Apr 13.
5
Mobile Applications for Control and Self Management of Diabetes: A Systematic Review.
J Med Syst. 2016 Sep;40(9):210. doi: 10.1007/s10916-016-0564-8. Epub 2016 Aug 13.

本文引用的文献

1
Mobile health use in low- and high-income countries: an overview of the peer-reviewed literature.
J R Soc Med. 2013 Apr;106(4):130-42. doi: 10.1177/0141076812472620.
2
Glucose meters with built-in automated bolus calculator: gadget or real value for insulin-treated diabetic patients?
Diabetes Ther. 2013 Jun;4(1):1-11. doi: 10.1007/s13300-012-0017-4. Epub 2012 Dec 19.
3
There's an app for that: content analysis of paid health and fitness apps.
J Med Internet Res. 2012 May 14;14(3):e72. doi: 10.2196/jmir.1977.
4
Evidence, preferences, recommendations--finding the right balance in patient care.
N Engl J Med. 2012 May 3;366(18):1653-5. doi: 10.1056/NEJMp1201535.
5
Guidelines for optimal bolus calculator settings in adults.
J Diabetes Sci Technol. 2011 Jan 1;5(1):129-35. doi: 10.1177/193229681100500118.
6
Standards of medical care in diabetes--2011.
Diabetes Care. 2011 Jan;34 Suppl 1(Suppl 1):S11-61. doi: 10.2337/dc11-S011.
7
Decision aids for people facing health treatment or screening decisions.
Cochrane Database Syst Rev. 2009 Jul 8(3):CD001431. doi: 10.1002/14651858.CD001431.pub2.
8
Insulin pump therapy: guidelines for successful outcomes.
Diabetes Educ. 2009 Mar-Apr;35 Suppl 2:29S-41S; quiz 28S, 42S-43S. doi: 10.1177/0145721709333493.
9
The next step in guideline development: incorporating patient preferences.
JAMA. 2008 Jul 23;300(4):436-8. doi: 10.1001/jama.300.4.436.

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