Literature DB >> 19914853

Real-life application and validation of flexible intensive insulin-therapy algorithms in type 1 diabetes patients.

S Franc1, D Dardari, B Boucherie, J-P Riveline, M Biedzinski, C Petit, E Requeda, P Leurent, M Varroud-Vial, G Hochberg, G Charpentier.   

Abstract

AIMS: Flexible intensive insulin therapy (FIT) has become the reference standard in type 1 diabetes. Besides carbohydrate counting (CHO), it requires the use of algorithms to adjust prandial insulin doses to the number of CHO portions. As recourse to standard algorithms is usual when initiating FIT, the use of personalized algorithms would also allow more precise adjustments to be made. The aim of the present study was to validate personalized prandial algorithms for FIT as proposed by Howorka et al. in 1990.
METHODS: We conducted a 4-month observational study of 35 patients with type 1 diabetes, treated with FIT for at least 6 months, who were already using Howorka's prandial algorithms (meal-related and correctional insulin doses for blood glucose increases induced by CHO). These patients were asked to use a personal digital assistant (PDA) phone with an electronic diary (instead of a paper one) to take advantage of the computerized data-collection system to assess the quality of postprandial metabolic control.
RESULTS: Whatever the number of CHO portions, mean postprandial blood glucose values remained close to the target of 7.8mmol/L, and the compensatory algorithm allowed precise correction of preprandial hyperglycaemia. In fact, the algorithms for meal-related and correctional insulin doses at the end of the study did not differ significantly from those initially calculated, but they generally differed from one patient to another.
CONCLUSION: In type 1 diabetic patients treated with FIT, the use of individualized parameters permits fast and accurate adjustment of mealtime insulin doses, leading to good control of the postprandial state.

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Year:  2009        PMID: 19914853     DOI: 10.1016/j.diabet.2009.05.006

Source DB:  PubMed          Journal:  Diabetes Metab        ISSN: 1262-3636            Impact factor:   6.041


  10 in total

1.  Can postprandial blood glucose excursion be predicted in type 2 diabetes?

Authors:  Sylvia Franc; Dured Dardari; Caroline Peschard; Jean-Pierre Riveline; Magdalena Biedzinski; Beatrix Boucherie; Catherine Petit; Elisabeth Requeda; Frederic Mistretta; Michel Varroud-Vial; Guillaume Charpentier
Journal:  Diabetes Care       Date:  2010-06-14       Impact factor: 17.152

2.  The Diabeo software enabling individualized insulin dose adjustments combined with telemedicine support improves HbA1c in poorly controlled type 1 diabetic patients: a 6-month, randomized, open-label, parallel-group, multicenter trial (TeleDiab 1 Study).

Authors:  Guillaume Charpentier; Pierre-Yves Benhamou; Dured Dardari; Annie Clergeot; Sylvia Franc; Pauline Schaepelynck-Belicar; Bogdan Catargi; Vincent Melki; Lucy Chaillous; Anne Farret; Jean-Luc Bosson; Alfred Penfornis
Journal:  Diabetes Care       Date:  2011-01-25       Impact factor: 19.112

3.  A Minority of Patients with Type 1 Diabetes Routinely Downloads and Retrospectively Reviews Device Data.

Authors:  Jenise C Wong; Aaron B Neinstein; Matthew Spindler; Saleh Adi
Journal:  Diabetes Technol Ther       Date:  2015-07-02       Impact factor: 6.118

Review 4.  Remote Blood Glucose Monitoring in mHealth Scenarios: A Review.

Authors:  Giordano Lanzola; Eleonora Losiouk; Simone Del Favero; Andrea Facchinetti; Alfonso Galderisi; Silvana Quaglini; Lalo Magni; Claudio Cobelli
Journal:  Sensors (Basel)       Date:  2016-11-24       Impact factor: 3.576

5.  Empowerment-Based Diabetes Self-Management Education to Maintain Glycemic Targets During Ramadan Fasting in People With Diabetes Who Are on Conventional Insulin: A Feasibility Study.

Authors:  Yara M Eid; Sahar I Sahmoud; Mona M Abdelsalam; Barbara Eichorst
Journal:  Diabetes Spectr       Date:  2017-02

6.  DIABEO App Software and Telemedicine Versus Usual Follow-Up in the Treatment of Diabetic Patients: Protocol for the TELESAGE Randomized Controlled Trial.

Authors:  Nathalie Jeandidier; Lucy Chaillous; Sylvia Franc; Pierre-Yves Benhamou; Pauline Schaepelynck; Hélène Hanaire; Bogdan Catargi; Anne Farret; Pierre Fontaine; Bruno Guerci; Yves Reznik; Alfred Penfornis; Sophie Borot; Pierre Serusclat; Yacine Kherbachi; Geneviève D'Orsay; Bruno Detournay; Pierre Simon; Guillaume Charpentier
Journal:  JMIR Res Protoc       Date:  2018-04-19

Review 7.  Considerations for the Development of Mobile Phone Apps to Support Diabetes Self-Management: Systematic Review.

Authors:  Mary D Adu; Usman H Malabu; Emily J Callander; Aduli Eo Malau-Aduli; Bunmi S Malau-Aduli
Journal:  JMIR Mhealth Uhealth       Date:  2018-06-21       Impact factor: 4.773

8.  DIABEO System Combining a Mobile App Software With and Without Telemonitoring Versus Standard Care: A Randomized Controlled Trial in Diabetes Patients Poorly Controlled with a Basal-Bolus Insulin Regimen.

Authors:  Sylvia Franc; Hélène Hanaire; Pierre-Yves Benhamou; Pauline Schaepelynck; Bogdan Catargi; Anne Farret; Pierre Fontaine; Bruno Guerci; Yves Reznik; Nathalie Jeandidier; Alfred Penfornis; Sophie Borot; Lucy Chaillous; Pierre Serusclat; Yacine Kherbachi; Geneviève d'Orsay; Bruno Detournay; Pierre Simon; Guillaume Charpentier
Journal:  Diabetes Technol Ther       Date:  2020-10-14       Impact factor: 6.118

Review 9.  Artificial Intelligence in Decision Support Systems for Type 1 Diabetes.

Authors:  Nichole S Tyler; Peter G Jacobs
Journal:  Sensors (Basel)       Date:  2020-06-05       Impact factor: 3.576

10.  Follow-Up Support for Effective type 1 Diabetes self-management (The FUSED Model): A systematic review and meta-ethnography of the barriers, facilitators and recommendations for sustaining self-management skills after attending a structured education programme.

Authors:  Fiona Campbell; Julia Lawton; David Rankin; Mark Clowes; Elizabeth Coates; Simon Heller; Nicole de Zoysa; Jackie Elliott; Jenna P Breckenridge
Journal:  BMC Health Serv Res       Date:  2018-11-27       Impact factor: 2.655

  10 in total

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