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.
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 diabeticpatients 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.
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
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
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