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Rigla Cros, Mercedes, García Sáez, Gema ORCID: https://orcid.org/0000-0002-8396-8185, Villaplana, María, Caballero Ruiz, Estefanía, Pons, Belén, Méndez, Anna, Aguilar, Montserrat, Gómez Aguilera, Enrique J.
ORCID: https://orcid.org/0000-0001-6998-1407 and Hernando Pérez, María Elena
ORCID: https://orcid.org/0000-0001-6182-313X
(2015).
Successful replacement of weekly face-to-face visits by unsupervised smart home telecare in diet-treated gestational diabetes (GD).
In: "American Diabetes Association's 75th Scientific Sessions", 05/06/2015 - 09/06/2015, Boston, EE.UU. pp..
https://doi.org/10.2337/db15-932-1471.
Title: | Successful replacement of weekly face-to-face visits by unsupervised smart home telecare in diet-treated gestational diabetes (GD) |
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Author/s: |
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Item Type: | Presentation at Congress or Conference (Poster) |
Event Title: | American Diabetes Association's 75th Scientific Sessions |
Event Dates: | 05/06/2015 - 09/06/2015 |
Event Location: | Boston, EE.UU |
Title of Book: | American Diabetes Association's 75th Scientific Sessions |
Date: | 2015 |
Volume: | 64 |
Subjects: | |
Faculty: | E.T.S.I. Telecomunicación (UPM) |
Department: | Tecnología Fotónica y Bioingeniería |
Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
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We have developed a computer-based smart telemedicine system with the aim of giving automated support to GD patients while insulin is not required. The smart telemedicine system combines a platform for remote monitoring of diabetes-related parameters with a decision-support system (DSS) based on expert knowledge that generates automatic feedback to patients and/or clinicians. The DSS generates initial and follow-up diet treatments and detects the need to start insulin. Blood glucose (BG) data downloaded to the system from the patient?s glucose meter is automatically classified into mealtime intervals and moments of measurement (preprandial,postprandial) by a classifier based on a decision tree. After downloading BG data and informing on ketonuria fasting status, the patient receives an evaluation of the data and, if needed, a proposal of diet adjustment. In case insulin therapy is advised, the system also informs the responsible doctor who schedules a face-to-face appointment. Sixty-nine patients diagnosed of GD following the NDDG criteria were randomized (2:1) to use the system (active group) or to attend the usual face-to-face visits (control group). At baseline, groups were comparable regarding all the clinical variables tested. During the follow-up period (36 days (1-141)), no correction of the automated-proposed treatment was done by doctors. Mean number of BG downloads by patients was 10.2±8 (1-29) and the mean number of changes in diet automatically proposed was 0.46. Mean number of BG values/day, mean BG and the % of BG values above 140 mg/dl, pre-partum HbA1c, and all the perinatal outcomes tested were similar between the groups. Mean number of face-to-face visits performed including first visit and training was 4.8±2.8 for the control group and 1.4±0.6 for the active group (p<0.001). In conclusion, this computer-based smart telemedicine system successfully replaced face-to-face follow-up visits in women diagnosed of GD while insulin therapy was not required.
Item ID: | 44044 |
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DC Identifier: | https://oa.upm.es/44044/ |
OAI Identifier: | oai:oa.upm.es:44044 |
DOI: | 10.2337/db15-932-1471 |
Deposited by: | Memoria Investigacion |
Deposited on: | 20 Dec 2016 16:48 |
Last Modified: | 01 Apr 2023 08:31 |