2026-04-14T02:51:55Zhttps://recercat.cat/oai/request

oai:recercat.cat:10256/195952024-06-18T12:18:14Zcom_2072_452955com_2072_2054col_2072_453069

2024-06-18T12:18:13Z urn:hdl:10256/19595 Generation of Virtual Patient Populations That Represent Real Type 1 Diabetes Cohorts Ahmad, Sayyar Ramkissoon, Charrise Mary Beneyto Tantiña, Aleix Conget, Ignacio Giménez, Marga Vehí, Josep Pàncrees artificial Artificial pancreas Diabetis Diabetes Intel·ligència artificial -- Aplicacions a la medicina Artificial intelligence -- Medical applications Simulació per ordinador Computer simulation Diabetis -- Simulació per ordinador Diabetes -- Computer simulation Preclinical testing and validation of therapeutic strategies developed for patients with type 1 diabetes (T1D) require a cohort of virtual patients (VPs). However, current simulators provide a limited number of VPs, lack real-life scenarios, and inadequately represent intra- and inter-day variability in insulin sensitivity and blood glucose (BG) profile. The generation of a realistic scenario was achieved by using the meal patterns, insulin profiles (basal and bolus), and exercise sessions estimated as disturbances using clinical data from a cohort of 14 T1D patients using the Medtronic 640G insulin pump provided by the Hospital Clínic de Barcelona. The UVa/Padova’s cohort of adult patients was used for the generation of a new cohort of VPs. Insulin model parameters were optimized and adjusted in a day-by-day fashion to replicate the clinical data to create a cohort of 75 VPs. All primary and secondary outcomes reflecting the BG profile of a T1D patient were analyzed and compared to the clinical data. The mean BG 166.3 versus 162.2 mg/dL (p = 0.19), coefficient of variation 32% versus 33% (p = 0.54), and percent of time in range (70 to 180 mg/dL) 59.6% versus 66.8% (p = 0.35) were achieved. The proposed methodology for generating a cohort of VPs is capable of mimicking the BG metrics of a real cohort of T1D patients from the Hospital Clínic de Barcelona. It can adopt the inter-day variations in the BG profile, similar to the observed clinical data, and thus provide a benchmark for preclinical testing of control techniques and therapy strategies for T1D patients This work was partially supported by the Spanish Ministry of Science and Innovation through grant PID2019-107722RB-C22/AEI/10.13039/501100011033 and the Government of Catalonia under 2017SGR1551 and 2019 FI_B 01200 2024-06-18T12:18:13Z 2024-06-18T12:18:13Z 2021-05-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion peer-reviewed http://hdl.handle.net/10256/19595 info:eu-repo/semantics/altIdentifier/doi/10.3390/math9111200 info:eu-repo/semantics/altIdentifier/eissn/2227-7390 PID2019-107722RB-C22 info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-107722RB-C22/ES/PATIENT-TAILORED SOLUTIONS FOR BLOOD GLUCOSE CONTROL IN TYPE 1 DIABETES/ Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess MDPI (Multidisciplinary Digital Publishing Institute) Mathematics, 2021, vol. 9, núm. 11, p. 1200 Articles publicats (D-IMA)