Displaying publications 41 - 41 of 41 in total

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  1. Rama Chandran S, A Vigersky R, Thomas A, Lim LL, Ratnasingam J, Tan A, et al.
    Diabetes Technol Ther, 2020 02;22(2):103-111.
    PMID: 31502876 DOI: 10.1089/dia.2019.0277
    Background:
    Complex changes of glycemia that occur in diabetes are not fully captured by any single measure. The Comprehensive Glucose Pentagon (CGP) measures multiple aspects of glycemia to generate the prognostic glycemic risk (PGR), which constitutes the relative risk of hypoglycemia combined with long-term complications. We compare the components of CGP and PGR across type 1 and type 2 diabetes.
    Methods:
    Participants: n = 60 type 1 and n = 100 type 2 who underwent continuous glucose monitoring (CGM). Mean glucose, coefficient of variation (%CV), intensity of hypoglycemia (INThypo), intensity of hyperglycemia (INThyper), time out-of-range (TOR <3.9 and >10 mmol/L), and PGR were calculated. PGR (median, interquartile ranges [IQR]) for diabetes types, and HbA1c classes were compared.
    Results:
    While HbA1c was lower in type 1 (type 1 vs. type 2: 8.0 ± 1.6 vs. 8.6 ± 1.7, P = 0.02), CGM-derived mean glucoses were similar across both groups (P > 0.05). TOR, %CV, INThypo, and INThyper were all higher in type 1 [type 1 vs. type 2: 665 (500, 863) vs. 535 (284, 823) min/day; 39% (33, 46) vs. 29% (24, 34); 905 (205, 2951) vs. 18 (0, 349) mg/dL × min2; 42,906 (23,482, 82,120) vs. 30,166 (10,276, 57,183) mg/dL × min2, respectively, all P 
    Matched MeSH terms: Blood Glucose Self-Monitoring
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