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Distinction of cardiometabolic profiles among people ≥75 years with type 2 diabetes: a latent profile analysis

BACKGROUND: Older patients with type 2 diabetes mellitus represent a heterogeneous group in terms of metabolic profile. It makes glucose-lowering-therapy (GLT) complex to manage, as it needs to be individualised according to the patient profile. This study aimed to identify and characterize subgroup...

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Autores principales: CHRISTIAENS, Antoine, HERMANS, Michel P., BOLAND, Benoit, HENRARD, Séverine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6683451/
https://www.ncbi.nlm.nih.gov/pubmed/31382941
http://dx.doi.org/10.1186/s12902-019-0411-2
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author CHRISTIAENS, Antoine
HERMANS, Michel P.
BOLAND, Benoit
HENRARD, Séverine
author_facet CHRISTIAENS, Antoine
HERMANS, Michel P.
BOLAND, Benoit
HENRARD, Séverine
author_sort CHRISTIAENS, Antoine
collection PubMed
description BACKGROUND: Older patients with type 2 diabetes mellitus represent a heterogeneous group in terms of metabolic profile. It makes glucose-lowering-therapy (GLT) complex to manage, as it needs to be individualised according to the patient profile. This study aimed to identify and characterize subgroups existing among older patients with diabetes. METHODS: Retrospective observational cohort study of outpatients followed in a Belgian diabetes clinic. Included participants were all aged ≥75 years, diagnosed with type 2 diabetes, Caucasian, and had a Homeostasis Model Assessment (HOMA2). A latent profile analysis was conducted to classify patients using the age at diabetes diagnosis and HOMA2 variables, i.e. insulin sensitivity (HOMA2%-S), beta-cell-function (HOMA2%-β), and the product between both (HOMA2%-βxS; as a measure of residual beta-cell function). GLT was expressed in defined daily dose (DDD). RESULTS: In total, 147 patients were included (median age: 80 years; 37.4% women; median age at diabetes diagnostic: 62 years). The resulting model classified patients into 6 distinct cardiometabolic profiles. Patients in profiles 1 and 2 had an older age at diabetes diagnosis (median: 68 years) and a lesser decrease in HOMA2%-S, as compared to other profiles. They also presented with the highest HOMA2%-βxS values. Patients in profiles 3, 4 and 5 had a moderate decrease in HOMA2%-βxS. Patients in profile 6 had the largest decrease in HOMA2%-β and HOMA2%-βxS. This classification was associated with significant differences in terms of HbA1c values and GLT total DDD between profiles. Thus, patients in profiles 1 and 2 presented with the lowest HbA1c values (median: 6.5%) though they received the lightest GLT (median GLT DDD: 0.75). Patients in profiles 3 to 5 presented with intermediate values of HbA1c (median: 7.3% and GLT DDD (median: 1.31). Finally, patients in profile 6 had the highest HbA1c values (median: 8.4%) despite receiving the highest GLT DDD (median: 2.28). Other metabolic differences were found between profiles. CONCLUSIONS: This study identified 6 groups among patients ≥75 years with type 2 diabetes by latent profile analysis, based on age at diabetes diagnosis, insulin sensitivity, absolute and residual β-cell function. Intensity and choice of GLT should be adapted on this basis in addition to other existing recommendations for treatment individualisation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12902-019-0411-2) contains supplementary material, which is available to authorized users.
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spelling pubmed-66834512019-08-09 Distinction of cardiometabolic profiles among people ≥75 years with type 2 diabetes: a latent profile analysis CHRISTIAENS, Antoine HERMANS, Michel P. BOLAND, Benoit HENRARD, Séverine BMC Endocr Disord Research Article BACKGROUND: Older patients with type 2 diabetes mellitus represent a heterogeneous group in terms of metabolic profile. It makes glucose-lowering-therapy (GLT) complex to manage, as it needs to be individualised according to the patient profile. This study aimed to identify and characterize subgroups existing among older patients with diabetes. METHODS: Retrospective observational cohort study of outpatients followed in a Belgian diabetes clinic. Included participants were all aged ≥75 years, diagnosed with type 2 diabetes, Caucasian, and had a Homeostasis Model Assessment (HOMA2). A latent profile analysis was conducted to classify patients using the age at diabetes diagnosis and HOMA2 variables, i.e. insulin sensitivity (HOMA2%-S), beta-cell-function (HOMA2%-β), and the product between both (HOMA2%-βxS; as a measure of residual beta-cell function). GLT was expressed in defined daily dose (DDD). RESULTS: In total, 147 patients were included (median age: 80 years; 37.4% women; median age at diabetes diagnostic: 62 years). The resulting model classified patients into 6 distinct cardiometabolic profiles. Patients in profiles 1 and 2 had an older age at diabetes diagnosis (median: 68 years) and a lesser decrease in HOMA2%-S, as compared to other profiles. They also presented with the highest HOMA2%-βxS values. Patients in profiles 3, 4 and 5 had a moderate decrease in HOMA2%-βxS. Patients in profile 6 had the largest decrease in HOMA2%-β and HOMA2%-βxS. This classification was associated with significant differences in terms of HbA1c values and GLT total DDD between profiles. Thus, patients in profiles 1 and 2 presented with the lowest HbA1c values (median: 6.5%) though they received the lightest GLT (median GLT DDD: 0.75). Patients in profiles 3 to 5 presented with intermediate values of HbA1c (median: 7.3% and GLT DDD (median: 1.31). Finally, patients in profile 6 had the highest HbA1c values (median: 8.4%) despite receiving the highest GLT DDD (median: 2.28). Other metabolic differences were found between profiles. CONCLUSIONS: This study identified 6 groups among patients ≥75 years with type 2 diabetes by latent profile analysis, based on age at diabetes diagnosis, insulin sensitivity, absolute and residual β-cell function. Intensity and choice of GLT should be adapted on this basis in addition to other existing recommendations for treatment individualisation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12902-019-0411-2) contains supplementary material, which is available to authorized users. BioMed Central 2019-08-05 /pmc/articles/PMC6683451/ /pubmed/31382941 http://dx.doi.org/10.1186/s12902-019-0411-2 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
CHRISTIAENS, Antoine
HERMANS, Michel P.
BOLAND, Benoit
HENRARD, Séverine
Distinction of cardiometabolic profiles among people ≥75 years with type 2 diabetes: a latent profile analysis
title Distinction of cardiometabolic profiles among people ≥75 years with type 2 diabetes: a latent profile analysis
title_full Distinction of cardiometabolic profiles among people ≥75 years with type 2 diabetes: a latent profile analysis
title_fullStr Distinction of cardiometabolic profiles among people ≥75 years with type 2 diabetes: a latent profile analysis
title_full_unstemmed Distinction of cardiometabolic profiles among people ≥75 years with type 2 diabetes: a latent profile analysis
title_short Distinction of cardiometabolic profiles among people ≥75 years with type 2 diabetes: a latent profile analysis
title_sort distinction of cardiometabolic profiles among people ≥75 years with type 2 diabetes: a latent profile analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6683451/
https://www.ncbi.nlm.nih.gov/pubmed/31382941
http://dx.doi.org/10.1186/s12902-019-0411-2
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