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Mellor J, Kuznetsov D, Heller S, Gall MA, Rosilio M, Amiel SA, Ibberson M, McGurnaghan S, Blackbourn L, Berthon W, Salem A, Qu Y, McCrimmon RJ, de Galan BE, Pedersen-Bjergaard U, Leaviss J, McKeigue PM, Colhoun HM. Risk factors and prediction of hypoglycaemia using the Hypo-RESOLVE cohort: a secondary analysis of pooled data from insulin clinical trials. Diabetologia 2024; 67:1588-1601. [PMID: 38795153 PMCID: PMC11343909 DOI: 10.1007/s00125-024-06177-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 03/28/2024] [Indexed: 05/27/2024]
Abstract
AIMS/HYPOTHESIS The objective of the Hypoglycaemia REdefining SOLutions for better liVES (Hypo-RESOLVE) project is to use a dataset of pooled clinical trials across pharmaceutical and device companies in people with type 1 or type 2 diabetes to examine factors associated with incident hypoglycaemia events and to quantify the prediction of these events. METHODS Data from 90 trials with 46,254 participants were pooled. Analyses were done for type 1 and type 2 diabetes separately. Poisson mixed models, adjusted for age, sex, diabetes duration and trial identifier were fitted to assess the association of clinical variables with hypoglycaemia event counts. Tree-based gradient-boosting algorithms (XGBoost) were fitted using training data and their predictive performance in terms of area under the receiver operating characteristic curve (AUC) evaluated on test data. Baseline models including age, sex and diabetes duration were compared with models that further included a score of hypoglycaemia in the first 6 weeks from study entry, and full models that included further clinical variables. The relative predictive importance of each covariate was assessed using XGBoost's importance procedure. Prediction across the entire trial duration for each trial (mean of 34.8 weeks for type 1 diabetes and 25.3 weeks for type 2 diabetes) was assessed. RESULTS For both type 1 and type 2 diabetes, variables associated with more frequent hypoglycaemia included female sex, white ethnicity, longer diabetes duration, treatment with human as opposed to analogue-only insulin, higher glucose variability, higher score for hypoglycaemia across the 6 week baseline period, lower BP, lower lipid levels and treatment with psychoactive drugs. Prediction of any hypoglycaemia event of any severity was greater than prediction of hypoglycaemia requiring assistance (level 3 hypoglycaemia), for which events were sparser. For prediction of level 1 or worse hypoglycaemia during the whole follow-up period, the AUC was 0.835 (95% CI 0.826, 0.844) in type 1 diabetes and 0.840 (95% CI 0.831, 0.848) in type 2 diabetes. For level 3 hypoglycaemia, the AUC was lower at 0.689 (95% CI 0.667, 0.712) for type 1 diabetes and 0.705 (95% CI 0.662, 0.748) for type 2 diabetes. Compared with the baseline models, almost all the improvement in prediction could be captured by the individual's hypoglycaemia history, glucose variability and blood glucose over a 6 week baseline period. CONCLUSIONS/INTERPRETATION Although hypoglycaemia rates show large variation according to sociodemographic and clinical characteristics and treatment history, looking at a 6 week period of hypoglycaemia events and glucose measurements predicts future hypoglycaemia risk.
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Affiliation(s)
- Joseph Mellor
- Usher Institute, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK.
| | | | - Simon Heller
- Division of Clinical Medicine, University of Sheffield, Sheffield, UK
| | - Mari-Anne Gall
- Medical & Science, Insulin, Clinical Drug Development, Novo Nordisk A/S, Soeberg, Denmark
| | - Myriam Rosilio
- Eli Lilly and Company, Diabetes Medical Unit, Neuilly sur seine, France
| | - Stephanie A Amiel
- Department of Diabetes, School of Cardiovascular and Metabolic Medicine and Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Mark Ibberson
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Stuart McGurnaghan
- Institute of Genetics and Cancer, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK
| | - Luke Blackbourn
- Institute of Genetics and Cancer, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK
| | - William Berthon
- Usher Institute, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK
| | - Adel Salem
- RW Data Assets, AI & Analytics (AIA), Novo Nordisk A/S, Soeberg, Denmark
| | - Yongming Qu
- Eli Lilly and Company, Indianapolis, IN, USA
| | - Rory J McCrimmon
- Systems Medicine, School of Medicine, University of Dundee, Dundee, UK
| | - Bastiaan E de Galan
- Department of Internal Medicine, Division of Endocrinology and Metabolic Disease, Maastricht University Medical Center, Maastricht, the Netherlands
| | | | - Joanna Leaviss
- School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK
| | - Paul M McKeigue
- Usher Institute, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK
| | - Helen M Colhoun
- Institute of Genetics and Cancer, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK
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Vonna A, Salahudeen MS, Peterson GM. Medication-Related Hospital Admissions and Emergency Department Visits in Older People with Diabetes: A Systematic Review. J Clin Med 2024; 13:530. [PMID: 38256662 PMCID: PMC10817070 DOI: 10.3390/jcm13020530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 01/05/2024] [Accepted: 01/15/2024] [Indexed: 01/24/2024] Open
Abstract
Limited data are available regarding adverse drug reactions (ADRs) and medication-related hospitalisations or emergency department (ED) visits in older adults with diabetes, especially since the emergence of newer antidiabetic agents. This systematic review aimed to explore the nature of hospital admissions and ED visits that are medication-related in older adults with diabetes. The review was conducted according to the PRISMA guidelines. Studies in English that reported on older adults (mean age ≥ 60 years) with diabetes admitted to the hospital or presenting to ED due to medication-related problems and published between January 2000 and October 2023 were identified using Medline, Embase, and International Pharmaceutical Abstracts databases. Thirty-five studies were included. Medication-related hospital admissions and ED visits were all reported as episodes of hypoglycaemia and were most frequently associated with insulins and sulfonylureas. The studies indicated a decline in hypoglycaemia-related hospitalisations or ED presentations in older adults with diabetes since 2015. However, the associated medications remain the same. This finding suggests that older patients on insulin or secretagogue agents should be closely monitored to prevent potential adverse events, and newer agents should be used whenever clinically appropriate.
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Affiliation(s)
- Azizah Vonna
- School of Pharmacy and Pharmacology, College of Health and Medicine, University of Tasmania, Hobart 7005, Australia; (M.S.S.); (G.M.P.)
- Department of Pharmacy, Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala, Banda Aceh 23111, Aceh, Indonesia
| | - Mohammed S. Salahudeen
- School of Pharmacy and Pharmacology, College of Health and Medicine, University of Tasmania, Hobart 7005, Australia; (M.S.S.); (G.M.P.)
| | - Gregory M. Peterson
- School of Pharmacy and Pharmacology, College of Health and Medicine, University of Tasmania, Hobart 7005, Australia; (M.S.S.); (G.M.P.)
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Gómez-Guijarro MD, Álvarez-Bueno C, Saz-Lara A, Sequí-Domínguez I, Lucerón-Lucas-Torres M, Cavero-Redondo I. Association between severe hypoglycaemia and risk of dementia in patients with type 2 diabetes mellitus: A systematic review and meta-analysis. Diabetes Metab Res Rev 2023; 39:e3610. [PMID: 36649373 DOI: 10.1002/dmrr.3610] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 10/04/2022] [Accepted: 11/22/2022] [Indexed: 01/19/2023]
Abstract
The aim of this systematic review was to analyse whether there is an association between severe hypoglycaemia and the incidence of dementia in patients with type 2 diabetes mellitus. We systematically searched the MEDLINE, Scopus, and Cochrane databases from their inception until September 2022 for observational studies on the association between hypoglycaemia and the risk of dementia. The DerSimonian and Laird method was used to compute a pooled estimate of the risk for such association. Risk ratio (RR) and its respective 95% confidence interval (95% CI). Two analyses were performed to estimate the risk of dementia: (i) any hypoglycaemia versus no hypoglycaemia and (ii) a dose-response analysis for one, two, or more than three hypoglycemic events versus no hypoglycaemia. PROSPERO registration number CRD42020219200. Seven studies were included. The pooled RR for the association of severe hypoglycaemia and risk of dementia was 1.47 (95% CI: 1.24-1.74). When the dose-response trend was analysed, the pooled RR for the risk of dementia was increased according to the hypoglycaemia events as follows: 1.29 (95% CI: 1.15-1.44) for one hypoglycemic event; 1.68 (95% CI: 1.38-2.04) for two hypoglycemic events; and 1.99 (95% CI: 1.48-2.68) for three or more hypoglycemic events. Our study demonstrates a 54% higher risk of dementia among people who suffer a hypoglycaemia event compared to nonhypoglycaemia. Considering our results and the prevalence of people suffering from diabetes mellitus, health education for both newly diagnosed and already diagnosed people could be a useful tool for glycaemic control, thus avoiding hypoglycaemic events.
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Affiliation(s)
| | - Celia Álvarez-Bueno
- Health and Social Research Center, Universidad de Castilla - La Mancha, Cuenca, Spain
- Universidad Politécnica y artística del Paraguay, Asunción, Paraguay
| | - Alicia Saz-Lara
- Health and Social Research Center, Universidad de Castilla - La Mancha, Cuenca, Spain
| | - Irene Sequí-Domínguez
- Health and Social Research Center, Universidad de Castilla - La Mancha, Cuenca, Spain
| | | | - Iván Cavero-Redondo
- Health and Social Research Center, Universidad de Castilla - La Mancha, Cuenca, Spain
- Facultad de Ciencias de la Salud, Universidad Autónoma de Chile, Talca, Chile
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Sebastian MJ, Khan SKA, Pappachan JM, Jeeyavudeen MS. Diabetes and cognitive function: An evidence-based current perspective. World J Diabetes 2023; 14:92-109. [PMID: 36926658 PMCID: PMC10011899 DOI: 10.4239/wjd.v14.i2.92] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 12/26/2022] [Accepted: 01/16/2023] [Indexed: 02/14/2023] Open
Abstract
Several epidemiological studies have clearly identified diabetes mellitus (DM) as a major risk factor for cognitive dysfunction, and it is going to be a major public health issue in the coming years because of the alarming rise in diabetes prevalence across the world. Brain and neural tissues predominantly depend on glucose as energy substrate and hence, any alterations in carbohydrate meta-bolism can directly impact on cerebral functional output including cognition, executive capacity, and memory. DM affects neuronal function and mental capacity in several ways, some of which include hypoperfusion of the brain tissues from cerebrovascular disease, diabetes-related alterations of glucose transporters causing abnormalities in neuronal glucose uptake and metabolism, local hyper- and hypometabolism of brain areas from insulin resistance, and recurrent hypoglycemic episodes inherent to pharmacotherapy of diabetes resulting in neuronal damage. Cognitive decline can further worsen diabetes care as DM is a disease largely self-managed by patients. Therefore, it is crucial to understand the pathobiology of cognitive dysfunction in relation to DM and its management for optimal long-term care plan for patients. A thorough appraisal of normal metabolic characteristics of the brain, how alterations in neural metabolism affects cognition, the diagnostic algorithm for patients with diabetes and dementia, and the management and prognosis of patients when they have this dangerous combination of illnesses is imperative in this context. This evidence-based narrative with the back-up of latest clinical trial reviews elaborates the current understanding on diabetes and cognitive function to empower physicians to manage their patients in day-to-day clinical practice.
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Affiliation(s)
| | - Shahanas KA Khan
- Department of Endocrinology and Metabolism, Lancashire Teaching Hospitals NHS Trust, Preston PR2 9HT, United Kingdom
| | - Joseph M Pappachan
- Department of Endocrinology and Metabolism, Lancashire Teaching Hospitals NHS Trust, Preston PR2 9HT, United Kingdom
- Faculty of Science, Manchester Metropolitan University, Manchester M15 6BH, United Kingdom
- Faculty of Biology, Medicine and Health, The University of Manchester, Manchester M13 9PL, United Kingdom
| | - Mohammad Sadiq Jeeyavudeen
- Department of Endocrinology and Metabolism, University Hospitals of Edinburgh, Edinburgh EH16 4SA, United Kingdom
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