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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. Estimating risk of consequences following hypoglycaemia exposure using the Hypo-RESOLVE cohort: a secondary analysis of pooled data from insulin clinical trials. Diabetologia 2024:10.1007/s00125-024-06225-1. [PMID: 39037602 DOI: 10.1007/s00125-024-06225-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 05/30/2024] [Indexed: 07/23/2024]
Abstract
AIMS/HYPOTHESIS Whether hypoglycaemia increases the risk of other adverse outcomes in diabetes remains controversial, especially for hypoglycaemia episodes not requiring assistance from another person. An objective of the Hypoglycaemia REdefining SOLutions for better liVEs (Hypo-RESOLVE) project was to create and use a dataset of pooled clinical trials in people with type 1 or type 2 diabetes to examine the association of exposure to all hypoglycaemia episodes across the range of severity with incident event outcomes: death, CVD, neuropathy, kidney disease, retinal disorders and depression. We also examined the change in continuous outcomes that occurred following a hypoglycaemia episode: change in eGFR, HbA1c, blood glucose, blood glucose variability and weight. METHODS Data from 84 trials with 39,373 participants were pooled. For event outcomes, time-updated Cox regression models adjusted for age, sex, diabetes duration and HbA1c were fitted to assess association between: (1) outcome and cumulative exposure to hypoglycaemia episodes; and (2) outcomes where an acute effect might be expected (i.e. death, acute CVD, retinal disorders) and any hypoglycaemia exposure within the last 10 days. Exposures to any hypoglycaemia episode and to episodes of given severity (levels 1, 2 and 3) were examined. Further adjustment was then made for a wider set of potential confounders. The within-person change in continuous outcomes was also summarised (median of 40.4 weeks for type 1 diabetes and 26 weeks for type 2 diabetes). Analyses were conducted separately by type of diabetes. RESULTS The maximally adjusted association analysis for type 1 diabetes found that cumulative exposure to hypoglycaemia episodes of any level was associated with higher risks of neuropathy, kidney disease, retinal disorders and depression, with risk ratios ranging from 1.55 (p=0.002) to 2.81 (p=0.002). Associations of a similar direction were found when level 1 episodes were examined separately but were significant for depression only. For type 2 diabetes cumulative exposure to hypoglycaemia episodes of any level was associated with higher risks of death, acute CVD, kidney disease, retinal disorders and depression, with risk ratios ranging from 2.35 (p<0.0001) to 3.00 (p<0.0001). These associations remained significant when level 1 episodes were examined separately. There was evidence of an association between hypoglycaemia episodes of any kind in the previous 10 days and death, acute CVD and retinal disorders in both type 1 and type 2 diabetes, with rate ratios ranging from 1.32 (p=0.017) to 2.68 (p<0.0001). These associations varied in magnitude and significance when examined separately by hypoglycaemia level. Within the range of hypoglycaemia defined by levels 1, 2 and 3, we could not find any evidence of a threshold at which risk of these consequences suddenly became pronounced. CONCLUSIONS/INTERPRETATION These data are consistent with hypoglycaemia being associated with an increased risk of adverse events across several body systems in diabetes. These associations are not confined to severe hypoglycaemia requiring assistance.
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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
- Diabetes Medical Unit, Eli Lilly and Company, 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
- Division of Endocrinology and Metabolic Disease, Department of Internal Medicine, 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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Li G, Zhong S, Wang X, Zhuge F. Association of hypoglycaemia with the risks of arrhythmia and mortality in individuals with diabetes - a systematic review and meta-analysis. Front Endocrinol (Lausanne) 2023; 14:1222409. [PMID: 37645418 PMCID: PMC10461564 DOI: 10.3389/fendo.2023.1222409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Accepted: 07/24/2023] [Indexed: 08/31/2023] Open
Abstract
Background Hypoglycaemia has been linked to an increased risk of cardiac arrhythmias by causing autonomic and metabolic alterations, which may be associated with detrimental outcomes in individuals with diabetes(IWD), such as cardiovascular diseases (CVDs) and mortality, especially in multimorbid or frail people. However, such relationships in this population have not been thoroughly investigated. For this reason, we conducted a systematic review and meta-analysis. Methods Relevant papers published on PubMed, Embase, Cochrane, Web of Knowledge, Scopus, and CINHAL complete from inception to December 22, 2022 were routinely searched without regard for language. All of the selected articles included odds ratio, hazard ratio, or relative risk statistics, as well as data for estimating the connection of hypoglycaemia with cardiac arrhythmia, CVD-induced death, or total death in IWD. Regardless of the heterogeneity assessed by the I2 statistic, pooled relative risks (RRs) and 95% confidence intervals (CI) were obtained using random-effects models. Results After deleting duplicates and closely evaluating all screened citations, we chose 60 studies with totally 5,960,224 participants for this analysis. Fourteen studies were included in the arrhythmia risk analysis, and 50 in the analysis of all-cause mortality. Hypoglycaemic patients had significantly higher risks of arrhythmia occurrence (RR 1.42, 95%CI 1.21-1.68), CVD-induced death (RR 1.59, 95% CI 1.24-2.04), and all-cause mortality (RR 1.68, 95% CI 1.49-1.90) compared to euglycaemic patients with significant heterogeneity. Conclusion Hypoglycaemic individuals are more susceptible to develop cardiac arrhythmias and die, but evidence of potential causal linkages beyond statistical associations must await proof by additional specifically well planned research that controls for all potential remaining confounding factors.
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Affiliation(s)
- Gangfeng Li
- Clinical Laboratory Center, Shaoxing People’s Hospital, Shaoxing, Zhejiang, China
| | - Shuping Zhong
- Department of Hospital Management, Shaoxing People’s Hospital, Shaoxing, Zhejiang, China
| | - Xingmu Wang
- Clinical Laboratory Center, Shaoxing People’s Hospital, Shaoxing, Zhejiang, China
| | - Fuyuan Zhuge
- Department of Endocrine and Metabolism, Shaoxing People’s Hospital, Shaoxing, Zhejiang, China
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Osaga S, Kimura T, Okumura Y, Chin R, Imori M, Minatoya M. Validation study of case-identifying algorithms for severe hypoglycemia using hospital administrative data in Japan. PLoS One 2023; 18:e0289840. [PMID: 37556433 PMCID: PMC10411751 DOI: 10.1371/journal.pone.0289840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 07/26/2023] [Indexed: 08/11/2023] Open
Abstract
OBJECTIVE The purpose of this study was to evaluate the performance of algorithms for identifying cases of severe hypoglycemia in Japanese hospital administrative data. METHODS This was a multicenter, retrospective, observational study conducted at 3 acute-care hospitals in Japan. The study population included patients aged ≥18 years with diabetes who had an outpatient visit or hospital admission for possible hypoglycemia. Possible cases of severe hypoglycemia were identified using health insurance claims data and Diagnosis Procedure Combination data. Sixty-one algorithms using combinations of diagnostic codes and prescription of high concentration (≥20% mass/volume) injectable glucose were used to define severe hypoglycemia. Independent manual chart reviews by 2 physicians at each hospital were used as the reference standard. Algorithm validity was evaluated using standard performance metrics. RESULTS In total, 336 possible cases of severe hypoglycemia were identified, and 260 were consecutively sampled for validation. The best performing algorithms included 6 algorithms that had sensitivity ≥0.75, and 6 algorithms that had positive predictive values ≥0.75 with sensitivity ≥0.30. The best-performing algorithm with sensitivity ≥0.75 included any diagnoses for possible hypoglycemia or prescription of high-concentration glucose but excluded suspected diagnoses (sensitivity: 0.986 [95% confidence interval 0.959-1.013]; positive predictive value: 0.345 [0.280-0.410]). Restricting the algorithm definition to those with both a diagnosis of possible hypoglycemia and a prescription of high-concentration glucose improved the performance of the algorithm to correctly classify cases as severe hypoglycemia but lowered sensitivity (sensitivity: 0.375 [0.263-0.487]; positive predictive value: 0.771 [0.632-0.911]). CONCLUSION The case-identifying algorithms in this study showed moderate positive predictive value and sensitivity for identification of severe hypoglycemia in Japanese healthcare data and can be employed by future pharmacoepidemiological studies using Japanese hospital administrative databases.
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Affiliation(s)
- Satoshi Osaga
- Japan Drug Development and Medical Affairs, Eli Lilly Japan K.K., Kobe, Hyogo Prefecture, Japan
| | - Takeshi Kimura
- Real World Data Co., Ltd., Nakagyo Ward, Kyoto, Kyoto Prefecture, Japan
| | - Yasuyuki Okumura
- Real World Data Co., Ltd., Nakagyo Ward, Kyoto, Kyoto Prefecture, Japan
| | - Rina Chin
- Japan Drug Development and Medical Affairs, Eli Lilly Japan K.K., Kobe, Hyogo Prefecture, Japan
| | - Makoto Imori
- Japan Drug Development and Medical Affairs, Eli Lilly Japan K.K., Kobe, Hyogo Prefecture, Japan
| | - Machiko Minatoya
- Japan Drug Development and Medical Affairs, Eli Lilly Japan K.K., Kobe, Hyogo Prefecture, Japan
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Ooi SW, Yeh ST, Chang YH, Li CY, Chen HF. Different levels of hypoglycemia in patients with type 2 diabetes, their achieved mean HbA1c vs. all-cause and cardiovascular mortality. PLoS One 2023; 18:e0288360. [PMID: 37494344 PMCID: PMC10370691 DOI: 10.1371/journal.pone.0288360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 06/23/2023] [Indexed: 07/28/2023] Open
Abstract
AIM In patients with type 2 diabetes (T2D), levels of hypoglycemia and their risk of mortality are not well understood. The aim of this study was to ascertain the correlation among disparate levels of hypoglycemia and patients with T2D's achieved mean glycated hemoglobin A1c (HbA1c) with all-cause and cardiovascular mortality. METHODS 27,932 T2D patients taking hypoglycemic medications at outpatient visits for more than 6 months between 2008 and 2018 were linked to Taiwan's National Death Registry. We determined the respective mortality rates with Poisson assumption, and explored the relative risks of all-cause and cardiovascular mortality according to dissimilar levels of hypoglycemia with their achieved mean HbA1c by Cox proportional hazard regression model with adjustment of potential confounders. RESULTS T2D patients with level 3 hypoglycemia had the highest rates of all-cause and cardiovascular mortality. Compared with those who never encountered hypoglycemia, study subjects with level 1 and level 2 hypoglycemia did not show excessive risks of either all-cause or cardiovascular mortality. Only those with level 3 hypoglycemia revealed marginal risk of all-cause (Hazard ratio [HR]: 1.18; 95% Confidence Interval [CI] 1.04-1.33) but not cardiovascular mortality (HR: 1.16; 95% CI 0.88-1.53). In T2D patients with hypoglycemia, only those with mean HbA1c ≥9.0% increased all-cause mortality in level 3 hypoglycemia, and cardiovascular mortality in level 1 hypoglycemia. CONCLUSIONS Elevated risk of all-cause mortality was exclusively found in patients with level 3 hypoglycemia. In T2D patients with hypoglycemia, mean HbA1c ≥ 9% increased all-cause or cardiovascular mortality. Aggressive treatment of accompanying serious illness in severe hypoglycemia may help reduce mortality in patients with T2DM.
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Affiliation(s)
- Seng-Wei Ooi
- Department of Endocrinology, Far Eastern Memorial Hospital, New Taipei City, Taiwan
| | - Shu-Tin Yeh
- Department of Endocrinology, Far Eastern Memorial Hospital, New Taipei City, Taiwan
| | - Ya-Hui Chang
- Department of Public Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan
- Department of Surgery, Massachusetts General Hospital, Boston, MA, United States of America
| | - Chung-Yi Li
- Department of Public Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan
- Department of Public Health, College of Public Health, China Medical University, Taichung, Taiwan
- Department of Healthcare Administration, College of Medical and Health Science, Asia University, Taichung, Taiwan
| | - Hua-Fen Chen
- Department of Endocrinology, Far Eastern Memorial Hospital, New Taipei City, Taiwan
- School of Medicine and Department of Public Health, College of Medicine, Fujen Catholic University, New Taipei City, Taiwan
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Ooi SW, Yeh ST, Chang YH, Li CY, Chen HF. Low mean HbA1c does not increase all-cause and cardiovascular mortality in patients with diabetes: Effect-modifications by anemia and chronic kidney disease stages. PLoS One 2022; 17:e0272137. [PMID: 35951657 PMCID: PMC9371313 DOI: 10.1371/journal.pone.0272137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 07/13/2022] [Indexed: 11/30/2022] Open
Abstract
Background Previous studies reported that low levels of glycated hemoglobin A1c (HbA1c) were associated with increased mortality. We investigated rates and risks of all-cause and cardiovascular mortality in association with mean HbA1c levels with stratification of anemia and chronic kidney disease (CKD) stages, major causes of low HbA1c. Methods 47,145 patients with prescription of antidiabetic agents >6 months in the outpatient visits (2003–2018) were linked to Taiwan’s National Death Registry to identify all-cause and cardiovascular mortality. Poisson assumption was used to estimate the mortality rates, and the Cox proportional hazard regression model was used to evaluate the relative hazards of respective mortality in relation to mean HbA1c in different statuses of anemia and CKD stages. Results All-cause and cardiovascular mortality rates were the lowest in non-anemic stages 1–2 CKD patients, and the highest in anemic stages 3–5 CKD patients. In stages 1–2 CKD, excessive HRs observed in those with mean HbA1c <6.0% (Hazard Ratio [HR]) 1.58; 95% Confidence Interval [CI] 1.18–2.12) became inconsequential after adjustment of medications and laboratory results (HR: 1.26; 95% CI 0.89–1.79). The similar patterns were observed in anemic stages 1–2 CKD, anemic or non-anemic stages 3–5 CKD. Low HbA1c was not related to cardiovascular mortality in any anemia status or CKD staging. Conclusions Higher risks associated with low mean HbA1c and all-cause mortality were attenuated by adjustment of medications and comorbidities. It is imperative for the diabetologists to consider confounding effects of underlying illness before concluding low HbA1c associated higher mortality.
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Affiliation(s)
- Seng-Wei Ooi
- Department of Endocrinology, Far Eastern Memorial Hospital, New Taipei City, Taiwan
| | - Shu-Tin Yeh
- Department of Endocrinology, Far Eastern Memorial Hospital, New Taipei City, Taiwan
| | - Ya-Hui Chang
- Department of Public Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Chung-Yi Li
- Department of Public Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan
- Department of Public Health, College of Public Health, China Medical University, Taichung, Taiwan
- Department of Healthcare Administration, College of Medical and Health Science, Asia University, Taichung, Taiwan
| | - Hua-Fen Chen
- Department of Endocrinology, Far Eastern Memorial Hospital, New Taipei City, Taiwan
- School of Medicine and Department of Public Health, College of Medicine, Fujen Catholic University, New Taipei City, Taiwan
- * E-mail:
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Zhao X, Ming J, Qu S, Li HJ, Wu J, Ji L, Chen Y. Cost-Effectiveness of Flash Glucose Monitoring for the Management of Patients with Type 1 and Patients with Type 2 Diabetes in China. Diabetes Ther 2021; 12:3079-3092. [PMID: 34689295 PMCID: PMC8586326 DOI: 10.1007/s13300-021-01166-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 09/27/2021] [Indexed: 01/16/2023] Open
Abstract
INTRODUCTION To compare the cost-effectiveness of flash glucose monitoring versus self-monitoring of blood glucose/point of care testing (SMBG/POCT) in both patients with type 1 and patients with type 2 diabetes (T1D/T2D) receiving insulin therapy. METHODS The IQVIA CORE Diabetes Model (version 9.5) was used to project the lifetime costs and health outcomes of flash glucose monitoring and SMBG/POCT from a Chinese societal perspective. We considered both hospital and individual version flash glucose monitoring to reflect the clinical practice in China. The clinical inputs leveraged the outcomes from both clinical trials and real-world studies. Cohort characteristics, intervention costs, treatment-related disutility and mortality were extracted from the literature. We also conducted scenario analyses and probabilistic sensitivity analyses to test the robustness of results. RESULTS Compared with SMBG/POCT using efficacy results from clinical trial, flash glucose monitoring brought the incremental costs of Chinese yuan (CNY) 58,021 and CNY 90,997 and additional quality-adjusted life years (QALYs) of 1.22 and 0.65 for patients with T1D and patients with T2D, respectively. According to the "WHO-CHOICE threshold" of three times the gross domestic product per capita in China (CNY 217,341 in 2020) as cost-effectiveness threshold, flash glucose monitoring was cost-effective for both patients with T1D and patients with T2D with incremental cost-effectiveness ratios (ICER) of CNY 47,636 and CNY 140,297 per QALY gained, respectively. According to the real-world effectiveness data, flash glucose monitoring was dominant for patients with T1D (lower costs and better effectiveness) and cost-effective for patients with T2D with an ICER of CNY 124,169 per QALY gained compared with SMBG/POCT. Scenario analyses and probabilistic sensitivity analyses confirmed the robustness of the results. CONCLUSION Flash glucose monitoring is likely to be considered as a cost-effective strategy compared to SMBG/POCT for Chinese patients with T1D and patients with T2D receiving insulin therapy.
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Affiliation(s)
- Xinran Zhao
- Real World Solutions, IQVIA, Shanghai, China
| | - Jian Ming
- Real World Solutions, IQVIA, Shanghai, China
- National Health Commission Key Laboratory of Health Technology Assessment, School of Public Health, Fudan University, Shanghai, China
| | - Shuli Qu
- Real World Solutions, IQVIA, Shanghai, China
| | | | - Jing Wu
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China
| | - Linong Ji
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Beijing, China.
| | - Yingyao Chen
- National Health Commission Key Laboratory of Health Technology Assessment, School of Public Health, Fudan University, Shanghai, China.
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