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Wang X, Cao Y. A Narrative Review: Relationship Between Glycemic Variability and Emerging Complications of Diabetes Mellitus. Biomolecules 2025; 15:188. [PMID: 40001491 PMCID: PMC11853042 DOI: 10.3390/biom15020188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2024] [Revised: 01/24/2025] [Accepted: 01/26/2025] [Indexed: 02/27/2025] Open
Abstract
A growing body of evidence emphasizes the role of glycemic variability (GV) in the development of conventional diabetes-related complications. Furthermore, advancements in diabetes management and increased life expectancy have led to the emergence of new complications, such as cancer, liver disease, fractures, infections, and cognitive dysfunction. GV is considered to exacerbate oxidative stress and inflammation, acting as a major mechanism underlying these complications. However, few reviews have synthesized the association between GV and these emerging complications or examined their underlying mechanisms. Hence, this narrative review provides a comprehensive discussion of the burden, risks, and mechanisms of GV in these complications, offering further evidence supporting GV as a potential therapeutic target for diabetes management.
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Affiliation(s)
| | - Yanli Cao
- Department of Endocrinology and Metabolism, Institute of Endocrinology, NHC Key Laboratory of Diagnosis and Treatment of Thyroid Diseases, The First Affiliated Hospital of China Medical University, Shenyang 110001, China;
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Thanh Phuc P, Nguyen PA, Nguyen NN, Hsu MH, Le NQK, Tran QV, Huang CW, Yang HC, Chen CY, Le TAH, Le MK, Nguyen HB, Lu CY, Hsu JC. Early Detection of Dementia in Populations With Type 2 Diabetes: Predictive Analytics Using Machine Learning Approach. J Med Internet Res 2024; 26:e52107. [PMID: 39434474 DOI: 10.2196/52107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 07/06/2024] [Accepted: 10/21/2024] [Indexed: 10/23/2024] Open
Abstract
BACKGROUND The possible association between diabetes mellitus and dementia has raised concerns, given the observed coincidental occurrences. OBJECTIVE This study aimed to develop a personalized predictive model, using artificial intelligence, to assess the 5-year and 10-year dementia risk among patients with type 2 diabetes mellitus (T2DM) who are prescribed antidiabetic medications. METHODS This retrospective multicenter study used data from the Taipei Medical University Clinical Research Database, which comprises electronic medical records from 3 hospitals in Taiwan. This study applied 8 machine learning algorithms to develop prediction models, including logistic regression, linear discriminant analysis, gradient boosting machine, light gradient boosting machine, AdaBoost, random forest, extreme gradient boosting, and artificial neural network (ANN). These models incorporated a range of variables, encompassing patient characteristics, comorbidities, medication usage, laboratory results, and examination data. RESULTS This study involved a cohort of 43,068 patients diagnosed with type 2 diabetes mellitus, which accounted for a total of 1,937,692 visits. For model development and validation, 1,300,829 visits were used, while an additional 636,863 visits were reserved for external testing. The area under the curve of the prediction models range from 0.67 for the logistic regression to 0.98 for the ANNs. Based on the external test results, the model built using the ANN algorithm had the best area under the curve (0.97 for 5-year follow-up period and 0.98 for 10-year follow-up period). Based on the best model (ANN), age, gender, triglyceride, hemoglobin A1c, antidiabetic agents, stroke history, and other long-term medications were the most important predictors. CONCLUSIONS We have successfully developed a novel, computer-aided, dementia risk prediction model that can facilitate the clinical diagnosis and management of patients prescribed with antidiabetic medications. However, further investigation is required to assess the model's feasibility and external validity.
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Affiliation(s)
- Phan Thanh Phuc
- College of Management, Taipei Medical University, New Taipei, Taiwan
- University Medical Center, University of Medicine and Pharmacy, Ho Chi Minh City, Vietnam
| | - Phung-Anh Nguyen
- Graduate Institute of Data Science, College of Management, Taipei Medical University, Taipei, Taiwan
- Clinical Data Center, Office of Data Science, Taipei Medical University, Taipei, Taiwan
- Research Center of Health Care Industry Data Science, College of Management, Taipei Medical University, Taipei, Taiwan
- Clinical Big Data Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan
| | - Nam Nhat Nguyen
- College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Min-Huei Hsu
- Graduate Institute of Data Science, College of Management, Taipei Medical University, Taipei, Taiwan
- Office of Data Science, Taipei Medical University, Taipei, Taiwan
| | - Nguyen Quoc Khanh Le
- Research Center for Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Quoc-Viet Tran
- Graduate Institute of Data Science, College of Management, Taipei Medical University, Taipei, Taiwan
| | - Chih-Wei Huang
- Clinical Big Data Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan
- International Center for Health Information Technology, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
| | - Hsuan-Chia Yang
- Clinical Big Data Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan
- International Center for Health Information Technology, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
- Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
| | - Cheng-Yu Chen
- Department of Radiology, College of Medicine, Taipei Medical University, Taipei, Taiwan
- Research Center for Artificial Intelligence in Medicine, Taipei Medical University, Taipei, Taiwan
| | - Thi Anh Hoa Le
- University Medical Center, University of Medicine and Pharmacy, Ho Chi Minh City, Vietnam
| | - Minh Khoi Le
- University Medical Center, University of Medicine and Pharmacy, Ho Chi Minh City, Vietnam
| | - Hoang Bac Nguyen
- University Medical Center, University of Medicine and Pharmacy, Ho Chi Minh City, Vietnam
| | - Christine Y Lu
- School of Pharmacy, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
- Kolling Institute, Faculty of Medicine and Health, The University of Sydney and the Northern Sydney Local Health District, Sydney, Australia
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, United States
| | - Jason C Hsu
- College of Management, Taipei Medical University, New Taipei, Taiwan
- Clinical Data Center, Office of Data Science, Taipei Medical University, Taipei, Taiwan
- Research Center of Health Care Industry Data Science, College of Management, Taipei Medical University, Taipei, Taiwan
- Clinical Big Data Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan
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Gonzales PNG, Ampil ER, Catindig-Dela Rosa JAS, Villaraza SG, Joson MLC. Increased Risk of Alzheimer's Disease With Glycemic Variability: A Systematic Review and Meta-Analysis. Cureus 2024; 16:e73353. [PMID: 39659303 PMCID: PMC11628202 DOI: 10.7759/cureus.73353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/05/2024] [Indexed: 12/12/2024] Open
Abstract
There is increasing evidence that establishes a connection between fluctuations in glucose metabolism and the onset of Alzheimer's disease (AD). Current research supports the notion that this metabolic imbalance significantly affects cognitive health. However, the specific mechanisms through which these fluctuations influence neurodegeneration, eventually leading to AD, require further exploration. This study aims to determine the risk of AD among individuals with fluctuations in blood glucose levels, with or without type 2 diabetes mellitus (T2DM), further providing the most recent and thorough overview of the evidence in this area. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, a thorough search was carried out utilizing particular phrases in the PubMed, Elsevier, Research Gate, and Cochrane databases: ("glucose variability" or "glycemic variability" or "glucose fluctuation" or "glucose instability" or "glycemic fluctuation") and ("Alzheimer's disease" or "Alzheimer disease" or "Alzheimer dementia" or "Alzheimer"). Studies published between January 2014 to January 2024, written in English, and examining the relationship between glucose variability and AD, were included. The outcomes measured were risk of cognitive impairment and AD, cognitive performance, and risk of AD. The results of the literature search produced 142 records, with six studies meeting the eligibility criteria. Parameters for glycemic variability included fasting plasma glucose (FPG) variability, glycated hemoglobin (HbA1c) variability, FPG variability independent of the mean (VIM), FPG coefficient of variation (CV), and FPG standard deviation (SD). The studies revealed a positive correlation between glycemic variability and the risk of AD over time, and the findings indicated that maintaining stable glycemic levels may reduce the risk of cognitive decline among individuals with or without T2DM. Due to the small number of studies that are currently available, despite a calculated relative risk of 2.65 indicating a higher risk of AD among subjects with glycemic variability, the inclusion of the null value in the confidence interval (0.61-11.45) renders these findings not statistically significant. This comprehensive review demonstrated that, in people with or without diabetes, glycemic variability influences cognitive decline and the risk of AD. The studies demonstrated a correlation between higher fluctuations in glucose levels and an increased risk of AD, highlighting the importance of managing blood sugar levels to mitigate dementia risks. Despite these strong associations, the actual incidence rates of AD in the studied populations remained relatively low. Overall, the results were not statistically significant. Further research is recommended to explore the risk of AD among individuals with fluctuations in blood glucose levels.
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Affiliation(s)
- Paul Nichol G Gonzales
- Department of Neurology, Jose R. Reyes Memorial Medical Center, Manila, PHL
- Department of Neuroscience and Behavioral Medicine, University of Santo Tomas Hospital, Manila, PHL
| | - Encarnita R Ampil
- Department of Neuroscience and Behavioral Medicine, University of Santo Tomas Hospital, Manila, PHL
- Faculty of Medicine and Surgery, University of Santo Tomas, Manila, PHL
- Institute for Neurosciences, St. Luke's Medical Center - Global City, Taguig, PHL
| | - Joseree-Ann S Catindig-Dela Rosa
- Department of Neurology, Jose R. Reyes Memorial Medical Center, Manila, PHL
- Department of Neuroscience and Behavioral Medicine, University of Santo Tomas Hospital, Manila, PHL
- Faculty of Medicine and Surgery, University of Santo Tomas, Manila, PHL
| | - Steven G Villaraza
- Department of Neurology, Jose R. Reyes Memorial Medical Center, Manila, PHL
| | - Ma Lourdes C Joson
- Department of Neuroscience and Behavioral Medicine, University of Santo Tomas Hospital, Manila, PHL
- Faculty of Medicine and Surgery, University of Santo Tomas, Manila, PHL
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Underwood PC, Zhang L, Mohr DC, Prentice JC, Nelson RE, Budson AE, Conlin PR. Glycated Hemoglobin A1c Time in Range and Dementia in Older Adults With Diabetes. JAMA Netw Open 2024; 7:e2425354. [PMID: 39093563 PMCID: PMC11297381 DOI: 10.1001/jamanetworkopen.2024.25354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 05/31/2024] [Indexed: 08/04/2024] Open
Abstract
Importance Individuals with diabetes commonly experience Alzheimer disease and related dementias (ADRD). Factors such as hypoglycemia, hyperglycemia, and glycemic variability have been associated with increased risk of ADRD. Traditional glycemic measures, such as mean glycated hemoglobin A1c (HbA1c), may not identify the dynamic and complex pathophysiologic factors in the association between diabetes and ADRD. The HbA1c time in range (TIR) is a previously developed measure of glycemic control that expresses HbA1c stability over time within specific ranges. This measure may inform the current understanding of the association between glucose levels over time and ADRD incidence. Objective To examine the association between HbA1c TIR and incidence of ADRD in older veterans with diabetes. Design, Setting, and Participants The study sample for this cohort study was obtained from administrative and health care utilization data from the Veterans Health Administration and Medicare from January 1, 2004, to December 31, 2018. Veterans 65 years or older with diabetes were assessed. Participants were required to have at least 4 HbA1c tests during the 3-year baseline period, which could start between January 1, 2005, and December 31, 2014. Data analysis was conducted between July and December 2023. Main Outcomes and Measures Hemoglobin A1c TIR was calculated as the percentage of days during baseline in which HbA1c was in individualized target ranges based on clinical characteristics and life expectancy, with higher HbA1c TIR viewed as more favorable. The association between HbA1c TIR and ADRD incidence was estimated. Additional models considered ADRD incidence in participants who were above or below HbA1c target ranges most of the time. Results The study included 374 021 veterans with diabetes (mean [SD] age, 73.2 [5.8] years; 369 059 [99%] male). During follow-up of up to 10 years, 41 424 (11%) developed ADRD. Adjusted Cox proportional hazards regression models showed that lower HbA1c TIR was associated with increased risk of incident ADRD (HbA1c TIR of 0 to <20% compared with ≥80%: hazard ratio, 1.19; 95% CI, 1.16-1.23). Furthermore, the direction of out-of-range HbA1c levels was associated with incident ADRD. Having greater time below range (≥60%, compared with ≥60% TIR) was associated with significantly increased risk (hazard ratio, 1.23; 95% CI, 1.19-1.27). Findings remained significant after excluding individuals with baseline use of medications associated with hypoglycemia risk (ie, insulin and sulfonylureas) or with hypoglycemia events. Conclusions and Relevance In this study of older adults with diabetes, increased HbA1c stability within patient-specific target ranges was associated with a lower risk of ADRD. Lower HbA1c TIR may identify patients at increased risk of ADRD.
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Affiliation(s)
- Patricia C. Underwood
- William F. Connell School of Nursing, Boston College, Boston, Massachusetts
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts
| | - Libin Zhang
- Center for Healthcare Organization & Implementation Research, Veterans Affairs, Boston, Massachusetts
| | - David C. Mohr
- National Center for Organizational Development, Veterans Health Administration, Cincinnati, Ohio
- Department of Health Law, Policy, and Management, School of Public Health, Boston University, Boston, Massachusetts
| | | | - Richard E. Nelson
- Department of Internal Medicine, University of Utah Health, Salt Lake City
- Veterans Affairs Salt Lake City Healthcare System, Salt Lake City, Utah
| | - Andrew E. Budson
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts
- National Center for Organizational Development, Veterans Health Administration, Cincinnati, Ohio
- Harvard Medical School, Boston, Massachusetts
| | - Paul R. Conlin
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts
- Boston University School of Medicine, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
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Heo JH, Jung HN, Roh E, Han KD, Kang JG, Lee SJ, Ihm SH. Association of remnant cholesterol with risk of dementia: a nationwide population-based cohort study in South Korea. THE LANCET. HEALTHY LONGEVITY 2024; 5:e524-e533. [PMID: 39068948 DOI: 10.1016/s2666-7568(24)00112-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 05/31/2024] [Accepted: 06/04/2024] [Indexed: 07/30/2024] Open
Abstract
BACKGROUND The association between remnant cholesterol (remnant-C) and cardiovascular disease risk is well established, but its association with dementia remains unclear. We aimed to examine this association using a large-scale population dataset. METHODS We did a nationwide, population-based cohort study in which we identified participants aged 40 years and older who underwent the national health examination in 2009 from South Korea's National Health Insurance Service. We excluded people who were younger than 40 years and those with a triglyceride concentration of 400 mg/dL or higher due to concerns regarding the accuracy of calculated low-density lipoprotein cholesterol concentration in individuals with extremely high triglyceride concentrations. People who were previously diagnosed with dementia before the index date, and those who had any missing variables were also excluded. To minimise the influence of possible reverse causation, we excluded individuals who had developed any type of dementia within 1 year of the baseline measurements. We calculated hazard ratios (HRs) for all-cause dementia, Alzheimer's disease, and vascular dementia in each quartile of remnant-C using the Cox proportional hazards model adjusted for age, sex, body-mass index, estimated glomerular filtration rate, income level, smoking status, alcohol consumption, regular exercise, diabetes, hypertension, statin and fibrate use, and total cholesterol concentrations. We also did subgroup analyses to investigate the association between remnant-C and the risk of dementia stratified by age, sex, obesity, glycaemic status (normoglycaemia, impaired fasting glucose, new-onset type 2 diabetes, type 2 diabetes with a duration of less than 5 years, and type 2 diabetes with a duration of 5 years or more), hypertension, chronic kidney disease, and dyslipidaemia, using likelihood ratio tests. FINDINGS 4 234 415 individuals who underwent the national health examination in 2009 were deemed eligible for inclusion. We excluded 1 612 819 individuals on the basis of age, triglyceride concentration, missing variables, or having dementia at baseline. We identified 2 621 596 participants aged 40 years and older (1 305 556 men and 1 316 040 women) who underwent the national health examination and followed them up until the date of any incident of dementia or the end of the study period of Dec 31, 2020. During a median follow-up of 10·3 years (IQR 10·1-10·6), 146 991 (5·6%) participants developed all-cause dementia, 117 739 (4·5%) developed Alzheimer's disease, and 14 536 (0·6%) developed vascular dementia. The risk of dementia increased progressively with higher remnant-C concentrations. Compared with the lowest quartile of remnant-C (quartile 1), HRs in the highest quartile (quartile 4) were 1·11 (95% CI 1·09-1·13) for all-cause dementia, 1·11 (1·08-1·13) for Alzheimer's disease, and 1·15 (1·09-1·21) for vascular dementia. Subgroup analyses revealed that the risk of dementia associated with high remnant-C concentrations was higher in middle-aged people aged 40-59 years than in older people. The risk of dementia associated with high concentrations of remnant-C was notably more pronounced in individuals with diabetes compared with those without diabetes, and the risk increased steeply with a longer duration of diabetes. INTERPRETATION Results showed that higher remnant-C concentrations were independently associated with increased risks of all-cause dementia, Alzheimer's disease, and vascular dementia. More research is needed to determine the mechanisms underlying this finding. Monitoring and managing higher concentrations of remnant-C might have important implications for reducing the risk of dementia. FUNDING None.
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Affiliation(s)
- Ji Hye Heo
- Department of Internal Medicine, Hallym University College of Medicine, Gangwon-do, South Korea
| | - Han Na Jung
- Department of Internal Medicine, Hallym University College of Medicine, Gangwon-do, South Korea
| | - Eun Roh
- Department of Internal Medicine, Hallym University College of Medicine, Gangwon-do, South Korea
| | - Kyung-do Han
- Department of Statistics and Actuarial Science, Soongsil University, Seoul, South Korea
| | - Jun Goo Kang
- Department of Internal Medicine, Hallym University College of Medicine, Gangwon-do, South Korea.
| | - Seong Jin Lee
- Department of Internal Medicine, Hallym University College of Medicine, Gangwon-do, South Korea
| | - Sung-Hee Ihm
- Department of Internal Medicine, Hallym University College of Medicine, Gangwon-do, South Korea
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Salinero-Fort MA, San Andrés-Rebollo FJ, Cárdenas-Valladolid J, Mostaza J, Lahoz C, Rodriguez-Artalejo F, Gómez-Campelo P, Vich-Pérez P, Jiménez-García R, de-Miguel-Yanes JM, Maroto-Rodriguez J, Taulero-Escalera B, Campo VI. Effect of glucose variability on the mortality of adults aged 75 years and over during the first year of the COVID-19 pandemic. BMC Geriatr 2024; 24:533. [PMID: 38902647 PMCID: PMC11188234 DOI: 10.1186/s12877-024-05149-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 06/13/2024] [Indexed: 06/22/2024] Open
Abstract
BACKGROUND To our knowledge, only one study has examined the association between glucose variability (GV) and mortality in the elderly population with diabetes. GV was assessed by HbA1c, and a J-shaped curve was observed in the relationship between HbA1c thresholds and mortality. No study of GV was conducted during the COVID-19 pandemic and its lockdown. This study aims to evaluate whether GV is an independent predictor of all-cause mortality in patients aged 75 years or older with and without COVID-19 who were followed during the first year of the COVID-19 pandemic and its lockdown measures. METHODS This was a retrospective cohort study of 407,492 patients from the AGED-MADRID dataset aged 83.5 (SD 5.8) years; 63.2% were women, and 29.3% had diabetes. GV was measured by the coefficient of variation of fasting plasma glucose (CV-FPG) over 6 years of follow-up (2015-2020). The outcome measure was all-cause mortality in 2020. Four models of logistic regression were performed, from simple (age, sex) to fully adjusted, to assess the effect of CV-FPG on all-cause mortality. RESULTS During follow-up, 34,925 patients died (14,999 women and 19,926 men), with an all-cause mortality rate of 822.3 per 10,000 person-years (95% confidence interval (CI), 813.7 to 822.3) (739 per 10,000; 95% CI 728.7 to 739.0 in women and 967.1 per 10,000; 95% CI 951.7 to 967.2 in men). The highest quartile of CV-FPG was significantly more common in the deceased group (40.1% vs. 23.6%; p < 0.001). In the fully adjusted model including dementia (Alzheimer's disease) and basal FPG, the odds ratio for mortality ranged from 1.88 to 2.06 in patients with T2DM and from 2.30 to 2.61 in patients with normoglycaemia, according to different sensitivity analyses. CONCLUSIONS GV has clear implications for clinical practice, as its assessment as a risk prediction tool should be included in the routine follow-up of the elderly and in a comprehensive geriatric assessment. Electronic health records can incorporate tools that allow its calculation, and with this information, clinicians will have a broader view of the medium- and long-term prognosis of their patients.
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Affiliation(s)
- Miguel A Salinero-Fort
- Department of Health, Foundation for Biosanitary Research and Innovation in Primary Care, The Hospital La Paz Institute for Health Research (IdiPAZ), Alfonso X El Sabio University, Research Network On Chronicity, Primary Care and Health Promotion -RICAPPS-(RICORS), General Subdirectorate of Research and Documentation, Madrid, Spain.
- Subdirección General de Investigación Sanitaria, Consejería de Sanidad, Madrid, Spain.
| | - F Javier San Andrés-Rebollo
- Foundation for Biosanitary Research and Innovation in Primary Care, Las Calesas Health Center, Madrid, Spain
| | - Juan Cárdenas-Valladolid
- Foundation for Biosanitary Research and Innovation in Primary Care, Information Systems Department, Primary Health Care Management of Madrid, Alfonso X El Sabio University, The Hospital La Paz Institute for Health Research (IdiPAZ), Madrid, Spain
| | - José Mostaza
- Lipids and Vascular Risk Unit, Internal Medicine, University Hospital La Paz-Cantoblanco-Carlos III, The Hospital La Paz Institute for Health Research (IdiPAZ), Madrid, Spain
| | - Carlos Lahoz
- Lipids and Vascular Risk Unit, Internal Medicine, University Hospital La Paz-Cantoblanco-Carlos III, The Hospital La Paz Institute for Health Research (IdiPAZ), Madrid, Spain
| | - Fernando Rodriguez-Artalejo
- Department of Preventive Medicine and Public Health, Universidad Autónoma de Madrid-IdIPAZ, CIBERESP (CIBER of Epidemiology and Public Health), and IMDEA-Food Institute, CEI UAM+CSIC, Madrid, Spain
| | - Paloma Gómez-Campelo
- Foundation for Biomedical Research of La Paz University Hospital (FIBHULP), The Hospital La Paz Institute for Health Research (IdiPAZ), Madrid, Spain
| | - Pilar Vich-Pérez
- Foundation for Biosanitary Research and Innovation in Primary Care, Los Alpes Health Center, Madrid, Spain
| | - Rodrigo Jiménez-García
- Department of Public Health & Maternal and Child Health, Faculty of Medicine, Universidad Complutense de Madrid, Madrid, 28040, Spain
| | - José M de-Miguel-Yanes
- School of Medicine, Internal Medicine Department, Complutense University of Madrid, Gregorio Marañón General University Hospital, Gregorio Marañón Health Research Institute (IiSGM), Madrid, Spain
| | - Javier Maroto-Rodriguez
- Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid, Calle del Arzobispo Morcillo 4, Madrid, 28029, Spain
| | | | - Víctor Iriarte Campo
- Foundation for Biosanitary Research and Innovation in Primary Care, Madrid, Spain
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Cao F, Yang F, Li J, Guo W, Zhang C, Gao F, Sun X, Zhou Y, Zhang W. The relationship between diabetes and the dementia risk: a meta-analysis. Diabetol Metab Syndr 2024; 16:101. [PMID: 38745237 PMCID: PMC11092065 DOI: 10.1186/s13098-024-01346-4] [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: 01/26/2024] [Accepted: 05/04/2024] [Indexed: 05/16/2024] Open
Abstract
BACKGROUND The link between diabetes and dementia risk is not well understood. This study evaluates the factors linking diabetes to dementia onset, providing guidance for preventing dementia in diabetic patients. METHODS This analysis utilized databases such as PubMed, Embase, Web of Science, and the Cochrane Library to review literature from January 31, 2012, to March 5, 2023. Articles were rigorously assessed using specific inclusion and exclusion criteria. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the studies. Data analysis was performed with STATA 15.0. RESULTS The study analyzed 15 articles, covering 10,103,868 patients, with 8,821,516 diagnosed with diabetes. The meta-analysis reveals a substantial association between diabetes and an increased risk of dementia [RR: 1.59, 95%CI (1.40-1.80), P < 0.01, I²=96.4%]. A diabetes duration of less than five years is linked to a higher dementia risk [RR: 1.29, 95%CI (1.20-1.39), P < 0.01, I²=92.6%]. Additionally, hypoglycemia significantly raises dementia risk [RR: 1.56, 95%CI (1.13-2.16), P < 0.01, I²=51.5%]. Analyses of blood sugar control, glycated hemoglobin, and fasting blood sugar indicated no significant effects on the onset of dementia. CONCLUSION Diabetes notably increases dementia risk, particularly where diabetes duration is under five years or hypoglycemia is present. REGISTRATION The research protocol was registered with PROSPERO and assigned the registration number CRD42023394942.
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Affiliation(s)
- Fang Cao
- School of Basic Medical Sciences, Changchun University of Chinese Medicine, Changchun, 130117, China
| | - Fushuang Yang
- College of Chinese Medicine, Changchun University of Chinese Medicine, Changchun, 130117, China
| | - Jian Li
- College of Chinese Medicine, Changchun University of Chinese Medicine, Changchun, 130117, China
| | - Wei Guo
- College of Chinese Medicine, Changchun University of Chinese Medicine, Changchun, 130117, China
| | - Chongheng Zhang
- College of Chinese Medicine, Changchun University of Chinese Medicine, Changchun, 130117, China
| | - Fa Gao
- College of Chinese Medicine, Changchun University of Chinese Medicine, Changchun, 130117, China
| | - Xinxin Sun
- Department of Nutrition, Chinese People's Armed Police Force Medical Characteristic Center, Tianjin, 300162, China
| | - Yi Zhou
- Department of Geriatrics, Baotou Mengshi Hospital of Traditional Chinese Medicine, Baotou, 014000, China
| | - Wenfeng Zhang
- School of Basic Medical Sciences, Changchun University of Chinese Medicine, Changchun, 130117, China.
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Kang SH, Choi Y, Chung SJ, Moon SJ, Kim CK, Kim JH, Oh K, Yoon JS, Seo SW, Cho GJ, Koh SB. Fasting glucose variability and risk of dementia in Parkinson's disease: a 9-year longitudinal follow-up study of a nationwide cohort. Front Aging Neurosci 2024; 15:1292524. [PMID: 38235038 PMCID: PMC10791804 DOI: 10.3389/fnagi.2023.1292524] [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: 09/11/2023] [Accepted: 11/21/2023] [Indexed: 01/19/2024] Open
Abstract
Background Diabetes is associated with an increased risk of Parkinson's disease dementia (PDD); however, it is unknown whether this association is dependent on continuous hyperglycemia, hypoglycemic events, or glycemic variability. We aimed to investigate the relationship between visit-to-visit fasting glucose variability and PDD development in patients with Parkinson's disease (PD). Methods Using data from the Korean National Health Insurance Service, we examined 9,264 patients aged ≥40 years with de novo Parkinson's disease (PD) who underwent ≥3 health examinations and were followed up until December 2019. Glucose variability was measured using the coefficient of variation, variability independent of the mean, and average real variability. Fine and Gray competing regression analysis was performed to determine the effect of glucose variability on incident PDD. Results During the 9.5-year follow-up period, 1,757 of 9,264 (19.0%) patients developed PDD. Patients with a higher visit-to-visit glucose variability had a higher risk of future PDD. In the multivariable adjusted model, patients with PD in the highest quartile (subdistribution hazard ratio [SHR] = 1.50, 95% CI 1.19 to 1.88), quartile 3 (SHR = 1.29, 95% CI 1.02 to 1.62), and quartile 2 (SHR = 1.30, 95% CI 1.04 to 1.63) were independently associated with a higher risk of PDD than those in the lowest quartile. Conclusion We highlighted the effect of long-term glucose variability on the development of PDD in patients with PD. Furthermore, our findings suggest that preventive measures for constant glucose control may be necessary to prevent PDD.
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Affiliation(s)
- Sung Hoon Kang
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Yunjin Choi
- Biomedical Research Institute, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Su Jin Chung
- Department of Neurology, Myongji Hospital, Hanyang University College of Medicine, Goyang, Republic of Korea
| | - Seok-Joo Moon
- Smart Healthcare Center, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Chi Kyung Kim
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Ji Hyun Kim
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Kyungmi Oh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Joon Shik Yoon
- Department of Physical Medicine and Rehabilitation, Korea University Guro Hospital, Seoul, Republic of Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Geum Joon Cho
- Department of Obstetrics and Gynecology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Seong-Beom Koh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
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Yu J, Lee KN, Kim HS, Han K, Lee SH. Cumulative effect of impaired fasting glucose on the risk of dementia in middle-aged and elderly people: a nationwide cohort study. Sci Rep 2023; 13:20600. [PMID: 37996487 PMCID: PMC10667225 DOI: 10.1038/s41598-023-47566-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 11/15/2023] [Indexed: 11/25/2023] Open
Abstract
The relationship between prediabetes and dementia remains controversial. We aimed to examine the association between cumulative exposure to impaired fasting glucose (IFG) and the risk of dementia in the general population. 1,463,066 middle-aged and elderly subjects who had had health examinations for four consecutive years were identified from a Korean nationwide population-based cohort database. IFG was defined as fasting blood glucose 100-125 mg/dL, and the risk of dementia-according to the number of IFG exposure (range 0-4)-was analyzed using the multivariable Cox proportional-hazards model. During the median 6.4 years of follow-up, 7614 cases of all-cause dementia, 5603 cases of Alzheimer's disease, and 1257 cases of vascular dementia occurred. There was a significant trend towards a higher risk of all-cause dementia (P for trend = 0.014) and Alzheimer's disease ( Pfor trend = 0.005) according to the cumulative exposure to IFG, but with a modest (approximately 7-14%) increase in the hazards. A significant stepwise increase in the risk of all-cause dementia and Alzheimer's disease was seen in non-obese subjects, whereas no significant association was observed in obese subjects. This study supports the association between prediabetes and incident dementia and emphasizes that even mild hyperglycemia should not be overlooked.
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Affiliation(s)
- Jin Yu
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222, Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea
| | - Kyu-Na Lee
- Department of Biomedicine and Health Science, The Catholic University of Korea, Seoul, Republic of Korea
| | - Hun-Sung Kim
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222, Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Kyungdo Han
- Department of Statistics and Actuarial Science, Soongsil University, #369 Sangdo-ro, Dongjak-gu, Seoul, 06978, Republic of Korea.
| | - Seung-Hwan Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222, Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea.
- Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
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10
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Mohamed-Mohamed H, García-Morales V, Sánchez Lara EM, González-Acedo A, Pardo-Moreno T, Tovar-Gálvez MI, Melguizo-Rodríguez L, Ramos-Rodríguez JJ. Physiological Mechanisms Inherent to Diabetes Involved in the Development of Dementia: Alzheimer's Disease. Neurol Int 2023; 15:1253-1272. [PMID: 37873836 PMCID: PMC10594452 DOI: 10.3390/neurolint15040079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 10/06/2023] [Accepted: 10/08/2023] [Indexed: 10/25/2023] Open
Abstract
Type 2 diabetes mellitus (T2D) is a metabolic disease reaching pandemic levels worldwide. In parallel, Alzheimer's disease (AD) and vascular dementia (VaD) are the two leading causes of dementia in an increasingly long-living Western society. Numerous epidemiological studies support the role of T2D as a risk factor for the development of dementia. However, few basic science studies have focused on the possible mechanisms involved in this relationship. On the other hand, this review of the literature also aims to explore the relationship between T2D, AD and VaD. The data found show that there are several alterations in the central nervous system that may be promoting the development of T2D. In addition, there are some mechanisms by which T2D may contribute to the development of neurodegenerative diseases such as AD or VaD.
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Affiliation(s)
- Himan Mohamed-Mohamed
- Department of Physiology, Faculty of Health Sciences of Ceuta, University of Granada, 51001 Ceuta, Spain
| | - Victoria García-Morales
- Physiology Area, Department of Biomedicine, Biotechnology and Public Health, Faculty of Medicine, University of Cádiz, Pl. Falla, 9, 11003 Cádiz, Spain
| | - Encarnación María Sánchez Lara
- Department of Personalidad, Evaluación y Tratamiento Psicológico, Faculty of Health Sciences (Ceuta), University of Granada, 51001 Ceuta, Spain;
| | - Anabel González-Acedo
- Department of Nursing, Faculty of Health Sciences of Ceuta, University of Granada, 51001 Ceuta, Spain
- Biomedical Group (BIO277), Department of Nursing, Faculty of Health Sciences, University of Granada, 18016 Granada, Spain
| | - Teresa Pardo-Moreno
- Department of Nursing, Faculty of Health Sciences of Ceuta, University of Granada, 51001 Ceuta, Spain
| | - María Isabel Tovar-Gálvez
- Department of Nursing, Faculty of Health Sciences of Ceuta, University of Granada, 51001 Ceuta, Spain
| | - Lucía Melguizo-Rodríguez
- Department of Nursing, Faculty of Health Sciences of Ceuta, University of Granada, 51001 Ceuta, Spain
- Biomedical Group (BIO277), Department of Nursing, Faculty of Health Sciences, University of Granada, 18016 Granada, Spain
| | - Juan José Ramos-Rodríguez
- Department of Physiology, Faculty of Health Sciences of Ceuta, University of Granada, 51001 Ceuta, Spain
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11
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Cho S, Ok Kim C, Cha BS, Kim E, Mo Nam C, Kim MG, Soo Park M. The effects of long-term cumulative HbA1c exposure on the development and onset time of dementia in the patients with type 2 diabetes mellitus: hospital based retrospective study (2005-2021). Diabetes Res Clin Pract 2023:110721. [PMID: 37196708 DOI: 10.1016/j.diabres.2023.110721] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Revised: 05/05/2023] [Accepted: 05/11/2023] [Indexed: 05/19/2023]
Abstract
AIMS We examine cumulative effect of long-term glycemic exposure in patients with type 2 diabetes mellitus (T2DM) on the development of dementia. METHODS The study involved 20,487 records of patients with T2DM identified in the electronic medical record at Severance Hospital, Korea. Cumulative HbA1c (AUCHbA1c) and mean HbA1c over time (HbA1cavg) as measures of long-term glycemic exposure were compared for the development of dementia and the time to dementia. RESULTS AUCHbA1c and HbA1cavg were significantly higher in patients who later developed dementia than in those who did not dementia (AUCHbA1c: 56.2 ± 26.4 vs. 52.1 ± 26.1 %*Year; HbA1cavg: 7.0 ± 1.0 vs. 7.3 ± 1.0 %). Odds ratio of dementia increased when HbA1cavg was 7.2% (55 mmol/mol) or above, and when AUCHbA1c was 42 %*Year (e.g., HbA1c 7.0% maintained for 6 years) or above. Among those who developed dementia, as HbA1cavg increased, the time to dementia onset decreased (β = -380.6 days, 95% confidence interval [CI]: -416.2 to -345.0). CONCLUSIONS Our results indicate poorly controlled T2DM was associated with an increased risk of developing dementia, as measured by AUCHbA1c and HbA1cavg. Higher cumulative glycemic exposure may lead to developing dementia in a shorter time.
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Affiliation(s)
- Sunyoung Cho
- Department of Pharmaceutical Medicine and Regulatory Sciences, College of Medicine and Pharmacy, Yonsei University, Seoul, Korea.
| | - Choon Ok Kim
- Department of Clinical Pharmacology and Clinical Trials Center, Severance Hospital, Yonsei University Health System, Seoul, Korea.
| | - Bong-Soo Cha
- Division of Endocrinology, Department of Internal Medicine, Severance Hospital, College of Medicine, Yonsei University, Seoul, Korea.
| | - Eosu Kim
- Department of Psychiatry, Institute of Behavioral Science in Medicine, College of Medicine, Yonsei University, Yonsei University, Seoul, Korea.
| | - Chung Mo Nam
- Department of Preventive Medicine, College of Medicine , Yonsei University, Seoul, Korea.
| | - Min-Gul Kim
- Department of Pharmacology, College of Medicine, Jeonbuk National University, Jeonju, Korea.
| | - Min Soo Park
- Department of Pediatrics, Department of Clinical Pharmacology, Severance Hospital, College of Medicine, Yonsei University, Seoul, Korea.
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12
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Cuevas H, Muñoz E, Nagireddy D, Kim J, Ganucheau G, Alomoush F. The Association of Glucose Variability and Dementia Incidence in Latinx Adults with Type 2 Diabetes: A Retrospective Study. Clin Nurs Res 2023; 32:249-255. [PMID: 36472225 DOI: 10.1177/10547738221141232] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Latinx adults with both cognitive dysfunction and type 2 diabetes mellitus (T2DM) are significantly more likely than Latinx adults with diabetes alone to have complications such as cardiovascular disease. Glucose variability may be a risk for dementia, but the course of glucose variability in the time before a dementia diagnosis for Latinx adults with T2DM has not been examined. We used a 10-year retrospective cohort of medical records of Latinx patients with T2DM who had at least one use of a continuous glucose monitor. The objective was to examine how glucose variability was associated with future dementia diagnoses. A total of 116 charts were included. Mean of daily differences and mean amplitude of glycemic excursions were more strongly associated with dementia diagnoses than other variability indices (p < .01). Understanding the relationships between cognitive function, glucose variability, and barriers to health care can translate into improved interventions to enhance diabetes care.
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Affiliation(s)
- Heather Cuevas
- The University of Texas at Austin, School of Nursing, USA
| | - Elizabeth Muñoz
- The University of Texas at Austin, College of Natural Sciences, USA
| | - Divya Nagireddy
- The University of Texas at Austin, College of Natural Sciences, USA
| | - Jeeyeon Kim
- The University of Texas at Austin, School of Nursing, USA
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