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Abrignani MG, Lucà F, Abrignani V, Pelaggi G, Aiello A, Colivicchi F, Fattirolli F, Gulizia MM, Nardi F, Pino PG, Parrini I, Rao CM. A Look at Primary and Secondary Prevention in the Elderly: The Two Sides of the Same Coin. J Clin Med 2024; 13:4350. [PMID: 39124617 PMCID: PMC11312802 DOI: 10.3390/jcm13154350] [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: 05/08/2024] [Revised: 07/16/2024] [Accepted: 07/18/2024] [Indexed: 08/12/2024] Open
Abstract
The global population is experiencing an aging trend; however, this increased longevity is not necessarily accompanied by improved health in older age. A significant consequence of this demographic shift is the rising prevalence of multiple chronic illnesses, posing challenges to healthcare systems worldwide. Aging is a major risk factor for multimorbidity, which marks a progressive decline in resilience and a dysregulation of multisystem homeostasis. Cardiovascular risk factors, along with aging and comorbidities, play a critical role in the development of heart disease. Among comorbidities, age itself stands out as one of the most significant risk factors for cardiovascular disease, with its prevalence and incidence notably increasing in the elderly population. However, elderly individuals, especially those who are frail and have multiple comorbidities, are under-represented in primary and secondary prevention trials aimed at addressing traditional cardiovascular risk factors, such as hypercholesterolemia, diabetes mellitus, and hypertension. There are concerns regarding the optimal intensity of treatment, taking into account tolerability and the risk of drug interactions. Additionally, uncertainty persists regarding therapeutic targets across different age groups. This article provides an overview of the relationship between aging and cardiovascular disease, highlighting various cardiovascular prevention issues in the elderly population.
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Affiliation(s)
| | - Fabiana Lucà
- O.U. Interventional Cardiology, Bianchi Melacrino Morelli Hospital, 89124 Reggio Calabria, Italy; (F.L.)
| | - Vincenzo Abrignani
- Internal Medicine and Stroke Care Ward, Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties, University of Palermo, 90141 Palermo, Italy
| | - Giuseppe Pelaggi
- O.U. Interventional Cardiology, Bianchi Melacrino Morelli Hospital, 89124 Reggio Calabria, Italy; (F.L.)
| | | | - Furio Colivicchi
- Cardiology Division, San Filippo Neri Hospital, 00135 Rome, Italy
| | - Francesco Fattirolli
- Department of Experimental and Clinical Medicine, Careggi University Hospital, University of Florence, 50121 Firenze, Italy
| | | | - Federico Nardi
- O.U. Cardiology, Santo Spirito Hospital, 15033 Casale Monferrato, Italy;
| | | | - Iris Parrini
- Cardiology Department, Mauriziano Umberto I Hospital, 10128 Turin, Italy
| | - Carmelo Massimiliano Rao
- O.U. Interventional Cardiology, Bianchi Melacrino Morelli Hospital, 89124 Reggio Calabria, Italy; (F.L.)
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Li S, Pan S, Jiang S, Shin JI, Liu GG, Lyu B. Prescription medication use among patients with type 2 diabetes in the United States: 1999-2020. Diabetes Obes Metab 2024; 26:2933-2944. [PMID: 38695210 DOI: 10.1111/dom.15619] [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: 01/26/2024] [Revised: 03/31/2024] [Accepted: 04/10/2024] [Indexed: 06/05/2024]
Abstract
AIMS We aimed to examine trends in overall prescription medication use among patients with type 2 diabetes in the United States to provide insights for patient care. MATERIALS AND METHODS We used nationally representative data from the National Health and Nutrition Examination Survey from 1999 to 2020 and included adult patients with type 2 diabetes. We examined the use of prescription drugs, overall and by drug class, polypharmacy (use of ≥5 medications), and number of medications attributed to specific classes. RESULTS In the period 2015-2020, the mean patient age was 59.6 (51.0-70.0) years, with 46.8% (43.6-49.9) being female and 57.8% (52.8-62.8) being non-Hispanic White. Among 9489 adults with type 2 diabetes, the prevalence of polypharmacy was high and increased from 35.1% (31.6-38.6) in 1999-2002 to 47.2% (43.7-50.7) in 2003-2006, and further to 51.1% (48.3-53.9) in 2015-2020 (p for trend <0.001). Increasing trends of polypharmacy were found across all population subgroups and across the majority of therapeutic classes. Use of non-cardiometabolic medications was common. Among them, the most common were antidepressants (19.8%), proton pump inhibitors (19.0%) and analgesics (16.2%). Among patients with polypharmacy, approximately 40% of medication use was attributed to non-cardiometabolic medications. CONCLUSIONS Prescription medication burden and complexity increased substantially among patients with type 2 diabetes, with more than 50% of patients with polypharmacy. Attention should be paid to this escalating medication use and regimen complexity, which requires multidisciplinary and coordinated care.
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Affiliation(s)
- Shanshan Li
- Institute for Global Health and Development, Peking University, Beijing, China
- China Center for Health Economic Research, Peking university, Beijing, China
| | - Shaoxi Pan
- Institute for Global Health and Development, Peking University, Beijing, China
- China Center for Health Economic Research, Peking university, Beijing, China
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Shaoxiang Jiang
- Institute for Global Health and Development, Peking University, Beijing, China
| | - Jung-Im Shin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, Maryland, USA
| | - Gordon G Liu
- Institute for Global Health and Development, Peking University, Beijing, China
- China Center for Health Economic Research, Peking university, Beijing, China
- National School of Development, Peking University, Beijing, China
| | - Beini Lyu
- Institute for Global Health and Development, Peking University, Beijing, China
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Li Q, Yuan D, Zeng G, Jiang L, Xu L, Xu J, Liu R, Song Y, Zhao X, Hui R, Gao R, Gao Z, Song L, Yuan J. The association between glycated hemoglobin levels and long-term prognosis in patients with diabetes and triple-vessel coronary disease across different age groups: A cohort study. Diabetes Res Clin Pract 2024; 213:111751. [PMID: 38906334 DOI: 10.1016/j.diabres.2024.111751] [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: 04/20/2024] [Revised: 06/13/2024] [Accepted: 06/15/2024] [Indexed: 06/23/2024]
Abstract
AIM Our study aimed to investigate the correlation between glycated hemoglobin (HbA1c) and adverse prognostic events in patients with diabetes and triple-vessel coronary disease (TVD). METHODS This study ultimately included 2051 patients with TVD and diabetes. Patients were categorized into five groups based on their HbA1c levels: < 6.0 %, 6.0-6.4 %, 6.5-6.9 %, 7.0-7.9 %, and ≥ 8.0 %. The primary endpoint was all-cause death, and the secondary endpoint was major adverse cardiovascular and cerebrovascular events (MACCE). RESULTS The median follow-up time was 5.88 years. During this period, a total of 323 (15.7 %) all-cause deaths and 537 (26.2 %) MACCEs were recorded. The relationship between HbA1c and the risk of endpoint events showed a J-shaped pattern, with the lowest risk observed between 6.0 % and 6.4 %. Further analysis revealed a significant interaction between HbA1c and age. In the subgroup with age < 70 years, as HbA1c increased, the risk of endpoint events gradually rose. While in the subgroup with age ≥70 years, there was an L-shaped relationship between HbA1c and endpoint events, with the highest risk observed in patients with HbA1c < 6.0 %. CONCLUSION Our study revealed variations in the relationship between HbA1c levels and endpoint events among patients with TVD and diabetes of different ages. In younger patients, elevated HbA1c levels were associated with a higher risk of death and MACCE, while in older patients, excessively low HbA1c levels (HbA1c < 6 %) were linked to a higher risk of death and MACCE.
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Affiliation(s)
- Qinxue Li
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Deshan Yuan
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Guyu Zeng
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Lin Jiang
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Lianjun Xu
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Jingjing Xu
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Ru Liu
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Ying Song
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Xueyan Zhao
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Rutai Hui
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Runlin Gao
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Zhan Gao
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Lei Song
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China.
| | - Jinqing Yuan
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China.
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Chua S, Todd A, Reeve E, Smith SM, Fox J, Elsisi Z, Hughes S, Husband A, Langford A, Merriman N, Harris JR, Devine B, Gray SL. Deprescribing interventions in older adults: An overview of systematic reviews. PLoS One 2024; 19:e0305215. [PMID: 38885276 PMCID: PMC11182547 DOI: 10.1371/journal.pone.0305215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 05/25/2024] [Indexed: 06/20/2024] Open
Abstract
OBJECTIVE The growing deprescribing field is challenged by a lack of consensus around evidence and knowledge gaps. The objective of this overview of systematic reviews was to summarize the review evidence for deprescribing interventions in older adults. METHODS 11 databases were searched from 1st January 2005 to 16th March 2023 to identify systematic reviews. We summarized and synthesized the results in two steps. Step 1 summarized results reported by the included reviews (including meta-analyses). Step 2 involved a narrative synthesis of review results by outcome. Outcomes included medication-related outcomes (e.g., medication reduction, medication appropriateness) or twelve other outcomes (e.g., mortality, adverse events). We summarized outcomes according to subgroups (patient characteristics, intervention type and setting) when direct comparisons were available within the reviews. The quality of included reviews was assessed using A MeaSurement Tool to Assess systematic Reviews 2 (AMSTAR 2). RESULTS We retrieved 3,228 unique citations and assessed 135 full-text articles for eligibility. Forty-eight reviews (encompassing 17 meta-analyses) were included. Thirty-one of the 48 reviews had a general deprescribing focus, 16 focused on specific medication classes or therapeutic categories and one included both. Twelve of 17 reviews meta-analyzed medication-related outcomes (33 outcomes: 25 favored the intervention, 7 found no difference, 1 favored the comparison). The narrative synthesis indicated that most interventions resulted in some evidence of medication reduction while for other outcomes we found primarily no evidence of an effect. Results were mixed for adverse events and few reviews reported adverse drug withdrawal events. Limited information was available for people with dementia, frailty and multimorbidity. All but one review scored low or critically low on quality assessment. CONCLUSION Deprescribing interventions likely resulted in medication reduction but evidence on other outcomes, in particular relating to adverse events, or in vulnerable subgroups or settings was limited. Future research should focus on designing studies powered to examine harms, patient-reported outcomes, and effects on vulnerable subgroups. SYSTEMATIC REVIEW REGISTRATION PROSPERO CRD42020178860.
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Affiliation(s)
- Shiyun Chua
- School of Public Health, University of Washington, Seattle, Washington, United States of America
| | - Adam Todd
- Newcastle University, School of Pharmacy, Newcastle-upon-Tyne, United Kingdom
- NIHR Patient Safety Research Collaborative, Newcastle-upon-Tyne, United Kingdom
| | - Emily Reeve
- Centre for Medicine Use and Safety, Monash Institute of Pharmaceutical Sciences, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, VIC, Australia
- Quality Use of Medicines and Pharmacy Research Centre, Clinical and Health Sciences, University of South Australia, Adelaide, Australia
| | - Susan M. Smith
- Discipline of Public Health and Primary Care, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Julia Fox
- School of Pharmacy, University of Washington, Seattle, Washington, United States of America
| | - Zizi Elsisi
- School of Pharmacy, University of Washington, Seattle, Washington, United States of America
| | - Stephen Hughes
- School of Pharmacy, University of Sydney, Sydney, Australia
| | - Andrew Husband
- Newcastle University, School of Pharmacy, Newcastle-upon-Tyne, United Kingdom
- NIHR Patient Safety Research Collaborative, Newcastle-upon-Tyne, United Kingdom
| | - Aili Langford
- Centre for Medicine Use and Safety, Monash Institute of Pharmaceutical Sciences, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, VIC, Australia
| | - Niamh Merriman
- Discipline of Public Health and Primary Care, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Jeffrey R. Harris
- School of Public Health, University of Washington, Seattle, Washington, United States of America
| | - Beth Devine
- School of Pharmacy, University of Washington, Seattle, Washington, United States of America
| | - Shelly L. Gray
- School of Pharmacy, University of Washington, Seattle, Washington, United States of America
- Plein Center for Geriatric Pharmacy Research, Education and Outreach, School of Pharmacy, University of Washington, Seattle, Washington, United States of America
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Price C, Callahan KE, Aloi JA, Usoh CO. Continuous Glucose Monitoring in Older Adults: What We Know and What We Have Yet to Learn. J Diabetes Sci Technol 2024; 18:577-583. [PMID: 38454549 PMCID: PMC11089865 DOI: 10.1177/19322968241234651] [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] [Indexed: 03/09/2024]
Abstract
OBJECTIVE To assess the growing use of continuous glucose monitoring (CGM) systems by older adults and explore additional areas integration that could benefit adults with frailty. BACKGROUND The use of CGM devices has expanded rapidly in the last decade. This has been supported by substantial data showing significant benefit in glycemic metrics: hemoglobin A1c improvements, less hypoglycemia, and improved quality of life. However, sub-populations, such as older persons, exist where available data are limited. Furthermore, frail older adults represent a heterogeneous population with their own unique challenges to the management of diabetes. This group has some of the poorest outcomes related to the sequela of diabetes. For example, hypoglycemia resulting in significant morbidity and mortality is more frequent in older person with diabetes than in younger persons with diabetes. METHOD We present a concise literature review on CGM use in the older adult as well as expand upon glycemic and nonglycemic benefits of CGM for patients, caregivers, and providers. Retrospective analysis of inpatient glycemic data of 16,935 older adults with Type 2 diabetes mellitus at Atrium Health Wake Forest Baptist indicated those with fraility managed with insulin or sulfonylurea had the highest rates of delirium (4.8%), hypoglycemia (3.5%), cardiovascular complications (20.2%) and ED visits/hospitalizatoins (49%). In addition, we address special consideration of specific situations including inpatient, palliative and long term care settings. CONCLUSION This review article summarizes the available data for CGM use in older adults, discusses the benefits and obstacles with CGM use in this population, and identifies areas of future research needed for improved delivery of care to older persons with diabetes.
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Affiliation(s)
- Catherine Price
- Section on Endocrinology,
Diabetes and Metabolism, Department of Internal Medicine, School of
Medicine, Wake Forest University, Winston-Salem, NC, USA
| | - Kathryn E. Callahan
- Section on Gerontology and
Geriatric Medicine, Department of Internal Medicine, School of Medicine,
Wake Forest University, Winston-Salem, NC, USA
| | - Joseph A. Aloi
- Section on Endocrinology,
Diabetes and Metabolism, Department of Internal Medicine, School of
Medicine, Wake Forest University, Winston-Salem, NC, USA
| | - Chinenye O. Usoh
- Section on Endocrinology,
Diabetes and Metabolism, Department of Internal Medicine, School of
Medicine, Wake Forest University, Winston-Salem, NC, USA
- Endocrinology, Medicine Service,
W. G. (Bill) Hefner VA Medical Center, Salisbury, NC, USA
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Zhang Q, Hu S, Jin Z, Wang S, Zhang B, Zhao L. Mechanism of traditional Chinese medicine in elderly diabetes mellitus and a systematic review of its clinical application. Front Pharmacol 2024; 15:1339148. [PMID: 38510656 PMCID: PMC10953506 DOI: 10.3389/fphar.2024.1339148] [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] [Received: 11/15/2023] [Accepted: 01/31/2024] [Indexed: 03/22/2024] Open
Abstract
Objective: Affected by aging, the elderly diabetes patients have many pathological characteristics different from the young people, including more complications, vascular aging, cognitive impairment, osteoporosis, and sarcopenia. This article will explore their pathogenesis and the mechanism of Traditional Chinese medicine (TCM) intervention, and use the method of systematic review to evaluate the clinical application of TCM in elderly diabetes. Method: Searching for randomized controlled trials (RCTs) published from January 2000 to November 2023 in the following databases: Web of Science, Pubmed, Embase, Cochrane Library, Sinomed, China National Knowledge Internet, Wanfang and VIP. They were evaluated by three subgroups of Traditional Chinese Prescription, Traditional Chinese patent medicines and Traditional Chinese medicine extracts for their common prescriptions, drugs, adverse reactions and the quality of them. Results and Conclusion: TCM has the advantages of multi-target and synergistic treatment in the treatment of elderly diabetes. However, current clinical researches have shortcomings including the inclusion of age criteria and diagnosis of subjects are unclear, imprecise research design, non-standard intervention measures, and its safety needs further exploration. In the future, the diagnosis of elderly people with diabetes needs to be further clarified. Traditional Chinese patent medicines included in the pharmacopoeia can be used to conduct more rigorous RCTs, and then gradually standardize the traditional Chinese medicine prescriptions and traditional Chinese medicine extracts, providing higher level evidence for the treatment of elderly diabetes with traditional Chinese medicine.
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Affiliation(s)
- Qiqi Zhang
- Institute of Metabolic Diseases, Guang’anmen Hospital, Chinese Academy of Chinese Medical Sciences, Beijing, China
| | - Shiwan Hu
- Institute of Metabolic Diseases, Guang’anmen Hospital, Chinese Academy of Chinese Medical Sciences, Beijing, China
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Zishan Jin
- Institute of Metabolic Diseases, Guang’anmen Hospital, Chinese Academy of Chinese Medical Sciences, Beijing, China
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Sicheng Wang
- Institute of Metabolic Diseases, Guang’anmen Hospital, Chinese Academy of Chinese Medical Sciences, Beijing, China
| | - Boxun Zhang
- Department of Endocrinology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Linhua Zhao
- Institute of Metabolic Diseases, Guang’anmen Hospital, Chinese Academy of Chinese Medical Sciences, Beijing, China
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Cristina García-Ulloa A, Jaime-Casas S, Rosado-Lozoya J, Serrano-Pérez NH, Hernández-Juárez D, Luis Cárdenas-Fragoso J, Eduardo Briones-García L, Jiménez-Soto R, García-Padilla C, García-Lara J, Aguilar-Salinas CA, Hernández-Jiménez S. De-escalating treatment indications for patients who achieve metabolic goals. Diabetes Res Clin Pract 2024; 208:111096. [PMID: 38244782 DOI: 10.1016/j.diabres.2024.111096] [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: 11/30/2023] [Revised: 01/10/2024] [Accepted: 01/13/2024] [Indexed: 01/22/2024]
Abstract
INTRODUCTION Robust evidence exists regarding initiation, intensification or modification of treatments. Recommendations to de-escalate therapy are lacking, specifically in diabetes. A successful treatment de-intensification reduces overtreatment, polypharmacy, and risk of adverse effects. OBJECTIVE To encompass current recommendations for deprescribing common drugs and create a consensus among health professionals. METHODS We reviewed four databases for deprescribing approaches published between 2010 and 2022. Articles were divided into different groups of drugs (for uric-acid, hypoglycemic, lipid-lowering, and psychotropic drugs). RESULTS Hypoglycemic agents: strategies were limited to newer agents and insulin regimens for elderly individuals. Reducing insulin was associated with 1.1% reduction of A1c over time. SGLT2i and GLP-1RAs dose reduction depends on adverse events. Lipid-lowering agents: studies show that patients with very low cholesterol have fewer cardiovascular events without associated increased risk. Antihypertensive agents: Younger patients, lower systolic blood pressure, and few comorbidities are ideal characteristics for discontinuation. Uric acid therapy: we found no recommendation for dose de-escalation. Poor treatment adherence is associated with episodes of gout and deforming arthritis in the long term. CONCLUSION Deprescribing hypoglycemic, statins, antihypertensives, and urate-lowering agents may be feasible in selected patients, but periodic surveillance is important. More evidence is necessary to support this decision entirely.
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Affiliation(s)
- Ana Cristina García-Ulloa
- Centro de Atención Integral del Paciente con Diabetes (CAIPaDi), Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | | | | | - Nancy H Serrano-Pérez
- Centro de Atención Integral del Paciente con Diabetes (CAIPaDi), Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Diana Hernández-Juárez
- Centro de Atención Integral del Paciente con Diabetes (CAIPaDi), Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - José Luis Cárdenas-Fragoso
- Centro de Atención Integral del Paciente con Diabetes (CAIPaDi), Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Luis Eduardo Briones-García
- Departamento de Reumatología, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Rodolfo Jiménez-Soto
- Departamento de Reumatología, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Carlos García-Padilla
- Departamento de Reumatología, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Juan García-Lara
- Departamento de Geriatría, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Carlos A Aguilar-Salinas
- Dirección de Investigación, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Sergio Hernández-Jiménez
- Centro de Atención Integral del Paciente con Diabetes (CAIPaDi), Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico.
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Guo L, Xiao X. Guideline for the Management of Diabetes Mellitus in the Elderly in China (2024 Edition). Aging Med (Milton) 2024; 7:5-51. [PMID: 38571669 PMCID: PMC10985780 DOI: 10.1002/agm2.12294] [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] [Received: 01/30/2024] [Revised: 02/08/2024] [Accepted: 02/08/2024] [Indexed: 04/05/2024] Open
Abstract
With the deepening of aging in China, the prevalence of diabetes in older people has increased noticeably, and standardized diabetes management is critical for improving clinical outcomes of diabetes in older people. In 2021, the National Center of Gerontology, Chinese Society of Geriatrics, and Diabetes Professional Committee of Chinese Aging Well Association organized experts to write the first guideline for diabetes diagnosis and treatment in older people in China, the Guideline for the Management of Diabetes Mellitus in the Elderly in China (2021 Edition). The guideline emphasizes that older patients with diabetes are a highly heterogeneous group requiring comprehensive assessment and stratified and individualized management strategies. The guideline proposes simple treatments and de-intensified treatment strategies for older patients with diabetes. This edition of the guideline provides clinicians with practical and operable clinical guidance, thus greatly contributing to the comprehensive and full-cycle standardized management of older patients with diabetes in China and promoting the extensive development of clinical and basic research on diabetes in older people and related fields. In the past 3 years, evidence-based medicine for older patients with diabetes and related fields has further advanced, and new treatment concepts, drugs, and technologies have been developed. The guideline editorial committee promptly updated the first edition of the guideline and compiled the Guideline for the Management of Diabetes Mellitus in the Elderly in China (2024 Edition). More precise management paths for older patients with diabetes are proposed, for achieving continued standardization of the management of older Chinese patients with diabetes and improving their clinical outcomes.
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Affiliation(s)
- Lixin Guo
- National Center of Gerontology, Chinese Society of Geriatrics, Diabetes Professional Committee of Chinese Aging Well AssociationBeijingChina
- Department of Endocrinology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric MedicineChinese Academy of Medical SciencesBeijingChina
| | - Xinhua Xiao
- National Center of Gerontology, Chinese Society of Geriatrics, Diabetes Professional Committee of Chinese Aging Well AssociationBeijingChina
- Department of EndocrinologyPeking Union Medical College Hospital, Chinese Academy of Medical SciencesBeijingChina
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Bernstein S, Gilson S, Zhu M, Nathan AG, Cui M, Press VG, Shah S, Zarei P, Laiteerapong N, Huang ES. Diabetes Life Expectancy Prediction Model Inputs and Results From Patient Surveys Compared With Electronic Health Record Abstraction: Survey Study. JMIR Aging 2023; 6:e44037. [PMID: 37962566 PMCID: PMC10662674 DOI: 10.2196/44037] [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: 11/03/2022] [Revised: 06/13/2023] [Accepted: 09/19/2023] [Indexed: 11/15/2023] Open
Abstract
Background Prediction models are being increasingly used in clinical practice, with some requiring patient-reported outcomes (PROs). The optimal approach to collecting the needed inputs is unknown. Objective Our objective was to compare mortality prediction model inputs and scores based on electronic health record (EHR) abstraction versus patient survey. Methods Older patients aged ≥65 years with type 2 diabetes at an urban primary care practice in Chicago were recruited to participate in a care management trial. All participants completed a survey via an electronic portal that included items on the presence of comorbid conditions and functional status, which are needed to complete a mortality prediction model. We compared the individual data inputs and the overall model performance based on the data gathered from the survey compared to the chart review. Results For individual data inputs, we found the largest differences in questions regarding functional status such as pushing/pulling, where 41.4% (31/75) of participants reported difficulties that were not captured in the chart with smaller differences for comorbid conditions. For the overall mortality score, we saw nonsignificant differences (P=.82) when comparing survey and chart-abstracted data. When allocating participants to life expectancy subgroups (<5 years, 5-10 years, >10 years), differences in survey and chart review data resulted in 20% having different subgroup assignments and, therefore, discordant glucose control recommendations. Conclusions In this small exploratory study, we found that, despite differences in data inputs regarding functional status, the overall performance of a mortality prediction model was similar when using survey and chart-abstracted data. Larger studies comparing patient survey and chart data are needed to assess whether these findings are reproduceable and clinically important.
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Affiliation(s)
- Sean Bernstein
- Rush University Medical Center, ChicagoIL, United States
| | - Sarah Gilson
- Section of General Internal Medicine, Department of Medicine, University of Chicago, ChicagoIL, United States
| | - Mengqi Zhu
- Section of General Internal Medicine, Department of Medicine, University of Chicago, ChicagoIL, United States
| | - Aviva G Nathan
- Section of General Internal Medicine, Department of Medicine, University of Chicago, ChicagoIL, United States
| | - Michael Cui
- Rush University Medical Center, ChicagoIL, United States
| | - Valerie G Press
- Section of General Internal Medicine, Department of Medicine, University of Chicago, ChicagoIL, United States
| | - Sachin Shah
- Section of General Internal Medicine, Department of Medicine, University of Chicago, ChicagoIL, United States
| | - Parmida Zarei
- College of Medicine, University of Illinois Chicago, ChicagoIL, United States
| | - Neda Laiteerapong
- Section of General Internal Medicine, Department of Medicine, University of Chicago, ChicagoIL, United States
| | - Elbert S Huang
- Section of General Internal Medicine, Department of Medicine, University of Chicago, ChicagoIL, United States
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Bourdel-Marchasson I, Maggi S, Abdelhafiz A, Bellary S, Demurtas J, Forbes A, Ivory P, Rodríguez-Mañas L, Sieber C, Strandberg T, Tessier D, Vergara I, Veronese N, Zeyfang A, Christiaens A, Sinclair A. Essential steps in primary care management of older people with Type 2 diabetes: an executive summary on behalf of the European geriatric medicine society (EuGMS) and the European diabetes working party for older people (EDWPOP) collaboration. Aging Clin Exp Res 2023; 35:2279-2291. [PMID: 37665557 PMCID: PMC10628003 DOI: 10.1007/s40520-023-02519-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 07/26/2023] [Indexed: 09/05/2023]
Abstract
We present an executive summary of a guideline for management of type 2 diabetes mellitus in primary care written by the European Geriatric Medicine Society, the European Diabetes Working Party for Older People with contributions from primary care practitioners and participation of a patient's advocate. This consensus document relies where possible on evidence-based recommendations and expert opinions in the fields where evidences are lacking. The full text includes 4 parts: a general strategy based on comprehensive assessment to enhance quality and individualised care plan, treatments decision guidance, management of complications, and care in case of special conditions. Screening for frailty and cognitive impairment is recommended as well as a comprehensive assessment all health conditions are concerned, including end of life situations. The full text is available online at the following address: essential_steps_inprimary_care_in_older_people_with_diabetes_-_EuGMS-EDWPOP___3_.pdf.
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Affiliation(s)
| | - Stefania Maggi
- National Research Council, Neuroscience Institute, Via Giustiniani 2, 35128, Padua, Italy
| | - Ahmed Abdelhafiz
- Department of Geriatric Medicine, Rotherham General Hospital, Rotherham, S60 2UD, UK
| | | | - Jacopo Demurtas
- Primary Care Department, Azienda USL Toscana Sud Est, Grosseto, Italy
| | - Angus Forbes
- Division of Care in Long Term Conditions, King's College London, London, UK
| | | | | | - Cornel Sieber
- Institute for Biomedicine of Aging, Friedrich-Alexander-Universität Erlangen-Nürnberg, Nuremberg, Germany
- Department of Medicine, Kantonsspital Winterthur, Winterthur, Switzerland
| | - Timo Strandberg
- University of Helsinki, Clinicum, and Helsinki University Hospital, Helsinki, Finland
- University of Oulu, Center for Life Course Health Research, Oulu, Finland
| | - Daniel Tessier
- Research Centre on Aging, Affiliated with CIUSSS de L'Estrie-CHUS, 1036, Rue Belvédère Sud, Sherbrooke, QC, J1H 4C4, Canada
- Faculty of Medicine and Health Sciences, University of Sherbrooke, 2500, Boul. de L'Université, Sherbrooke, QC, J1K 2R1, Canada
| | - Itziar Vergara
- Biodonostia Health Research Institute, Paseo Dr. Begiristain S/N, 20014, Donostia, Basque Country, Spain
| | - Nicola Veronese
- Geriatric Unit, Department of Internal Medicine and Geriatrics, University of Palermo, Palermo, Italy
| | - Andrej Zeyfang
- Department of Internal Medicine, Geriatric Medicine, Palliative Medicine and Diabetology, Medius Klinik Ostfildern-Ruit and Nürtingen, Nürtingen, Germany
| | - Antoine Christiaens
- Louvain Drug Research Institute, Université Catholique de Louvain, Brussels, Belgium
- Fund for Scientific Research, Brussels, Belgium
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11
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Wan KS, Mustapha F, Chandran A, Ganapathy SS, Zakariah N, Ramasamy S, Subbarao GR, Mohd Yusoff MF. Baseline treatments and metabolic control of 288,913 type 2 diabetes patients in a 10-year retrospective cohort in Malaysia. Sci Rep 2023; 13:17338. [PMID: 37833402 PMCID: PMC10576047 DOI: 10.1038/s41598-023-44564-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: 03/24/2023] [Accepted: 10/10/2023] [Indexed: 10/15/2023] Open
Abstract
Diabetes is one of the quickest-growing global health emergencies of the twenty-first century, and data-driven care can improve the quality of diabetes management. We aimed to describe the formation of a 10-year retrospective open cohort of type 2 diabetes patients in Malaysia. We also described the baseline treatment profiles and HbA1c, blood pressure, and lipid control to assess the quality of diabetes care. We used 10 years of cross-sectional audit datasets from the National Diabetes Registry and merged 288,913 patients with the same identifying information into a 10-year open cohort dataset. Treatment targets for HbA1c, blood pressure, LDL-cholesterol, HDL-cholesterol, and triglycerides were based on Malaysian clinical practice guidelines. IBM SPSS Statistics version 23.0 was used, and frequencies and percentages with 95% confidence intervals were reported. In total, 288,913 patients were included, with 62.3% women and 54.1% younger adults. The commonest diabetes treatment modality was oral hypoglycaemic agents (75.9%). Meanwhile, 19.3% of patients had ≥ 3 antihypertensive agents, and 71.2% were on lipid-lowering drugs. Metformin (86.1%), angiotensin-converting enzyme inhibitors (49.6%), and statins (69.2%) were the most prescribed antidiabetic, antihypertensive, and lipid-lowering medications, respectively. The mean HbA1c was 7.96 ± 2.11, and 31.2% had HbA1c > 8.5%. Only 35.8% and 35.2% attained blood pressure < 140/80 mmHg and LDL-cholesterol < 2.6 mmol/L, respectively. About 57.5% and 52.9% achieved their respective triglyceride and HDL-cholesterol goals. In conclusion, data integration is a feasible method in this diabetes registry. HbA1c, blood pressure, and lipids are not optimally controlled, and these findings can be capitalized as a guideline by clinicians, programme managers, and health policymakers to improve the quality of diabetes care and prevent long-term complications in Malaysia.
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Affiliation(s)
- Kim Sui Wan
- Institute for Public Health, National Institutes of Health, Ministry of Health Malaysia, Setia Alam, 40170, Shah Alam, Selangor, Malaysia.
| | - Feisul Mustapha
- Disease Control Division, Ministry of Health Malaysia, Federal Government Administration Centre, 62590, Putrajaya, Malaysia
| | - Arunah Chandran
- Disease Control Division, Ministry of Health Malaysia, Federal Government Administration Centre, 62590, Putrajaya, Malaysia
| | - Shubash Shander Ganapathy
- Institute for Public Health, National Institutes of Health, Ministry of Health Malaysia, Setia Alam, 40170, Shah Alam, Selangor, Malaysia
| | - Nurhaliza Zakariah
- Disease Control Division, Ministry of Health Malaysia, Federal Government Administration Centre, 62590, Putrajaya, Malaysia
| | - Sivarajan Ramasamy
- State Health Department of Negeri Sembilan, Ministry of Health Malaysia, Jalan Rasah, 70300, Seremban, Negeri Sembilan, Malaysia
| | - Gunenthira Rao Subbarao
- Medical Development Division, Ministry of Health Malaysia, Federal Government Administration Centre, 62590, Putrajaya, Malaysia
| | - Muhammad Fadhli Mohd Yusoff
- Institute for Public Health, National Institutes of Health, Ministry of Health Malaysia, Setia Alam, 40170, Shah Alam, Selangor, Malaysia
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12
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Anderson TS, Ayanian JZ, Curto VE, Politzer E, Souza J, Zaslavsky AM, Landon BE. Changes in the Use of Long-Term Medications Following Incident Dementia Diagnosis. JAMA Intern Med 2023; 183:1098-1108. [PMID: 37603340 PMCID: PMC10442785 DOI: 10.1001/jamainternmed.2023.3575] [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: 03/27/2023] [Accepted: 06/09/2023] [Indexed: 08/22/2023]
Abstract
Importance Dementia is a life-altering diagnosis that may affect medication safety and goals for chronic disease management. Objective To examine changes in medication use following an incident dementia diagnosis among community-dwelling older adults. Design, Setting, and Participants In this cohort study of adults aged 67 years or older enrolled in traditional Medicare and Medicare Part D, patients with incident dementia diagnosed between January 2012 and December 2018 were matched to control patients based on demographics, geographic location, and baseline medication count. The index date was defined as the date of first dementia diagnosis or, for controls, the date of the closest office visit. Data were analyzed from August 2021 to June 2023. Exposure Incident dementia diagnosis. Main Outcomes and Measures The main outcomes were overall medication counts and use of cardiometabolic, central nervous system (CNS)-active, and anticholinergic medications. A comparative time-series analysis was conducted to examine quarterly changes in medication use in the year before through the year following the index date. Results The study included 266 675 adults with incident dementia and 266 675 control adults; in both groups, 65.1% were aged 80 years or older (mean [SD] age, 82.2 [7.1] years) and 67.8% were female. At baseline, patients with incident dementia were more likely than controls to use CNS-active medications (54.32% vs 48.39%) and anticholinergic medications (17.79% vs 15.96%) and less likely to use most cardiometabolic medications (eg, diabetes medications, 31.19% vs 36.45%). Immediately following the index date, the cohort with dementia had a greater increase in mean number of medications used (0.41 vs -0.06; difference, 0.46 [95% CI, 0.27-0.66]) and in the proportion of patients using CNS-active medications (absolute change, 3.44% vs 0.79%; difference, 2.65% [95% CI, 0.85%-4.45%]) owing to an increased use of antipsychotics, antidepressants, and antiepileptics. The cohort with dementia also had a modestly greater decline in use of anticholinergic medications (quarterly change in use, -0.53% vs -0.21%; difference, -0.32% [95% CI, -0.55% to -0.08%]) and most cardiometabolic medications (eg, quarterly change in antihypertensive use: -0.84% vs -0.40%; difference, -0.44% [95% CI, -0.64% to -0.25%]). One year after diagnosis, 75.2% of the cohort with dementia were using 5 or more medications (2.8% increase). Conclusions and Relevance In this cohort study of Medicare Part D beneficiaries, following an incident dementia diagnosis, patients were more likely to initiate CNS-active medications and modestly more likely to discontinue cardiometabolic and anticholinergic medications compared with the control group. These findings suggest missed opportunities to reduce burdensome polypharmacy by deprescribing long-term medications with high safety risks or limited likelihood of benefit or that may be associated with impaired cognition.
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Affiliation(s)
- Timothy S. Anderson
- Division of General Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - John Z. Ayanian
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor
- Division of General Medicine, University of Michigan, Ann Arbor
| | - Vilsa E. Curto
- Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Eran Politzer
- Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts
| | - Jeffrey Souza
- Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts
| | - Alan M. Zaslavsky
- Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts
| | - Bruce E. Landon
- Division of General Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
- Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts
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Paris J, Legris P, Devaux M, Bost S, Gueneau P, Rossi C, Manfredi S, Bouillet B, Petit JM, Pistre P, Boulin M. Impact of a Tripartite Collaboration between Oncologist, Pharmacist and Diabetologist in the Management of Patients with Diabetes Starting Chemotherapy: The ONCODIAB Trial. Cancers (Basel) 2023; 15:4544. [PMID: 37760514 PMCID: PMC10526306 DOI: 10.3390/cancers15184544] [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: 08/07/2023] [Revised: 08/30/2023] [Accepted: 09/08/2023] [Indexed: 09/29/2023] Open
Abstract
BACKGROUND Diabetes negatively impacts cancer prognosis. The objective of this work was to evaluate a tripartite oncologist-pharmacist-diabetologist collaboration in the management of patients with diabetes starting chemotherapy. PATIENTS AND METHODS The prospective ONCODIAB study (NCT04315857) included 102 adults with diabetes starting chemotherapy by whom a continuous glucose monitoring device was worn for fourteen days from the first day of the first and second chemotherapy cycles. The primary outcome was to assess pharmacist and diabetologist interventions. The secondary outcome was to evaluate the impact of the ONCODIAB follow-up on individualized patient glycemic targets at 6 months. RESULTS A total of 191 (2 per patient) were made either by clinical pharmacists (n = 95) or diabetologists (n = 96) during the first two chemotherapy cycles. The anatomic therapeutic chemical drug classes most frequently involved in pharmacist interventions were cardiovascular system (23%), alimentary tract and metabolism (22%), and anti-infectives for systemic use (14%). Diabetologists modified the antidiabetic treatment in 58 (62%) of patients: dose reduction (34%), drug discontinuation (28%), drug addition (24%), and dose increase (15%). Glycated hemoglobin decreased from 7.6 ± 1.7% at baseline to 7.1 ± 1.1% at 6 months (p = 0.02). Compared to individualized targets, HbA1c was higher, in the interval, or lower in 29%, 44%, and 27% of patients at baseline vs. in 8%, 70%, and 22% of patients at 6 months, respectively (p < 10-3). CONCLUSIONS In our study, a close collaboration between oncologists, pharmacists, and diabetologists helped by continuous glucose monitoring led to overall medication optimization and better glycemic control in patients with diabetes starting chemotherapy.
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Affiliation(s)
- Justine Paris
- Department of Pharmacy, University Hospital, 21000 Dijon, France; (J.P.); (M.D.); (S.B.); (P.G.); (P.P.)
| | - Pauline Legris
- Department of Endocrinology, Diabetes and Metabolic Disorders, University Hospital, 21000 Dijon, France; (P.L.); (B.B.); (J.-M.P.)
| | - Madeline Devaux
- Department of Pharmacy, University Hospital, 21000 Dijon, France; (J.P.); (M.D.); (S.B.); (P.G.); (P.P.)
| | - Stephanie Bost
- Department of Pharmacy, University Hospital, 21000 Dijon, France; (J.P.); (M.D.); (S.B.); (P.G.); (P.P.)
| | - Pauline Gueneau
- Department of Pharmacy, University Hospital, 21000 Dijon, France; (J.P.); (M.D.); (S.B.); (P.G.); (P.P.)
| | - Cedric Rossi
- Department of Clinical Hematology, University Hospital and SAPHIIT UMR 1231, University of Burgundy & Franche Comte, 21000 Dijon, France;
| | - Sylvain Manfredi
- Department of Hepatogastroenterology and Digestive Oncology, University Hospital and EPICAD LNC UMR 1231, University of Burgundy & Franche Comte, 21000 Dijon, France;
| | - Benjamin Bouillet
- Department of Endocrinology, Diabetes and Metabolic Disorders, University Hospital, 21000 Dijon, France; (P.L.); (B.B.); (J.-M.P.)
- PADYS LNC UMR 1231, University of Burgundy & Franche Comte, 21000 Dijon, France
| | - Jean-Michel Petit
- Department of Endocrinology, Diabetes and Metabolic Disorders, University Hospital, 21000 Dijon, France; (P.L.); (B.B.); (J.-M.P.)
- PADYS LNC UMR 1231, University of Burgundy & Franche Comte, 21000 Dijon, France
| | - Pauline Pistre
- Department of Pharmacy, University Hospital, 21000 Dijon, France; (J.P.); (M.D.); (S.B.); (P.G.); (P.P.)
| | - Mathieu Boulin
- Department of Pharmacy, University Hospital, 21000 Dijon, France; (J.P.); (M.D.); (S.B.); (P.G.); (P.P.)
- EPICAD LNC UMR 1231, University of Burgundy & Franche Comte, 21000 Dijon, France
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14
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Schuttner L, Richardson C, Parikh T, Wong ES. "Low-value" glycemic outcomes among older adults with diabetes cared for by primary care nurse practitioners or physicians: A retrospective cohort study. Int J Nurs Stud 2023; 145:104532. [PMID: 37315453 PMCID: PMC10760981 DOI: 10.1016/j.ijnurstu.2023.104532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 05/16/2023] [Accepted: 05/17/2023] [Indexed: 06/16/2023]
Abstract
BACKGROUND "Low-value" healthcare is care without benefit to patients. Overly intensive glycemic control (i.e., HgbA1C < 7 %) can cause harm to patients at high risk of hypoglycemia, particularly among older adults with co-morbidities. It is unknown whether overly intensive glycemic control differs among patients with diabetes and at high-risk of hypoglycemia cared for by primary care nurse practitioners versus physicians. OBJECTIVE This study examined patients with diabetes at high risk of hypoglycemia receiving primary care between Jan 2010 and Jan 2012, comparing patients reassigned to nurse practitioners to those reassigned to physicians after their previous physician separated from practice in an integrated United States health system. DESIGN This was a retrospective cohort study. Study outcomes were collected at two years after reassignment to a new primary care provider. Outcomes were predicted probabilities of HgbA1C < 7 % using two-stage residual inclusion instrumental variable models, controlling for baseline confounders. SETTING Primary care clinics within the United States Veterans Health Administration. PARTICIPANTS 38,543 patients with diabetes at increased risk for hypoglycemia (age ≥ 65 years with renal disease, dementia, or cognitive impairment), who had their primary care physician leave the Veterans Health Administration and who were reassigned to a new primary care provider in the following year. RESULTS Cohort patients were on average 76 years and 99 % men. Of these, 33,700 were reassigned to physicians and 4843 to nurse practitioners. After two years with their new provider, in adjusted models, patients reassigned to nurse practitioners had a -20.4 percentage-point [95 % CI -37.9 to -2.8] lower probability of two-year HgbA1C < 7 %. CONCLUSIONS Aligned with prior studies on care quality, rates of overly intensive glycemic control may be appropriately lower among older patients with diabetes at high-risk of hypoglycemia, cared for by nurse practitioners than physicians. TWEETABLE ABSTRACT Primary care nurse practitioners deliver equivalent or better rates of low-value diabetes care for older patients, compared to physicians.
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Affiliation(s)
- Linnaea Schuttner
- VA Puget Sound Health Care System, Seattle, WA, USA; Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA.
| | - Claire Richardson
- VA Puget Sound Health Care System, Seattle, WA, USA; Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA
| | - Toral Parikh
- VA Puget Sound Health Care System, Seattle, WA, USA; Department of Gerontology and Geriatric Medicine, University of Washington School of Medicine, Seattle, WA, USA
| | - Edwin S Wong
- VA Puget Sound Health Care System, Seattle, WA, USA; Department of Health Systems and Population Health, University of Washington School of Public Health, Seattle, WA, USA
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15
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Baretella O, Alwan H, Feller M, Aubert CE, Del Giovane C, Papazoglou D, Christiaens A, Meinders AJ, Byrne S, Kearney PM, O'Mahony D, Knol W, Boland B, Gencer B, Aujesky D, Rodondi N. Overtreatment and associated risk factors among multimorbid older patients with diabetes. J Am Geriatr Soc 2023; 71:2893-2901. [PMID: 37286338 DOI: 10.1111/jgs.18465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Revised: 04/21/2023] [Accepted: 05/16/2023] [Indexed: 06/09/2023]
Abstract
BACKGROUND In multimorbid older patients with type 2 diabetes mellitus (T2DM), the intensity of glucose-lowering medication (GLM) should be focused on attaining a suitable level of glycated hemoglobin (HbA1c ) while avoiding side effects. We aimed at identifying patients with overtreatment of T2DM as well as associated risk factors. METHODS In a secondary analysis of a multicenter study of multimorbid older patients, we evaluated HbA1c levels among patients with T2DM. Patients were aged ≥70 years, with multimorbidity (≥3 chronic diagnoses) and polypharmacy (≥5 chronic medications), enrolled in four university medical centers across Europe (Belgium, Ireland, Netherlands, and Switzerland). We defined overtreatment as HbA1c < 7.5% with ≥1 GLM other than metformin, as suggested by Choosing Wisely and used prevalence ratios (PRs) to evaluate risk factors of overtreatment in age- and sex-adjusted analyses. RESULTS Among the 564 patients with T2DM (median age 78 years, 39% women), mean ± standard deviation HbA1c was 7.2 ± 1.2%. Metformin (prevalence 51%) was the most frequently prescribed GLM and 199 (35%) patients were overtreated. The presence of severe renal impairment (PR 1.36, 1.21-1.53) and outpatient physician (other than general practitioner [GP], i.e. specialist) or emergency department visits (PR 1.22, 1.03-1.46 for 1-2 visits, and PR 1.35, 1.19-1.54 for ≥3 visits versus no visits) were associated with overtreatment. These factors remained associated with overtreatment in multivariable analyses. CONCLUSIONS In this multicountry study of multimorbid older patients with T2DM, more than one third were overtreated, highlighting the high prevalence of this problem. Careful balancing of benefits and risks in the choice of GLM may improve patient care, especially in the context of comorbidities such as severe renal impairment, and frequent non-GP healthcare contacts.
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Affiliation(s)
- Oliver Baretella
- Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland
- Department of General Internal Medicine, Inselspital, Bern University Hospital, Bern, Switzerland
| | - Heba Alwan
- Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland
- Graduate School for Health Sciences, University of Bern, Bern, Switzerland
| | - Martin Feller
- Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland
- Department of General Internal Medicine, Inselspital, Bern University Hospital, Bern, Switzerland
| | - Carole E Aubert
- Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland
- Department of General Internal Medicine, Inselspital, Bern University Hospital, Bern, Switzerland
| | - Cinzia Del Giovane
- Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland
| | - Dimitrios Papazoglou
- Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland
- Department of General Internal Medicine, Inselspital, Bern University Hospital, Bern, Switzerland
| | - Antoine Christiaens
- Institut Pierre Louis d'Epidémiologie et de Santé Publique, Sorbonne Université, INSERM, Paris, France
- Clinical Pharmacy research group, Louvain Drug Research Institute (LDRI), Université catholique de Louvain, Brussels, Belgium
| | - Arend-Jan Meinders
- Department of Internal Medicine, St Antonius Hospital, Nieuwegein, the Netherlands
| | - Stephen Byrne
- School of Pharmacy, University College Cork - National University of Ireland, Cork, Republic of Ireland
| | - Patricia M Kearney
- School of Public Health, University College Cork, Cork, Republic of Ireland
- Department of Medicine Cork, University College Cork - National University of Ireland, Cork, Republic of Ireland
| | - Denis O'Mahony
- Department of Medicine Cork, University College Cork - National University of Ireland, Cork, Republic of Ireland
- Department of Geriatric Medicine Cork, Cork University Hospital Group, Cork, Republic of Ireland
| | - Wilma Knol
- Department of Geriatrics and Expertise Centre Pharmacotherapy in Old Persons (EPHOR), University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Benoît Boland
- Clinical Pharmacy research group, Louvain Drug Research Institute (LDRI), Université catholique de Louvain, Brussels, Belgium
- Department of Geriatric Medicine, Cliniques universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium
| | - Baris Gencer
- Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland
- Service de cardiologie, Hôpitaux Universitaires de Genève (HUG), Geneva, Switzerland
| | - Drahomir Aujesky
- Department of General Internal Medicine, Inselspital, Bern University Hospital, Bern, Switzerland
| | - Nicolas Rodondi
- Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland
- Department of General Internal Medicine, Inselspital, Bern University Hospital, Bern, Switzerland
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16
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Bao H, Cao J, Chen M, Chen M, Chen W, Chen X, Chen Y, Chen Y, Chen Y, Chen Z, Chhetri JK, Ding Y, Feng J, Guo J, Guo M, He C, Jia Y, Jiang H, Jing Y, Li D, Li J, Li J, Liang Q, Liang R, Liu F, Liu X, Liu Z, Luo OJ, Lv J, Ma J, Mao K, Nie J, Qiao X, Sun X, Tang X, Wang J, Wang Q, Wang S, Wang X, Wang Y, Wang Y, Wu R, Xia K, Xiao FH, Xu L, Xu Y, Yan H, Yang L, Yang R, Yang Y, Ying Y, Zhang L, Zhang W, Zhang W, Zhang X, Zhang Z, Zhou M, Zhou R, Zhu Q, Zhu Z, Cao F, Cao Z, Chan P, Chen C, Chen G, Chen HZ, Chen J, Ci W, Ding BS, Ding Q, Gao F, Han JDJ, Huang K, Ju Z, Kong QP, Li J, Li J, Li X, Liu B, Liu F, Liu L, Liu Q, Liu Q, Liu X, Liu Y, Luo X, Ma S, Ma X, Mao Z, Nie J, Peng Y, Qu J, Ren J, Ren R, Song M, Songyang Z, Sun YE, Sun Y, Tian M, Wang S, Wang S, Wang X, Wang X, Wang YJ, Wang Y, Wong CCL, Xiang AP, Xiao Y, Xie Z, Xu D, Ye J, Yue R, Zhang C, Zhang H, Zhang L, Zhang W, Zhang Y, Zhang YW, Zhang Z, Zhao T, Zhao Y, Zhu D, Zou W, Pei G, Liu GH. Biomarkers of aging. SCIENCE CHINA. LIFE SCIENCES 2023; 66:893-1066. [PMID: 37076725 PMCID: PMC10115486 DOI: 10.1007/s11427-023-2305-0] [Citation(s) in RCA: 77] [Impact Index Per Article: 77.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 02/27/2023] [Indexed: 04/21/2023]
Abstract
Aging biomarkers are a combination of biological parameters to (i) assess age-related changes, (ii) track the physiological aging process, and (iii) predict the transition into a pathological status. Although a broad spectrum of aging biomarkers has been developed, their potential uses and limitations remain poorly characterized. An immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research: How old are we? Why do we get old? And how can we age slower? This review aims to address this need. Here, we summarize our current knowledge of biomarkers developed for cellular, organ, and organismal levels of aging, comprising six pillars: physiological characteristics, medical imaging, histological features, cellular alterations, molecular changes, and secretory factors. To fulfill all these requisites, we propose that aging biomarkers should qualify for being specific, systemic, and clinically relevant.
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Affiliation(s)
- Hainan Bao
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Jiani Cao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Mengting Chen
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China
| | - Min Chen
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Wei Chen
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China
| | - Xiao Chen
- Department of Nuclear Medicine, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Yanhao Chen
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yu Chen
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Yutian Chen
- The Department of Endovascular Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Zhiyang Chen
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China
| | - Jagadish K Chhetri
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Yingjie Ding
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Junlin Feng
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Jun Guo
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China
| | - Mengmeng Guo
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China
| | - Chuting He
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Yujuan Jia
- Department of Neurology, First Affiliated Hospital, Shanxi Medical University, Taiyuan, 030001, China
| | - Haiping Jiang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Ying Jing
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Dingfeng Li
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, China
| | - Jiaming Li
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jingyi Li
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Qinhao Liang
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China
| | - Rui Liang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China
| | - Feng Liu
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China
| | - Xiaoqian Liu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Zuojun Liu
- School of Life Sciences, Hainan University, Haikou, 570228, China
| | - Oscar Junhong Luo
- Department of Systems Biomedical Sciences, School of Medicine, Jinan University, Guangzhou, 510632, China
| | - Jianwei Lv
- School of Life Sciences, Xiamen University, Xiamen, 361102, China
| | - Jingyi Ma
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Kehang Mao
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China
| | - Jiawei Nie
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xinhua Qiao
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Xinpei Sun
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China
| | - Xiaoqiang Tang
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Jianfang Wang
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Qiaoran Wang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Siyuan Wang
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China
| | - Xuan Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China
| | - Yaning Wang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yuhan Wang
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Rimo Wu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China
| | - Kai Xia
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Fu-Hui Xiao
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Lingyan Xu
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Yingying Xu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Haoteng Yan
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Liang Yang
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China
| | - Ruici Yang
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yuanxin Yang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China
| | - Yilin Ying
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China
| | - Le Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Weiwei Zhang
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China
| | - Wenwan Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Xing Zhang
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China
| | - Zhuo Zhang
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Min Zhou
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China
| | - Rui Zhou
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Qingchen Zhu
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Zhengmao Zhu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
| | - Feng Cao
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China.
| | - Zhongwei Cao
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Piu Chan
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
| | - Chang Chen
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Guobing Chen
- Department of Microbiology and Immunology, School of Medicine, Jinan University, Guangzhou, 510632, China.
- Guangdong-Hong Kong-Macau Great Bay Area Geroscience Joint Laboratory, Guangzhou, 510000, China.
| | - Hou-Zao Chen
- Department of Biochemistryand Molecular Biology, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100005, China.
| | - Jun Chen
- Peking University Research Center on Aging, Beijing Key Laboratory of Protein Posttranslational Modifications and Cell Function, Department of Biochemistry and Molecular Biology, Department of Integration of Chinese and Western Medicine, School of Basic Medical Science, Peking University, Beijing, 100191, China.
| | - Weimin Ci
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
| | - Bi-Sen Ding
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Qiurong Ding
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Feng Gao
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China.
| | - Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China.
| | - Kai Huang
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
| | - Zhenyu Ju
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China.
| | - Qing-Peng Kong
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
| | - Ji Li
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China.
| | - Jian Li
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China.
| | - Xin Li
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Baohua Liu
- School of Basic Medical Sciences, Shenzhen University Medical School, Shenzhen, 518060, China.
| | - Feng Liu
- Metabolic Syndrome Research Center, The Second Xiangya Hospital, Central South Unversity, Changsha, 410011, China.
| | - Lin Liu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China.
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
- Institute of Translational Medicine, Tianjin Union Medical Center, Nankai University, Tianjin, 300000, China.
- State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin, 300350, China.
| | - Qiang Liu
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, China.
| | - Qiang Liu
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, 300052, China.
- Tianjin Institute of Immunology, Tianjin Medical University, Tianjin, 300070, China.
| | - Xingguo Liu
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China.
| | - Yong Liu
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China.
| | - Xianghang Luo
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China.
| | - Shuai Ma
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Xinran Ma
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
| | - Zhiyong Mao
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Jing Nie
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
| | - Yaojin Peng
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jing Qu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jie Ren
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Ruibao Ren
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Center for Aging and Cancer, Hainan Medical University, Haikou, 571199, China.
| | - Moshi Song
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Zhou Songyang
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China.
- Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China.
| | - Yi Eve Sun
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China.
| | - Yu Sun
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Department of Medicine and VAPSHCS, University of Washington, Seattle, WA, 98195, USA.
| | - Mei Tian
- Human Phenome Institute, Fudan University, Shanghai, 201203, China.
| | - Shusen Wang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China.
| | - Si Wang
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
| | - Xia Wang
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China.
| | - Xiaoning Wang
- Institute of Geriatrics, The second Medical Center, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100853, China.
| | - Yan-Jiang Wang
- Department of Neurology and Center for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China.
| | - Yunfang Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China.
| | - Catherine C L Wong
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China.
| | - Andy Peng Xiang
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China.
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Yichuan Xiao
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Zhengwei Xie
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China.
- Beijing & Qingdao Langu Pharmaceutical R&D Platform, Beijing Gigaceuticals Tech. Co. Ltd., Beijing, 100101, China.
| | - Daichao Xu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China.
| | - Jing Ye
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China.
| | - Rui Yue
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Cuntai Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China.
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
| | - Hongbo Zhang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Liang Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Weiqi Zhang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Yong Zhang
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Yun-Wu Zhang
- Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, School of Medicine, Xiamen University, Xiamen, 361102, China.
| | - Zhuohua Zhang
- Key Laboratory of Molecular Precision Medicine of Hunan Province and Center for Medical Genetics, Institute of Molecular Precision Medicine, Xiangya Hospital, Central South University, Changsha, 410078, China.
- Department of Neurosciences, Hengyang Medical School, University of South China, Hengyang, 421001, China.
| | - Tongbiao Zhao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Yuzheng Zhao
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China.
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China.
| | - Dahai Zhu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Weiguo Zou
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Gang Pei
- Shanghai Key Laboratory of Signaling and Disease Research, Laboratory of Receptor-Based Biomedicine, The Collaborative Innovation Center for Brain Science, School of Life Sciences and Technology, Tongji University, Shanghai, 200070, China.
| | - Guang-Hui Liu
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
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Chen JTC, Austin PC, Luo J, Campitelli MA, Bronskill SE, Yu C, Rochon PA, Lipscombe LL, Lega IC. Patterns of diabetes testing for older adults without diabetes in Ontario's nursing homes: A population-based study. J Am Geriatr Soc 2023; 71:720-729. [PMID: 36515210 DOI: 10.1111/jgs.18152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 10/31/2022] [Accepted: 11/06/2022] [Indexed: 12/15/2022]
Abstract
BACKGROUND Asymptomatic diabetes testing may be of limited value for older nursing home residents, but most diabetes guidelines lack upper-age cutoffs for screening cessation. We evaluated patterns of glycated hemoglobin (HbA1c) and serum blood glucose (SBG) testing among older residents without diabetes in Ontario, Canada. METHODS This population-based retrospective cohort study used provincial health administrative data from ICES to identify older nursing home residents in Ontario without diabetes between January 1, 2015 and December 31, 2018. We examined HbA1c and glucose testing rates overall, by age, sex, and near end-of-life. The number of tests needed to identify one case of diabetes (using HbA1c thresholds of 6.5% and 8.0%) were also calculated. RESULTS Among 102,923 older nursing home residents (70.3% women; average age 85.6 ± SD 7.7 years), 46.1% of residents received ≥1 HbA1c test over an average follow-up period of 2.15 (± SD 1.49) years, and 18.2% of these tested residents received ≥4 HbA1c tests. The crude HbA1c testing rate was 52.6 tests/100 person-years (95% CI 52.3-52.9). Testing rates among residents aged ≥80 years was 50.7 HbA1c tests/100 person-years (95% CI 50.4-51.0), and 47.8 tests/100 person-years (95% CI 46.5-49.0) among residents near end-of-life. The number of tests to identify a case of diabetes (HbA1c ≥ 6.5%) was 44, while the number of tests to identify a case of actionable diabetes (HbA1c ≥ 8%) was 310. Less than 1% of residents with an HbA1c test met criteria for actionable diabetes. CONCLUSIONS Nursing home residents without diabetes receive frequent diabetes testing, with high testing rates even in residents over 80 years old and residents near end-of-life. The high number of tests needed to identify a case of actionable diabetes highlights the urgent need to re-evaluate diabetes testing practices in nursing homes.
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Affiliation(s)
- Jim T C Chen
- Women's College Research Institute, Women's College Hospital, Toronto, Canada
- Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
| | | | | | | | - Susan E Bronskill
- Women's College Research Institute, Women's College Hospital, Toronto, Canada
- ICES, Toronto, Canada
- Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, Canada
| | - Catherine Yu
- Department of Medicine, University of Toronto, Toronto, Canada
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada
| | - Paula A Rochon
- Women's College Research Institute, Women's College Hospital, Toronto, Canada
- ICES, Toronto, Canada
- Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, Canada
- Department of Medicine, University of Toronto, Toronto, Canada
| | - Lorraine L Lipscombe
- Women's College Research Institute, Women's College Hospital, Toronto, Canada
- ICES, Toronto, Canada
- Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, Canada
- Department of Medicine, University of Toronto, Toronto, Canada
| | - Iliana C Lega
- Women's College Research Institute, Women's College Hospital, Toronto, Canada
- ICES, Toronto, Canada
- Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, Canada
- Department of Medicine, University of Toronto, Toronto, Canada
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18
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Hypoglycaemia aggravates impaired endothelial-dependent vasodilation in diabetes by suppressing endothelial nitric oxide synthase activity and stimulating inducible nitric oxide synthase expression. Microvasc Res 2023; 146:104468. [PMID: 36513147 DOI: 10.1016/j.mvr.2022.104468] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 11/16/2022] [Accepted: 12/06/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND Diabetes exacerbates vascular injury by triggering endothelial dysfunction. Endothelial nitric oxide synthase (eNOS) and inducible nitric oxide synthase (iNOS) both play major roles in endothelial dysfunction. However, effects of hypoglycaemia, the main complication of the insulin therapy to the glycemic control in diabetes, on eNOS activity and iNOS expression, and underlying mechanisms in diabetes remain unknown. Hence, we aimed to determine the effects of hypoglycaemia on eNOS activity and iNOS expression in different arterial beds of diabetic rats. METHODS Sprague-Dawley rats were subjected to Streptozotocin (STZ) combined with high fat diet (HFD) to induce diabetes and then received insulin injection to attain acute and recurrent hypoglycaemia. Immunoblotting was used to analyse the phosphorylation and O-glycosylation status of eNOS and iNOS level from thoracic aorta and mesenteric artery tissue. Indicators of oxidative stress from plasm were determined, and endothelial-dependent vasodilation was detected via wire myograph system. RESULTS Hypoglycaemia was associated with a marked increase in eNOS O-GlcNAcylation and decrease in Serine (Ser)-1177 phosphorylation from thoracic aortas and mesenteric arteries. Moreover, hypoglycaemia resulted in elevated phosphorylation of eNOS at Threonine (Thr)-495 site in mesenteric arteries. Besides, changes in these post-translational modifications were associated with increased O-GlcNAc transferase (OGT), decreased phosphorylation of Akt at Ser-473, and increased protein kinase C α subunit (PKCα). iNOS expression was induced in hypoglycaemia. Furthermore, endothelial-dependent vasodilation was impaired under insulin-induced hypoglycaemia, and further in recurrent hypoglycaemia. CONCLUSIONS Conclusively, these findings strongly indicate that hypoglycaemia-dependent vascular dysfunction in diabetes is mediated through altered eNOS activity and iNOS expression. Therefore, this implies that therapeutic modulation of eNOS activity and iNOS expression in diabetics under intensive glucose control may prevent and treat adverse cardiovascular events.
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19
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Cui W, Luo K, Xiao Q, Sun Z, Wang Y, Cui C, Chen F, Xu B, Shen W, Wan F, Cheng A. Effect of mulberry leaf or mulberry leaf extract on glycemic traits: a systematic review and meta-analysis. Food Funct 2023; 14:1277-1289. [PMID: 36644880 DOI: 10.1039/d2fo02645g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Mulberry leaf (ML) and mulberry leaf extract (MLE) have numerous biological properties, such as regulating sugar and lipid metabolism, reducing blood glucose, and increasing insulin secretion. The aim of this study was to perform a systematic review and meta-analysis of randomized clinical trials to examine the effect of ML/MLE supplementation on glycemic traits in adults, including fasting blood glucose (FBG), glycosylated hemoglobin (HbA1c), and fasting plasma insulin (FPI). Twelve clinical trials (615 participants) fulfilled the eligibility criteria for the present meta-analysis, which included sensitivity analysis and GRADE (grading of recommendations assessment, development, and evaluation) certainty. Based on the heterogeneity between included studies, a random effects model was applied in the meta-analysis, and the results are expressed as WMD (weighted mean differences) with 95% CI (confidence intervals). Meta-analysis showed that ML/MLE supplementation resulted in a significant reduction in FBG by -0.47 mmol L-1, HbA1c by -2.92 mmol mol-1, and FPI by -0.58 μIU mL-1. In addition, subgroup analysis indicated that long-term supplementation of ML/MLE (≥8 weeks) was more effective for regulation of the glycemic traits in the non-healthy and baseline FPG >6.1 mmol L-1 subgroups. Glycemic regulation by ML/MLE may be attributed to the phytochemicals they contain, which are mainly 1-deoxynojirimycin, flavonoids, phenolics, and polysaccharides.
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Affiliation(s)
- Wenyu Cui
- College of Food Science and Technology/Engineering Center of Rapeseed Oil Nutrition Health and Deep Development of Hunan Province, Hunan Agricultural University, Changsha, 410128, China.
| | - Kaiyun Luo
- College of Food Science and Technology/Engineering Center of Rapeseed Oil Nutrition Health and Deep Development of Hunan Province, Hunan Agricultural University, Changsha, 410128, China.
| | - Qian Xiao
- College of Food Science and Technology/Engineering Center of Rapeseed Oil Nutrition Health and Deep Development of Hunan Province, Hunan Agricultural University, Changsha, 410128, China.
| | - Zhaoyue Sun
- College of Food Science and Technology/Engineering Center of Rapeseed Oil Nutrition Health and Deep Development of Hunan Province, Hunan Agricultural University, Changsha, 410128, China.
| | - Yunfu Wang
- College of Food Science and Technology/Engineering Center of Rapeseed Oil Nutrition Health and Deep Development of Hunan Province, Hunan Agricultural University, Changsha, 410128, China.
| | - Caifang Cui
- College of Food Science and Technology/Engineering Center of Rapeseed Oil Nutrition Health and Deep Development of Hunan Province, Hunan Agricultural University, Changsha, 410128, China.
| | - Fuchun Chen
- College of Food Science and Technology/Engineering Center of Rapeseed Oil Nutrition Health and Deep Development of Hunan Province, Hunan Agricultural University, Changsha, 410128, China.
| | - Ben Xu
- College of Food Science and Technology/Engineering Center of Rapeseed Oil Nutrition Health and Deep Development of Hunan Province, Hunan Agricultural University, Changsha, 410128, China.
| | - Weijun Shen
- College of Animal Science and Technology, Hunan Agricultural University, Changsha, 410128, China.
| | - Fachun Wan
- College of Animal Science and Technology, Hunan Agricultural University, Changsha, 410128, China.
| | - Anwei Cheng
- College of Food Science and Technology/Engineering Center of Rapeseed Oil Nutrition Health and Deep Development of Hunan Province, Hunan Agricultural University, Changsha, 410128, China.
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20
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Chow E, Merchant AA, Molnar F, Frank C. Approach to chronic kidney disease in the elderly. CANADIAN FAMILY PHYSICIAN MEDECIN DE FAMILLE CANADIEN 2023; 69:25-27. [PMID: 36693745 PMCID: PMC9873299 DOI: 10.46747/cfp.690125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Affiliation(s)
| | | | - Frank Molnar
- Specialist in geriatric medicine practising in the Department of Medicine at the University of Ottawa and at the Ottawa Hospital Research Institute in Ontario
| | - Chris Frank
- Family physician specializing in care of the elderly and palliative care at Queen's University in Kingston, Ont
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21
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Chow E, Merchant AA, Molnar F, Frank C. Approche de la néphropathie chronique chez les personnes âgées. CANADIAN FAMILY PHYSICIAN MEDECIN DE FAMILLE CANADIEN 2023; 69:e14-e16. [PMID: 36693754 PMCID: PMC9873291 DOI: 10.46747/cfp.6901e14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Affiliation(s)
| | | | - Frank Molnar
- Spécialiste en médecine gériatrique; il exerce au Département de médecine de l'Université d'Ottawa et à l'Institut de recherche de l'Hôpital d'Ottawa (Ontario)
| | - Chris Frank
- Médecin de famille spécialisé en soins aux personnes âgées et en soins palliatifs à l'Université Queen's à Kingston (Ontario)
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22
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Medications for Chronic Conditions and Mortality in Older Adults. Nurs Res 2023; 72:30-37. [PMID: 36053079 DOI: 10.1097/nnr.0000000000000618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
BACKGROUND With the population aging, examining the relationship between polypharmacy and mortality based on population data sources is important for clinical management and policy direction. OBJECTIVES This study aimed to examine the association between the number of chronic medications and the risk of mortality in older adults. METHODS This population-based retrospective cohort study used data from the National Health Insurance Research Database in Taiwan for information regarding chronic medication use (over 4 years) in older adults aged 65 years and older. The association between medication use and mortality numbers was analyzed using Cox proportional hazards regression models adjusted for demographic variables and comorbidity. RESULTS The number of medications was significantly associated with high mortality risk. Within polypharmacy, being 65-74 years old, male, living in northern Taiwan, having one type of comorbid disease, and receiving <84 days of refillable chronic prescription were associated with greater mortality risk. Subgroup analyses' results regarding comorbidity showed significant positive associations between the number of medications and mortality in most comorbid diseases except for mental disorders and diseases of the skin and subcutaneous tissue. DISCUSSION General practitioners should know that chronic polypharmacy is associated with increased mortality risk. Recognizing the possible adverse effects of multiple medication use could help physicians optimize drug regimens in the future.
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23
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The effects of oral magnesium supplementation on glycaemic control in patients with type 2 diabetes: a systematic review and dose-response meta-analysis of controlled clinical trials. Br J Nutr 2022; 128:2363-2372. [PMID: 35045911 DOI: 10.1017/s0007114521005201] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
The current systematic review and meta-analysis were conducted to evaluate the effects of oral Mg supplementation on glycaemic control in type 2 diabetes mellitus (T2DM) patients. Related articles were found by searching the PubMed, SCOPUS, Embase and Web of Science databases (from inception to 30 February 2020). A one-stage robust error meta-regression model based on inverse variance weighted least squares regression and cluster robust error variances was used for the dose-response analysis between Mg supplementation and duration of intervention and glycaemic control factors. Eighteen eligible randomised clinical trials were included in our final analysis. The dose-response testing indicated that the estimated mean difference in HbA1c at 500 mg/d was -0·73 % (95 % CI: -1·25, -0·22) suggesting modest improvement in HbA1c with strong evidence (P value: 0·004). And in fasting blood sugar (FBS) at 360 mg/d was -7·11 mg/dl (95 % CI: -14·03, -0·19) suggesting minimal amelioration in FBS with weak evidence (P value: 0·092) against the model hypothesis at this sample size. The estimated mean difference in FBS and HbA1c at 24 weeks was -15·58 mg/dl (95 % CI: -24·67, -6·49) and -0·48 (95 % CI: -0·77, -0·19), respectively, suggesting modest improvement in FBS (P value: 0·034) and HbA1c (P value: 0·001) with strong evidence against the model hypothesis at this sample size. Oral Mg supplementation could have an effect on glycaemic control in T2DM patients. However, the clinical trials so far are not sufficient to make guidelines for clinical practice.
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24
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Martinez-De la Torre A, Perez-Cruz F, Weiler S, Burden AM. Comorbidity clusters associated with newly treated type 2 diabetes mellitus: a Bayesian nonparametric analysis. Sci Rep 2022; 12:20653. [PMID: 36450743 PMCID: PMC9712684 DOI: 10.1038/s41598-022-24217-2] [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] [Received: 05/26/2022] [Accepted: 11/11/2022] [Indexed: 12/05/2022] Open
Abstract
Type 2 diabetes mellitus (T2DM) is associated with the development of chronic comorbidities, which can lead to high drug utilization and adverse events. We aimed to identify common comorbidity clusters and explore the progression over time in newly treated T2DM patients. The IQVIA Medical Research Data incorporating data from THIN, a Cegedim database of anonymized electronic health records, was used to identify all patients with a first-ever prescription for a non-insulin antidiabetic drug (NIAD) between January 2006 and December 2019. We selected 58 chronic comorbidities of interest and used Bayesian nonparametric models to identify disease clusters and model their progression over time. Among the 175,383 eligible T2DM patients, we identified the 20 most frequent comorbidity clusters, which were comprised of 14 latent features (LFs). Each LF was associated with a primary disease (e.g., 98% of patients in cluster 2, characterized by LF2, had congestive heart failure [CHF]). The presence of certain LFs increased the probability of having another LF active. For example, LF2 (CHF) frequently appeared with LFs related to chronic kidney disease (CKD). Over time, the clusters associated with cardiovascular diseases, such as CHF, progressed rapidly. Moreover, the onset of certain diseases led to further complications. Our models identified established T2DM complications and previously unknown connections, thus, highlighting the potential for Bayesian nonparametric models to characterize complex comorbidity patterns.
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Affiliation(s)
- Adrian Martinez-De la Torre
- grid.5801.c0000 0001 2156 2780Institute of Pharmaceutical Sciences, Department of Chemistry and Applied Biosciences, ETH Zurich, Vladimir-Prelog-Weg 1-5/10, 8093 Zurich, Switzerland
| | - Fernando Perez-Cruz
- grid.5801.c0000 0001 2156 2780Swiss Data Science Center, ETH Zurich and EPFL, Zurich, Switzerland ,grid.5801.c0000 0001 2156 2780Institute of Machine Learning, Department of Computer Science, ETH Zurich, Zurich, Switzerland
| | - Stefan Weiler
- grid.5801.c0000 0001 2156 2780Institute of Pharmaceutical Sciences, Department of Chemistry and Applied Biosciences, ETH Zurich, Vladimir-Prelog-Weg 1-5/10, 8093 Zurich, Switzerland
| | - Andrea M. Burden
- grid.5801.c0000 0001 2156 2780Institute of Pharmaceutical Sciences, Department of Chemistry and Applied Biosciences, ETH Zurich, Vladimir-Prelog-Weg 1-5/10, 8093 Zurich, Switzerland
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25
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Kumari S, Jain S, Kumar S. Effects of Polypharmacy in Elderly Diabetic Patients: A Review. Cureus 2022; 14:e29068. [PMID: 36249664 PMCID: PMC9554834 DOI: 10.7759/cureus.29068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 09/12/2022] [Indexed: 11/26/2022] Open
Abstract
Diabetes is a chronic condition brought on by either insufficient insulin production by the pancreas or inefficient insulin utilization by the body or both. A hormone called insulin controls blood sugar. Multiple co-morbidities can arise as a result of the progressive nature of diabetes, necessitating the use of numerous medications. As one or more medications may be used to treat each ailment, the older population with multimorbidity frequently uses many medications, also known as polypharmacy. Due to polypharmacy, harmful medication interactions, and food-drug interactions can occur. Because of the numerous co-morbidities that already exist, there is an increasing tendency of prescribing polypharmacy.
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26
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Abd.Ghafar MZA, O’Donovan M, Sezgin D, Moloney E, Rodríguez-Laso Á, Liew A, O’Caoimh R. Frailty and diabetes in older adults: Overview of current controversies and challenges in clinical practice. FRONTIERS IN CLINICAL DIABETES AND HEALTHCARE 2022; 3:895313. [PMID: 36992729 PMCID: PMC10012063 DOI: 10.3389/fcdhc.2022.895313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Accepted: 07/27/2022] [Indexed: 11/13/2022]
Affiliation(s)
- Mohd Zaquan Arif Abd.Ghafar
- Faculty of Medicine, Universiti Teknologi MARA (Sungai Buloh), Selangor, Malaysia
- Geriatrics Unit, Selayang Hospital, Selangor, Malaysia
- *Correspondence: Mohd Zaquan Arif Abd.Ghafar,
| | - Mark O’Donovan
- Department of Geriatric Medicine, Mercy University Hospital, Cork, Ireland
- Health Research Board Clinical Research Facility, University College Cork, Cork, Ireland
| | - Duygu Sezgin
- School of Nursing and Midwifery, Aras Moyola, National University of Ireland Galway, Galway, Ireland
| | - Elizabeth Moloney
- Department of Geriatric Medicine, Mercy University Hospital, Cork, Ireland
- Health Research Board Clinical Research Facility, University College Cork, Cork, Ireland
| | - Ángel Rodríguez-Laso
- CIBERFES (Área temática de Fragilidad y Envejecimiento Saludable del Centros de Investigación Biomédica en Red), Instituto de Salud Carlos III, Madrid, Spain
| | - Aaron Liew
- Department of Endocrinology, National University of Ireland Galway, Galway, Ireland
| | - Rónán O’Caoimh
- Department of Geriatric Medicine, Mercy University Hospital, Cork, Ireland
- Health Research Board Clinical Research Facility, University College Cork, Cork, Ireland
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27
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Jiang DH, O'Connor PJ, Huguet N, Golden SH, McCoy RG. Modernizing Diabetes Care Quality Measures. Health Aff (Millwood) 2022; 41:955-962. [PMID: 35759700 PMCID: PMC9288231 DOI: 10.1377/hlthaff.2022.00233] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
The proliferation of diabetes quality measures in the US since the mid-1990s has increased the burden of measurement without commensurate improvements in the quality of care or health outcomes. Measures in use today do not represent or incentivize achievement of care goals in all domains of quality that are necessary to achieve optimal diabetes health. We recommend reimagining and improving diabetes quality measurement through the following propositions: widespread adoption of new measures and modernization of existing measures across six domains of quality; use of a subset of new and modernized metrics as top-line measures for reporting and reimbursement; and optional use of the remaining new and modernized measures for evaluative purposes at all levels of the care delivery system to identify and address gaps in care quality and outcomes. These propositions would support practices and policies at all levels of the health care system to improve the health of people with diabetes.
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Affiliation(s)
| | | | - Nathalie Huguet
- Nathalie Huguet, Oregon Health & Science University, Portland, Oregon
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28
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Raghavan S, Warsavage T, Liu WG, Raffle K, Josey K, Saxon DR, Phillips LS, Caplan L, Reusch JEB. Trends in Timing of and Glycemia at Initiation of Second-line Type 2 Diabetes Treatment in U.S. Adults. Diabetes Care 2022; 45:1335-1345. [PMID: 35344584 PMCID: PMC9210868 DOI: 10.2337/dc21-2492] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 02/24/2022] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Therapeutic inertia threatens the potential long-term benefits of achieving early glycemic control after type 2 diabetes diagnosis. We evaluated temporal trends in second-line diabetes medication initiation among individuals initially treated with metformin. RESEARCH DESIGN AND METHODS We included data from 199,042 adults with type 2 diabetes in the U.S. Department of Veterans Affairs health care system initially treated with metformin monotherapy from 2005 to 2013. We used multivariable Cox proportional hazards and linear regression to estimate associations of year of metformin monotherapy initiation with time to second-line diabetes treatment over 5 years of follow-up (primary outcome) and with hemoglobin A1c (HbA1c) at the time of second-line diabetes treatment initiation (secondary outcome). RESULTS The cumulative 5-year incidence of second-line medication initiation declined from 47% among metformin initiators in 2005 to 36% in 2013 counterparts (P < 0.0001) despite a gradual increase in mean HbA1c at the end of follow-up (from 6.94 ± 1.28% to 7.09 ± 1.42%, Ptrend < 0.0001). In comparisons with metformin monotherapy initiators in 2005, adjusted hazard ratios for 5-year initiation of second-line diabetes treatment ranged from 0.90 (95% CI 0.87, 0.92) for 2006 metformin initiators to 0.68 (0.66, 0.70) for 2013 counterparts. Among those receiving second-line treatment within 5 years of metformin initiation, HbA1c at second-line medication initiation increased from 7.74 ± 1.66% in 2005 metformin initiators to 8.55 ± 1.92% in 2013 counterparts (Ptrend < 0.0001). CONCLUSIONS We observed progressive delays in diabetes treatment intensification consistent with therapeutic inertia. Process-of-care interventions early in the diabetes disease course may be needed to reverse adverse temporal trends in diabetes care.
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Affiliation(s)
- Sridharan Raghavan
- Medicine Service, U.S. Department of Veterans Affairs, Eastern Colorado Health Care System, Aurora, CO.,Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO.,Colorado Cardiovascular Outcomes Research Consortium, Aurora, CO
| | - Theodore Warsavage
- Medicine Service, U.S. Department of Veterans Affairs, Eastern Colorado Health Care System, Aurora, CO.,Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO
| | - Wenhui G Liu
- Medicine Service, U.S. Department of Veterans Affairs, Eastern Colorado Health Care System, Aurora, CO
| | - Katherine Raffle
- Medicine Service, U.S. Department of Veterans Affairs, Eastern Colorado Health Care System, Aurora, CO
| | - Kevin Josey
- Medicine Service, U.S. Department of Veterans Affairs, Eastern Colorado Health Care System, Aurora, CO.,Department of Biostatistics, Harvard School of Public Health, Boston, MA
| | - David R Saxon
- Medicine Service, U.S. Department of Veterans Affairs, Eastern Colorado Health Care System, Aurora, CO.,Division of Endocrinology, Metabolism, and Diabetes, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Lawrence S Phillips
- Medicine Service, Atlanta Veterans Affairs Medical Center, Decatur, GA.,Department of Medicine, Emory University School of Medicine, Atlanta, GA
| | - Liron Caplan
- Medicine Service, U.S. Department of Veterans Affairs, Eastern Colorado Health Care System, Aurora, CO.,Division of Rheumatology, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Jane E B Reusch
- Medicine Service, U.S. Department of Veterans Affairs, Eastern Colorado Health Care System, Aurora, CO.,Division of Endocrinology, Metabolism, and Diabetes, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
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29
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Lega IC, Rochon PA. Diabetes treatment deintensification in nursing homes: When less is more. J Am Geriatr Soc 2022; 70:1946-1949. [PMID: 35587266 DOI: 10.1111/jgs.17832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 04/20/2022] [Indexed: 11/28/2022]
Affiliation(s)
- Iliana C Lega
- Department of Medicine, Division of Endocrinology, University of Toronto, Toronto, Canada.,Women's Age Lab, Women's College Hospital, Toronto, Canada.,Women's College Research Institute, Toronto, Canada.,ICES, Toronto, Canada
| | - Paula A Rochon
- Women's Age Lab, Women's College Hospital, Toronto, Canada.,Department of Medicine, Division of Geriatric Medicine, University of Toronto, Toronto, Canada
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30
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Hume AL, Osundolire S, Mbrah AK, Nunes AP, Lapane KL. Antihyperglycemic Drug Use in Long-Stay Nursing Home Residents with Diabetes Mellitus. THE JOURNAL OF NURSING HOME RESEARCH SCIENCES 2022; 8:10-19. [PMID: 36451895 PMCID: PMC9706405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
BACKGROUND About 29.2% of American adults ≥ 65 years of age have diabetes mellitus, but details regarding diabetes management especially among nursing home residents are dated. OBJECTIVES Evaluate the prevalence of antihyperglycemic agents in residents with diabetes mellitus and describe resident characteristics using major drug classes. DESIGN cross-sectional study. SETTING virtually all United States nursing homes. PARTICIPANTS 141,636 residents with diabetes mellitus. MEASUREMENTS Minimum Data Set (2016) and Medicare Part D claims determined use of metformin, sulfonylureas, meglitinide analogs, alpha-glucosidase inhibitors, TZDs, DPP4 inhibitors, SGLT2 inhibitors, GLP1 agonists, as monotherapy and with basal insulin. RESULTS Seventy-two percent received antihyperglycemic drugs [most common: basal insulins (53.9% total; 46.9% with other non-insulin agents), metformin (35.5% total; 14.2% monotherapy), sulfonylureas (19.6% total; 6.3% monotherapy), and DPP4 inhibitors (12.2% total; 2.2% monotherapy)]. Sixty-three percent of meglitinide monotherapy versus 34.1% of metformin monotherapy users; and 38.3% meglitinide-basal insulin versus 22.2% metformin-basal insulin users were ≥85 years. Obesity was greater among users of GLP1 agonists compared to those receiving other agents (monotherapy: 60.5% versus 33-42%; with basal insulin: 76.2% versus 50-58%). End-stage renal disease was least prevalent among metformin users (monotherapy: 6.6%; with basal insulin: 8.8%) and most common among meglitinide monotherapy (19.6%) and GLP1 agonists with basal insulin (22%) users. CONCLUSIONS There is heterogeneity of diabetes treatment in nursing homes. Use of antihyperglycemic drugs with a higher risk of hypoglycemia, such as insulin with sulfonylureas or meglitinides, continue in nursing home residents.
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Affiliation(s)
- Anne L. Hume
- College of Pharmacy, University of Rhode Island, Kingston, RI, USA
- Division of Epidemiology, Department of Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, USA
| | - Seun Osundolire
- Division of Epidemiology, Department of Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, USA
| | - Attah K. Mbrah
- Division of Epidemiology, Department of Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, USA
| | - Anthony P. Nunes
- Division of Epidemiology, Department of Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, USA
| | - Kate L. Lapane
- Division of Epidemiology, Department of Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, USA
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Seidu S, Cos X, Brunton S, Harris SB, Jansson SPO, Mata-Cases M, Neijens AMJ, Topsever P, Khunti K. 2022 update to the position statement by Primary Care Diabetes Europe: a disease state approach to the pharmacological management of type 2 diabetes in primary care. Prim Care Diabetes 2022; 16:223-244. [PMID: 35183458 DOI: 10.1016/j.pcd.2022.02.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 01/25/2022] [Accepted: 02/02/2022] [Indexed: 12/12/2022]
Abstract
Type 2 diabetes and its associated comorbidities are growing more prevalent, and the complexity of optimising glycaemic control is increasing, especially on the frontlines of patient care. In many countries, most patients with type 2 diabetes are managed in a primary care setting. However, primary healthcare professionals face the challenge of the growing plethora of available treatment options for managing hyperglycaemia, leading to difficultly in making treatment decisions and contributing to treatment and therapeutic inertia. This position statement offers a simple and patient-centred clinical decision-making model with practical treatment recommendations that can be widely implemented by primary care clinicians worldwide through shared-decision conversations with their patients. It highlights the importance of managing cardiovascular disease and elevated cardiovascular risk in people with type 2 diabetes and aims to provide innovative risk stratification and treatment strategies that connect patients with the most effective care.
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Affiliation(s)
- S Seidu
- Diabetes Research Centre, University of Leicester, Leicester General Hospital, Gwendolen Road, Leicester, LE5 4PW, United Kingdom.
| | - X Cos
- Sant Marti de Provenҫals Primary Care Centres, Institut Català de la Salut, University Research Institute in Primary Care (IDIAP Jordi Gol), Barcelona, Spain
| | - S Brunton
- Primary Care Metabolic Group, Winnsboro, SC, USA
| | - S B Harris
- Department of Family Medicine, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - S P O Jansson
- School of Medical Sciences, University Health Care Research Centre, Örebro University, Örebro, Sweden
| | - M Mata-Cases
- La Mina Primary Care Centre, Institut Català de la Salut, University Research Institute in Primary Care (IDIAP Jordi Gol), CIBER of Diabetes and Associated Metabolic Diseases (CIBERDEM), Instituto de Salud Carlos III (ISCIII), Barcelona, Spain
| | - A M J Neijens
- Praktijk De Diabetist, Nurse-Led Case Management in Diabetes, QOL-consultancy, Deventer, The Netherlands
| | - P Topsever
- Department of Family Medicine, Acibadem Mehmet Ali Aydinlar University School of Medicine, Kerem Aydinlar Campus, 34752 Atasehir, Istanbul, Turkey
| | - K Khunti
- Diabetes Research Centre, University of Leicester, Leicester General Hospital, Gwendolen Road, Leicester, LE5 4PW, United Kingdom
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Ha J, Baek KH. Response to letter, re. "Comparison of fracture risk between type 1 and type 2 diabetes: a comprehensive real-world data". Osteoporos Int 2022; 33:955-956. [PMID: 35175393 DOI: 10.1007/s00198-022-06336-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 02/07/2022] [Indexed: 11/24/2022]
Affiliation(s)
- J Ha
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - K-H Baek
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
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Gudi SK, Bugden S, Singer A, Falk J. Potential Overtreatment and Overtesting Among Older Adults With Type 2 Diabetes Across Canada: An Observational, Retrospective Cohort Study. Can J Diabetes 2022; 46:S1499-2671(22)00022-3. [PMID: 35933318 DOI: 10.1016/j.jcjd.2022.02.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 12/23/2021] [Accepted: 02/24/2022] [Indexed: 11/26/2022]
Abstract
OBJECTIVE Our aim in this study was to assess potential overtreatment and overtesting among older adults with type 2 diabetes across Canada. METHODS An observational, population-based cohort study was conducted using data available through the Canadian Primary Care Sentinel Surveillance Network. All patients included in the study were seen by a primary care provider between 2010 and 2017, ≥65 years with type 2 diabetes and had at least one glycated hemoglobin (A1C) measurement. Potential overtreatment was defined as an index A1C of <7% and being prescribed antidiabetes medications other than metformin within 1 year of the index A1C. Testing ≥3 times/year in patients with A1C <7% was considered potential overtesting. Analyses were performed/compared within 2 cross-sectional cohorts (2012 and 2016). A subcohort analysis was performed on those with advanced age and dementia. RESULTS An overall cohort of 41,032 patients (mean age, 76.6 years) was identified. Proportions of potential overtreatment were 7.0% (2012) and 6.9% (2016) (difference in rate in %: 0.1; 95% confidence interval [CI], -0.32 to 0.52]). Overall, 19.2% (2012) and 19.0% (2016) of patients were potentially overtested (difference in rate in %: 0.2; 95% CI, -0.45 to 0.85), whereas 2.4% (2012) and 2.3% (2016) were potentially undertested (difference in rate in %: 0.1; 95% CI, -0.15 to 0.35). Among patients with dementia and advanced age, proportions of patients potentially overtreated were 14.5% and 12.1%, and those overtested were 29.2% and 25.0% in 2012 and 2016, respectively. CONCLUSIONS Potential overtreatment and overtesting exists among older adults with diabetes in Canadian primary care practices with minimal change over time. Higher proportions of potentially unnecessary care were observed in those with advanced age and dementia. Our study highlights an opportunity for primary care clinicians to improve testing and treatment practices considering the individual patient, context and potential for net benefit.
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Affiliation(s)
- Sai Krishna Gudi
- College of Pharmacy, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Shawn Bugden
- School of Pharmacy, Memorial University of Newfoundland, Health Sciences Centre, St. John's, Newfoundland, Canada
| | - Alexander Singer
- Department of Family Medicine, Max Rady College of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Jamie Falk
- College of Pharmacy, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada.
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Kim J, Kwon HS. Not Control but Conquest: Strategies for the Remission of Type 2 Diabetes Mellitus. Diabetes Metab J 2022; 46:165-180. [PMID: 35385632 PMCID: PMC8987695 DOI: 10.4093/dmj.2021.0377] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 03/02/2022] [Indexed: 12/14/2022] Open
Abstract
A durable normoglycemic state was observed in several studies that treated type 2 diabetes mellitus (T2DM) patients through metabolic surgery, intensive therapeutic intervention, or significant lifestyle modification, and it was confirmed that the functional β-cell mass was also restored to a normal level. Therefore, expert consensus introduced the concept of remission as a common term to express this phenomenon in 2009. Throughout this article, we introduce the recently updated consensus statement on the remission of T2DM in 2021 and share our perspective on the remission of diabetes. There is a need for more research on remission in Korea as well as in Western countries. Remission appears to be prompted by proactive treatment for hyperglycemia and significant weight loss prior to irreversible β-cell changes. T2DM is not a diagnosis for vulnerable individuals to helplessly accept. We attempt to explain how remission of T2DM can be achieved through a personalized approach. It may be necessary to change the concept of T2DM towards that of an urgent condition that requires rapid intervention rather than a chronic, progressive disease. We must grasp this paradigm shift in our understanding of T2DM for the benefit of our patients as endocrine experts.
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Affiliation(s)
- Jinyoung Kim
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Hyuk-Sang Kwon
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
- Corresponding author: Hyuk-Sang Kwon https://orcid.org/0000-0003-4026-4572 Division of Endocrinology and Metabolism, Department of Internal Medicine, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, 10 63(yuksam)-ro, Yeongdeungpo-gu, Seoul 07345, Korea E-mail:
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Callahan KE. The future of frailty: Opportunity is knocking. J Am Geriatr Soc 2022; 70:78-80. [PMID: 34694001 PMCID: PMC8742769 DOI: 10.1111/jgs.17510] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Accepted: 09/29/2021] [Indexed: 01/03/2023]
Abstract
This editorial comments on the article by Cooper et al. in this issue.
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Affiliation(s)
- Kathryn E. Callahan
- Department of Internal Medicine: Division on Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, NC, 27157
- Center for Healthcare Innovation, Wake Forest School of Medicine, Winston-Salem, NC, 27157
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Callahan KE, Lenoir KM, Usoh CO, Williamson JD, Brown LY, Moses AW, Hinely M, Neuwirth Z, Pajewski NM. Using an Electronic Health Record and Deficit Accumulation to Pragmatically Identify Candidates for Optimal Prescribing in Patients With Type 2 Diabetes. Diabetes Spectr 2022; 35:344-350. [PMID: 36082014 PMCID: PMC9396712 DOI: 10.2337/ds21-0068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
OBJECTIVE Despite guidelines recommending less stringent glycemic goals for older adults with type 2 diabetes, overtreatment is prevalent. Pragmatic approaches for prioritizing patients for optimal prescribing are lacking. We describe glycemic control and medication patterns for older adults with type 2 diabetes in a contemporary cohort, exploring variability by frailty status. RESEARCH DESIGN AND METHODS This was a cross-sectional observational study based on electronic health record (EHR) data, within an accountable care organization (ACO) affiliated with an academic medical center/health system. Participants were ACO-enrolled adults with type 2 diabetes who were ≥65 years of age as of 1 November 2020. Frailty status was determined by an automated EHR-based frailty index (eFI). Diabetes management was described by the most recent A1C in the past 2 years and use of higher-risk medications (insulin and/or sulfonylurea). RESULTS Among 16,973 older adults with type 2 diabetes (mean age 75.2 years, 9,154 women [53.9%], 77.8% White), 9,134 (53.8%) and 6,218 (36.6%) were classified as pre-frail (0.10 < eFI ≤0.21) or frail (eFI >0.21), respectively. The median A1C level was 6.7% (50 mmol/mol) with an interquartile range of 6.2-7.5%, and 74.1 and 38.3% of patients had an A1C <7.5% (58 mmol/mol) and <6.5% (48 mmol/mol), respectively. Frailty status was not associated with level of glycemic control (P = 0.08). A majority of frail patients had an A1C <7.5% (58 mmol/mol) (n = 4,544, 73.1%), and among these patients, 1,755 (38.6%) were taking insulin and/or a sulfonylurea. CONCLUSION Treatment with insulin and/or a sulfonylurea to an A1C levels <7.5% is common in frail older adults. Tools such as the eFI may offer a scalable approach to targeting optimal prescribing interventions.
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Affiliation(s)
- Kathryn E. Callahan
- Section on Gerontology and Geriatric Medicine, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC
- Center for Health Care Innovation, Wake Forest School of Medicine, Winston-Salem, NC
- Corresponding author: Kathryn E. Callahan,
| | - Kristin M. Lenoir
- Center for Health Care Innovation, Wake Forest School of Medicine, Winston-Salem, NC
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC
| | - Chinenye O. Usoh
- Section on Endocrinology and Metabolism, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC
| | - Jeff D. Williamson
- Section on Gerontology and Geriatric Medicine, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC
- Center for Health Care Innovation, Wake Forest School of Medicine, Winston-Salem, NC
| | - LaShanda Y. Brown
- Center for Health Care Innovation, Wake Forest School of Medicine, Winston-Salem, NC
| | - Adam W. Moses
- Center for Health Care Innovation, Wake Forest School of Medicine, Winston-Salem, NC
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC
| | - Molly Hinely
- Department of Pharmacy, Wake Forest Baptist Health, Winston-Salem, NC
| | | | - Nicholas M. Pajewski
- Center for Health Care Innovation, Wake Forest School of Medicine, Winston-Salem, NC
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC
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Balkhi B, AlQahtani N, Alwhaibi M, Alshammari TM, Alhawassi TM, Mahmoud MA, Almetwazi M, Ata S, Basyoni M, Aljadhey H. Prevalence and Factors Associated With Polypharmacy Use Among Adult Patients in Saudi Arabia. J Patient Saf 2021; 17:e1119-e1124. [PMID: 29087978 DOI: 10.1097/pts.0000000000000439] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
BACKGROUND Polypharmacy is very common in clinical practice, especially among adult patients. The use of multiple medications may increase the risk of adverse drug events, medication cost, and medication errors. In addition, polypharmacy exacerbates treatment complexity, which consequently leads to poor patients' adherence to their medications. Despite being a well-recognized problem, few studies have investigated the prevalence and predictors of polypharmacy in Saudi Arabia. OBJECTIVES The aims of the study were to investigate the prevalence of polypharmacy among adult patients in a tertiary teaching hospital and to determine patients' characteristics that are associated with polypharmacy. METHODS This was a retrospective cross-sectional study using data extracted from the electronic health records database for a period of 6 months between January and June 2016 in outpatient setting. Descriptive statistics were used to analyze the study sample. A multivariate logistic regression model was used to examine the association between different variables and polypharmacy. Statistical analysis software (SAS 9.2) was used to analyze the study data. RESULTS A total of 17,237 observations (67.2% females) were included in the final analysis. Of these, nearly 54% (n = 9222) of reported observations were found using up to four prescription drugs and the other 46% (n = 8015) were using five or more prescription drugs. Interestingly, the prevalence of polypharmacy use was doubled among adults with hypertension as compared with those without hypertension (odds ratio [OR] = 2.68, 95% confidence interval [CI] = 2.51-2.87). In addition, polypharmacy use was two times more prevalent among adults with diabetes as compared with those without diabetes (OR = 2.31, 95% CI = 1.99-2.28) and five times more prevalent in patient with dementia (OR = 5.57, 95% CI = 1.26-24.7). Moreover, polypharmacy in adult patients was significantly influenced by sex (OR = 1.69, 95% CI = 1.59-1.80) and nationality (OR = 2.15, 95% CI = 2.00-2.31). CONCLUSIONS Polypharmacy is common among adult patients especially those who are older than 60 years. Polypharmacy may affect the overall process of drug therapy. It can be a risk factor to develop undesirable adverse drug events, especially in those with chronic health conditions. A special care should be taken to manage polypharmacy among adults in Saudi Arabia.
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Affiliation(s)
| | | | | | | | | | - Mansour A Mahmoud
- Medication Safety Research Chair, College of Pharmacy, King Saud University
| | | | - Sondus Ata
- Investigational Drugs and Research Unit, King Khalid University Hospital, Riyadh, Saudi Arabia
| | - Mada Basyoni
- Investigational Drugs and Research Unit, King Khalid University Hospital, Riyadh, Saudi Arabia
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Piro S, Purrello F. Acute diabetes complications. JOURNAL OF GERONTOLOGY AND GERIATRICS 2021. [DOI: 10.36150/2499-6564-n457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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Asbaghi O, Moodi V, Neisi A, Shirinbakhshmasoleh M, Abedi S, Oskouie FH, Eslampour E, Ghaedi E, Miraghajani M. The effect of almond intake on glycemic control: A systematic review and dose-response meta-analysis of randomized controlled trials. Phytother Res 2021; 36:395-414. [PMID: 34841609 DOI: 10.1002/ptr.7328] [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: 03/01/2020] [Revised: 10/12/2021] [Accepted: 10/23/2021] [Indexed: 11/08/2022]
Abstract
Number trials have evaluated the effect of almond intake on glycemic control in adults; however, the results remain equivocal. Therefore, the present meta-analysis aims to examine the effectiveness of almond intake on glycemic parameters. Online databases including PubMed, Scopus, ISI web of science, Embase, and Cochrane Library were searched up to August 2021 for trials that examined the effect of almond intake on glycemic control parameters including fasting blood sugar (FBS), insulin, HOMA-IR, and HbA1C. Treatment effects were expressed as mean difference (MD) and the standard deviation (SD) of outcomes. To estimate the overall effect of almond intake, we used the random-effects model. In total, 24 studies with 31 arms were included in our analysis. The meta-analysis revealed that almond intake did not significantly change the concentrations of FBS, HbA1c, insulin levels, and HOMA-IR. In conclusion, there is currently no convincing evidence that almonds have a clear beneficial effect on glycemic control. Future studies are needed before any confirmed conclusion could be drowned.
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Affiliation(s)
- Omid Asbaghi
- Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Vihan Moodi
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Azadeh Neisi
- Department of Nutrition, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | | | - Sajjad Abedi
- Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
| | - Fatemeh Hosseini Oskouie
- Department of Clinical Nutrition and Dietetics, Faculty of Nutrition and Food Technology, National Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Elham Eslampour
- Student Research Committee, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Ehsan Ghaedi
- Department of Cellular and Molecular Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran
| | - Maryam Miraghajani
- Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.,The Early Life Research Unit, Academic Division of Child Health, Obstetrics and Gynaecology, and Nottingham Digestive Disease Centre and Biomedical Research Centre, The School of Medicine, University of Nottingham, Nottingham, UK
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Tuladhar LR, Shrestha SL, Regmi D, Bimali S, Bhusal S, Khadka P. Drug-drug Interactions between Hypoglycemic and Non-hypoglycemic Medication in Diabetic Patients with Comorbidities in a Tertiary Care Center: A Descriptive Cross-sectional Study. JNMA J Nepal Med Assoc 2021; 59:1125-1130. [PMID: 35199748 PMCID: PMC9124339 DOI: 10.31729/jnma.7080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 11/17/2021] [Indexed: 11/01/2022] Open
Abstract
INTRODUCTION Drug-drug interaction is one of the causes of adverse drug reactions. Generally, drug-drug interaction is common in multidrug therapy. Diabetic patients, particularly due to associated comorbidities tend to have various drug-drug interactions due to the effect of multiple drugs. The objective of this study was to find out the prevalence of drug-drug interactions in diabetic patients. METHODS It was a descriptive cross-sectional study that was conducted among previously diagnosed diabetic patients visiting the outpatient department of medicine at a tertiary care hospital between March 2021 and August 2021. Ethical approval was taken from the institutional review committee (Ref no: 030-076/077). Data was collected from diabetic patients presenting to the outpatient department of medicine using a preformed self-constructed questionnaire. Convenient sampling was done. Statistical Package for Social Sciences version 21 and Microsoft Excel were used for data analysis. Point estimate at 95% confidence interval was calculated along with frequency and proportion for binary data. RESULTS The prevalence of drug-drug interaction between hypoglycemic and non-hypoglycemic medication was 56 (44.1%) (35.5-52.7 at 95% Confidence Interval) of the patients out of which at least one drug-drug interaction was seen in 48 (37.8%) of the patients. CONCLUSIONS Our study showed the prevalence of drug-drug interactions in diabetic patients to be higher than other studies done in similar settings. Based on the severity, we observed two types of drug-drug interactions; close monitoring drug-drug interactions and minor drug-drug interactions.
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Affiliation(s)
- Lujaw Ratna Tuladhar
- Department of Pharmacology, Nepal Medical College and Teaching Hospital, Kathmandu, Nepal
| | - Shirish Lall Shrestha
- Department of Internal Medicine, Nepal Medical College and Teaching Hospital, Kathmandu, Nepal
| | - Deepak Regmi
- Nepal Medical College and Teaching Hospital, Kathmandu, Nepal
| | - Sneha Bimali
- Nepal Medical College and Teaching Hospital, Kathmandu, Nepal
| | - Srijana Bhusal
- Nepal Medical College and Teaching Hospital, Kathmandu, Nepal
| | - Pingala Khadka
- Nepal Medical College and Teaching Hospital, Kathmandu, Nepal
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Al-Musawe L, Torre C, Guerreiro JP, Rodrigues AT, Raposo JF, Mota-Filipe H, Martins AP. Overtreatment and undertreatment in a sample of elderly people with diabetes. Int J Clin Pract 2021; 75:e14847. [PMID: 34516684 DOI: 10.1111/ijcp.14847] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Accepted: 09/10/2021] [Indexed: 12/29/2022] Open
Abstract
AIMS In older adults with type 2 diabetes (T2D), overtreatment remains prevalent and undertreatment ignored. The main objective is to estimate the prevalence and examine factors associated with potential overtreatment and undertreatment. METHOD Observational study conducted within an administrative database of older adults with T2D who registered in 2018 at the Portuguese Diabetes Association. Participants were categorized either as potentially overtreated (HbA1c ≤ 7.5%), appropriately on target (HbA1c ≥7.5 to ≤9%), or potentially undertreated (HbA1c > 9%). RESULTS The study included 444 participants: potential overtreatment and undertreatment were found in 60.5% and 12.6% of the study population. Taking the patients on target as a comparator, the group of potentially overtreated showed to be more men (61.3% vs 52.2%), less-obese (34.1% vs 39.2), higher cardiovascular diseases (13.7% vs 11%), peripheral vascular diseases (16.7% vs 12.8%), diabetic foot (10% vs 4.5%), and severe kidney disease (5.2% vs 4.5%). Conversely, the potentially undertreated participants were more women (64.2% vs 47.7%), obese (49% vs 39.2%), had more dyslipidemia (69% vs 63.1%), peripheral vascular disease (14.2% vs 12.8%), diabetic foot (8.9% vs 4.5%), and infections (14.2% vs 11.9%). The odds of potential overtreatment were mostly decreased by 59% of women, 73.5% in those with retinopathy, and 86.3% in insulin, 65.4% sulfonylureas, and 66.8% in SGLT2 inhibitors users. Contrariwise, an increase in the odds of potential undertreatment was more than 4.8 times higher in insulin, and more than 3.1 times higher in sulfonylureas users. CONCLUSION Potential overtreatment and undertreatment in older adults with T2D in routine clinical practice should guide the clinicians to balance the use of newer oral antidiabetic agents considering its safety profile regarding hypoglycemia.
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Affiliation(s)
| | - Carla Torre
- Faculty of Pharmacy, University of Lisbon, Lisbon, Portugal
| | | | | | - Joao Filipe Raposo
- Nova Medical School, New University of Lisbon, Lisbon, Portugal
- Portuguese Diabetes Association (APDP), Lisbon, Portugal
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Abdelhafiz AH, Peters S, Sinclair AJ. Low glycaemic state increases risk of frailty and functional decline in older people with type 2 diabetes mellitus - Evidence from a systematic review. Diabetes Res Clin Pract 2021; 181:109085. [PMID: 34634389 DOI: 10.1016/j.diabres.2021.109085] [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: 07/11/2021] [Revised: 09/18/2021] [Accepted: 09/29/2021] [Indexed: 10/20/2022]
Abstract
AIMS To explore risk of frailty and functional decline associated with low glycaemia in older people with type 2 diabetes. METHODS Systematic review. RESULTS 11 studies included. Six studies investigated risk of frailty or physical decline with hypoglycaemia. Hypoglycaemia increased risk of incident frailty (HR 1.60, 95% CI 1.14 to 2.42) in one study and risk of fractures in four studies (2.24, 1.56 to 3.21, 1.24, 1.13 to 1.37, 1.94, 1.67 to 2.24 and 1.71, 1.35 to 2.16 respectively). In sixth study, hypoglycaemia associated with dependency (P < 0.001). Five studies explored association of low blood glucose/HbA1c with frailty. One study showed that mean blood glucose decreased with increasing frailty (p = 0.003). Two studies reported that HbA1c inversely correlated with clinical frailty scale (r = -0.31, p < 0.01) and HbA1c < 6.9% increased risk of frailty (HR, 1.41 95% CI 1.12 to 1.78) respectively. Last two studies showed that HbA1c < 6.5% associated with risk of any fracture (HR 1.08, 95% CI 1.06 to 1.11) and HbA1c < 6.0% associated with increased risk of care need (3.45, 1.02 to 11.6) respectively. CONCLUSIONS Low glycaemia increases risk of frailty and functional decline in older people with type 2 diabetes. Management should minimise incidence of low glycaemia in these patients.
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Affiliation(s)
- A H Abdelhafiz
- Department of Geriatric Medicine, Rotherham General Hospital, Moorgate Road, Rotherham S60 2UD, United Kingdom
| | - S Peters
- Department of Geriatric Medicine, Rotherham General Hospital, Moorgate Road, Rotherham S60 2UD, United Kingdom
| | - A J Sinclair
- King's College, London, United Kingdom; Foundation for Diabetes Research in Older People (fDROP), Droitwich Spa WR9 0QH, UK.
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Cabré Font C, Colungo Francia C, Vinagre Torres I, Jansà I Morató M, Conget Donlo I. A therapeutic education program with a diabetes specialist nurse for type 2 diabetes patients using insulin in a primary care setting. A diabetes education program with a diabetes specialist nurse in a primary care setting. ENDOCRINOL DIAB NUTR 2021; 68:628-635. [PMID: 34906343 DOI: 10.1016/j.endien.2021.11.022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Accepted: 10/30/2020] [Indexed: 06/14/2023]
Abstract
INTRODUCTION Therapeutic education is an essential part in the management of type 2 diabetes mellitus (T2D). Implementing a therapeutic education program with the participation of a diabetes specialist nurse (DSN) addressed to patients with T2D using more than 2 insulin injections and sub-optimal metabolic control in primary care (PC) could improve health care and clinical outcomes. Our purpose was to evaluate the clinical, educational and patient satisfaction outcomes of this program. MATERIAL AND METHODS A prospective, longitudinal study was performed with an evaluation before and after the intervention. The program had a duration of 6 months and included individual on-site, phone and group visits. RESULTS 184 subjects were included and 161 were finally evaluated. 89.4% were included due to sub-optimal metabolic control and 10.6% because of repeated hypoglycemia. In the first group, the mean reduction in HbA1c was -1.34%±1.45% without any increase in hypoglycemia episodes. In the second group, a significant reduction in hypoglycemia episodes/week was observed (2.52±1.66 vs. 0.53±1.06; p<0.05) without any increase in HbA1c. Learning skills, lifestyle, adherence to care, and the perception of quality of life had significantly improved at 6 months (p<0.05). The overall program was positively evaluated by patients, the role of DSN being considered essential by 98% of the responders. CONCLUSION A structured therapeutic education program, including a DSN, addressed to insulin treated T2D patients attending primary care facilities and with sub-optimal metabolic control is associated with beneficial effects in terms of clinical, educational and patient satisfaction endpoints.
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Affiliation(s)
- Carla Cabré Font
- Unidad de Diabetes, Endocrinología y Nutrición, Hospital Clínic i Universitari, Barcelona, Spain
| | - Cristina Colungo Francia
- Centro de Atención Primaria Comte Borrell, Consorci d'Atenció Primària de Salut de Barcelona Esquerre (CAPSBE), Barcelona, Spain
| | - Irene Vinagre Torres
- Unidad de Diabetes, Endocrinología y Nutrición, Hospital Clínic i Universitari, Barcelona, Spain.
| | - Marga Jansà I Morató
- Unidad de Diabetes, Endocrinología y Nutrición, Hospital Clínic i Universitari, Barcelona, Spain
| | - Ignacio Conget Donlo
- Unidad de Diabetes, Endocrinología y Nutrición, Hospital Clínic i Universitari, Barcelona, Spain; IDIBAPS, Institut d'investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain; CIBERDEM, Centro de Investigación Biomédica en Red de Diabetes y Enfermedades metabólicas, Barcelona, Spain
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Bilgin S, Aktas G, Kurtkulagi O, Atak BM, Kahveci G, Demirkol ME, Duman TT. Characteristics of the type 2 diabetic patients with hypoglycemia in a tertiary referral hospital. INTERNATIONAL JOURNAL OF ENDOCRINOLOGY (UKRAINE) 2021; 17:472-476. [DOI: 10.22141/2224-0721.17.6.2021.243209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/16/2023]
Abstract
Background. Hypoglycemia is an important complication of the treatment of type 2 diabetes mellitus, which constitutes a barrier in stringent diabetic control. Beside it constitutes nearly 10 % of emergency department admissions that caused by adverse drug events, it may also increase morbidities and mortality by inducing, cardiac arrhythmias, neurological impairment and ischemic events. Hypoglycemia is the most common side effect of insulin treatment, however, oral antidiabetic agents may also induce hypoglycemic complications. In present retrospective study, we purposed to observe general characteristics and laboratory data of the type 2 diabetic patients whom presented with mild or moderate/severe hypoglycemia. Materials and methods. Patients with type 2 diabetes mellitus whom presented to our institution with hypoglycemia between January 2019 and January 2020 were retrospectively analyzed. General characteristics and laboratory data of the subjects recorded. Patients grouped into two groups, group I consisted of subjects with mild hypoglycemia and group II consisted of patients with moderate/severe hypoglycemia. Data of the subjects in groups I and II were compared. Results. There were 15 subjects in group I and 23 in group II. HbA1c and other laboratory markers were not significantly different in study groups. Similarly diabetes duration and anti-diabetic treatment were not significantly different in study groups. The rate of geriatric patients was significantly higher in group II compared to group I (p = 0.04). Conclusions. Subjects with moderate/severe hypoglycemia tend to be more frequently in geriatric age and HbA1c not correlates with the degree of the hypoglycemia. Since neither duration of diabetes, nor anti-diabetic treatment were associated with the severity of the hypoglycemia, each case should be evaluated individually to prevent further episodes which could increase morbidity and mortality in diabetic population.
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Fortes C, Mastroeni S, Tubili C, Gianni S, Pandolfo MM, Fano V. Mediterranean diet, walking outdoors and polypharmacy in older patients with type II diabetes. Eur J Public Health 2021; 31:829-835. [PMID: 34499712 DOI: 10.1093/eurpub/ckab113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Polypharmacy and its adverse health effects is an emerging public health issue, with increasing prevalence among patients with multiple chronic conditions, such as older adults with diabetes. A healthy lifestyle has been shown to improve both diabetes and polypharmacy incidence. We conducted a cross-sectional study to investigate the association of a healthy lifestyle with polypharmacy and comorbidities in older people with diabetes. METHODS All out-patients from January 2013 to June 2015 with type II diabetes aged 65 years or more from a Lazio Region reference centre for diabetes were included in the study. Socio-demographic, clinical and lifestyle data were collected from medical records and through face-to-face standardized questionnaires. The comorbidity-polypharmacy score (CPS) was used to characterize the overall patients' frailty, by assessing concurrently the presence of comorbidities and polypharmacy. The cumulative logit model was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS Adjusted ORs for age, sex, body mass index, physical activity and cognitive status, showed that CPS score was inversely related to weekly consumption of cruciferous vegetables (OR: 0.56, 95% CI: 0.35-0.90; P-trend = 0.015), leafy green vegetables (OR: 0.54, 95% CI: 0.33-0.87; P-trend = 0.013) and daily intake of fruits (OR: 0.63, 95% CI: 0.41-0.97; P-trend = 0.036). Walking outdoors was found inversely related to CPS score (age- and sex-adjusted OR: 0.60, 95% CI: 0.42-0.86). CONCLUSION Our findings suggest that eating some dietary factors present in the Mediterranean diet and walking outdoors regularly is associated with a lower intensity of medicines need to treat comorbidities among older people with diabetes.
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Affiliation(s)
- Cristina Fortes
- Istituto Dermopatico dell'Immacolata, IDI-IRCCS, Rome, Italy
| | | | - Claudio Tubili
- Diabetes Unit, S. Camillo-Forlanini Hospital, Rome, Italy
| | - Simona Gianni
- Diabetes Unit, S. Camillo-Forlanini Hospital, Rome, Italy
| | | | - Valeria Fano
- Local Health Authority Roma 3 (Asl RM3), Rome, Italy
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Soldevila-Domenech N, Cuenca-Royo A, Babio N, Forcano L, Nishi S, Vintró-Alcaraz C, Gómez-Martínez C, Jiménez-Murcia S, Fernández-Carrión R, Gomis-González M, Alvarez-Sala A, Carlos S, Pintó X, Corella D, Díez-Espino J, Castañer O, Fernández-Aranda F, Salas-Salvadó J, de la Torre R. Metformin Use and Cognitive Function in Older Adults With Type 2 Diabetes Following a Mediterranean Diet Intervention. Front Nutr 2021; 8:742586. [PMID: 34676236 PMCID: PMC8523839 DOI: 10.3389/fnut.2021.742586] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 09/07/2021] [Indexed: 12/28/2022] Open
Abstract
Background and Purpose: Both adherence to the Mediterranean diet (MedDiet) and the use of metformin could benefit the cognitive performance of individuals with type 2 diabetes, but evidence is still controversial. We examined the association between metformin use and cognition in older adults with type 2 diabetes following a MedDiet intervention. Methods: Prospective cohort study framed in the PREDIMED-Plus-Cognition sub-study. The PREDIMED-Plus clinical trial aims to compare the cardiovascular effect of two MedDiet interventions, with and without energy restriction, in individuals with overweight/obesity and metabolic syndrome. The present sub-study included 487 cognitively normal subjects (50.5% women, mean ± SD age of 65.2 ± 4.7 years), 30.4% of them (N = 148) with type 2 diabetes. A comprehensive battery of neurocognitive tests was administered at baseline and after 1 and 3 years. Individuals with type 2 diabetes that exhibited a good glycemic control trajectory, either using or not using metformin, were compared to one another and to individuals without diabetes using mixed-effects models with inverse probability of treatment weights. Results: Most subjects with type 2 diabetes (83.1%) presented a good and stable glycemic control trajectory. Before engaging in the MedDiet intervention, subjects using metformin scored higher in executive functions (Cohen's d = 0.51), memory (Cohen's d = 0.38) and global cognition (Cohen's d = 0.48) than those not using metformin. However, these differences were not sustained during the 3 years of follow-up, as individuals not using metformin experienced greater improvements in memory (β = 0.38 vs. β = 0.10, P = 0.036), executive functions (β = 0.36 vs. β = 0.02, P = 0.005) and global cognition (β = 0.29 vs. β = -0.02, P = 0.001) that combined with a higher MedDiet adherence (12.6 vs. 11.5 points, P = 0.031). Finally, subjects without diabetes presented greater improvements in memory than subjects with diabetes irrespective of their exposure to metformin (β = 0.55 vs. β = 0.10, P < 0.001). However, subjects with diabetes not using metformin, compared to subjects without diabetes, presented greater improvements in executive functions (β = 0.33 vs. β = 0.08, P = 0.032) and displayed a higher MedDiet adherence (12.6 points vs. 11.6 points, P = 0.046). Conclusions: Although both metformin and MedDiet interventions are good candidates for future cognitive decline preventive studies, a higher adherence to the MedDiet could even outweigh the potential neuroprotective effects of metformin in subjects with diabetes.
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Affiliation(s)
- Natalia Soldevila-Domenech
- Integrative Pharmacology and Systems Neurosciences Research Group, Neurosciences Research Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain
| | - Aida Cuenca-Royo
- Integrative Pharmacology and Systems Neurosciences Research Group, Neurosciences Research Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Nancy Babio
- Department of Biochemistry and Biotechnology, Hospital Universitari de Sant Joan de Reus, Institut d'Investigacions Sanitàries Pere i Virgili, Human Nutrition Unit, Universitat Rovira i Virgili, Reus, Spain
- Centro de Investigación Biomédica en Red (CIBER) de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Laura Forcano
- Integrative Pharmacology and Systems Neurosciences Research Group, Neurosciences Research Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Centro de Investigación Biomédica en Red (CIBER) de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Stephanie Nishi
- Department of Biochemistry and Biotechnology, Hospital Universitari de Sant Joan de Reus, Institut d'Investigacions Sanitàries Pere i Virgili, Human Nutrition Unit, Universitat Rovira i Virgili, Reus, Spain
- Centro de Investigación Biomédica en Red (CIBER) de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Cristina Vintró-Alcaraz
- Centro de Investigación Biomédica en Red (CIBER) de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Department of Psychiatry, University Hospital of Bellvitge, Barcelona, Spain
- Psychiatry and Mental Health Group, Neuroscience Program, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain
| | - Carlos Gómez-Martínez
- Department of Biochemistry and Biotechnology, Hospital Universitari de Sant Joan de Reus, Institut d'Investigacions Sanitàries Pere i Virgili, Human Nutrition Unit, Universitat Rovira i Virgili, Reus, Spain
- Centro de Investigación Biomédica en Red (CIBER) de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Susana Jiménez-Murcia
- Centro de Investigación Biomédica en Red (CIBER) de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Department of Psychiatry, University Hospital of Bellvitge, Barcelona, Spain
- Psychiatry and Mental Health Group, Neuroscience Program, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain
- Department of Clinical Sciences, School of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
| | - Rebeca Fernández-Carrión
- Centro de Investigación Biomédica en Red (CIBER) de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine, School of Medicine, University of Valencia, Valencia, Spain
| | - Maria Gomis-González
- Integrative Pharmacology and Systems Neurosciences Research Group, Neurosciences Research Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Andrea Alvarez-Sala
- Centro de Investigación Biomédica en Red (CIBER) de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine, School of Medicine, University of Valencia, Valencia, Spain
| | - Silvia Carlos
- Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain
- Navarra Health Research Institute (IDISNA), Pamplona, Spain
| | - Xavier Pintó
- Centro de Investigación Biomédica en Red (CIBER) de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Lipid Unit, Department of Internal Medicine, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
- Faculty of Medicine, Universitat de Barcelona, Barcelona, Spain
| | - Dolores Corella
- Centro de Investigación Biomédica en Red (CIBER) de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine, School of Medicine, University of Valencia, Valencia, Spain
| | - Javier Díez-Espino
- Centro de Investigación Biomédica en Red (CIBER) de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain
- Navarra Health Research Institute (IDISNA), Pamplona, Spain
| | - Olga Castañer
- Centro de Investigación Biomédica en Red (CIBER) de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Cardiovascular Risk and Nutrition Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Endocrinology Service, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Fernando Fernández-Aranda
- Centro de Investigación Biomédica en Red (CIBER) de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Department of Psychiatry, University Hospital of Bellvitge, Barcelona, Spain
- Psychiatry and Mental Health Group, Neuroscience Program, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain
- Department of Clinical Sciences, School of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
| | - Jordi Salas-Salvadó
- Department of Biochemistry and Biotechnology, Hospital Universitari de Sant Joan de Reus, Institut d'Investigacions Sanitàries Pere i Virgili, Human Nutrition Unit, Universitat Rovira i Virgili, Reus, Spain
- Centro de Investigación Biomédica en Red (CIBER) de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Rafael de la Torre
- Integrative Pharmacology and Systems Neurosciences Research Group, Neurosciences Research Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain
- Centro de Investigación Biomédica en Red (CIBER) de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
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Abstract
Diabetes is one of the most common disease states in older adults and there are significant risks to the use of antidiabetic medications. The older adult population varies greatly in functional ability, independence, and cognition. These factors, along with increased risk of hypoglycemia, falls, and other comorbidities, add to the complexity of creating medication regimens to treat diabetes in older adults. In the current review, a person-centered approach to diabetes care in older adults is described to aid clinician decision making. By keeping the patient and their individual factors in the center of the decision, risks of over- or under-treating diabetes can be minimized. The review will discuss person-centered goal setting, practical approaches to diabetes medication management, and specific considerations for choosing medication classes based on patient characteristics. [Journal of Gerontological Nursing, 47(10), 7-13.].
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Anderson TS, Lee AK, Jing B, Lee S, Herzig SJ, Boscardin WJ, Fung K, Rizzo A, Steinman MA. Intensification of Diabetes Medications at Hospital Discharge and Clinical Outcomes in Older Adults in the Veterans Administration Health System. JAMA Netw Open 2021; 4:e2128998. [PMID: 34673963 PMCID: PMC8531994 DOI: 10.1001/jamanetworkopen.2021.28998] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/05/2022] Open
Abstract
IMPORTANCE Transient elevations of blood glucose levels are common in hospitalized older adults with diabetes and may lead clinicians to discharge patients with more intensive diabetes medications than they were using before hospitalization. OBJECTIVE To investigate outcomes associated with intensification of outpatient diabetes medications at discharge. DESIGN, SETTING, AND PARTICIPANTS This retrospective cohort study assessed patients 65 years and older with diabetes not taking insulin who were hospitalized in the Veterans Health Administration Health System between January 1, 2011, and September 28, 2016, for common medical conditions. Data analysis was performed from January 1, 2020, to March 31, 2021. EXPOSURE Discharge with intensified diabetes medications, defined as filling a prescription at hospital discharge for a new or higher-dose medication than was being used before hospitalization. Propensity scores were used to construct a matched cohort of patients who did and did not receive diabetes medication intensifications. MAIN OUTCOMES AND MEASURES Coprimary outcomes of severe hypoglycemia and severe hyperglycemia were assessed at 30 and 365 days using competing risk regressions. Secondary outcomes included all-cause readmissions, mortality, change in hemoglobin A1c (HbA1c) level, and persistent use of intensified medications at 1 year after discharge. RESULTS The propensity-matched cohort included 5296 older adults with diabetes (mean [SD] age, 73.7 [7.7] years; 5212 [98.4%] male; and 867 [16.4%] Black, 47 [0.9%] Hispanic, 4138 [78.1%] White), equally split between those who did and did not receive diabetes medication intensifications at hospital discharge. Within 30 days, patients who received medication intensifications had a higher risk of severe hypoglycemia (hazard ratio [HR], 2.17; 95% CI, 1.10-4.28), no difference in risk of severe hyperglycemia (HR, 1.00; 95% CI, 0.33-3.08), and a lower risk of death (HR, 0.55; 95% CI, 0.33-0.92). At 1 year, no differences were found in the risk of severe hypoglycemia events, severe hyperglycemia events, or death and no difference in change in HbA1c level was found among those who did vs did not receive intensifications (mean postdischarge HbA1c, 7.72% vs 7.70%; difference-in-differences, 0.02%; 95% CI, -0.12% to 0.16%). At 1 year, 48.0% (591 of 1231) of new oral diabetes medications and 38.5% (548 of 1423) of new insulin prescriptions filled at discharge were no longer being filled. CONCLUSIONS AND RELEVANCE In this national cohort study, among older adults hospitalized for common medical conditions, discharge with intensified diabetes medications was associated with an increased short-term risk of severe hypoglycemia events but was not associated with reduced severe hyperglycemia events or improve HbA1c control. These findings indicate that short-term hospitalization may not be an effective time to intervene in long-term diabetes management.
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Affiliation(s)
- Timothy S. Anderson
- Division of General Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
- San Francisco Veterans Affairs Medical Center, San Francisco, California
| | - Alexandra K. Lee
- San Francisco Veterans Affairs Medical Center, San Francisco, California
- Division of Geriatrics, University of California, San Francisco
| | - Bocheng Jing
- San Francisco Veterans Affairs Medical Center, San Francisco, California
- Division of Geriatrics, University of California, San Francisco
| | - Sei Lee
- San Francisco Veterans Affairs Medical Center, San Francisco, California
- Division of Geriatrics, University of California, San Francisco
| | - Shoshana J. Herzig
- Division of General Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - W. John Boscardin
- San Francisco Veterans Affairs Medical Center, San Francisco, California
- Division of Geriatrics, University of California, San Francisco
| | - Kathy Fung
- San Francisco Veterans Affairs Medical Center, San Francisco, California
- Division of Geriatrics, University of California, San Francisco
| | - Anael Rizzo
- San Francisco Veterans Affairs Medical Center, San Francisco, California
- Division of Geriatrics, University of California, San Francisco
| | - Michael A. Steinman
- San Francisco Veterans Affairs Medical Center, San Francisco, California
- Division of Geriatrics, University of California, San Francisco
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Tanabe H, Masuzaki H, Shimabukuro M. Novel strategies for glycaemic control and preventing diabetic complications applying the clustering-based classification of adult-onset diabetes mellitus: A perspective. Diabetes Res Clin Pract 2021; 180:109067. [PMID: 34563587 DOI: 10.1016/j.diabres.2021.109067] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 09/13/2021] [Accepted: 09/20/2021] [Indexed: 12/17/2022]
Abstract
Diabetes mellitus results from an interplay between insulin resistance and β-cell dysfunction. Since their relative contributions to its pathogenesis are difficult to quantify, therapeutic strategies for glycaemic control are determined primarily based on two limited metrics: plasma glucose and haemoglobin A1c. Recent attempts have been made to subclassify diabetes mellitus to better predict its associated pathology and plan appropriate therapeutic strategies. These classifications are based on data-driven cluster analysis using autoimmunity, age, obesity (metabolically unhealthy and healthy phenotypes), insulin secretory capacity and resistance, and ethnicity. This review addresses potential therapeutic strategies for the cluster-based classifications of adult-onset diabetes mellitus to achieve better glycaemic control and prevent or at least delay the concomitant complications.
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Affiliation(s)
- Hayato Tanabe
- Department of Diabetes, Endocrinology and Metabolism, School of Medicine, Fukushima Medical University, Fukushima 960-1295, Japan
| | - Hiroaki Masuzaki
- Division of Endocrinology, Diabetes and Metabolism, Hematology, Rheumatology (Second Department of Internal Medicine), University of the Ryukyus, Okinawa 903-0215, Japan
| | - Michio Shimabukuro
- Department of Diabetes, Endocrinology and Metabolism, School of Medicine, Fukushima Medical University, Fukushima 960-1295, Japan.
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İnci H. Evaluation of multiple drug use in patients with type 2 diabetes mellitus. Diabetol Int 2021; 12:399-404. [PMID: 34567922 DOI: 10.1007/s13340-021-00495-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Accepted: 01/28/2021] [Indexed: 10/22/2022]
Abstract
Objective Multiple drug use (Polypharmacy) is common in Diabetes Mellitus (DM) patients. The purpose of this study was to evaluate the presence of polypharmacy and comorbid conditions in patients with DM. Method The sociodemographic data, comorbidity diseases, and prescription records of 607 patients diagnosed with type 2 DM were retrospectively analyzed. Polypharmacy was defined as the use of five or more different drugs. Results The mean number of drugs used by the DM patients was 6.7 ± 2.5. It was observed that 77.9% of the DM patients had polypharmacy. The mean number of drugs used by the patients in the polypharmacy group was 7.7 ± 1.7. The most common comorbidities in DM patients were diseases of the musculoskeletal system. The use of drugs for musculoskeletal diseases and the number of drugs were statistically higher in female patients than in male patients. In the DM patients, polypharmacy was higher in the females, those older age, those having a longer history of DM disease, and those having a comorbid disease. Conclusion The total number of drugs used by the DM patients showed the presence of polypharmacy. Advanced age, long disease duration, female gender, and presence of comorbidities were predictive factors for polypharmacy in diabetic patients. Before starting additional medication for DM patients, it is necessary to pay attention to the interaction of the drugs to be used and to plan prescriptions considering the medications used by the patient continuously.
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Affiliation(s)
- Habibe İnci
- Department of Family Medicine, Faculty of Medicine, Karabuk University, Karabuk, Turkey
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