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Olive J, Wong THT, Chik F, Tan SY, George ES. Knowledge, Attitudes, and Behaviors around Dietary Fats among People with Type 2 Diabetes: A Systematic Review. Nutrients 2024; 16:2185. [PMID: 39064629 PMCID: PMC11279953 DOI: 10.3390/nu16142185] [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: 04/12/2024] [Revised: 07/01/2024] [Accepted: 07/01/2024] [Indexed: 07/28/2024] Open
Abstract
This systematic review assesses the knowledge, attitudes, and behaviors (KAB) surrounding dietary fat intake among people with type 2 diabetes mellitus (T2DM) and healthcare professionals. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, four databases were searched to identify studies published between 1995 and 2023 reporting people with T2DM or healthcare professionals that measured KAB towards dietary fat. This work was registered at PROSPERO (CRD42020140247). Twenty-four studies were included. Studies assessed knowledge of people with T2DM and reported poor nutrition knowledge regarding the health effect of fat consumption. Two opposing attitudes towards dietary fat was reported: (1) dietary fat should be limited, (2) promoted dietary fat intake through a low-carbohydrate diet. Participants reported behaviors of limiting fat intake, including trimming visible fat or choosing lower-fat alternatives. Total fat intake ranged between 10 and 66% of participants' total energy intake, while saturated fat intake ranged between 10 and 17%. People with T2DM reported poor knowledge of dietary fats in particular, and they were frequently unable to identify high-fat food. Attitudes towards dietary fat were heterogenous, and regarding behaviors, saturated fat intake was higher than recommended. Future studies should assess the KAB of people with T2DM based on dietary fat subtypes.
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Affiliation(s)
- Justin Olive
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC 3220, Australia; (J.O.); (F.C.); (S.-Y.T.)
| | - Tommy Hon Ting Wong
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong;
| | - Faye Chik
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC 3220, Australia; (J.O.); (F.C.); (S.-Y.T.)
| | - Sze-Yen Tan
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC 3220, Australia; (J.O.); (F.C.); (S.-Y.T.)
| | - Elena S. George
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC 3220, Australia; (J.O.); (F.C.); (S.-Y.T.)
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Al‐Qahtani AA. Improving outcomes of type 2 diabetes mellitus patients in primary care with Chronic Care Model: A narrative review. J Gen Fam Med 2024; 25:171-178. [PMID: 38966652 PMCID: PMC11221057 DOI: 10.1002/jgf2.659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 10/30/2023] [Accepted: 11/07/2023] [Indexed: 07/06/2024] Open
Abstract
Designed and implemented over two decades ago, the Chronic Care Model is a well-established chronic disease management framework that has steered several healthcare systems in successfully improving the clinical outcomes of patients with type 2 diabetes mellitus. Research evidence cements the role of the Chronic Care Model (with its six key elements of organization of healthcare delivery system, self-management support, decision support, delivery system design, clinical information systems, and community resources and policies) as an integrated framework to revamp the type 2 diabetes mellitus-related clinical practice and care that betters the patient care and clinical outcomes. The current review is an evidence-lit summary of importance of use of Chronic Care Model in primary care and their impact on clinical outcomes for patients afflicted with one of the most debilitating metabolic diseases, type 2 diabetes mellitus.
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Affiliation(s)
- Arwa Ahmed Al‐Qahtani
- Department of Family Medicine, College of MedicineAl‐Imam Mohammed Ibn Saud Islamic UniversityRiyadhSaudi Arabia
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Yapi SM, Boudrias M, Tremblay A, Belanger G, Sourial N, Boivin A, Sasseville M, Côté A, Gartner JB, Taleb N, Lavoie ME, Trépanier E, Vachon B, Labelle M, Layani G. Intersectoral health interventions to improve the well-being of people living with type 2 diabetes: a scoping review protocol. BMJ Open 2024; 14:e080659. [PMID: 38772897 PMCID: PMC11110582 DOI: 10.1136/bmjopen-2023-080659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 05/07/2024] [Indexed: 05/23/2024] Open
Abstract
INTRODUCTION Intersectoral collaboration is a collaborative approach between the health sectors and other sectors to address the interdependent nature of the social determinants of health associated with chronic diseases such as diabetes. This scoping review aims to identify intersectoral health interventions implemented in primary care and community settings to improve the well-being and health of people living with type 2 diabetes. METHODS AND ANALYSIS This protocol is developed by the Arksey and O'Malley (2005) framework for scoping reviews and the Levac et al methodological enhancement. MEDLINE, Embase, CINAHL, grey literature and the reference list of key studies will be searched to identify any study, published between 2000 and 2023, related to the concepts of intersectorality, diabetes and primary/community care. Two reviewers will independently screen all titles/abstracts, full-text studies and grey literature for inclusion and extract data. Eligible interventions will be classified by sector of action proposed by the Social Determinants of Health Map and the conceptual framework for people-centred and integrated health services and further sorted according to the actors involved. This work started in September 2023 and will take approximately 10 months to be completed. ETHICS AND DISSEMINATION This review does not require ethical approval. The results will be disseminated through a peer-reviewed publication and presentations to stakeholders.
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Affiliation(s)
- Sopie Marielle Yapi
- Centre de Recherche du Centre Hospitalier de l'Universite de Montreal, Montreal, Quebec, Canada
| | - Marguerite Boudrias
- Centre de Recherche du Centre Hospitalier de l'Universite de Montreal, Montreal, Quebec, Canada
| | - Alexandre Tremblay
- Centre de Recherche du Centre Hospitalier de l'Universite de Montreal, Montreal, Quebec, Canada
| | - Gabrielle Belanger
- Centre de Recherche du Centre Hospitalier de l'Universite de Montreal, Montreal, Quebec, Canada
| | - Nadia Sourial
- Centre de Recherche du Centre Hospitalier de l'Universite de Montreal, Montreal, Quebec, Canada
- Department of Health Management, Evaluation & Policy, Université de Montréal, Montreal, Quebec, Canada
| | - Antoine Boivin
- Centre de Recherche du Centre Hospitalier de l'Universite de Montreal, Montreal, Quebec, Canada
- Department of Family and Emergency Medicine, Faculty of Medicine, Université de Montréal, Montreal, Quebec, Canada
| | - Maxime Sasseville
- Université Laval, Quebec, Quebec, Canada
- VITAM Centre de Recherche en Santé Durable, Quebec, Quebec, Canada
| | - André Côté
- VITAM Centre de Recherche en Santé Durable, Quebec, Quebec, Canada
- Département de management, Université Laval, Quebec, Quebec, Canada
- Centre de recherche en gestion des services de santé, Université Laval, Quebec, Quebec, Canada
| | - Jean-Baptiste Gartner
- VITAM Centre de Recherche en Santé Durable, Quebec, Quebec, Canada
- Département de management, Université Laval, Quebec, Quebec, Canada
- Centre de recherche en gestion des services de santé, Université Laval, Quebec City, Quebec, Canada
| | - Nadine Taleb
- Institut de recherches cliniques de Montreal, Montreal, Quebec, Canada
- Centre Hospitalier de l'Universite de Montreal, Montreal, Quebec, Canada
- Universite de Montreal, Montreal, Quebec, Canada
| | - Marie-Eve Lavoie
- Centre de Recherche du Centre Hospitalier de l'Universite de Montreal, Montreal, Quebec, Canada
| | - Emmanuelle Trépanier
- Department of Family and Emergency Medicine, Faculty of Medicine, Université de Montréal, Montreal, Quebec, Canada
| | | | - Marcel Labelle
- Centre de Recherche du Centre Hospitalier de l'Universite de Montreal, Montreal, Quebec, Canada
| | - Géraldine Layani
- Centre de Recherche du Centre Hospitalier de l'Universite de Montreal, Montreal, Quebec, Canada
- Department of Family and Emergency Medicine, Faculty of Medicine, Université de Montréal, Montreal, Quebec, Canada
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ElSayed NA, Aleppo G, Bannuru RR, Bruemmer D, Collins BS, Ekhlaspour L, Hilliard ME, Johnson EL, Khunti K, Lingvay I, Matfin G, McCoy RG, Perry ML, Pilla SJ, Polsky S, Prahalad P, Pratley RE, Segal AR, Seley JJ, Stanton RC, Gabbay RA. 1. Improving Care and Promoting Health in Populations: Standards of Care in Diabetes-2024. Diabetes Care 2024; 47:S11-S19. [PMID: 38078573 PMCID: PMC10725798 DOI: 10.2337/dc24-s001] [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] [Indexed: 12/18/2023]
Abstract
The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at https://professional.diabetes.org/SOC.
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Donohue JF, Elborn JS, Lansberg P, Javed A, Tesfaye S, Rugo H, Duddi SRD, Jithoo N, Huang PH, Subramaniam K, Ramanjinappa N, Koltun A, Melamed S, Chan JCN. Bridging the "Know-Do" Gaps in Five Non-Communicable Diseases Using a Common Framework Driven by Implementation Science. J Healthc Leadersh 2023; 15:103-119. [PMID: 37416849 PMCID: PMC10320809 DOI: 10.2147/jhl.s394088] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 04/12/2023] [Indexed: 07/08/2023] Open
Abstract
According to the United Nations High-Level Meeting 2018, five non-communicable diseases (NCDs) including cardiovascular diseases, chronic respiratory diseases, diabetes mellitus, cancer, and mental health conditions accounted for two-thirds of global deaths. These five NCDs share five common risk factors including tobacco use, unhealthy diets, physical inactivity, alcohol use, and air pollution. Low- and middle-income countries (LMICs) face larger burden of NCDs than high-income countries (HICs), due to differences in ecological, technological, socioeconomic and health system development. Based on high-level evidence albeit mainly from HICs, the burden caused by NCDs can be reduced by affordable medicines and best practices. However, "know-do" gaps, ie, gaps between what we know in science and what we do in practice, has limited the impact of these strategies, especially in LMICs. Implementation science advocates the use of robust methodologies to evaluate sustainable solutions in health, education and social care aimed at informing practice and policies. In this article, physician researchers with expertise in NCDs reviewed the common challenges shared by these five NCDs with different clinical courses. They explained the principles of implementation science and advocated the use of an evidence-based framework to implement solutions focusing on early detection, prevention and empowerment, supplemented by best practices in HICs and LMICs. These successful stories can be used to motivate policymakers, payors, providers, patients and public to co-design frameworks and implement context-relevant, multi-component, evidence-based practices. In pursuit of this goal, we propose partnership, leadership, and access to continuing care as the three pillars in developing roadmaps for addressing the multiple needs during the journey of a person with or at risk of these five NCDs. By transforming the ecosystem, raising awareness and aligning context-relevant practices and policies with ongoing evaluation, it is possible to make healthcare accessible, affordable and sustainable to reduce the burden of these five NCDs.
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Affiliation(s)
| | | | | | - Afzal Javed
- Warwick Medical School, University of Warwick, Warwick, UK & Pakistan Psychiatric Research Centre, Coventry, UK
| | - Solomon Tesfaye
- Sheffield Teaching Hospitals and the University of Sheffield, Sheffield, UK
| | - Hope Rugo
- University of California San Francisco Comprehensive Cancer Center, San Francisco, CA, USA
| | - Sita Ratna Devi Duddi
- International Alliance of Patients’ Organisations, London, United Kingdom
- DakshamA Health and Education, Delhi, India
| | | | | | | | | | | | | | - Juliana C N Chan
- Department of Medicine and Therapeutics, Hong Kong Institute of Diabetes and Obesity, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, Special Administrative Regions of the People’s Republic of China
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Li Z, Shen Y, Ning J. Accommodating time-varying heterogeneity in risk estimation under the Cox model: a transfer learning approach. J Am Stat Assoc 2023; 118:2276-2287. [PMID: 38505403 PMCID: PMC10950074 DOI: 10.1080/01621459.2023.2210336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 04/26/2023] [Indexed: 03/21/2024]
Abstract
Transfer learning has attracted increasing attention in recent years for adaptively borrowing information across different data cohorts in various settings. Cancer registries have been widely used in clinical research because of their easy accessibility and large sample size. Our method is motivated by the question of how to utilize cancer registry data as a complement to improve the estimation precision of individual risks of death for inflammatory breast cancer (IBC) patients at The University of Texas MD Anderson Cancer Center. When transferring information for risk estimation based on the cancer registries (i.e., source cohort) to a single cancer center (i.e., target cohort), time-varying population heterogeneity needs to be appropriately acknowledged. However, there is no literature on how to adaptively transfer knowledge on risk estimation with time-to-event data from the source cohort to the target cohort while adjusting for time-varying differences in event risks between the two sources. Our goal is to address this statistical challenge by developing a transfer learning approach under the Cox proportional hazards model. To allow data-adaptive levels of information borrowing, we impose Lasso penalties on the discrepancies in regression coefficients and baseline hazard functions between the two cohorts, which are jointly solved in the proposed transfer learning algorithm. As shown in the extensive simulation studies, the proposed method yields more precise individualized risk estimation than using the target cohort alone. Meanwhile, our method demonstrates satisfactory robustness against cohort differences compared with the method that directly combines the target and source data in the Cox model. We develop a more accurate risk estimation model for the MD Anderson IBC cohort given various treatment and baseline covariates, while adaptively borrowing information from the National Cancer Database to improve risk assessment.
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Affiliation(s)
- Ziyi Li
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Yu Shen
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jing Ning
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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Ke C, Mohammad E, Chan JCN, Kong APS, Leung FH, Shah BR, Lee D, Luk AO, Ma RCW, Chow E, Wei X. Team-Based Diabetes Care in Ontario and Hong Kong: a Comparative Review. Curr Diab Rep 2023:10.1007/s11892-023-01508-0. [PMID: 37043089 PMCID: PMC10091345 DOI: 10.1007/s11892-023-01508-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/29/2023] [Indexed: 04/13/2023]
Abstract
PURPOSE OF REVIEW There are gaps in implementing and accessing team-based diabetes care. We reviewed and compared how team-based diabetes care was implemented in the primary care contexts of Ontario and Hong Kong. RECENT FINDINGS Ontario's Diabetes Education Programs (DEPs) were scaled-up incrementally. Hong Kong's Multidisciplinary Risk Assessment and Management Program for Diabetes Mellitus (RAMP-DM) evolved from a research-driven quality improvement program. Each jurisdiction had a mixture of non-team and team-based primary care with variable accessibility. Referral procedures, follow-up processes, and financing models varied. DEPs used a flexible approach, while the RAMP-DM used structured assessment for quality assurance. Each approach depended on adequate infrastructure, processes, and staff. Diabetes care is most accessible and functional when integrated team-based services are automatically initiated upon diabetes diagnosis within a strong primary care system, ideally linked to a register with supports including specialist care. Structured assessment and risk stratification are the basis of a well-studied, evidence-based approach for achieving the standards of team-based diabetes care, although flexibility in care delivery may be needed to meet the unique needs of some individuals. Policymakers and funders should ensure investment in skilled health professionals, infrastructure, and processes to improve care quality.
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Affiliation(s)
- Calvin Ke
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada.
- Department of Medicine, Toronto General Hospital, University Health Network, Toronto, Ontario, Canada.
- ICES, Toronto, Ontario, Canada.
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China.
- , Toronto, Canada.
| | - Emaad Mohammad
- Department of Medicine, Queen's University, Kingston, Ontario, Canada
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Asia Diabetes Foundation, Shatin, Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
| | - Alice P S Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Asia Diabetes Foundation, Shatin, Hong Kong SAR, China
| | - Fok-Han Leung
- Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department of Community and Family Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Baiju R Shah
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
- ICES, Toronto, Ontario, Canada
- Department of Medicine, Sunnybrook Hospital, Toronto, Ontario, Canada
| | - Douglas Lee
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department of Medicine, Toronto General Hospital, University Health Network, Toronto, Ontario, Canada
- ICES, Toronto, Ontario, Canada
| | - Andrea O Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Asia Diabetes Foundation, Shatin, Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Asia Diabetes Foundation, Shatin, Hong Kong SAR, China
| | - Elaine Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
- Asia Diabetes Foundation, Shatin, Hong Kong SAR, China
| | - Xiaolin Wei
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
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Lim LL, Chow E, Chan JCN. Cardiorenal diseases in type 2 diabetes mellitus: clinical trials and real-world practice. Nat Rev Endocrinol 2023; 19:151-163. [PMID: 36446898 DOI: 10.1038/s41574-022-00776-2] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/27/2022] [Indexed: 11/30/2022]
Abstract
Patients with type 2 diabetes mellitus (T2DM) can have multiple comorbidities and premature mortality due to atherosclerotic cardiovascular disease, hospitalization with heart failure and/or chronic kidney disease. Traditional drugs that lower glucose, such as metformin, or that treat high blood pressure and blood levels of lipids, such as renin-angiotensin-system inhibitors and statins, have organ-protective effects in patients with T2DM. Amongst patients with T2DM treated with these traditional drugs, randomized clinical trials have confirmed the additional cardiorenal benefits of sodium-glucose co-transporter 2 inhibitors (SGLT2i), glucagon-like peptide 1 receptor agonists (GLP1RA) and nonsteroidal mineralocorticoid receptor antagonists. The cardiorenal benefits of SGLT2i extended to patients with heart failure and/or chronic kidney disease without T2DM, whereas incretin-based therapy (such as GLP1RA) reduced cardiovascular events in patients with obesity and T2DM. However, considerable care gaps exist owing to insufficient detection, therapeutic inertia and poor adherence to these life-saving medications. In this Review, we discuss the complex interconnections of cardiorenal-metabolic diseases and strategies to implement evidence-based practice. Furthermore, we consider the need to conduct clinical trials combined with registers in specific patient segments to evaluate existing and emerging therapies to address unmet needs in T2DM.
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Affiliation(s)
- Lee-Ling Lim
- Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China
| | - Elaine Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China
- Phase 1 Clinical Trial Centre, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China.
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China.
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China.
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Chwal BC, Dos Reis RCP, Schmidt MI, Duncan BB, Barreto SM, Griep RH. Levels and correlates of risk factor control in diabetes mellitus -ELSA-Brasil. Diabetol Metab Syndr 2023; 15:4. [PMID: 36604768 PMCID: PMC9817330 DOI: 10.1186/s13098-022-00961-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 12/02/2022] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Control of glucose, blood pressure, cholesterol, and smoking improves the prognosis of individuals with diabetes mellitus. Our objective was to assess the level of control of these risk factors in Brazilian adults with known diabetes and evaluate correlates of target achievement. METHODS Cross-sectional sample of the Brazilian Longitudinal Study of Adult Health, composed of participants reporting a previous diagnosis of diabetes or the use oof antidiabetic medication. We measured glycated hemoglobin (HbA1c) and LDL-cholesterol at a central laboratory and blood pressure following standardized protocols. We defined HbA1c < 7% as glucose control (target A); blood pressure < 140/90 mmHg (or < 130/80 mmHg in high cardiovascular risk) as blood pressure control (target B), and LDL-c < 100 mg/dl (or < 70 mg/dl in high risk) as lipid control (target C), according to the 2022 American Diabetes Association guidelines. RESULTS Among 2062 individuals with diabetes, 1364 (66.1%) reached target A, 1596 (77.4%) target B, and 1086 (52.7%) target C; only 590 (28.6%) achieved all three targets. When also considering a non-smoking target, those achieving all targets dropped to 555 (26.9%). Women (PR = 1.13; 95%CI 1.07-1.20), those aged ≥ 74 (PR = 1.20; 95%CI 1.08-1.34), and those with greater per capita income (e.g., greatest income PR = 1.26; 95%CI 1.10-1.45) were more likely to reach glucose control. Those black (PR = 0.91; 95%CI 0.83-1.00) or with a longer duration of diabetes (e.g., ≥ 10 years PR = 0.43; 95%CI 0.39-0.47) were less likely. Women (PR = 1.05; 95%CI 1.00-1.11) and those with private health insurance (PR = 1.15; 95%CI 1.07-1.23) were more likely to achieve two or more ABC targets; and those black (PR = 0.86; 95%CI 0.79-0.94) and with a longer duration of diabetes (e.g., > 10 years since diabetes diagnosis, PR = 0.68; 95%CI 0.63-0.73) less likely. CONCLUSION Control of ABC targets was poor, notably for LDL-c and especially when considering combined control. Indicators of a disadvantaged social situation were associated with less frequent control.
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Affiliation(s)
- Bruna Cristine Chwal
- Postgraduate Program in Epidemiology, Universidade Federal do Rio Grande do Sul, R. Ramiro Barcelos, 2600/518, Porto Alegre, Rio Grande do Sul, 90035-003, Brazil
| | - Rodrigo Citton Padilha Dos Reis
- Postgraduate Program in Epidemiology, Universidade Federal do Rio Grande do Sul, R. Ramiro Barcelos, 2600/518, Porto Alegre, Rio Grande do Sul, 90035-003, Brazil
- Departamento de Estatística, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Maria Inês Schmidt
- Postgraduate Program in Epidemiology, Universidade Federal do Rio Grande do Sul, R. Ramiro Barcelos, 2600/518, Porto Alegre, Rio Grande do Sul, 90035-003, Brazil
- Hospital de Clínicas de Porto Alegre, R. Ramiro Barcelos, 2600/518, Porto Alegre, Rio Grande do Sul, 90035-003, Brazil
| | - Bruce B Duncan
- Postgraduate Program in Epidemiology, Universidade Federal do Rio Grande do Sul, R. Ramiro Barcelos, 2600/518, Porto Alegre, Rio Grande do Sul, 90035-003, Brazil.
- Hospital de Clínicas de Porto Alegre, R. Ramiro Barcelos, 2600/518, Porto Alegre, Rio Grande do Sul, 90035-003, Brazil.
| | - Sandhi Maria Barreto
- Faculdade de Medicina e Hospital das Clínicas/EBSERH, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Minas Gerais, Brazil
| | - Rosane Harter Griep
- Laboratório de Educação em Ambiente e Saúde, Instituto Oswaldo Cruz, Fundação Oswaldo Cruz, Rio de Janeiro, Rio de Janeiro, Brazil
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10
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ElSayed NA, Aleppo G, Aroda VR, Bannuru RR, Brown FM, Bruemmer D, Collins BS, Hilliard ME, Isaacs D, Johnson EL, Kahan S, Khunti K, Leon J, Lyons SK, Perry ML, Prahalad P, Pratley RE, Seley JJ, Stanton RC, Gabbay RA. 1. Improving Care and Promoting Health in Populations: Standards of Care in Diabetes-2023. Diabetes Care 2023; 46:S10-S18. [PMID: 36507639 PMCID: PMC9810463 DOI: 10.2337/dc23-s001] [Citation(s) in RCA: 55] [Impact Index Per Article: 55.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.
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Goh LH, Siah CJR, Tam WWS, Tai ES, Young DYL. Effectiveness of the chronic care model for adults with type 2 diabetes in primary care: a systematic review and meta-analysis. Syst Rev 2022; 11:273. [PMID: 36522687 PMCID: PMC9753411 DOI: 10.1186/s13643-022-02117-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 11/02/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Mixed evidence exists regarding the effectiveness of the Chronic Care Model (CCM) with patient outcomes. The aim of this review is to examine the effectiveness of CCM interventions on hemoglobin A1c (HbA1c), systolic BP (SBP), diastolic BP (DBP), LDL cholesterol and body mass index (BMI) among primary care adults with type 2 diabetes. METHODS PubMed, Embase, CINAHL, Cochrane Central Registry of Controlled Trials, Scopus and Web of Science were searched from January 1990 to June 2021 for randomized controlled trials (RCTs) comparing CCM interventions against usual care among adults with type 2 diabetes mellitus in primary care with HbA1c, SBP, DBP, LDL cholesterol and BMI as outcomes. An abbreviated search was performed from 2021 to April 2022. This study followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines for data extraction and Cochrane risk of bias assessment. Two reviewers independently extracted the data. Meta-analysis was performed using Review Manager software. Heterogeneity was evaluated using χ2 and I2 test statistics. Overall effects were evaluated using Z statistic. RESULTS A total of 17 studies involving 16485 patients were identified. Most studies had low risks of bias. Meta-analysis of all 17 studies revealed that CCM interventions significantly decreased HbA1c levels compared to usual care, with a mean difference (MD) of -0.21%, 95% CI -0.30, -0.13; Z = 5.07, p<0.00001. Larger effects were experienced among adults with baseline HbA1c ≥8% (MD -0.36%, 95% CI -0.51, -0.21; Z = 5.05, p<0.00001) and when four or more CCM elements were present in the interventions (MD -0.25%, 95% CI -0.35, -0.15; Z = 4.85, p<0.00001). Interventions with CCM decreased SBP (MD -2.93 mmHg, 95% CI -4.46, -1.40, Z = 3.75, p=0.0002) and DBP (MD -1.35 mmHg, 95% CI -2.05, -0.65, Z = 3.79, p=0.0002) compared to usual care but there was no impact on LDL cholesterol levels or BMI. CONCLUSIONS CCM interventions, compared to usual care, improve glycaemic control among adults with type 2 diabetes in primary care, with greater reductions when the mean baseline HbA1c is ≥8% and with interventions containing four or more CCM elements. SYSTEMATIC REVIEW REGISTRATION PROSPERO CRD42021273959.
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Affiliation(s)
- Lay Hoon Goh
- Division of Family Medicine, Yong Loo Lin School of Medicine, National University of Singapore, NUHS Tower Block Level 9, 1E Kent Ridge Road, Singapore, 119228, Singapore.
| | - Chiew Jiat Rosalind Siah
- Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Wilson Wai San Tam
- Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - E Shyong Tai
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Doris Yee Ling Young
- Division of Family Medicine, Yong Loo Lin School of Medicine, National University of Singapore, NUHS Tower Block Level 9, 1E Kent Ridge Road, Singapore, 119228, Singapore
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12
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Ng NM, Ng YS, Chu TK, Lau P. Factors affecting prescription of sodium-glucose co-transporter 2 inhibitors in patients with type 2 diabetes mellitus with established cardiovascular disease/ chronic kidney disease in Hong Kong: a qualitative study. BMC PRIMARY CARE 2022; 23:317. [PMID: 36476327 PMCID: PMC9730654 DOI: 10.1186/s12875-022-01928-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 11/25/2022] [Indexed: 12/13/2022]
Abstract
BACKGROUND Sodium-glucose co-transporter 2 inhibitors (SGLT2 I) has cardiorenal protective properties and are recommended for patients with diabetes and established atherosclerotic cardiovascular disease (ASCVD) and/or chronic kidney disease (CKD). Although cardiorenal complications are high in diabetes and pose a significant financial burden on the Hong Kong health care system, the use of SGLT2 I in these populations remains low. And yet this issue has not been explored in Hong Kong primary care. This study aimed to explore factors affecting primary care doctors' prescribing of SGLT2 I in patients with diabetes and established ASCVD/CKD in Hong Kong. METHODS A phenomenological qualitative research using semi-structured interviews was conducted between January and May 2021 in one Hospital Authority cluster in Hong Kong. Purposive sampling was employed to recruit primary care doctors in the cluster. The Theoretical Domains Framework (TDF) underpinned the study and guided the development of the interview questions. Data was analysed using both inductive and deductive approaches. The Consolidated criteria for reporting qualitative research (COREQ) checklist was used to guide the reporting. RESULTS Interviews were conducted with 17 primary care doctors. Four overarching themes were inductively identified: knowledge and previous practice patterns influence prescription, balancing risks and benefits, doctors' professional responsibilities, and system barriers. The four themes were then deductively mapped to the nine specific domains of the TDF: knowledge; intention; memory; beliefs about capabilities; beliefs about consequences; goals; role and identity; emotion; and environmental constraints. Most interviewees, to varying extent, were aware of the cardio-renal advantages and safety profile of SGLT2 I but are reluctant to prescribe or change their patients to SGLT2 I because of their knowledge gap that the cardio-renal benefits of SGLT2 I was independent of glyacemic efficacy. Other barriers included their considerations of patients' age and renal impairment, and patients' perceptions and preferences. CONCLUSIONS Despite evidence-based recommendations of the utilisation of SGLT2 I in patients with established ASCVD/CKD, the prescription behaviour among primary care doctors was affected by various factors, most of which were amendable. Our findings will inform the development of structured interventions to address these factors to improve patients' cardio-renal outcomes.
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Affiliation(s)
- Ngai Mui Ng
- grid.417336.40000 0004 1771 3971Department of Family Medicine and Primary Health Care, Tuen Mun Hospital, 23 Tsing Chung Koon Road, Tuen Mun, New Territories, Hong Kong SAR, China
| | - Yeung Shing Ng
- grid.417336.40000 0004 1771 3971Department of Family Medicine and Primary Health Care, Tuen Mun Hospital, 23 Tsing Chung Koon Road, Tuen Mun, New Territories, Hong Kong SAR, China
| | - Tsun Kit Chu
- grid.417336.40000 0004 1771 3971Department of Family Medicine and Primary Health Care, Tuen Mun Hospital, 23 Tsing Chung Koon Road, Tuen Mun, New Territories, Hong Kong SAR, China
| | - Phyllis Lau
- grid.1008.90000 0001 2179 088XDepartment of General Practice, University of Melbourne, 780, Elizabeth Street, Melbourne, VIC 3010 Australia ,grid.1029.a0000 0000 9939 5719School of Medicine, Western Sydney University, Locked Bag 1797, Penrith, NSW 2751 Australia
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13
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Benning TJ, Heien HC, McCoy RG. Evolution of Clinical Complexity, Treatment Burden, Health Care Use, and Diabetes-Related Outcomes Among Commercial and Medicare Advantage Plan Beneficiaries With Diabetes in the U.S., 2006-2018. Diabetes Care 2022; 45:2299-2308. [PMID: 35926104 PMCID: PMC9643151 DOI: 10.2337/dc21-2623] [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: 12/17/2021] [Accepted: 06/18/2022] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To characterize trends in clinical complexity, treatment burden, health care use, and diabetes-related outcomes among adults with diabetes. RESEARCH DESIGN AND METHODS We used a nationwide claims database to identify enrollees in commercial and Medicare Advantage plans who met claims criteria for diabetes between 1 January 2006 and 31 March 2019 and to quantify annual trends in clinical complexity (e.g., active health conditions), treatment burden (e.g., medications), health care use (e.g., ambulatory, emergency department [ED], and hospital visits), and diabetes-related outcomes (e.g., hemoglobin A1c [HbA1c] levels) between 2006 and 2018. RESULTS Among 1,470,799 commercially insured patients, the proportion with ≥10 active health conditions increased from 33.3% (95% CI 33.1-33.4) in 2006 to 38.9% (38.8-39.1) in 2018 (P = 0.001) and the proportion taking three or more glucose-lowering medications increased from 11.6% (11.5-11.7) to 23.1% (22.9-23.2) (P = 0.007). The proportion with HbA1c ≥8.0% (≥64 mmol/mol) increased from 28.0% (27.7-28.3) in 2006 to 30.5% (30.2-30.7) in 2015, decreasing to 27.8% (27.5-28.0) in 2018 (overall trend P = 0.04). Number of ambulatory visits per patient per year decreased from 6.86 (6.84-6.88) to 6.19 (6.17-6.21), (P = 0.001) while ED visits increased from 0.26 (0.257-0.263) to 0.29 (0.287-0.293) (P = 0.001). Among 1,311,903 Medicare Advantage enrollees, the proportion with ≥10 active conditions increased from 51.6% (51.2-52.0) to 65.1% (65.0-65.2) (P < 0.001); the proportion taking three or more glucose-lowering medications was stable at 16.6% (16.3-16.9) and 18.1% (18.0-18.2) (P = 0.98), and the proportion with HbA1c ≥8.0% increased from 17.4% (16.7-18.1) to 18.6% (18.4-18.7) (P = 0.008). Ambulatory visits per patient per year remained stable at 8.01 (7.96-8.06) and 8.17 (8.16-8.19) (P = 0.23), but ED visits increased from 0.41 (0.40-0.42) to 0.66 (0.66-0.66) (P < 0.001). CONCLUSIONS Among patients with diabetes, clinical complexity and treatment burden have increased over time. ED utilization has also increased, and patients may be using ED services for low-acuity conditions.
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Affiliation(s)
- Tyler J. Benning
- Mayo Clinic, Department of Pediatric and Adolescent Medicine, Rochester, MN
| | - Herbert C. Heien
- Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Rochester, MN
| | - Rozalina G. McCoy
- Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Rochester, MN
- Division of Community Internal Medicine, Geriatrics, and Palliative Care, Department of Medicine, Mayo Clinic, Rochester, MN
- OptumLabs, Eden Prairie, MN
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14
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Chung SM, Lee JI, Han E, Seo HA, Jeon E, Kim HS, Yoon JS. Association between the Diabetes Drug Cost and Cardiovascular Events and Death in Korea: A National Health Insurance Service Database Analysis. Endocrinol Metab (Seoul) 2022; 37:759-769. [PMID: 36195551 PMCID: PMC9633219 DOI: 10.3803/enm.2022.1515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 08/18/2022] [Indexed: 12/30/2022] Open
Abstract
BACKGRUOUND This study aimed to investigate the long-term effects of diabetes drug costs on cardiovascular (CV) events and death. METHODS This retrospective observational study used data from 2009 to 2018 from the National Health Insurance in Korea. Among the patients with type 2 diabetes, those taking antidiabetic drugs and who did not have CV events until 2009 were included. Patients were divided into quartiles (Q1 [lowest]-4 [highest]) according to the 2009 diabetes drug cost. In addition, the 10-year incidences of CV events (non-fatal myocardial infarction, stroke, hospitalization for heart failure, and coronary revascularization) and CV death (death due to CV events) were analyzed. RESULTS A total of 441,914 participants were enrolled (median age, 60 years; men, 57%). CV events and death occurred in 28.1% and 8.36% of the patients, respectively. The 10-year incidences of CV events and deaths increased from Q1 to 4. After adjusting for sex, age, income, type of diabetes drugs, comorbidities, and smoking and drinking status, the risk of CV events significantly increased according to the sequential order of the cost quartiles. In contrast, the risk of CV death showed a U-shaped pattern, which was the lowest in Q3 (hazard ratio [HR], 0.953; 95% confidence interval [CI], 0.913 to 0.995) and the highest in Q4 (HR, 1.266; 95% CI, 1.213 to 1.321). CONCLUSION Diabetes drug expenditure affects 10-year CV events and mortality. Therefore, affording an appropriate diabetes drug cost at a similar risk of CV is an independent protective factor against CV death.
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Affiliation(s)
- Seung Min Chung
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Yeungnam University College of Medicine, Daegu, Korea
| | - Ji-In Lee
- Research Institute of The Way Healthcare, Seoul, Korea
| | - Eugene Han
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Keimyung University School of Medicine, Daegu, Korea
| | - Hyun-Ae Seo
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Daegu Fatima Hospital, Daegu, Korea
| | - Eonju Jeon
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Daegu Catholic University School of Medicine, Daegu, Korea
| | - Hye Soon Kim
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Keimyung University School of Medicine, Daegu, Korea
| | - Ji Sung Yoon
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Yeungnam University College of Medicine, Daegu, Korea
- Corresponding author: Ji Sung Yoon. Division of Endocrinology and Metabolism, Department of Internal Medicine, Yeungnam University College of Medicine, 170 Hyeonchung-ro, Nam-gu, Daegu 42415, Korea Tel: +82-53-620-4049, Fax: +82-53-654-8386, E-mail:
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15
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Youn HM, Quan J, Mak IL, Yu EYT, Lau CS, Ip MSM, Tang SCW, Wong ICK, Lau KK, Lee MSF, Ng CS, Grépin KA, Chao DVK, Ko WWK, Lam CLK, Wan EYF. Long-term spill-over impact of COVID-19 on health and healthcare of people with non-communicable diseases: a study protocol for a population-based cohort and health economic study. BMJ Open 2022; 12:e063150. [PMID: 35973704 PMCID: PMC9385580 DOI: 10.1136/bmjopen-2022-063150] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
INTRODUCTION The COVID-19 pandemic has a significant spill-over effect on people with non-communicable diseases (NCDs) over the long term, beyond the direct effect of COVID-19 infection. Evaluating changes in health outcomes, health service use and costs can provide evidence to optimise care for people with NCDs during and after the pandemic, and to better prepare outbreak responses in the future. METHODS AND ANALYSIS This is a population-based cohort study using electronic health records of the Hong Kong Hospital Authority (HA) CMS, economic modelling and serial cross-sectional surveys on health service use. This study includes people aged ≥18 years who have a documented diagnosis of diabetes mellitus, hypertension, cardiovascular disease, cancer, chronic respiratory disease or chronic kidney disease with at least one attendance at the HA hospital or clinic between 1 January 2010 and 31 December 2019, and without COVID-19 infection. Changes in all-cause mortality, disease-specific outcomes, and health services use rates and costs will be assessed between pre-COVID-19 and-post-COVID-19 pandemic or during each wave using an interrupted time series analysis. The long-term health economic impact of healthcare disruptions during the COVID-19 pandemic will be studied using microsimulation modelling. Multivariable Cox proportional hazards regression and Poisson/negative binomial regression will be used to evaluate the effect of different modes of supplementary care on health outcomes. ETHICS AND DISSEMINATION The study was approved by the institutional review board of the University of Hong Kong, the HA Hong Kong West Cluster (reference number UW 21-297). The study findings will be disseminated through peer-reviewed publications and international conferences.
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Affiliation(s)
- Hin Moi Youn
- Department of Family Medicine and Primary Care, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Jianchao Quan
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Ivy Lynn Mak
- Department of Family Medicine and Primary Care, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Esther Yee Tak Yu
- Department of Family Medicine and Primary Care, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Chak Sing Lau
- School of Clinical Medicine, Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Mary Sau Man Ip
- Division of Respiratory, Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Sydney Chi Wai Tang
- Division of Nephrology, Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Ian Chi Kei Wong
- Centre for Safe Medication Practice and research, Department of Pharmacology and Pharmacy, The University of Hong Kong, Hong Kong SAR, China
- School of Pharmacy, University College London, London, UK
- Aston Pharmacy School, Aston University, Birmingham, UK
- Department of Pharmacy, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong SAR, China
| | - Kui Kai Lau
- Division of Neurology, Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
- The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR, China
| | - Michael Shing Fung Lee
- Department of Clinical Oncology, Tuen Mun Hospital, Hospital Authority, Hong Kong SAR, China
- Department of Clinical Oncology, Queen Mary Hospital, Hong Kong SAR, China
- Department of Radiation Oncology, National University Cancer Institute, Singapore
| | - Carmen S Ng
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Karen Ann Grépin
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - David Vai Kiong Chao
- Department of Family Medicine and Primary Health Care, Hospital Authority Kowloon East Cluster, Hong Kong SAR, China
| | - Welchie Wai Kit Ko
- Department of Family Medicine and Primary Health Care, Hospital Authority Hong Kong West Cluster, Hong Kong SAR, China
| | - Cindy Lo Kuen Lam
- Department of Family Medicine and Primary Care, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
- Department of Family Medicine, The University of Hong Kong Shenzhen Hospital, Shenzhen, China
| | - Eric Yuk Fai Wan
- Department of Family Medicine and Primary Care, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
- Centre for Safe Medication Practice and research, Department of Pharmacology and Pharmacy, The University of Hong Kong, Hong Kong SAR, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong SAR, China
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16
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Riddle MC, Bakris G, Blonde L, Boulton AJM, Castle J, DiMeglio L, Gonder-Frederick L, Hu F, Kahn S, Kaul S, Moses R, Rich S, Rosenstock J, Selvin E, Vella A, Wylie-Rosett J. Editorial Cycles and Continuity of Diabetes Care. Diabetes Care 2022; 45:1493-1494. [PMID: 35796770 DOI: 10.2337/dci22-0020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Affiliation(s)
- Matthew C Riddle
- Division of Endocrinology, Diabetes and Clinical Nutrition, Oregon Health & Science University, Portland, OR
| | | | - George Bakris
- Endocrine Division, American Society of Hypertension Comprehensive Hypertension Center, University of Chicago Medicine, Chicago, IL
| | - Lawrence Blonde
- Diabetes Clinical Research Unit, Frank Riddick Institute, Department of Endocrinology, Ochsner Medical Center, New Orleans, LA
| | | | - Jessica Castle
- Harold Schnitzer Diabetes Health Center, Division of Endocrinology, Diabetes Clinical Nutrition, Oregon Health & Science University, Portland, OR
| | - Linda DiMeglio
- Division of Pediatric Endocrinology and Diabetology, Department of Pediatrics, University of Indiana School of Medicine, Indianapolis, IN
| | - Linda Gonder-Frederick
- Center for Diabetes Technology, Center for Behavioral Health and Technology, Department of Psychiatry and Neurobehavioral Sciences, University of Virginia, Charlottesville, VA
| | - Frank Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Steven Kahn
- VA Puget Sound Health Care System and Department of Medicine, University of Washington, Seattle, WA
| | - Sanjay Kaul
- Medicine/Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Robert Moses
- Diabetes Center, South Eastern Sydney and Illawarra Area Health Service, Wollongong, New South Wales, Australia
| | - Stephen Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA
| | - Julio Rosenstock
- Dallas Diabetes Research Center, Medical City Dallas, Dallas, TX
| | - Elizabeth Selvin
- Welch Center for Prevention, Epidemiology, and Clinical Research, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore MD
| | - Adrian Vella
- Endocrinology, Mayo Clinic and Mayo Foundation for Medical Education and Research, Rochester, MN
| | - Judith Wylie-Rosett
- New York Regional Center for Diabetes Translational Research, Albert Einstein College of Medicine, Bronx, NY
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17
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Abstract
The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee (https://doi.org/10.2337/dc22-SPPC), are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc22-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.
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18
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Chan JCN, Lim LL, Wareham NJ, Shaw JE, Orchard TJ, Zhang P, Lau ESH, Eliasson B, Kong APS, Ezzati M, Aguilar-Salinas CA, McGill M, Levitt NS, Ning G, So WY, Adams J, Bracco P, Forouhi NG, Gregory GA, Guo J, Hua X, Klatman EL, Magliano DJ, Ng BP, Ogilvie D, Panter J, Pavkov M, Shao H, Unwin N, White M, Wou C, Ma RCW, Schmidt MI, Ramachandran A, Seino Y, Bennett PH, Oldenburg B, Gagliardino JJ, Luk AOY, Clarke PM, Ogle GD, Davies MJ, Holman RR, Gregg EW. The Lancet Commission on diabetes: using data to transform diabetes care and patient lives. Lancet 2021; 396:2019-2082. [PMID: 33189186 DOI: 10.1016/s0140-6736(20)32374-6] [Citation(s) in RCA: 303] [Impact Index Per Article: 101.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 07/06/2020] [Accepted: 11/05/2020] [Indexed: 01/19/2023]
Affiliation(s)
- Juliana C N Chan
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Asia Diabetes Foundation, Hong Kong Special Administrative Region, China.
| | - Lee-Ling Lim
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Asia Diabetes Foundation, Hong Kong Special Administrative Region, China; Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Nicholas J Wareham
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Jonathan E Shaw
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia; School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia; School of Life Sciences, La Trobe University, Melbourne, VIC, Australia
| | - Trevor J Orchard
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, KS, USA
| | - Ping Zhang
- Division of Diabetes Translation, US Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Eric S H Lau
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Asia Diabetes Foundation, Hong Kong Special Administrative Region, China
| | - Björn Eliasson
- Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Department of Endocrinology and Metabolism, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Alice P S Kong
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Majid Ezzati
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; Medical Research Council Centre for Environment and Health, Imperial College London, London, UK; WHO Collaborating Centre on NCD Surveillance and Epidemiology, Imperial College London, London, UK
| | - Carlos A Aguilar-Salinas
- Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Margaret McGill
- Diabetes Centre, Royal Prince Alfred Hospital, University of Sydney, Sydney, NSW, Australia
| | - Naomi S Levitt
- Chronic Disease Initiative for Africa, Department of Medicine, Faculty of Medicine and Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Guang Ning
- Shanghai Clinical Center for Endocrine and Metabolic Disease, Department of Endocrinology, Ruijin Hospital, Shanghai Jiaotong University, School of Medicine, Shanghai, China; Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai, China
| | - Wing-Yee So
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Jean Adams
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Paula Bracco
- School of Medicine and Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Nita G Forouhi
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Gabriel A Gregory
- Life for a Child Program, Diabetes NSW and ACT, Glebe, NSW, Australia; Sydney Medical School, University of Sydney, Sydney, NSW, Australia
| | - Jingchuan Guo
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, KS, USA
| | - Xinyang Hua
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Emma L Klatman
- Life for a Child Program, Diabetes NSW and ACT, Glebe, NSW, Australia
| | - Dianna J Magliano
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia; School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Boon-Peng Ng
- Division of Diabetes Translation, US Centers for Disease Control and Prevention, Atlanta, GA, USA; College of Nursing and Disability, Aging and Technology Cluster, University of Central Florida, Orlando, FL, USA
| | - David Ogilvie
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Jenna Panter
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Meda Pavkov
- Division of Diabetes Translation, US Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Hui Shao
- Division of Diabetes Translation, US Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Nigel Unwin
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Martin White
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Constance Wou
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Maria I Schmidt
- School of Medicine and Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Ambady Ramachandran
- India Diabetes Research Foundation and Dr A Ramachandran's Diabetes Hospitals, Chennai, India
| | - Yutaka Seino
- Center for Diabetes, Endocrinology and Metabolism, Kansai Electric Power Hospital, Osaka, Japan; Yutaka Seino Distinguished Center for Diabetes Research, Kansai Electric Power Medical Research Institute, Kobe, Japan
| | - Peter H Bennett
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - Brian Oldenburg
- Nossal Institute for Global Health, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia; WHO Collaborating Centre on Implementation Research for Prevention and Control of NCDs, University of Melbourne, Melbourne, VIC, Australia
| | - Juan José Gagliardino
- Centro de Endocrinología Experimental y Aplicada, UNLP-CONICET-CICPBA, Facultad de Ciencias Médicas, Universidad Nacional de La Plata, La Plata, Argentina
| | - Andrea O Y Luk
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Asia Diabetes Foundation, Hong Kong Special Administrative Region, China
| | - Philip M Clarke
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Graham D Ogle
- Life for a Child Program, Diabetes NSW and ACT, Glebe, NSW, Australia; National Health and Medical Research Council Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia
| | - Melanie J Davies
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Rury R Holman
- Diabetes Trials Unit, Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
| | - Edward W Gregg
- Division of Diabetes Translation, US Centers for Disease Control and Prevention, Atlanta, GA, USA; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
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19
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Haque F, Ibne Reaz MB, Chowdhury MEH, Md Ali SH, Ashrif A Bakar A, Rahman T, Kobashi S, Dhawale CA, Sobhan Bhuiyan MA. A nomogram-based diabetic sensorimotor polyneuropathy severity prediction using Michigan neuropathy screening instrumentations. Comput Biol Med 2021; 139:104954. [PMID: 34715551 DOI: 10.1016/j.compbiomed.2021.104954] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 10/14/2021] [Accepted: 10/15/2021] [Indexed: 12/15/2022]
Abstract
BACKGROUND Diabetic Sensorimotor polyneuropathy (DSPN) is one of the major indelible complications in diabetic patients. Michigan neuropathy screening instrumentation (MNSI) is one of the most common screening techniques used for DSPN, however, it does not provide any direct severity grading system. METHOD For designing and modeling the DSPN severity grading systems for MNSI, 19 years of data from Epidemiology of Diabetes Interventions and Complications (EDIC) clinical trials were used. Different Machine learning-based feature ranking techniques were investigated to identify the important MNSI features associated with DSPN diagnosis. A multivariable logistic regression-based nomogram was generated and validated for DSPN severity grading using the best performing top-ranked MNSI features. RESULTS Top-10 ranked features from MNSI features: Appearance of Feet (R), Ankle Reflexes (R), Vibration perception (L), Vibration perception (R), Appearance of Feet (L), 10-gm filament (L), Ankle Reflexes (L), 10-gm filament (R), Bed Cover Touch, and Ulceration (R) were identified as important features for identifying DSPN by Multi-Tree Extreme Gradient Boost model. The nomogram-based prediction model exhibited an accuracy of 97.95% and 98.84% for the EDIC test set and an independent test set, respectively. A DSPN severity score technique was generated for MNSI from the DSPN severity prediction model. DSPN patients were stratified into four severity levels: absent, mild, moderate, and severe using the cut-off values of 17.6, 19.1, 20.5 for the DSPN probability less than 50%, 75%-90%, and above 90%, respectively. CONCLUSIONS The findings of this work provide a machine learning-based MNSI severity grading system which has the potential to be used as a secondary decision support system by health professionals in clinical applications and large clinical trials to identify high-risk DSPN patients.
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Affiliation(s)
- Fahmida Haque
- Department of Electrical, Electronic and System Engineering, Universiti Kebangsaan Malaysia, Bangi, 43600, Selangor, Malaysia
| | - Mamun Bin Ibne Reaz
- Department of Electrical, Electronic and System Engineering, Universiti Kebangsaan Malaysia, Bangi, 43600, Selangor, Malaysia.
| | | | - Sawal Hamid Md Ali
- Department of Electrical, Electronic and System Engineering, Universiti Kebangsaan Malaysia, Bangi, 43600, Selangor, Malaysia
| | - Ahmad Ashrif A Bakar
- Department of Electrical, Electronic and System Engineering, Universiti Kebangsaan Malaysia, Bangi, 43600, Selangor, Malaysia
| | - Tawsifur Rahman
- Department of Electrical Engineering, Qatar University, Doha, 2713, Qatar
| | - Syoji Kobashi
- Graduate School of Engineering, University of Hyogo, Hyogo, Japan
| | - Chitra A Dhawale
- P. R. Pote College of Engineering and Management, Kathora Road, Amravati, 444602, India
| | - Mohammad Arif Sobhan Bhuiyan
- Department Electrical and Electronic Engineering, Xiamen University Malaysia, Bandar Sunsuria, Sepang, 43900, Selangor, Malaysia.
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20
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Mancilla RB, Tấn BP, Daul C, Martínez JG, Salas LL, Wolf D, Hernández AV. Anatomical 3D Modeling Using IR Sensors and Radiometric Processing Based on Structure from Motion: Towards a Tool for the Diabetic Foot Diagnosis. SENSORS (BASEL, SWITZERLAND) 2021; 21:3918. [PMID: 34204151 PMCID: PMC8201207 DOI: 10.3390/s21113918] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 06/01/2021] [Accepted: 06/02/2021] [Indexed: 12/31/2022]
Abstract
Medical infrared thermography has proven to be a complementary procedure to physiological disorders, such as the diabetic foot. However, the technique remains essentially based on 2D images that display partial anatomy. In this context, a 3D thermal model provides improved visualization and faster inspection. This paper presents a 3D reconstruction method associated with temperature information. The proposed solution is based on a Structure from Motion and Multi-view Stereo approach, exploiting a set of multimodal merged images. The infrared images were obtained by automatically processing the radiometric data to remove thermal interferences, segment the RoI, enhance false-color contrast, and for multimodal co-registration under a controlled environment and a ∆T < 2.6% between the RoI and thermal interferences. The geometric verification accuracy was 77% ± 2%. Moreover, a normalized error was adjusted per sample based on a linear model to compensate for the curvature emissivity (error ≈ 10% near to 90°). The 3D models were displayed with temperature information and interaction controls to observe any point of view. The temperature sidebar values were assigned with information retrieved only from the RoI. The results have proven the feasibility of the 3D multimodal construction to be used as a promising tool in the diagnosis of diabetic foot.
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Affiliation(s)
- Rafael Bayareh Mancilla
- Departamento de Ingeniería Eléctrica/Sección de Bioelectrónica, Centro de Investigación y de Estudios Avanzados del IPN, Av. Instituto Politécnico Nacional 2508, Col. San Pedro Zacatenco, Gustavo A. Madero, Ciudad de México 07360, Mexico; (L.L.S.); (A.V.H.)
- Centre de Recherche en Automatique de Nancy (CRAN)/CNRS, Université de Lorraine, 2 Avenue de la Forêt de Haye, 54516 Vandœuvre-Lès-Nancy, Lorraine, France; (B.P.T.); (C.D.); (D.W.)
| | - Bình Phan Tấn
- Centre de Recherche en Automatique de Nancy (CRAN)/CNRS, Université de Lorraine, 2 Avenue de la Forêt de Haye, 54516 Vandœuvre-Lès-Nancy, Lorraine, France; (B.P.T.); (C.D.); (D.W.)
| | - Christian Daul
- Centre de Recherche en Automatique de Nancy (CRAN)/CNRS, Université de Lorraine, 2 Avenue de la Forêt de Haye, 54516 Vandœuvre-Lès-Nancy, Lorraine, France; (B.P.T.); (C.D.); (D.W.)
| | - Josefina Gutiérrez Martínez
- División de Ingeniería Biomédica, Instituto Nacional de Rehabilitación “Luis Guillermo Ibarra Ibarrra” (INR-LGII), Calzada México-Xochimilco 289, Coapa, Ciudad de México 14389, Mexico;
| | - Lorenzo Leija Salas
- Departamento de Ingeniería Eléctrica/Sección de Bioelectrónica, Centro de Investigación y de Estudios Avanzados del IPN, Av. Instituto Politécnico Nacional 2508, Col. San Pedro Zacatenco, Gustavo A. Madero, Ciudad de México 07360, Mexico; (L.L.S.); (A.V.H.)
| | - Didier Wolf
- Centre de Recherche en Automatique de Nancy (CRAN)/CNRS, Université de Lorraine, 2 Avenue de la Forêt de Haye, 54516 Vandœuvre-Lès-Nancy, Lorraine, France; (B.P.T.); (C.D.); (D.W.)
| | - Arturo Vera Hernández
- Departamento de Ingeniería Eléctrica/Sección de Bioelectrónica, Centro de Investigación y de Estudios Avanzados del IPN, Av. Instituto Politécnico Nacional 2508, Col. San Pedro Zacatenco, Gustavo A. Madero, Ciudad de México 07360, Mexico; (L.L.S.); (A.V.H.)
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21
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Haque F, Bin Ibne Reaz M, Chowdhury MEH, Srivastava G, Hamid Md Ali S, Bakar AAA, Bhuiyan MAS. Performance Analysis of Conventional Machine Learning Algorithms for Diabetic Sensorimotor Polyneuropathy Severity Classification. Diagnostics (Basel) 2021; 11:diagnostics11050801. [PMID: 33925190 PMCID: PMC8146253 DOI: 10.3390/diagnostics11050801] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 04/23/2021] [Accepted: 04/27/2021] [Indexed: 12/26/2022] Open
Abstract
Background: Diabetic peripheral neuropathy (DSPN), a major form of diabetic neuropathy, is a complication that arises in long-term diabetic patients. Even though the application of machine learning (ML) in disease diagnosis is a very common and well-established field of research, its application in diabetic peripheral neuropathy (DSPN) diagnosis using composite scoring techniques like Michigan Neuropathy Screening Instrumentation (MNSI), is very limited in the existing literature. Method: In this study, the MNSI data were collected from the Epidemiology of Diabetes Interventions and Complications (EDIC) clinical trials. Two different datasets with different MNSI variable combinations based on the results from the eXtreme Gradient Boosting feature ranking technique were used to analyze the performance of eight different conventional ML algorithms. Results: The random forest (RF) classifier outperformed other ML models for both datasets. However, all ML models showed almost perfect reliability based on Kappa statistics and a high correlation between the predicted output and actual class of the EDIC patients when all six MNSI variables were considered as inputs. Conclusions: This study suggests that the RF algorithm-based classifier using all MNSI variables can help to predict the DSPN severity which will help to enhance the medical facilities for diabetic patients.
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Affiliation(s)
- Fahmida Haque
- Department of Electrical, Electronic and System Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia; (F.H.); (M.B.I.R.); (S.H.M.A.); (A.A.A.B.)
| | - Mamun Bin Ibne Reaz
- Department of Electrical, Electronic and System Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia; (F.H.); (M.B.I.R.); (S.H.M.A.); (A.A.A.B.)
| | | | - Geetika Srivastava
- Department of Physics and Electronics, Dr. Ram Manohar Lohia Avadh University, Ayodhya 224001, India;
| | - Sawal Hamid Md Ali
- Department of Electrical, Electronic and System Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia; (F.H.); (M.B.I.R.); (S.H.M.A.); (A.A.A.B.)
| | - Ahmad Ashrif A. Bakar
- Department of Electrical, Electronic and System Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia; (F.H.); (M.B.I.R.); (S.H.M.A.); (A.A.A.B.)
| | - Mohammad Arif Sobhan Bhuiyan
- Department Electrical and Electronic Engineering, Xiamen University Malaysia, Bandar Sunsuria, Sepang 43900, Malaysia
- Correspondence:
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22
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Mosenzon O, Del Prato S, Schechter M, Leiter LA, Ceriello A, DeFronzo RA, Raz I. From glucose lowering agents to disease/diabetes modifying drugs: a "SIMPLE" approach for the treatment of type 2 diabetes. Cardiovasc Diabetol 2021; 20:92. [PMID: 33910583 PMCID: PMC8082901 DOI: 10.1186/s12933-021-01281-y] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 04/15/2021] [Indexed: 12/11/2022] Open
Abstract
During the last decade we experienced a surge in the number of glucose lowering agents that can be used to treat patients with type 2 diabetes. Especially important are the discoveries that sodium glucose co-transporter type 2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP-1 RA) improve patients’ cardiovascular and renal outcomes. Accordingly, various medical associations have updated their guidelines for the treatment of diabetes in this new era. Though not agreeing on every issue, these position-statements generally share a detailed and often complex workflow that may be too complicated for the busy and overworked primary care setting, where the majority of patients with type 2 diabetes are managed in many countries. Other guidelines, generally those from the cardiology associations focus primarily on the population of patients with high risk for or pre-existing cardiovascular disease, which represent only the minority of patients with type 2 diabetes. We believe that we should re-define SGLT2i and GLP-1 RA as diabetes/disease modifying drugs (DMDs) given the recent evidence of their cardiovascular and renal benefits. Based on this definition we have designed a SIMPLE approach in order to assist primary care teams in selecting the most appropriate therapy for their patients. We believe that most subjects newly diagnosed with type 2 diabetes should initiate early combination therapy with metformin and a prognosis changing DMD. The decision whether to use GLP-1 RA or SGLT2i should be made based on specific patient’s risk factors and preferences. Importantly, DMDs are known to have a generally safe side-effect profile, with lower risk for hypoglycemia and weight gain, further promoting their wider usage. Early combination therapy with DMDs may improve the multiple pathophysiological abnormalities responsible for type 2 diabetes and its complications, thus resulting in the greatest long term benefits.
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Affiliation(s)
- Ofri Mosenzon
- The Diabetes Unit, Department of Endocrinology and Metabolism, Hadassah Medical Center, P.O. Box 12000, 9112001, Jerusalem, Israel. .,Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Stefano Del Prato
- Department of Clinical and Experimental Medicine, Section of Diabetes, Nuovo Ospedale Santa Chiara, University of Pisa, Pisa, Italy
| | - Meir Schechter
- The Diabetes Unit, Department of Endocrinology and Metabolism, Hadassah Medical Center, P.O. Box 12000, 9112001, Jerusalem, Israel.,Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Lawrence A Leiter
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, University of Toronto, Toronto, Canada
| | | | - Ralph A DeFronzo
- University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Itamar Raz
- The Diabetes Unit, Department of Endocrinology and Metabolism, Hadassah Medical Center, P.O. Box 12000, 9112001, Jerusalem, Israel.,Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
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23
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McMorrow R, Thuraisingam S, Furler J, Manski-Nankervis JA. Professional flash glucose monitoring and health service utilisation in type 2 diabetes: A secondary analysis of the GP-OSMOTIC study. Prim Care Diabetes 2021; 15:178-183. [PMID: 32863148 DOI: 10.1016/j.pcd.2020.08.001] [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: 06/15/2020] [Revised: 07/30/2020] [Accepted: 08/01/2020] [Indexed: 11/30/2022]
Abstract
AIM Professional flash glucose monitoring involves people with diabetes wearing a glucose monitor for up to two weeks, with the data downloaded by their health professional, and the information used to help guide treatment. This study describes if professional flash glucose monitoring was associated with a change in health services utilisation. METHODS Administrative claims data from three data sources were linked to 288 participants from the GP-OSMOTIC study, a randomised controlled trial evaluating the use of professional flash glucose monitoring versus usual care in people with type 2 diabetes in primary care. Generalised linear models with the Poisson family specified and log link function were used to compare general practice consultations between the intervention and control groups at 0-6- and 6-12-month time points, with adjustment for baseline health services utilisation. RESULTS GP consultations increased in the flash glucose monitoring group in the 6 months following initial flash glucose monitoring sensor application from a median (IQR) 6 (4,9) to 8 (5,11); (P < 0.001). Participants in the professional FGM group were 1.2 times (95 % CI 1.1-1.4 (P = 0.0014)) more likely at 6-12 months to have GP consultation visits. CONCLUSIONS Administrative claims data identified changes in health services utilisation associated with professional flash glucose monitoring, despite minimal changes in glycaemic control.
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Affiliation(s)
- Rita McMorrow
- Department of General Practice, University of Melbourne, Level 2, 780 Elizabeth St, Melbourne, VIC 3004, Australia.
| | - Sharmala Thuraisingam
- Department of General Practice, University of Melbourne, Level 2, 780 Elizabeth St, Melbourne, VIC 3004, Australia
| | - John Furler
- Department of General Practice, University of Melbourne, Level 2, 780 Elizabeth St, Melbourne, VIC 3004, Australia
| | - Jo-Anne Manski-Nankervis
- Department of General Practice, University of Melbourne, Level 2, 780 Elizabeth St, Melbourne, VIC 3004, Australia
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24
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Abstract
The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee (https://doi.org/10.2337/dc21-SPPC), are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc21-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.
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25
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Wong C, O WW, Wong KS, Ma R, Hui E, Kwok CT. Randomized trial of a patient empowerment and cognitive training program for older people with diabetes mellitus and cognitive impairment. Geriatr Gerontol Int 2020; 20:1164-1170. [DOI: 10.1111/ggi.14062] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Revised: 09/20/2020] [Accepted: 09/24/2020] [Indexed: 01/21/2023]
Affiliation(s)
- Chit‐wai Wong
- Department of Medicine & Geriatrics Caritas Medical Centre, Hospital Authority Hong Kong
| | - Wai‐Tsun William O
- Department of Medicine & Therapeutics Prince of Wales Hospital Shatin Hong Kong
| | - Kin‐Wai Shirley Wong
- Senior Citizens Services, Social Services Department The Salvation Army Hong Kong & Macau Command Hong Kong
| | - Ronald Ma
- Department of Medicine & Therapeutics Prince of Wales Hospital Shatin Hong Kong
| | - Elsie Hui
- Medicine and Geriatric Unit Shatin Hospital, Hospital Authority Hong Kong
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Abstract
BACKGROUND Uninsured patients with end-stage renal disease face barriers to peritoneal dialysis (PD), a type of home dialysis that is associated with improved quality of life and reduced Medicare costs. Although uninsured patients using PD at dialysis start receive retroactive Medicare coverage for required predialysis services, coverage only applies for the calendar month of dialysis start. Thus, initiating dialysis later in the month yields longer retroactive coverage. OBJECTIVES To examine whether differences in retroactive Medicare were associated with decreased long-term PD use. RESEARCH DESIGN We exploited the dialysis start date using a regression discontinuity design on a national cohort from the US Renal Data System. SUBJECTS 36,256 uninsured adults starting dialysis between January 1, 2006 and December 31, 2014. MEASURES PD use at dialysis days 1, 90, 180, and 360. RESULTS Starting dialysis on the first versus last day of the calendar month was associated with an absolute decrease in PD use of 2.7% [95% confidence interval (CI), 1.5%-3.9%], or a relative decrease of 20% (95% CI, 12%-27%) at dialysis day 360. The absolute decrease was 5.5% (95% CI, 3.5%-7.2%) after Medicare established provider incentives for PD in 2011 and 7.2% (95% CI, 2.5%-11.9%) after Medicaid expansion in 2014. Patients were unlikely to switch from hemodialysis to PD after the first month of dialysis (probability of 6.9% in month 1, 1.5% in month 2, and 0.9% in month 4). CONCLUSIONS Extending retroactive coverage for preparatory dialysis services could increase PD use and reduce overall Medicare spending in the uninsured.
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27
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Liu M, Yuan X, Ouyang J, Chaisson J, Bergeron T, Cantrell D, Washington V, Zhang Y, Nigam S. Evaluation of four disease management programs: evidence from blue cross blue shield of Louisiana. J Med Econ 2020; 23:557-565. [PMID: 31990232 DOI: 10.1080/13696998.2020.1722677] [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] [Indexed: 10/25/2022]
Abstract
Aims: Chronic diseases impose a substantial healthcare burden. This study sought to evaluate the clinical and economic impact of new disease management (DM) programs, targeting four major chronic disease groups: diabetes, coronary heart disease (CHD)/hypertension (HTN), asthma/chronic obstructive pulmonary disease (COPD), and congestive heart failure (CHF)/chronic kidney disease (CKD).Materials and methods: Between March 1, 2015, and February 28, 2018, members with Blue Cross Blue Shield of Louisiana insurance were contacted and enrolled in a DM program if they were aged 18 years through 64 years, eligible for a DM program, and had not been previously enrolled in a DM program. Active enrollees of a DM program ("IN" group) were compared to members who were not yet enrolled ("OUT" group). Average per member per month (PMPM) costs were aggregated annually to document any descriptive trends. Multivariable model estimates were used to compare PMPM costs for all IN subjects and all OUT subjects. Total medical savings were evaluated for the following time intervals: 1-12 months, 13-24 months, and 25-36 months.Results: For all four DM programs, average costs PMPM trended upward over time for the OUT cohort, while they remained relatively stable for the IN cohort. Some evidence also showed that DM programs improved clinical outcomes, such as hemoglobin A1c values. A difference in difference analysis showed PMPM savings for all four programs combined of $31.61, $50.45, and $53.72 after 1, 2, and 3 years, respectively. Multivariable modeling results showed total savings after 3 years of $14,460,174 for all DM programs combined.Limitations: Although multivariable models adjusted for several clinical, demographic, and economic characteristics; it is possible that some important confounders were missing due to lack of data.Conclusions: DM programs implemented to control diabetes, CHD/HTN, CHF/CKD, and asthma/COPD are cost-effective and show some evidence of improved clinical outcomes.
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Affiliation(s)
- M Liu
- Blue Cross Blue Shield of Louisiana, Baton Rouge, LA, USA
| | - X Yuan
- Blue Cross Blue Shield of Louisiana, Baton Rouge, LA, USA
| | - J Ouyang
- Blue Cross Blue Shield of Louisiana, Baton Rouge, LA, USA
| | - J Chaisson
- Blue Cross Blue Shield of Louisiana, Baton Rouge, LA, USA
| | - T Bergeron
- Blue Cross Blue Shield of Louisiana, Baton Rouge, LA, USA
| | - D Cantrell
- Blue Cross Blue Shield of Louisiana, Baton Rouge, LA, USA
| | - V Washington
- Blue Cross Blue Shield of Louisiana, Baton Rouge, LA, USA
| | - Y Zhang
- Blue Cross Blue Shield of Louisiana, Baton Rouge, LA, USA
| | - S Nigam
- Blue Cross Blue Shield of Louisiana, Baton Rouge, LA, USA
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Lee TY, Kuo S, Yang CY, Ou HT. Cost-effectiveness of long-acting insulin analogues vs intermediate/long-acting human insulin for type 1 diabetes: A population-based cohort followed over 10 years. Br J Clin Pharmacol 2020; 86:852-860. [PMID: 31782975 DOI: 10.1111/bcp.14188] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2018] [Revised: 11/02/2019] [Accepted: 11/10/2019] [Indexed: 12/22/2022] Open
Abstract
AIMS This study assessed the cost-effectiveness of long-acting insulin analogues (LAIAs) vs intermediate/long-acting human insulin (ILAHI) for patients with type 1 diabetes (T1D) in real-world clinical practice. METHODS Individual-level analyses were conducted within a longitudinal population-based cohort of 540 propensity score-matched T1D patients (LAIAs, n = 270; ILAHI, n = 270) with over 10 years of follow-up using Taiwan's National Health Insurance Research Database, 2004-2013, from third-party payer and healthcare sector perspectives. The study outcomes included the number needed to treat (NNT) to prevent one case of clinical events (eg, hypoglycaemia, diabetes-related complications), medical costs, and cost per case of events prevented. Cost estimates are presented in 2013 British pounds (GBP, £). RESULTS The NNTs using LAIAs vs ILAHI to avoid one case of hypoglycaemia requiring medical assistance, outpatient hypoglycaemia and any diabetes-related complications were 12, 9 and 10 for mean follow-up periods of 5.84, 6.02 and 3.62 years, respectively. From third-party payer and healthcare sector perspectives, using LAIAs instead of ILAHI saved GBP6924-GBP7116 per case of hypoglycaemia requiring medical assistance prevented, GBP5346-GBP5508 per case of outpatient hypoglycaemia prevented, and GBP3570-GBP3680 per case of any diabetes-related complications prevented. Sensitivity analyses considering sampling uncertainty showed that using LAIAs over ILAHI yields at least a 76% probability of cost-saving for avoiding one case of hypoglycaemia requiring medical assistance, outpatient hypoglycaemia or any diabetes-related complications. CONCLUSIONS This real-world evidence reveals that compared with ILAHI, the greater pharmaceutical costs associated with LAIAs for patients with T1D could be substantially offset by savings from averted hypoglycaemia or diabetes-related complications.
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Affiliation(s)
- Tsung-Ying Lee
- School of Pharmacy, Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Shihchen Kuo
- Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
| | - Chen-Yi Yang
- School of Pharmacy, Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Huang-Tz Ou
- School of Pharmacy, Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan
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29
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Abstract
The American Diabetes Association (ADA) “Standards of Medical Care in Diabetes” includes the ADA’s current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee (https://doi.org/10.2337/dc20-SPPC), are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA’s clinical practice recommendations, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc20-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.
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Chan JCN, Lim LL, Luk AOY, Ozaki R, Kong APS, Ma RCW, So WY, Lo SV. From Hong Kong Diabetes Register to JADE Program to RAMP-DM for Data-Driven Actions. Diabetes Care 2019; 42:2022-2031. [PMID: 31530658 DOI: 10.2337/dci19-0003] [Citation(s) in RCA: 77] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2019] [Accepted: 08/14/2019] [Indexed: 02/03/2023]
Abstract
In 1995, the Hong Kong Diabetes Register (HKDR) was established by a doctor-nurse team at a university-affiliated, publicly funded, hospital-based diabetes center using a structured protocol for gathering data to stratify risk, triage care, empower patients, and individualize treatment. This research-driven quality improvement program has motivated the introduction of a territory-wide diabetes risk assessment and management program provided by 18 hospital-based diabetes centers since 2000. By linking the data-rich HKDR to the territory-wide electronic medical record, risk equations were developed and validated to predict clinical outcomes. In 2007, the HKDR protocol was digitalized to establish the web-based Joint Asia Diabetes Evaluation (JADE) Program complete with risk levels and algorithms for issuance of personalized reports to reduce clinical inertia and empower self-management. Through this technologically assisted, integrated diabetes care program, we have generated big data to track secular trends, identify unmet needs, and verify interventions in a naturalistic environment. In 2009, the JADE Program was adapted to form the Risk Assessment and Management Program for Diabetes Mellitus (RAMP-DM) in the publicly funded primary care clinics, which reduced all major events by 30-60% in patients without complications. Meanwhile, a JADE-assisted assessment and empowerment program provided by a university-affiliated, self-funded, nurse-coordinated diabetes center, aimed at complementing medical care in the community, also reduced all major events by 30-50% in patients with different risk levels. By combining universal health coverage, public-private partnerships, and data-driven integrated care, the Hong Kong experience provides a possible solution than can be adapted elsewhere to make quality diabetes care accessible, affordable, and sustainable.
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Affiliation(s)
- Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China .,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Asia Diabetes Foundation, Hong Kong SAR, China
| | - Lee-Ling Lim
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Asia Diabetes Foundation, Hong Kong SAR, China.,Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Andrea O Y Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Asia Diabetes Foundation, Hong Kong SAR, China
| | - Risa Ozaki
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Alice P S Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Wing-Yee So
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.,Hospital Authority, Hong Kong SAR, China
| | - Su-Vui Lo
- Hospital Authority, Hong Kong SAR, China
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Riddle MC, Blonde L, Gerstein HC, Gregg EW, Holman RR, Lachin JM, Nichols GA, Turchin A, Cefalu WT. Diabetes Care Editors' Expert Forum 2018: Managing Big Data for Diabetes Research and Care. Diabetes Care 2019; 42:1136-1146. [PMID: 31666233 DOI: 10.2337/dci19-0020] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Accepted: 03/20/2019] [Indexed: 02/03/2023]
Abstract
Technological progress in the past half century has greatly increased our ability to collect, store, and transmit vast quantities of information, giving rise to the term "big data." This term refers to very large data sets that can be analyzed to identify patterns, trends, and associations. In medicine-including diabetes care and research-big data come from three main sources: electronic medical records (EMRs), surveys and registries, and randomized controlled trials (RCTs). These systems have evolved in different ways, each with strengths and limitations. EMRs continuously accumulate information about patients and make it readily accessible but are limited by missing data or data that are not quality assured. Because EMRs vary in structure and management, comparisons of data between health systems may be difficult. Registries and surveys provide data that are consistently collected and representative of broad populations but are limited in scope and may be updated only intermittently. RCT databases excel in the specificity, completeness, and accuracy of their data, but rarely include a fully representative sample of the general population. Also, they are costly to build and seldom maintained after a trial's end. To consider these issues, and the challenges and opportunities they present, the editors of Diabetes Care convened a group of experts in management of diabetes-related data on 21 June 2018, in conjunction with the American Diabetes Association's 78th Scientific Sessions in Orlando, FL. This article summarizes the discussion and conclusions of that forum, offering a vision of benefits that might be realized from prospectively designed and unified data-management systems to support the collective needs of clinical, surveillance, and research activities related to diabetes.
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Affiliation(s)
- Matthew C Riddle
- Division of Endocrinology, Diabetes & Clinical Nutrition, Oregon Health & Science University, Portland, OR
| | - Lawrence Blonde
- Ochsner Diabetes Clinical Research Unit, Frank Riddick Diabetes Institute, Department of Endocrinology, Ochsner Medical Center, New Orleans, LA
| | - Hertzel C Gerstein
- McMaster University and Hamilton Health Sciences, Hamilton, Ontario, Canada
| | | | - Rury R Holman
- Diabetes Trial Unit, Radcliffe Department of Medicine, University of Oxford, Oxford, U.K
| | - John M Lachin
- The George Washington University Biostatistics Center, Rockville, MD
| | - Gregory A Nichols
- Center for Health Research, Kaiser Permanente Northwest, Portland, OR
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Jiao F, Wan EYF, Fung CSC, Chan AKC, McGhee SM, Kwok RLP, Lam CLK. Cost-effectiveness of a primary care multidisciplinary Risk Assessment and Management Program for patients with diabetes mellitus (RAMP-DM) over lifetime. Endocrine 2019; 63:259-269. [PMID: 30155847 DOI: 10.1007/s12020-018-1727-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2018] [Accepted: 08/14/2018] [Indexed: 11/24/2022]
Abstract
PURPOSE The multidisciplinary Risk Assessment and Management Program for patients with diabetes mellitus (RAMP-DM) was found to be cost-saving in comparison with usual primary care over 5 years' follow-up. This study aimed to estimate the cost-effectiveness of RAMP-DM over lifetime. METHODS We built a Discrete Event Simulation model to evaluate the cost-effectiveness of RAMP-DM over lifespan from public health service provider's perspective. Transition probabilities among disease states were extrapolated from a cohort of 17,140 propensity score matched participants in RAMP-DM and those under usual primary care over 5-year's follow-up. The mortality of patients with specific DM-related complications was estimated from a cohort of 206,238 patients with diabetes. Health preference and direct medical costs of DM patients referred to our previous studies among Chinese DM patients. RESULTS RAMP-DM individuals gained 0.745 QALYs and cost US$1404 less than those under usual care. The probabilistic sensitivity analysis found that RAMP-DM had 86.0% chance of being cost-saving compared to usual care under the assumptions and estimates used in the model. The probability of RAMP-DM being cost-effective compared to usual care would be over 99%, when the willingness to pay threshold is HK$20,000 (US$ 2564) or higher. CONCLUSION RAMP-DM added to usual primary care was cost-saving in managing people with diabetes over lifetime. These findings support the integration of RAMP-DM as part of routine primary care for all patients with diabetes.
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Affiliation(s)
- Fangfang Jiao
- Department of Family Medicine and Primary Care, The University of Hong Kong, 3/F., 161 Main Street, Ap Lei Chau Clinic, Ap Lei Chau, Hong Kong, Hong Kong
| | - Eric Yuk Fai Wan
- Department of Family Medicine and Primary Care, The University of Hong Kong, 3/F., 161 Main Street, Ap Lei Chau Clinic, Ap Lei Chau, Hong Kong, Hong Kong.
| | - Colman Siu Cheung Fung
- Department of Family Medicine and Primary Care, The University of Hong Kong, 3/F., 161 Main Street, Ap Lei Chau Clinic, Ap Lei Chau, Hong Kong, Hong Kong
| | - Anca Ka Chun Chan
- Department of Family Medicine and Primary Care, The University of Hong Kong, 3/F., 161 Main Street, Ap Lei Chau Clinic, Ap Lei Chau, Hong Kong, Hong Kong
| | - Sarah Morag McGhee
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, 5/F, William MW Mong Block, 21 Sassoon Road, Hong Kong, Hong Kong
| | - Ruby Lai Ping Kwok
- Primary and Community Services, Hospital Authority Head Office, Hong Kong Hospital Authority, Hospital Authority Building, 147B Argyle Street, Kowloon, Hong Kong, Hong Kong
| | - Cindy Lo Kuen Lam
- Department of Family Medicine and Primary Care, The University of Hong Kong, 3/F., 161 Main Street, Ap Lei Chau Clinic, Ap Lei Chau, Hong Kong, Hong Kong
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Abstract
PURPOSE OF REVIEW Formalized chronic care management has the potential to improve the quality and cost-effectiveness of complex diabetes management in adults, but has historically not been sustainably supported by health care systems. This review discusses the application of the chronic care model in the care of complex diabetes and its translation in the current reimbursement structure designed by Centers for Medicare and Medicaid Services (CMS). RECENT FINDINGS Following the introduction of Wagner's Chronic Care Model (CCM) in the late 1990s, evidence gathered over the past 2 decades has supported the shift in focus of health care systems from acute to chronic disease management and proactive care. Acknowledging evidence and potential for improved cost-effectiveness, in 2015, Medicare began reimbursing for chronic care management services (CCMS) for patients with multiple chronic conditions. The CCMS billing codes allow a program to be reimbursed for up to 90 min per month spent by clinical staff performing interim care within a comprehensive care plan. Recent data from local and global programs support the application of formalized CCM in diabetes management. Although reimbursement models for CCM have been designed for use in primary care, the challenges of the reimbursement model has opened the door for specialty areas focused on multimorbidity care such as diabetes care to explore this approach. With the broader availability of remote glucose monitoring and telemedicine, a strategy that combines goal-oriented care and telehealth solutions appears to be most effective in diabetes CCM care. Despite widespread acceptance of the chronic care model of care, there remain significant barriers to its incorporation into standard practice.
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Affiliation(s)
- Kayla L Del Valle
- Brigham and Women's Hospital, Division of Endocrinology, Harvard Medical School, 221 Longwood Avenue, Suite 381, Boston, MA, 02115, USA
| | - Marie E McDonnell
- Brigham and Women's Hospital, Division of Endocrinology, Harvard Medical School, 221 Longwood Avenue, Suite 381, Boston, MA, 02115, USA.
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Wong CKH, Jiao F, Tang EHM, Tong T, Thokala P, Lam CLK. Direct medical costs of diabetes mellitus in the year of mortality and year preceding the year of mortality. Diabetes Obes Metab 2018; 20:1470-1478. [PMID: 29430799 DOI: 10.1111/dom.13253] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Revised: 01/25/2018] [Accepted: 02/07/2018] [Indexed: 01/04/2023]
Abstract
AIM To report the health resource use and estimate the direct medical costs among patients with diabetes mellitus (DM) in the year of mortality and the year preceding the year of mortality. MATERIALS AND METHODS We analysed data from a population-based, retrospective cohort study including all adults with a DM diagnosis in Hong Kong between 2009 and 2013, and who died between January 1, 2010 and December 31, 2013. The annual direct medical costs in the year of mortality and the year preceding the year of mortality were determined by summing the costs of health services utilized within the respective year. The costs were analysed by gender, the presence of comorbidities, diabetic complications and primary cause of death. RESULTS A total of 10 649 patients met the eligibility criteria for analysis. On average, the direct medical costs in the year of death were 1.947 times higher than those in the year before death. Men and women with DM incurred similar costs in the year preceding the year of mortality and in the mortality year. Patients with any diabetic complications incurred greater costs in the year of mortality and the year before mortality than those without. CONCLUSIONS This analysis provides new evidence on incorporating additional direct medical costs in the mortality year, and refining the structure of total cost estimates for use in costing and cost-effectiveness analyses of interventions for DM.
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Affiliation(s)
- Carlos K H Wong
- Department of Family Medicine and Primary Care, University of Hong Kong, Hong Kong
| | - Fangfang Jiao
- Department of Family Medicine and Primary Care, University of Hong Kong, Hong Kong
| | - Eric H M Tang
- Department of Family Medicine and Primary Care, University of Hong Kong, Hong Kong
| | - Thaison Tong
- Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Sheffield, UK
| | - Praveen Thokala
- Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Sheffield, UK
| | - Cindy L K Lam
- Department of Family Medicine and Primary Care, University of Hong Kong, Hong Kong
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Affiliation(s)
- Matthew C Riddle
- Division of Endocrinology, Diabetes & Clinical Nutrition, Oregon Health & Science University, Portland, OR
| | - William H Herman
- University of Michigan Schools of Medicine and Public Health, Ann Arbor, MI
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Ng IHY, Cheung KKT, Yau TTL, Chow E, Ozaki R, Chan JCN. Evolution of Diabetes Care in Hong Kong: From the Hong Kong Diabetes Register to JADE-PEARL Program to RAMP and PEP Program. Endocrinol Metab (Seoul) 2018; 33:17-32. [PMID: 29589385 PMCID: PMC5874192 DOI: 10.3803/enm.2018.33.1.17] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2018] [Revised: 02/26/2018] [Accepted: 02/28/2018] [Indexed: 12/14/2022] Open
Abstract
The rapid increase in diabetes prevalence globally has contributed to large increases in health care expenditure on diabetic complications, posing a major health burden to countries worldwide. Asians are commonly observed to have poorer β-cell function and greater insulin resistance compared to the Caucasian population, which is attributed by their lower lean body mass and central obesity. This "double phenotype" as well as the rising prevalence of young onset diabetes in Asia has placed Asians with diabetes at high risk of cardiovascular and renal complications, with cancer emerging as an important cause of morbidity and mortality. The experience from Hong Kong had demonstrated that a multifaceted approach, involving team-based integrated care, information technological advances, and patient empowerment programs were able to reduce the incidence of diabetic complications, hospitalizations, and mortality. System change and public policies to enhance implementation of such programs may provide solutions to combat the burgeoning health problem of diabetes at a societal level.
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Affiliation(s)
- Ivy H Y Ng
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Sha Tin, Hong Kong
- Department of Medicine and Geriatrics, United Christian Hospital, Kwun Tong, Hong Kong
| | - Kitty K T Cheung
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Sha Tin, Hong Kong
| | - Tiffany T L Yau
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Sha Tin, Hong Kong
| | - Elaine Chow
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Sha Tin, Hong Kong
| | - Risa Ozaki
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Sha Tin, Hong Kong
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Sha Tin, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, Prince of Wales Hospital, The Chinese University of Hong Kong, Sha Tin, Hong Kong.
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