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Ortega E, Redondo-Antón J, Díaz-Cerezo S, Rubio-de Santos M, Romera I. Glycaemic and Weight Control in People Aged 65 or Younger Newly Diagnosed with Type 2 Diabetes in Spain: Insights from the PRIORITY-T2D Study. Adv Ther 2025:10.1007/s12325-025-03230-7. [PMID: 40388088 DOI: 10.1007/s12325-025-03230-7] [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: 02/25/2025] [Accepted: 04/30/2025] [Indexed: 05/20/2025]
Abstract
INTRODUCTION The objective of this study was to determine the number of people within glycated haemoglobin (HbA1c) targets and achieving weight-loss goals during the first 5 years after type 2 diabetes (T2D) diagnosis and to explore the relationship between early weight loss and glycaemic control in routine care in Spain. METHODS This was an observational retrospective study using IQVIA's electronic medical record database, including adults aged ≤ 65 years newly diagnosed with T2D. Variables included baseline sociodemographic/clinical characteristics, yearly HbA1c and weight data, and treatment patterns. Descriptive statistics and regression analyses were used. RESULTS A total of 8973 people with T2D were included (mean age 53 years; mean baseline HbA1c 7.7%; obesity at diagnosis: 64%). During the first 5 years post-T2D diagnosis, 46-63% of the population did not have HbA1c < 6.5%, and > 60%, and > 80% of subjects did not achieve ≥ 5% and ≥ 10% weight loss, respectively. Early weight loss goal achievement (1st year after diagnosis) and weight loss magnitude were associated with a higher percentage of people with HbA1c < 6.5%. CONCLUSIONS Many individuals with T2D did not have HbA1c < 6.5% in the first 5 years after diagnosis and did not achieve ≥ 5% or ≥ 10% weight loss. Early weight loss after T2D diagnosis was associated with higher likelihood of achieving early glycaemic control.
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Affiliation(s)
- Emilio Ortega
- Diabetes Unit, Department of Endocrinology and Nutrition, Hospital Clínic, C. de Villarroel, 170, L'Eixample, 08036, Barcelona, Spain
- Centro de Investigación Biomédica en Red de la Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Monforte de Lemos, 3-5, 28029, Madrid, Spain
- Institut d'Investigacions, Hospital Clínic, Biomèdiques August Pi i Sunyer, C. de Villarroel, 170, L'Eixample, 08036, Barcelona, Spain
| | | | - Silvia Díaz-Cerezo
- Eli Lilly and Company, Av. de la Industria, 30, Alcobendas, 28108, Madrid, Spain
| | | | - Irene Romera
- Eli Lilly and Company, Av. de la Industria, 30, Alcobendas, 28108, Madrid, Spain.
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Sasidharan S, Nair A K, R L, Nair AV, SA S, Joseph SG, Chand CP A, Satheesan S, Pratap A, Kumar S N, Paul J, Nair V V, R V, Nair J H. A randomized multi-arm open labelled comparative clinical trial report of Pankajakasthuri DiabetEaze powder, a novel polyherbal formulation on the nutritional management and glycemic control in type 2 diabetic and prediabetic patients. Heliyon 2025; 11:e42631. [PMID: 40083990 PMCID: PMC11903805 DOI: 10.1016/j.heliyon.2025.e42631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2024] [Revised: 02/05/2025] [Accepted: 02/10/2025] [Indexed: 03/16/2025] Open
Abstract
Background and aims Recently Diabetes Mellitus (DM) has been associated with heightened susceptibility to malnutrition, suggesting that augmenting nutritional intake stands out as a potent therapeutic strategy for addressing malnutrition in individuals with DM. The aim of this clinical investigation was to evaluate the effect of DiabetEaze powder, a polyherbal nutritional formulation developed by us for nutritional management and glycaemic control, on patients with diabetic and prediabetic conditions. Methods A total of 143 type II diabetic (T2D) patients who were managing their diabetic condition through modern medicine, AYUSH medicine, lifestyle modification and 68 pre-diabetic patients, aged between 40 and 65 years, were randomly assigned into six groups: control, modern, AYUSH, lifestyle, prediabetic control and prediabetic trial. The treatment groups were administered 5 g of DiabetEaze powder two times a day after food for 6 months. Microminerals, vitamins, glycaemic parameters, Quality of Life (QoL), hematology, lipid profiles, Renal Function Test (RFT) and Liver Function Test (LFL) parameters, and electrolytes were evaluated at Day 0, Day 90, and Day 180. Results Out of 211 enrolled patients, 189 individuals successfully completed the entire 180-day duration of the study, indicating a retention rate of approximately 89.6 %. In our study, we observed a statistically significant elevation in the levels of vitamin D, B2, and B6 across all treatment groups. Besides, the treatment groups displayed a notable increase in zinc and manganese levels compared to the other minerals tested. Notably, the treatment groups demonstrated distinct mineral and vitamin profiles. In terms of metabolic markers, significant reductions in Fasting Blood Sugar (FBS)/Post Prandial Blood Sugar (PPBS) were observed across the modern, AYUSH, and lifestyle groups, while the modern group also showed a marked decrease in glycated haemoglobin (HbA1c) levels. Furthermore, overall QoL among the tested groups was also statistically significant. The consistent maintenance of normal LFT and RFT parameters and electrolyte levels across trial groups throughout the study duration indicates that the supplement does not induce liver toxicity or negatively impact hepatic function. Conclusion In conclusion, the nutrients present in the DiabetEaze powder contribute to the effective management of nutritional status in diabetic people and thus effectively reduce sugar spikes by regulating PPBS and HbA1c levels, which is a critical aspect of its role in diabetes management. These properties benefit in managing diabetes-related outcomes and overall quality of life. Clinical trial registry of India under registration no CTRI/2021/04/032956 on 20/04/2021.
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Affiliation(s)
- Shan Sasidharan
- HCEMM-SU Cardiovascular Comorbidities Research Group, Department of Pharmacology and Pharmacotherapy, Semmelweis University, 1089, Budapest, Hungary
- Department of R&D, Pankajakasthuri Herbal Research Foundation, Pankajakasthuri Ayurveda Medical College Campus, Trivandrum, India
| | - Kasthuri Nair A
- Department of Kayachikitsa, Pankajakasthuri Ayurveda Medical College & PG Centre, Killy, Kattakada, Thiruvananthapuram, Kerala, India
| | - Lekshmi R
- Department of Kayachikitsa, Pankajakasthuri Ayurveda Medical College & PG Centre, Killy, Kattakada, Thiruvananthapuram, Kerala, India
| | - Arun Visakh Nair
- Pankajakasthuri Herbals India Pvt. Ltd., Poovachal, Trivandrum, India
| | - Sajna SA
- Department of Rasashastra & Bhaishajya Kalpana, Pankajakasthuri Ayurveda Medical College & P.G. Centre, Killy, Kattakada, Thiruvananthapuram, Kerala, India
| | - Sandhu G. Joseph
- Department of Dravyagunavijnanam, Pankajakasthuri Ayurveda Medical College & P.G. Centre, Killy, Kattakada, Thiruvananthapuram, Kerala, India
| | - Arjun Chand CP
- Department of Kayachikitsa, Pankajakasthuri Ayurveda Medical College & PG Centre, Killy, Kattakada, Thiruvananthapuram, Kerala, India
| | - Sreejith Satheesan
- Department of Shalyatantra, Pankajakasthuri Ayurveda Medical College & PG Centre, Killy, Kattakada, Thiruvananthapuram, Kerala, India
| | - Arun Pratap
- Department of Kayachikitsa, Pankajakasthuri Ayurveda Medical College & PG Centre, Killy, Kattakada, Thiruvananthapuram, Kerala, India
| | - Nishanth Kumar S
- Department of R&D, Pankajakasthuri Herbal Research Foundation, Pankajakasthuri Ayurveda Medical College Campus, Trivandrum, India
| | - Jerin Paul
- Department of Statistics, Vimala College (Autonomous), Thrissur, Kerala, 680009, India
| | - Vipin Nair V
- Neyyar Medicity, Killy, Kattakada, Thiruvananthapuram, Kerala, India
| | - Vijaya R
- Department of Dravyagunavijnanam, Pankajakasthuri Ayurveda Medical College & P.G. Centre, Killy, Kattakada, Thiruvananthapuram, Kerala, India
| | - Hareendran Nair J
- Pankajakasthuri Herbals India Pvt. Ltd., Poovachal, Trivandrum, India
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Zheng M, Begum M, Bernardo CDO, Stocks N, Gonzalez-Chica D. Comparing the Effect of Early Versus Delayed Metformin Treatment on Glycaemic Parameters Among Australian Adults With Incident Diabetes: Evidence Using a National General Practice Database. Clin Ther 2024; 46:396-403. [PMID: 38565499 DOI: 10.1016/j.clinthera.2024.03.001] [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: 11/04/2023] [Revised: 02/18/2024] [Accepted: 03/05/2024] [Indexed: 04/04/2024]
Abstract
PURPOSE To compare the effect of early vs delayed metformin treatment for glycaemic management among patients with incident diabetes. METHODS Cohort study using electronic health records of regular patients (1+ visits per year in 3 consecutive years) aged 40+ years with 'incident' diabetes attending Australian general practices (MedicineInsight, 2011-2018). Patients with incident diabetes were defined as those who had a) 12+ months of medical data before the first recording of a diabetes diagnosis AND b) a diagnosis of 'diabetes' recorded at least twice in their electronic medical records or a diagnosis of 'diabetes' recorded only once combined with at least 1 abnormal glycaemic result (i.e., HbA1c ≥6.5%, fasting blood glucose [FBG] ≥7.0 mmol/L, or oral glucose tolerance test ≥11.1mmol/L) in the preceding 3 months. The effect of early (<3 months), timely (3-6 months), or delayed (6-12 months) initiation of metformin treatment vs no metformin treatment within 12 months of diagnosis on HbA1c and FBG levels 3 to 24 months after diagnosis was compared using linear regression and augmented inverse probability weighted models. Patients initially managed with other antidiabetic medications (alone or combined with metformin) were excluded. FINDINGS Of 18,856 patients with incident diabetes, 38.8% were prescribed metformin within 3 months, 3.9% between 3 and 6 months, and 6.2% between 6 and 12 months after diagnosis. The untreated group had the lowest baseline parameters (mean HbA1c 6.4%; FBG 6.9mmol/L) and maintained steady levels throughout follow-up. Baseline glycaemic parameters for those on early treatment with metformin (<3 months since diagnosis) were the highest among all groups (mean HbA1c 7.6%; FBG 8.8mmol/L), reaching controlled levels at 3 to 6 months (mean HbA1c 6.5%; FBG 6.9mmol/L) with sustained improvement until the end of follow-up (mean HbA1c 6.4%; FBG 6.9mmol/L at 18-24 months). Patients with timely and delayed treatment also improved their glycaemic parameters after initiating treatment (timely treatment: mean HbA1c 7.3% and FBG 8.3mmol/L at 3-6 months; 6.6% and 6.9mmol/L at 6-12 months; delayed treatment: mean HbA1c 7.2% and FBG 8.4mmol/L at 6-12 months; 6.7% and 7.1mmol/L at 12-18 months). Compared to those not managed with metformin, the corresponding average treatment effect for HbA1c at 18-24 months was +0.04% (95%CI -0.05;0.10) for early, +0.24% (95%CI 0.11;0.37) for timely, and +0.29% (95%CI 0.20;0.39) for delayed treatment. IMPLICATIONS Early metformin therapy (<3 months) for patients recently diagnosed with diabetes consistently improved HbA1c and FBG levels in the first 24 months of diagnosis.
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Affiliation(s)
- Mingyue Zheng
- Discipline of General Practice, Adelaide Medical School, University of Adelaide, Adelaide, Australia
| | - Mumtaz Begum
- Discipline of General Practice, Adelaide Medical School, University of Adelaide, Adelaide, Australia
| | | | - Nigel Stocks
- Discipline of General Practice, Adelaide Medical School, University of Adelaide, Adelaide, Australia
| | - David Gonzalez-Chica
- Discipline of General Practice, Adelaide Medical School, University of Adelaide, Adelaide, Australia; Adelaide Rural Clinical School, University of Adelaide, Adelaide, Australia.
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Ahmad A, Lim LL, Morieri ML, Tam CHT, Cheng F, Chikowore T, Dudenhöffer-Pfeifer M, Fitipaldi H, Huang C, Kanbour S, Sarkar S, Koivula RW, Motala AA, Tye SC, Yu G, Zhang Y, Provenzano M, Sherifali D, de Souza RJ, Tobias DK, Gomez MF, Ma RCW, Mathioudakis N. Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis. COMMUNICATIONS MEDICINE 2024; 4:11. [PMID: 38253823 PMCID: PMC10803333 DOI: 10.1038/s43856-023-00429-z] [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: 05/12/2023] [Accepted: 12/14/2023] [Indexed: 01/24/2024] Open
Abstract
BACKGROUND Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with Type 2 diabetes (T2D). METHODS We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies. RESULTS Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort. CONCLUSIONS Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.
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Affiliation(s)
- Abrar Ahmad
- Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden
| | - 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, Hong Kong SAR, China
- Asia Diabetes Foundation, Hong Kong SAR, China
| | - Mario Luca Morieri
- Metabolic Disease Unit, University Hospital of Padova, Padova, Italy
- Department of Medicine, University of Padova, Padova, Italy
| | - Claudia Ha-Ting Tam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Feifei Cheng
- Health Management Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing Medical University, Chongqing, China
| | - Tinashe Chikowore
- MRC/Wits Developmental Pathways for Health Research Unit, Department of Paediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | | | - Hugo Fitipaldi
- Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden
| | - Chuiguo Huang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China
| | | | - Sudipa Sarkar
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Robert Wilhelm Koivula
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom
| | - Ayesha A Motala
- Department of Diabetes and Endocrinology, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Sok Cin Tye
- Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, Groningen, the Netherlands
- Sections on Genetics and Epidemiology, Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Gechang Yu
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Yingchai Zhang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Michele Provenzano
- Nephrology, Dialysis and Renal Transplant Unit, IRCCS-Azienda Ospedaliero-Universitaria di Bologna, Alma Mater Studiorum University of Bologna, Bologna, Italy
| | - Diana Sherifali
- Heather M. Arthur Population Health Research Institute, McMaster University, Ontario, Canada
| | - Russell J de Souza
- Department of Health Research Methods, Evidence, and Impact, Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada
- Population Health Research Institute, Hamilton Health Sciences Corporation, Hamilton, Ontario, Canada
| | | | - Maria F Gomez
- Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden.
- Faculty of Health, Aarhus University, Aarhus, Denmark.
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China.
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China.
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China.
| | - Nestoras Mathioudakis
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
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Ahmad A, Lim LL, Morieri ML, Tam CHT, Cheng F, Chikowore T, Dudenhöffer-Pfeifer M, Fitipaldi H, Huang C, Kanbour S, Sarkar S, Koivula RW, Motala AA, Tye SC, Yu G, Zhang Y, Provenzano M, Sherifali D, de Souza R, Tobias DK, Gomez MF, Ma RCW, Mathioudakis NN. Precision Prognostics for Cardiovascular Disease in Type 2 Diabetes: A Systematic Review and Meta-analysis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.26.23289177. [PMID: 37162891 PMCID: PMC10168509 DOI: 10.1101/2023.04.26.23289177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Background Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with type 2 diabetes (T2D). Methods We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies. Results Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort. Conclusions Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.
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Wong R, Vaddavalli R, Hall MA, Patel MV, Bramante CT, Casarighi E, Johnson SG, Lingam V, Miller JD, Reusch J, Saltz M, Stürmer T, Tronieri JS, Wilkins KJ, Buse JB, Saltz J, Huling JD, Moffitt R. Effect of SARS-CoV-2 Infection and Infection Severity on Longer-Term Glycemic Control and Weight in People With Type 2 Diabetes. Diabetes Care 2022; 45:2709-2717. [PMID: 36098660 PMCID: PMC9679257 DOI: 10.2337/dc22-0730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 07/16/2022] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To evaluate the association of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and severity of infection with longer-term glycemic control and weight in people with type 2 diabetes (T2D) in the U.S. RESEARCH DESIGN AND METHODS We conducted a retrospective cohort study using longitudinal electronic health record data of patients with SARS-CoV-2 infection from the National COVID Cohort Collaborative (N3C). Patients were ≥18 years old with an ICD-10 diagnosis of T2D and at least one HbA1c and weight measurement prior to and after an index date of their first coronavirus disease 2019 (COVID-19) diagnosis or negative SARS-CoV-2 test. We used propensity scores to identify a matched cohort balanced on demographic characteristics, comorbidities, and medications used to treat diabetes. The primary outcome was the postindex average HbA1c and postindex average weight over a 1 year time period beginning 90 days after the index date among patients who did and did not have SARS-CoV-2 infection. Secondary outcomes were postindex average HbA1c and weight in patients who required hospitalization or mechanical ventilation. RESULTS There was no significant difference in the postindex average HbA1c or weight in patients who had SARS-CoV-2 infection compared with control subjects. Mechanical ventilation was associated with a decrease in average HbA1c after COVID-19. CONCLUSIONS In a multicenter cohort of patients in the U.S. with preexisting T2D, there was no significant change in longer-term average HbA1c or weight among patients who had COVID-19. Mechanical ventilation was associated with a decrease in HbA1c after COVID-19.
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Affiliation(s)
- Rachel Wong
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY
| | - Rohith Vaddavalli
- Department of Computer Science, Stony Brook University, Stony Brook, NY
| | - Margaret A. Hall
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY
| | - Monil V. Patel
- Department of Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY
| | - Carolyn T. Bramante
- Division of General Internal Medicine, University of Minnesota Medical School, Minneapolis, MN
| | - Elena Casarighi
- AnacletoLab, Department of Computer Science “Giovanni degli Antoni,” Università degli Studi di Milano, Milan, Italy
- CINI, Infolife National Laboratory, Roma, Italy
| | - Steven G. Johnson
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN
| | - Veena Lingam
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY
| | - Joshua D. Miller
- Division of Endocrinology and Metabolism, Department of Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY
| | - Jane Reusch
- Division of Endocrinology, Metabolism & Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Mary Saltz
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY
| | - Til Stürmer
- Department of Epidemiology, University of North Carolina at Chapel Hill Gillings School of Global Public Health, Chapel Hill, NC
| | - Jena S. Tronieri
- Department of Psychiatry, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - Kenneth J. Wilkins
- Office of the Director, Biostatistics Program/Office of Clinical Research Support, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD
| | - John B. Buse
- Division of Endocrinology and Metabolism, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC
- North Carolina Translational and Clinical Sciences Institute, University of North Carolina School of Medicine, Chapel Hill, NC
| | - Joel Saltz
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY
| | - Jared D. Huling
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN
| | - Richard Moffitt
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY
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Daly MJ, Elvidge J, Chantler T, Dawoud D. A Review of Economic Models Submitted to NICE's Technology Appraisal Programme, for Treatments of T1DM & T2DM. Front Pharmacol 2022; 13:887298. [PMID: 35645790 PMCID: PMC9130744 DOI: 10.3389/fphar.2022.887298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 04/12/2022] [Indexed: 11/20/2022] Open
Abstract
Background: In the UK, 4.7 million people are currently living with diabetes. This is projected to increase to 5 million by 2025. The direct and indirect costs of T1DM and T2DM are rising, and direct costs already account for approximately 10% of the National Health Service (NHS) budget. Objective: The aim of this review is to assess the economic models used in the context of NICE’s Technology Appraisals (TA) Programme of T1DM and T2DM treatments, as well as to examine their compliance with the American Diabetes Association’s (ADA) guidelines on computer modelling. Methods: A review of the economic models used in NICE’s TA programme of T1DM and T2DM treatments was undertaken. Relevant TAs were identified through searching the NICE website for published appraisals completed up to April 2021. The review also examined the associated Evidence Review Group (ERG) reports and Final Appraisal Documents (FAD), which are publicly accessible. ERG reports were scrutinised to identify major issues pertaining to the economic modelling. The FAD documents were then examined to assess how these issues reflected on NICE recommendations. Results: Overall, 10 TAs pertaining to treatments of T1DM and T2DM were identified. Two TAs were excluded as they did not use economic models. Seven of the 8 included TAs related to a novel class of oral antidiabetic drugs (OADs), gliflozins, and one to continuous subcutaneous insulin infusion (CSII) devices. There is a lack of recent, robust data informing risk equations to enable the derivation of transition probabilities. Despite uncertainty surrounding its clinical relevance, bodyweight/BMI is a key driver in many T2DM-models. HbA1c’s reliability as a predictor of hard outcomes is uncertain, chiefly for macrovascular complications. The external validity of T1DM is even less clear. There is an inevitable trade-off between the sophistication of models’ design, their transparency and practicality. Conclusion: Economic models are essential tools to support decision-making in relation to market access and ascertain diabetes technologies’ cost effectiveness. However, key structural and methodological issues exist. Models’ shortcomings should be acknowledged and contextualised within the framework of technology appraisals. Diabetes medications and other technologies should also be subject to regular and consistent re-appraisal to inform disinvestment decisions. Artificial intelligence could potentially enhance models’ transparency and practicality.
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Affiliation(s)
- Marie-Josée Daly
- Division of Anesthesiology, Department of Anesthesiology, Pharmacology, Intensive Care and Emergency Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Jamie Elvidge
- National Institute for Health and Care Excellence (NICE), London, United Kingdom
| | - Tracey Chantler
- London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Dalia Dawoud
- National Institute for Health and Care Excellence (NICE), London, United Kingdom.,Faculty of Pharmacy, Cairo University, Giza, Egypt
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Heald A, Stedman M, Robinson A, Davies M, Livingston M, Alshames R, Moreno G, Gadsby R, Rayman G, Gibson M, de Lusignan S, Whyte M. Mortality Rate Associated with Diabetes: Outcomes From a General Practice Level Analysis in England Using the Royal College of General Practitioners (RCGP) Database Indicate Stability Over a 15 Year Period. Diabetes Ther 2022; 13:505-516. [PMID: 35187627 PMCID: PMC8934837 DOI: 10.1007/s13300-022-01215-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Accepted: 01/28/2022] [Indexed: 12/04/2022] Open
Abstract
INTRODUCTION Total population mortality rates have been falling and life expectancy increasing for more than 30 years. Diabetes remains a significant risk factor for premature death. Here we used the Oxford Royal College of General Practitioners Research and Surveillance Centre (RCGP RSC) practices to determine diabetes-related vs non-diabetes-related mortality rates. METHODS RCGP RSC data were provided on annual patient numbers and deaths, at practice level, for those with and without diabetes across four age groups (< 50, 50-64, 65-79, ≥ 80 years) over 15 years. Investment in diabetes control, as measured by the cost of primary care medication, was also taken from GP prescribing data. RESULTS We included 527 general practices. Over the period 2004-2019, there was no significant change in life years lost, which varied between 4.6 and 5.1 years over this period. The proportion of all diabetes deaths by age band was significantly higher in the 65-79 years age group for men and women with diabetes than for their non-diabetic counterparts. For the year 2019, 26.6% of deaths were of people with diabetes. Of this 26.6%, 18.5% would be expected from age group and non-diabetes status, while the other 8.1% would not have been expected-pro rata to nation, this approximates to approximately 40,000 excess deaths in people with diabetes vs the general population. CONCLUSION There remains a wide variation in mortality rate of people with diabetes between general practices in UK. The mortality rate and life years lost for people with diabetes vs non-diabetes individuals have remained stable in recent years, while mortality rates for the general population have fallen. Investment in diabetes management at a local and national level is enabling us to hold the ground regarding the life-shortening consequences of having diabetes as increasing numbers of people develop T2DM at a younger age.
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Affiliation(s)
- Adrian Heald
- The School of Medicine and Manchester Academic Health Sciences Centre, Manchester University, Manchester, UK.
- Department of Endocrinology and Diabetes, Salford Royal Hospital, Salford, M6 8HD, UK.
| | | | - Adam Robinson
- Department of Endocrinology and Diabetes, Salford Royal Hospital, Salford, M6 8HD, UK
| | | | - Mark Livingston
- Black Country Pathology Services, Walsall Manor Hospital, Walsall, UK
| | - Ramadan Alshames
- Biochemistry Department, Faculty of Dentistry, Tripoli University, Tripoli, Libya, UK
| | - Gabriela Moreno
- , Marina Nacional 162, Anáhuac Secc, Miguel Hidalgo, 11320, Mexico City, Mexico
| | - Roger Gadsby
- Warwick Medical School, University of Warwick, Warwick, UK
| | - Gerry Rayman
- The Ipswich Diabetes Centre and Research Unit, Ipswich Hospital NHS Trust, Colchester, Essex, UK
| | - Martin Gibson
- The School of Medicine and Manchester Academic Health Sciences Centre, Manchester University, Manchester, UK
- Department of Endocrinology and Diabetes, Salford Royal Hospital, Salford, M6 8HD, UK
| | - Simon de Lusignan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Martin Whyte
- Clinical and Experimental Medicine, University of Surrey, Guildford, UK
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Camargo MS, Passos LCS, Mistro S, Soares DA, Kochergin CN, de Carvalho VCHDS, Macedo JCL, Cortes TBA, de Souza AA, Rumel D, Oliveira MG. Improving Access to the Glycated Hemoglobin Test in Rural Communities With Point-of-Care Devices: An Application Study. Front Med (Lausanne) 2021; 8:734306. [PMID: 34881257 PMCID: PMC8645789 DOI: 10.3389/fmed.2021.734306] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 10/29/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Living in a rural or remote area is frequently associated with impaired access to health services, which directly affects the possibility of early diagnosis and appropriate monitoring of diseases, mainly non-communicable ones, because of their asymptomatic onset and evolution. Point-of-care devices have emerged as useful technologies for improving access to several laboratory tests closely patients' beds or homes, which makes it possible to eliminate the distance barrier. Objective: To evaluate the application of point-of-care technology for glycated hemoglobin (HbA1c) estimation in the assessment of glycemic control and identification of new diagnoses of diabetes in primary care among rural communities in a Brazilian municipality. Materials and Methods: We included individuals aged 18 years or older among rural communities in a Brazilian municipality. From September 2019 to February 2020, participants were assessed for anthropometrics, blood pressure, and capillary glycemia during routine primary care team activities at health fairs and in patient groups. Participants previously diagnosed with diabetes but without recent HbA1c test results or those without a previous diagnosis but with random capillary glycemia higher than 140 mg/dL were considered positive and were tested for HbA1c by using a point-of-care device. Results: At the end of the study, 913 individuals were accessed. Of these, 600 (65.7%) had no previous diagnosis of diabetes, 58/600 (9.7%) refused capillary glycemia screening and 542/600 (90.7%) were tested. Among tested individuals, 73/542 (13.5%) cases without a previous diagnosis of diabetes, were positive for capillary glycemia. Among positives, 31/73 (42.5%) had HbA1c levels that were considered indicative of prediabetes and 16/73 (21.9%) were newly diagnosed with diabetes. Among the participants, 313/913 (34.3%) were previously diagnosed with diabetes. Recent HbA1c results were unavailable for 210/313 (67.1%). These individuals were tested using point-of-care devices. Among them, 143/210 (68.1%) had HbA1c levels higher than target levels (>7% and >8% for adults and elderly individuals, respectively. Conclusion: The application of point-of-care devices for HbA1c level measurement improved the access to this test for people living in rural or remote areas. Thus, it was possible to include this technology in the routine activities of primary health care teams, which increased the rates of new diagnoses and identification of patients with uncontrolled glycemia.
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Affiliation(s)
| | | | - Sostenes Mistro
- Program of Post-graduation in Collective Health, Multidisciplinary Institute of Health, Federal University of Bahia, Vitória da Conquista, Brazil
| | - Daniela Arruda Soares
- Program of Post-graduation in Collective Health, Multidisciplinary Institute of Health, Federal University of Bahia, Vitória da Conquista, Brazil
| | | | | | - Jéssica Caline Lemos Macedo
- Program of Post-graduation in Collective Health, Multidisciplinary Institute of Health, Federal University of Bahia, Vitória da Conquista, Brazil
| | - Taciana Borges Andrade Cortes
- Program of Post-graduation in Collective Health, Multidisciplinary Institute of Health, Federal University of Bahia, Vitória da Conquista, Brazil
| | - Amós Alves de Souza
- Multidisciplinary Institute of Health, Federal University of Bahia, Vitória da Conquista, Brazil
| | - Davi Rumel
- Department of Community Health, School of Medicine, Municipal University of São Caetano do sul, São Caetano Do Sul, Brazil
| | - Marcio Galvão Oliveira
- Program of Post-graduation in Collective Health, Multidisciplinary Institute of Health, Federal University of Bahia, Vitória da Conquista, Brazil
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Sampson M, Clark A, Bachmann M, Garner N, Irvine L, Howe A, Greaves C, Auckland S, Smith J, Turner J, Rea D, Rayman G, Dhatariya K, John WG, Barton G, Usher R, Ferns C, Pascale M. Effects of the Norfolk diabetes prevention lifestyle intervention (NDPS) on glycaemic control in screen-detected type 2 diabetes: a randomised controlled trial. BMC Med 2021; 19:183. [PMID: 34407811 PMCID: PMC8375190 DOI: 10.1186/s12916-021-02053-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 07/06/2021] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND The purpose of this trial was to test if the Norfolk Diabetes Prevention Study (NDPS) lifestyle intervention, recently shown to reduce the incidence of type 2 diabetes in high-risk groups, also improved glycaemic control in people with newly diagnosed screen-detected type 2 diabetes. METHODS We screened 12,778 participants at high risk of type 2 diabetes using a fasting plasma glucose and glycosylated haemoglobin (HbA1c). People with screen-detected type 2 diabetes were randomised in a parallel, three-arm, controlled trial with up to 46 months of follow-up, with a control arm (CON), a group-based lifestyle intervention of 6 core and up to 15 maintenance sessions (INT), or the same intervention with additional support from volunteers with type 2 diabetes trained to co-deliver the lifestyle intervention (INT-DPM). The pre-specified primary end point was mean HbA1c compared between groups at 12 months. RESULTS We randomised 432 participants (CON 149; INT 142; INT-DPM 141) with a mean (SD) age of 63.5 (10.0) years, body mass index (BMI) of 32.4 (6.4) kg/m2, and HbA1c of 52.5 (10.2) mmol/mol. The primary outcome of mean HbA1c at 12 months (CON 48.5 (9.1) mmol/mol, INT 46.5 (8.1) mmol/mol, and INT-DPM 45.6 (6.0) mmol/mol) was significantly lower in the INT-DPM arm compared to CON (adjusted difference -2.57 mmol/mol; 95% CI -4.5, -0.6; p = 0.007) but not significantly different between the INT-DPM and INT arms (-0.55 mmol/mol; 95% CI -2.46, 1.35; p = 0.57), or INT vs CON arms (-2.14 mmol/mol; 95% CI -4.33, 0.05; p = 0.07). Subgroup analyses showed the intervention had greater effect in participants < 65 years old (difference in mean HbA1c compared to CON -4.76 mmol/mol; 95% CI -7.75, -1.78 mmol/mol) than in older participants (-0.46 mmol/mol; 95% CI -2.67, 1.75; interaction p = 0.02). This effect was most significant in the INT-DPM arm (-6.01 mmol/mol; 95% CI -9.56, -2.46 age < 65 years old and -0.22 mmol/mol; 95% CI -2.7, 2.25; aged > 65 years old; p = 0.007). The use of oral hypoglycaemic medication was associated with a significantly lower mean HbA1c but only within the INT-DPM arm compared to CON (-7.0 mmol/mol; 95% CI -11.5, -2.5; p = 0.003). CONCLUSION The NDPS lifestyle intervention significantly improved glycaemic control after 12 months in people with screen-detected type 2 diabetes when supported by trained peer mentors with type 2 diabetes, particularly those receiving oral hypoglycaemics and those under 65 years old. The effect size was modest, however, and not sustained at 24 months. TRIAL REGISTRATION ISRCTN34805606 . Retrospectively registered 14.4.16.
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Affiliation(s)
- Michael Sampson
- Elsie Bertram Diabetes Centre, Department of Diabetes and Endocrinology, Norfolk and Norwich University Hospital NHS Trust, Colney Lane, Norwich, NR4 7UY, UK.
- Norwich Medical School, University of East Anglia, Norwich, UK.
| | - Allan Clark
- Norwich Medical School, University of East Anglia, Norwich, UK
| | - Max Bachmann
- Norwich Medical School, University of East Anglia, Norwich, UK
| | - Nikki Garner
- Elsie Bertram Diabetes Centre, Department of Diabetes and Endocrinology, Norfolk and Norwich University Hospital NHS Trust, Colney Lane, Norwich, NR4 7UY, UK
| | - Lisa Irvine
- Norwich Medical School, University of East Anglia, Norwich, UK
| | - Amanda Howe
- Norwich Medical School, University of East Anglia, Norwich, UK
| | - Colin Greaves
- School of Sport, Exercise & Rehabilitation Sciences, University of Birmingham, Birmingham, UK
| | - Sara Auckland
- Elsie Bertram Diabetes Centre, Department of Diabetes and Endocrinology, Norfolk and Norwich University Hospital NHS Trust, Colney Lane, Norwich, NR4 7UY, UK
| | - Jane Smith
- University of Exeter Medical School, College of Medicine & Health, University of Exeter, Exeter, UK
| | - Jeremy Turner
- Elsie Bertram Diabetes Centre, Department of Diabetes and Endocrinology, Norfolk and Norwich University Hospital NHS Trust, Colney Lane, Norwich, NR4 7UY, UK
| | - Dave Rea
- Elsie Bertram Diabetes Centre, Department of Diabetes and Endocrinology, Norfolk and Norwich University Hospital NHS Trust, Colney Lane, Norwich, NR4 7UY, UK
| | - Gerry Rayman
- Department of Diabetes and Endocrinology, Ipswich General Hospital NHS Trust, Ipswich, UK
| | - Ketan Dhatariya
- Elsie Bertram Diabetes Centre, Department of Diabetes and Endocrinology, Norfolk and Norwich University Hospital NHS Trust, Colney Lane, Norwich, NR4 7UY, UK
| | - W Garry John
- Norwich Medical School, University of East Anglia, Norwich, UK
- Department Clinical Biochemistry, Norfolk and Norwich University Hospital NHS Trust, Norwich, UK
| | - Garry Barton
- Norwich Medical School, University of East Anglia, Norwich, UK
| | - Rebecca Usher
- Elsie Bertram Diabetes Centre, Department of Diabetes and Endocrinology, Norfolk and Norwich University Hospital NHS Trust, Colney Lane, Norwich, NR4 7UY, UK
| | - Clare Ferns
- Elsie Bertram Diabetes Centre, Department of Diabetes and Endocrinology, Norfolk and Norwich University Hospital NHS Trust, Colney Lane, Norwich, NR4 7UY, UK
| | - Melanie Pascale
- Elsie Bertram Diabetes Centre, Department of Diabetes and Endocrinology, Norfolk and Norwich University Hospital NHS Trust, Colney Lane, Norwich, NR4 7UY, UK
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Chen CN, Chen TC, Tsai SC, Hwu CM. Factors associated with relative muscle strength in patients with type 2 diabetes mellitus. Arch Gerontol Geriatr 2021; 95:104384. [PMID: 33740478 DOI: 10.1016/j.archger.2021.104384] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Revised: 02/22/2021] [Accepted: 02/24/2021] [Indexed: 12/20/2022]
Abstract
OBJECTIVES Some patients with type 2 diabetes mellitus (T2DM) experience decreased mobility associated with lower relative muscle strength (normalized with muscle mass). This study aimed to identify factors predicting relative muscle strength of patients with T2DM assessed at regular clinical visits. METHODS A total of 144 T2DM patients underwent fasting blood drawing (determining white blood cell count [WBC], diabetic kidney disease [DKD], and glycated hemoglobin [HbA1c]) and the assessment of body composition, diabetic peripheral neuropathy (DPN), activity level, and muscle strength (grip, knee extensor, and ankle plantar flexor strength). One-way ANOVA and multiple regression models were used to identify factors associated with the relative muscle strength. RESULTS Our data showed that age, diabetes duration, fat percentage, WBC, DPN, and DKD were negatively associated with the relative muscle strength. Specifically, a greater WBC was associated with lower relative muscle strength of both distal and proximal muscle groups of extremities after the adjustment of other associated factors. DPN was associated with lower relative strength of the distal muscle groups of extremities. CONCLUSIONS WBC may be used as a marker of inflammation, and greater count, even within the normal range, is negatively associated with the relative muscle strength in patients with T2DM.
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Affiliation(s)
- Chiao-Nan Chen
- Department of Physical Therapy and Assistive Technology, School of Biomedical Science and Engineering, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Ting-Chung Chen
- Department of Physical Therapy and Assistive Technology, School of Biomedical Science and Engineering, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Shiow-Chwen Tsai
- Institute of Sports Sciences, University of Taipei, Taipei, Taiwan
| | - Chii-Min Hwu
- Section of Endocrinology and Metabolism, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan; Faculty of Medicine, National Yang Ming Chiao Tung University School of Medicine, Taipei, Taiwan.
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12
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An LW, Li XL, Chen LH, Tang H, Yuan Q, Liu YJ, Ji Y, Lu JM. Clinical Inertia and 2-Year Glycaemic Trajectories in Patients with Non-Newly Diagnosed Type 2 Diabetes Mellitus in Primary Care: A Retrospective Cohort Study. Patient Prefer Adherence 2021; 15:2497-2508. [PMID: 34795477 PMCID: PMC8593594 DOI: 10.2147/ppa.s328165] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Accepted: 10/27/2021] [Indexed: 01/11/2023] Open
Abstract
OBJECTIVE To analyse diabetes treatment, treatment change and self-management behaviours in association with 2-year glycaemic trajectories in patients with non-newly diagnosed type 2 diabetes mellitus in Chinese primary care. METHODS This was an observational, multi-centre, longitudinal, retrospective cohort study. Clinical data of 4690 subjects were extracted from electronic medical records, including serial glycated haemoglobin A1c (HbA1c) measurements, antidiabetic medication records and compliance to exercise, diet, medications and self-monitoring of blood glucose (SMBG). Patterns of longitudinal HbA1c trajectories were identified using the percentage of HbA1c measurements <7.5% from the second available HbA1c measurement. Clinical relevance of the clusters was assessed through multivariable analysis. RESULTS Approximately half of the participants demonstrated good glycaemic control; of these, 34.5% demonstrated stable, good control, and 13.7% demonstrated relatively good control. About 16.2% demonstrated moderate control, and 35.6% demonstrated poor control. From the good to poor control groups, the percentage of subjects treated with insulin at baseline and during the follow-up period increased gradually, while the percentage of subjects adhering to exercise, diet, medications and SMBG decreased gradually. Compared with baseline, the adherence to exercise, diet, medications and SMBG improved significantly. Approximately 50% and 26% of subjects in the two poorest control groups, respectively, experienced treatment changes. After multivariable adjustments, baseline HbA1c ≥7.5%, HbA1c change ≥-0.5% from baseline to visit 1, insulin treatment, treatment change, poor adherence to diet, exercise, SMBG during the follow-up period and HbA1c measurements <3 per year were significantly associated with poorer glycaemic control. CONCLUSION We identified four longitudinal HbA1c trajectories in patients with non-newly diagnosed type 2 diabetes. Even if baseline HbA1c is suboptimal, aggressive treatment changes, good adherence during the follow-up period, ≥3 HbA1c measurements per year and reducing HbA1c levels to a certain extent by the first follow-up visit were important for good, stable, long-term glycaemic control.
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Affiliation(s)
- Ling-Wang An
- Department of Endocrinology, Beijing Ruijing Diabetes Hospital, Beijing, 100079, People’s Republic of China
| | - Xiang-Lan Li
- Department of Endocrinology, Beijing Ruijing Diabetes Hospital, Beijing, 100079, People’s Republic of China
| | - Lin-Hui Chen
- Department of Endocrinology, Taiyuan Diabetes Hospital, Taiyuan, 030013, People’s Republic of China
| | - Hong Tang
- Department of Share-Care Center, Chengdu Ruien Diabetes Hospital, Chengdu, 610000, People’s Republic of China
| | - Qun Yuan
- Department of Endocrinology, Heilongjiang Ruijing Diabetes Hospital, Harbin, 150009, People’s Republic of China
| | - Yan-Jun Liu
- Department of Endocrinology, Lanzhou Ruijing Diabetes Hospital, Lanzhou, 730000, People’s Republic of China
| | - Yu Ji
- Department of Endocrinology, Beijing Aerospace General Hospital, Beijing, 100076, People’s Republic of China
| | - Ju-Ming Lu
- Department of Endocrinology, Beijing Ruijing Diabetes Hospital, Beijing, 100079, People’s Republic of China
- Department of Endocrinology, The General Hospital of the People’s Liberation Army, Beijing, 100853, People’s Republic of China
- Correspondence: Ju-Ming Lu Department of Endocrinology, The General Hospital of the People’s Liberation Army, No. 28 of Fuxing Road, Haidian District, Beijing, 100853, People’s Republic of ChinaTel +86 10 8822 9999 Email
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Yang MC, Zhu XB, Wang YX, Wu SL, Wang Q, Yan YN, Yang X, Yang JY, Chen MX, Lei YH, Wei WB. Influencing factors for peripheral and posterior lesions in mild non-proliferative diabetic retinopathy-the Kailuan Eye Study. Int J Ophthalmol 2020; 13:1467-1476. [PMID: 32953588 DOI: 10.18240/ijo.2020.09.20] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 06/18/2020] [Indexed: 02/08/2023] Open
Abstract
AIM To explore the influencing factors of diabetes type 2 patients with mild non-proliferative diabetic retinopathy (NPDR) in the Kailuan area of Tangshan, Hebei Province, China. METHODS In this non-interventional, retrospective study, 683 patients with type 2 diabetes were included in the Kailuan Diabetic Retinopathy Study involving participants with diabetes in the community-based longitudinal Kailuan Study. Based on the undilated ultra-wide field (200°; UWF) images and partial dilated digital fundus images, the diabetic retinopathy (DR) of the surveyed population was graded. Interobserver agreement was estimated by using Cohen's Kappa statistics. The main outcome indicators included gender, age, weight, height, body mass index, blood pressure, circumferences of neck, waist and hip, current smoking, levels of fasting plasma glucose (FPG), hypersensitive C-reactive protein, creatinine, and cholesterol, etc. According to different lesions' locations of patients with mild NPDR, logistic regression models were used to estimate the odds ratios (ORs) and their 95%CIs of each risk factor. RESULTS The study group of 683 patients included 570 males and 113 females. The mean age of the patients was 62.18±9.41y. Compared with dilated fundus examinations, there was fair agreement with the level of DR identified on UWF images in 63.91% of eyes (k=0.369, 95%CI, 0.00-0.00). Detected by UWF images, there were 98 patients with mild NPDR having peripheral retinal lesions, 35 patients with mild NPDR having posterior lesions, 44 patients with mild NPDR whose lesions were detected both in and out the standard two fields area, and 336 patients with non obvious DR. Parameters that conferred a statistically significant increased risks for mild NPDR with having peripheral retinal lesions were neck circumstance (OR, 1.124; 95%CI, 1.044-1.211), and with posterior lesions were FPG (OR, 1.052; 95%CI, 1.007-1.099). CONCLUSION UWF is an effectiveness means of DR screening. Moreover, it is necessary to evaluate peripheral diabetic retinal lesions which can help to estimate the severity of DR. The phenomenon that nonuniform and inhomogeneous distribution of DR lesions has been found. And the influencing factors in mild NPDR are differing by different lesions' locations.
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Affiliation(s)
- Mo-Chi Yang
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China.,Department of Ophthalmology, General Hospital of Ningxia Medical University, Yinchuan 750004, Ningxia Hui Autonomous Region, China
| | - Xiao-Bo Zhu
- Dongfang Hospital Beijing University of Chinese Medicine, Beijing 100078, China
| | - Ya-Xing Wang
- Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Shou-Ling Wu
- Department of Cardiology, Kailuan General Hospital, Tangshan 063000, Hebei Province, China
| | - Qian Wang
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Yan-Ni Yan
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Xuan Yang
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Jing-Yan Yang
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Meng-Xi Chen
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Ya-Hui Lei
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Wen-Bin Wei
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
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