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Handelsman Y, Anderson JE, Bakris GL, Ballantyne CM, Bhatt DL, Bloomgarden ZT, Bozkurt B, Budoff MJ, Butler J, Cherney DZI, DeFronzo RA, Del Prato S, Eckel RH, Filippatos G, Fonarow GC, Fonseca VA, Garvey WT, Giorgino F, Grant PJ, Green JB, Greene SJ, Groop PH, Grunberger G, Jastreboff AM, Jellinger PS, Khunti K, Klein S, Kosiborod MN, Kushner P, Leiter LA, Lepor NE, Mantzoros CS, Mathieu C, Mende CW, Michos ED, Morales J, Plutzky J, Pratley RE, Ray KK, Rossing P, Sattar N, Schwarz PEH, Standl E, Steg PG, Tokgözoğlu L, Tuomilehto J, Umpierrez GE, Valensi P, Weir MR, Wilding J, Wright EE. DCRM 2.0: Multispecialty practice recommendations for the management of diabetes, cardiorenal, and metabolic diseases. Metabolism 2024; 159:155931. [PMID: 38852020 DOI: 10.1016/j.metabol.2024.155931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Accepted: 04/30/2024] [Indexed: 06/10/2024]
Abstract
The spectrum of cardiorenal and metabolic diseases comprises many disorders, including obesity, type 2 diabetes (T2D), chronic kidney disease (CKD), atherosclerotic cardiovascular disease (ASCVD), heart failure (HF), dyslipidemias, hypertension, and associated comorbidities such as pulmonary diseases and metabolism dysfunction-associated steatotic liver disease and metabolism dysfunction-associated steatohepatitis (MASLD and MASH, respectively, formerly known as nonalcoholic fatty liver disease and nonalcoholic steatohepatitis [NAFLD and NASH]). Because cardiorenal and metabolic diseases share pathophysiologic pathways, two or more are often present in the same individual. Findings from recent outcome trials have demonstrated benefits of various treatments across a range of conditions, suggesting a need for practice recommendations that will guide clinicians to better manage complex conditions involving diabetes, cardiorenal, and/or metabolic (DCRM) diseases. To meet this need, we formed an international volunteer task force comprising leading cardiologists, nephrologists, endocrinologists, and primary care physicians to develop the DCRM 2.0 Practice Recommendations, an updated and expanded revision of a previously published multispecialty consensus on the comprehensive management of persons living with DCRM. The recommendations are presented as 22 separate graphics covering the essentials of management to improve general health, control cardiorenal risk factors, and manage cardiorenal and metabolic comorbidities, leading to improved patient outcomes.
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Affiliation(s)
| | | | | | - Christie M Ballantyne
- Department of Medicine, Baylor College of Medicine, Texas Heart Institute, Houston, TX, USA
| | - Deepak L Bhatt
- Mount Sinai Fuster Heart Hospital, Icahn School of Medicine at Mount Sinai, NY, New York, USA
| | - Zachary T Bloomgarden
- Department of Internal Medicine, Icahn School of Medicine at Mount Sinai, NY, New York, USA
| | - Biykem Bozkurt
- Department of Medicine, Baylor College of Medicine, Houston, TX, USA
| | | | - Javed Butler
- University of Mississippi Medical Center, Jackson, MS, USA
| | - David Z I Cherney
- Division of Nephrology, Department of Medicine, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Canada
| | | | - Stefano Del Prato
- Interdisciplinary Research Center "Health Science", Sant'Anna School of Advanced Studies, Pisa, Italy
| | - Robert H Eckel
- University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Gerasimos Filippatos
- Department of Cardiology, National and Kapodistrian University of Athens, Athens, Greece
| | | | | | | | - Francesco Giorgino
- Department of Precision and Regenerative Medicine and Ionian Area, University of Bari Aldo Moro, Bari, Italy
| | | | - Jennifer B Green
- Division of Endocrinology, Metabolism, and Nutrition, Duke University School of Medicine, Durham, NC, USA
| | - Stephen J Greene
- Division of Cardiology, Duke University School of Medicine, Durham, NC, USA
| | - Per-Henrik Groop
- Department of Nephrology, University of Helsinki, Finnish Institute for Health and Helsinki University HospitalWelfare, Folkhälsan Research Center, Helsinki, Finland; Department of Diabetes, Central Clinical School, Monash University, Melbourne, Australia
| | - George Grunberger
- Grunberger Diabetes Institute, Bloomfield Hills, MI, USA; Wayne State University School of Medicine, Detroit, MI, USA; Oakland University William Beaumont School of Medicine, Rochester, MI, USA; Charles University, Prague, Czech Republic
| | | | - Paul S Jellinger
- The Center for Diabetes & Endocrine Care, University of Miami Miller School of Medicine, Hollywood, FL, USA
| | | | - Samuel Klein
- Washington University School of Medicine, Saint Louis, MO, USA
| | - Mikhail N Kosiborod
- Saint Luke's Mid America Heart Institute, University of Missouri-Kansas City, Kansas City, MO, USA
| | | | | | - Norman E Lepor
- David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
| | | | - Chantal Mathieu
- Department of Endocrinology, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Christian W Mende
- University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Erin D Michos
- Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Javier Morales
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, Advanced Internal Medicine Group, PC, East Hills, NY, USA
| | - Jorge Plutzky
- Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA
| | | | | | | | | | - Peter E H Schwarz
- Department for Prevention and Care of Diabetes, Faculty of Medicine Carl Gustav Carus at the Technische Universität/TU Dresden, Dresden, Germany
| | - Eberhard Standl
- Munich Diabetes Research Group e.V. at Helmholtz Centre, Munich, Germany
| | - P Gabriel Steg
- Université Paris-Cité, Institut Universitaire de France, AP-HP, Hôpital Bichat, Cardiology, Paris, France
| | | | - Jaakko Tuomilehto
- University of Helsinki, Finnish Institute for Health and Welfare, Helsinki, Finland
| | | | - Paul Valensi
- Polyclinique d'Aubervilliers, Aubervilliers and Paris-Nord University, Paris, France
| | - Matthew R Weir
- Division of Nephrology, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - John Wilding
- University of Liverpool, Liverpool, United Kingdom
| | - Eugene E Wright
- Department of Medicine, Duke University Medical Center, Durham, NC, USA
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2
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Nurmohamed NS, van Rosendael AR, Danad I, Ngo-Metzger Q, Taub PR, Ray KK, Figtree G, Bonaca MP, Hsia J, Rodriguez F, Sandhu AT, Nieman K, Earls JP, Hoffmann U, Bax JJ, Min JK, Maron DJ, Bhatt DL. Atherosclerosis evaluation and cardiovascular risk estimation using coronary computed tomography angiography. Eur Heart J 2024; 45:1783-1800. [PMID: 38606889 PMCID: PMC11129796 DOI: 10.1093/eurheartj/ehae190] [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: 10/07/2023] [Revised: 02/13/2024] [Accepted: 03/13/2024] [Indexed: 04/13/2024] Open
Abstract
Clinical risk scores based on traditional risk factors of atherosclerosis correlate imprecisely to an individual's complex pathophysiological predisposition to atherosclerosis and provide limited accuracy for predicting major adverse cardiovascular events (MACE). Over the past two decades, computed tomography scanners and techniques for coronary computed tomography angiography (CCTA) analysis have substantially improved, enabling more precise atherosclerotic plaque quantification and characterization. The accuracy of CCTA for quantifying stenosis and atherosclerosis has been validated in numerous multicentre studies and has shown consistent incremental prognostic value for MACE over the clinical risk spectrum in different populations. Serial CCTA studies have advanced our understanding of vascular biology and atherosclerotic disease progression. The direct disease visualization of CCTA has the potential to be used synergistically with indirect markers of risk to significantly improve prevention of MACE, pending large-scale randomized evaluation.
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Affiliation(s)
- Nick S Nurmohamed
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit
Amsterdam, Amsterdam, The
Netherlands
- Department of Vascular Medicine, Amsterdam UMC, University of
Amsterdam, Amsterdam, The
Netherlands
- Division of Cardiology, The George Washington University School of
Medicine, Washington, DC, United States
| | | | - Ibrahim Danad
- Department of Cardiology, University Medical Center Utrecht,
Utrecht, The Netherlands
- Department of Cardiology, Radboud University Medical Center,
Nijmegen, The Netherlands
| | - Quyen Ngo-Metzger
- Department of Health Systems Science, Kaiser Permanente Bernard J. Tyson
School of Medicine, Pasadena, CA, United States
| | - Pam R Taub
- Section of Cardiology, Department of Medicine, University of
California, San Diego, CA, United States
| | - Kausik K Ray
- Department of Primary Care and Public Health, Imperial College
London, London, United
Kingdom
| | - Gemma Figtree
- Faculty of Medicine and Health, University of Sydney,
Australia, St Leonards, Australia
| | - Marc P Bonaca
- Department of Medicine, University of Colorado School of
Medicine, Aurora, CO, United States
| | - Judith Hsia
- Department of Medicine, University of Colorado School of
Medicine, Aurora, CO, United States
| | - Fatima Rodriguez
- Department of Medicine, Stanford University School of
Medicine, Stanford, CA, United States
| | - Alexander T Sandhu
- Department of Medicine, Stanford University School of
Medicine, Stanford, CA, United States
| | - Koen Nieman
- Department of Medicine, Stanford University School of
Medicine, Stanford, CA, United States
| | - James P Earls
- Cleerly, Inc., Denver, CO, United States
- Department of Radiology, The George Washington University School of
Medicine, Washington, DC, United States
| | | | - Jeroen J Bax
- Department of Cardiology, Leiden University Medical Center,
Leiden, The Netherlands
| | | | - David J Maron
- Department of Medicine, Stanford University School of
Medicine, Stanford, CA, United States
| | - Deepak L Bhatt
- Mount Sinai Fuster Heart Hospital, Icahn School of Medicine at Mount
Sinai, 1 Gustave Levy Place, Box 1030, New York, NY
10029, United States
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3
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Zhu D, Vernon ST, D'Agostino Z, Wu J, Giles C, Chan AS, Kott KA, Gray MP, Gholipour A, Tang O, Beyene HB, Patrick E, Grieve SM, Meikle PJ, Figtree GA, Yang JYH. Lipidomics Profiling and Risk of Coronary Artery Disease in the BioHEART-CT Discovery Cohort. Biomolecules 2023; 13:917. [PMID: 37371497 DOI: 10.3390/biom13060917] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 05/25/2023] [Accepted: 05/29/2023] [Indexed: 06/29/2023] Open
Abstract
The current coronary artery disease (CAD) risk scores for predicting future cardiovascular events rely on well-recognized traditional cardiovascular risk factors derived from a population level but often fail individuals, with up to 25% of first-time heart attack patients having no risk factors. Non-invasive imaging technology can directly measure coronary artery plaque burden. With an advanced lipidomic measurement methodology, for the first time, we aim to identify lipidomic biomarkers to enable intervention before cardiovascular events. With 994 participants from BioHEART-CT Discovery Cohort, we collected clinical data and performed high-performance liquid chromatography with mass spectrometry to determine concentrations of 683 plasma lipid species. Statin-naive participants were selected based on subclinical CAD (sCAD) categories as the analytical cohort (n = 580), with sCAD+ (n = 243) compared to sCAD- (n = 337). Through a machine learning approach, we built a lipid risk score (LRS) and compared the performance of the existing Framingham Risk Score (FRS) in predicting sCAD+. We obtained individual classifiability scores and determined Body Mass Index (BMI) as the modifying variable. FRS and LRS models achieved similar areas under the receiver operating characteristic curve (AUC) in predicting the validation cohort. LRS enhanced the prediction of sCAD+ in the healthy-weight group (BMI < 25 kg/m2), where FRS performed poorly and identified individuals at risk that FRS missed. Lipid features have strong potential as biomarkers to predict CAD plaque burden and can identify residual risk not captured by traditional risk factors/scores. LRS compliments FRS in prediction and has the most significant benefit in healthy-weight individuals.
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Affiliation(s)
- Dantong Zhu
- School of Mathematics and Statistics, The University of Sydney, Sydney, NSW 2006, Australia
- Kolling Institute of Medical Research, The University of Sydney, Sydney, NSW 2065, Australia
| | - Stephen T Vernon
- Kolling Institute of Medical Research, The University of Sydney, Sydney, NSW 2065, Australia
- Department of Cardiology, Royal North Shore Hospital, Sydney, NSW 2065, Australia
| | - Zac D'Agostino
- School of Mathematics and Statistics, The University of Sydney, Sydney, NSW 2006, Australia
| | - Jingqin Wu
- Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia
| | - Corey Giles
- Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia
| | - Adam S Chan
- School of Mathematics and Statistics, The University of Sydney, Sydney, NSW 2006, Australia
| | - Katharine A Kott
- Kolling Institute of Medical Research, The University of Sydney, Sydney, NSW 2065, Australia
- Department of Cardiology, Royal North Shore Hospital, Sydney, NSW 2065, Australia
| | - Michael P Gray
- Kolling Institute of Medical Research, The University of Sydney, Sydney, NSW 2065, Australia
| | - Alireza Gholipour
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia
| | - Owen Tang
- Kolling Institute of Medical Research, The University of Sydney, Sydney, NSW 2065, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia
| | - Habtamu B Beyene
- Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia
| | - Ellis Patrick
- School of Mathematics and Statistics, The University of Sydney, Sydney, NSW 2006, Australia
| | - Stuart M Grieve
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia
| | - Peter J Meikle
- Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia
- Department of Cardiovascular Research Translation and Implementation, La Trobe University, Melbourne, VIC 3086, Australia
| | - Gemma A Figtree
- Kolling Institute of Medical Research, The University of Sydney, Sydney, NSW 2065, Australia
- Department of Cardiology, Royal North Shore Hospital, Sydney, NSW 2065, Australia
| | - Jean Y H Yang
- School of Mathematics and Statistics, The University of Sydney, Sydney, NSW 2006, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia
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Zhang Y, Wang Y, Li J, Zhang G, Di A, Yuan H. Refining the radiation and contrast medium dose in weight-grouped scanning protocols for coronary CT angiography. J Appl Clin Med Phys 2023:e14041. [PMID: 37211752 DOI: 10.1002/acm2.14041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 04/13/2023] [Accepted: 05/03/2023] [Indexed: 05/23/2023] Open
Abstract
PURPOSE To refine the currently used, weight-grouped protocol for coronary computed tomography angiography (CCTA), in terms of the radiation and contrast medium dose, through clinical evaluation. METHODS Following the current routine setting that varies between three weight groups (group A: 55-65 kg, group B: 66-75 kg, group C: 76-85 kg), three additional reduction protocols were proposed to each group, with different combinations of lowered tube voltage (70-100 kVp), tube current (100-220 mAs), and iodine delivery rate (0.8-1.5 gI/s). A total of 321 patients scheduled for CCTA due to suspected coronary artery disease were enrolled, who were randomly assigned to one of the four subgroups of settings under the corresponding weight group. The resulting objective image quality was compared by measuring the contrast-to-noise ratio and signal-to-noise ratio. Subjective image quality was graded by two radiologists using a 4-point Likert scale, on a total of 3848 segments. The optimal protocol for each weight group was determined with respect to the image quality and the applied radiation dose. RESULTS For all three groups, no significant difference was noticed in objective images quality between subgroups of dose settings (all p > 0.05). The average score on subjective image quality was ≥3 for every subgroup, while the percentage of score 4 showed greater dependence on the setting, ranging from 83.2% to 91.5%, and was chosen to be the determining factor. The optimal dose settings were found to be 80 kVp, 150 mAs, and 1.0 gI/s for patients of 55-75 kg in weight, and 100 kVp, 170 mAs, and 1.5 gI/s for those of 76-85 kg. CONCLUSION It is feasible to refine the currently used, weight-grouped protocol for CCTA in terms of radiation and contrast medium dose, by use of an optimization strategy where the balance between dose and image quality can be improved in a routine clinical setting.
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Affiliation(s)
- Yan Zhang
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Ying Wang
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Jing Li
- United Imaging Healthcare, Shanghai, China
| | | | - Aihui Di
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Huishu Yuan
- Department of Radiology, Peking University Third Hospital, Beijing, China
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5
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Galli E, Baritussio A, Sitges M, Donnellan E, Jaber WA, Gimelli A. Multi-modality imaging to guide the implantation of cardiac electronic devices in heart failure: is the sum greater than the individual components? Eur Heart J Cardiovasc Imaging 2023; 24:163-176. [PMID: 36458875 DOI: 10.1093/ehjci/jeac237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 11/03/2022] [Indexed: 12/05/2022] Open
Abstract
Heart failure is a clinical syndrome with an increasing prevalence and incidence worldwide that impacts patients' quality of life, morbidity, and mortality. Implantable cardioverter-defibrillator and cardiac resynchronization therapy are pillars of managing patients with HF and reduced left ventricular ejection fraction. Despite the advances in cardiac imaging, the assessment of patients needing cardiac implantable electronic devices relies essentially on the measure of left ventricular ejection fraction. However, multi-modality imaging can provide important information concerning the aetiology of heart failure, the extent and localization of myocardial scar, and the pathophysiological mechanisms of left ventricular conduction delay. This paper aims to highlight the main novelties and progress in the field of multi-modality imaging to identify patients who will benefit from cardiac resynchronization therapy and/or implantable cardioverter-defibrillator. We also want to underscore the boundaries that prevent the application of imaging-derived parameters to patients who will benefit from cardiac implantable electronic devices and orient the choice of the device. Finally, we aim at providing some reflections for future research in this field.
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Affiliation(s)
- Elena Galli
- Department of Cardiology, University Hospital of Rennes, 35000 Rue Henri Le Guilloux, Rennes, France
| | - Anna Baritussio
- Cardiology, Department of Cardiac, Vascular, Thoracic Sciences and Public Health, University Hospital of Padua, 35121 Via Nicolò Giustiniani, Padua, Italy
| | - Marta Sitges
- Cardiovascular Institute, Hospital Clínic, Universitat de Barcelona, 08036 C. de Villarroel, Barcelona, Spain
| | - Eoin Donnellan
- Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195, USA
| | - Wael A Jaber
- Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195, USA
| | - Alessia Gimelli
- Fondazione Toscana G. Monasterio, 56124 Via Giuseppe Moruzzi, Pisa, Italy
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Handelsman Y, Anderson JE, Bakris GL, Ballantyne CM, Beckman JA, Bhatt DL, Bloomgarden ZT, Bozkurt B, Budoff MJ, Butler J, Dagogo-Jack S, de Boer IH, DeFronzo RA, Eckel RH, Einhorn D, Fonseca VA, Green JB, Grunberger G, Guerin C, Inzucchi SE, Jellinger PS, Kosiborod MN, Kushner P, Lepor N, Mende CW, Michos ED, Plutzky J, Taub PR, Umpierrez GE, Vaduganathan M, Weir MR. DCRM Multispecialty Practice Recommendations for the management of diabetes, cardiorenal, and metabolic diseases. J Diabetes Complications 2022; 36:108101. [PMID: 34922811 PMCID: PMC9803322 DOI: 10.1016/j.jdiacomp.2021.108101] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2021] [Accepted: 11/27/2021] [Indexed: 02/06/2023]
Abstract
Type 2 diabetes (T2D), chronic kidney disease (CKD), atherosclerotic cardiovascular disease (ASCVD), and heart failure (HF)-along with their associated risk factors-have overlapping etiologies, and two or more of these conditions frequently occur in the same patient. Many recent cardiovascular outcome trials (CVOTs) have demonstrated the benefits of agents originally developed to control T2D, ASCVD, or CKD risk factors, and these agents have transcended their primary indications to confer benefits across a range of conditions. This evolution in CVOT evidence calls for practice recommendations that are not constrained by a single discipline to help clinicians manage patients with complex conditions involving diabetes, cardiorenal, and/or metabolic (DCRM) diseases. The ultimate goal for these recommendations is to be comprehensive yet succinct and easy to follow by the nonexpert-whether a specialist or a primary care clinician. To meet this need, we formed a volunteer task force comprising leading cardiologists, nephrologists, endocrinologists, and primary care physicians to develop the DCRM Practice Recommendations, a multispecialty consensus on the comprehensive management of the patient with complicated metabolic disease. The task force recommendations are based on strong evidence and incorporate practical guidance that is clinically relevant and simple to implement, with the aim of improving outcomes in patients with DCRM. The recommendations are presented as 18 separate graphics covering lifestyle therapy, patient self-management education, technology for DCRM management, prediabetes, cognitive dysfunction, vaccinations, clinical tests, lipids, hypertension, anticoagulation and antiplatelet therapy, antihyperglycemic therapy, hypoglycemia, nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH), ASCVD, HF, CKD, and comorbid HF and CKD, as well as a graphical summary of medications used for DCRM.
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Affiliation(s)
| | | | | | | | | | - Deepak L Bhatt
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | | | | | - Javed Butler
- University of Mississippi Medical Center, Jackson, MS, USA
| | | | | | | | - Robert H Eckel
- University of Colorado Anschutz Medical Campus, Denver, CO, USA
| | - Daniel Einhorn
- Scripps Whittier Institute for Diabetes, San Diego, CA, USA
| | | | | | - George Grunberger
- Grunberger Diabetes Institute, Bloomfield Hills, MI, USA, Wayne State University School of Medicine, Detroit, MI, USA, Oakland University William Beaumont School of Medicine, Rochester, MI, USA, Charles University, Prague, Czech Republic
| | - Chris Guerin
- University of California San Diego School of Medicine, San Diego, CA, USA
| | | | - Paul S Jellinger
- The Center for Diabetes & Endocrine Care, University of Miami Miller School of Medicine, Hollywood, FL, USA
| | - Mikhail N Kosiborod
- Saint Luke's Mid America Heart Institute, University of Missouri-Kansas City, Kansas City, MO, USA
| | | | - Norman Lepor
- David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
| | - Christian W Mende
- University of California San Diego School of Medicine, San Diego, CA, USA
| | - Erin D Michos
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jorge Plutzky
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Pam R Taub
- University of California San Diego School of Medicine, San Diego, CA, USA
| | | | | | - Matthew R Weir
- University of Maryland School of Medicine, Baltimore, MD, USA
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