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Khan SS, Matsushita K, Sang Y, Ballew SH, Grams ME, Surapaneni A, Blaha MJ, Carson AP, Chang AR, Ciemins E, Go AS, Gutierrez OM, Hwang SJ, Jassal SK, Kovesdy CP, Lloyd-Jones DM, Shlipak MG, Palaniappan LP, Sperling L, Virani SS, Tuttle K, Neeland IJ, Chow SL, Rangaswami J, Pencina MJ, Ndumele CE, Coresh J. Development and Validation of the American Heart Association's PREVENT Equations. Circulation 2024; 149:430-449. [PMID: 37947085 PMCID: PMC10910659 DOI: 10.1161/circulationaha.123.067626] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Accepted: 11/03/2023] [Indexed: 11/12/2023]
Abstract
BACKGROUND Multivariable equations are recommended by primary prevention guidelines to assess absolute risk of cardiovascular disease (CVD). However, current equations have several limitations. Therefore, we developed and validated the American Heart Association Predicting Risk of CVD EVENTs (PREVENT) equations among US adults 30 to 79 years of age without known CVD. METHODS The derivation sample included individual-level participant data from 25 data sets (N=3 281 919) between 1992 and 2017. The primary outcome was CVD (atherosclerotic CVD and heart failure). Predictors included traditional risk factors (smoking status, systolic blood pressure, cholesterol, antihypertensive or statin use, and diabetes) and estimated glomerular filtration rate. Models were sex-specific, race-free, developed on the age scale, and adjusted for competing risk of non-CVD death. Analyses were conducted in each data set and meta-analyzed. Discrimination was assessed using the Harrell C-statistic. Calibration was calculated as the slope of the observed versus predicted risk by decile. Additional equations to predict each CVD subtype (atherosclerotic CVD and heart failure) and include optional predictors (urine albumin-to-creatinine ratio and hemoglobin A1c), and social deprivation index were also developed. External validation was performed in 3 330 085 participants from 21 additional data sets. RESULTS Among 6 612 004 adults included, mean±SD age was 53±12 years, and 56% were women. Over a mean±SD follow-up of 4.8±3.1 years, there were 211 515 incident total CVD events. The median C-statistics in external validation for CVD were 0.794 (interquartile interval, 0.763-0.809) in female and 0.757 (0.727-0.778) in male participants. The calibration slopes were 1.03 (interquartile interval, 0.81-1.16) and 0.94 (0.81-1.13) among female and male participants, respectively. Similar estimates for discrimination and calibration were observed for atherosclerotic CVD- and heart failure-specific models. The improvement in discrimination was small but statistically significant when urine albumin-to-creatinine ratio, hemoglobin A1c, and social deprivation index were added together to the base model to total CVD (ΔC-statistic [interquartile interval] 0.004 [0.004-0.005] and 0.005 [0.004-0.007] among female and male participants, respectively). Calibration improved significantly when the urine albumin-to-creatinine ratio was added to the base model among those with marked albuminuria (>300 mg/g; 1.05 [0.84-1.20] versus 1.39 [1.14-1.65]; P=0.01). CONCLUSIONS PREVENT equations accurately and precisely predicted risk for incident CVD and CVD subtypes in a large, diverse, and contemporary sample of US adults by using routinely available clinical variables.
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Affiliation(s)
- Sadiya S Khan
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (S.S.K.)
| | - Kunihiro Matsushita
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (K.M., Y.S., S.H.B., J.C.)
| | - Yingying Sang
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (K.M., Y.S., S.H.B., J.C.)
- Department of Population Health, New York University Grossman School of Medicine, New York, NY (Y.S., S.H.B., J.C.)
| | - Shoshana H Ballew
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (K.M., Y.S., S.H.B., J.C.)
- Department of Population Health, New York University Grossman School of Medicine, New York, NY (Y.S., S.H.B., J.C.)
| | - Morgan E Grams
- Department of Medicine, Division of Precision Medicine, New York University Grossman School of Medicine, New York, NY (M.E.G., A.S.)
| | - Aditya Surapaneni
- Department of Medicine, Division of Precision Medicine, New York University Grossman School of Medicine, New York, NY (M.E.G., A.S.)
| | - Michael J Blaha
- Johns Hopkins Ciccarone Center for Prevention of Cardiovascular Disease, Baltimore, MD (M.J.B.)
| | - April P Carson
- University of Mississippi Medical Center, Jackson (A.P.C.)
| | - Alexander R Chang
- Departments of Nephrology and Population Health Sciences, Geisinger Health, Danville, PA (A.R.C.)
| | | | - Alan S Go
- Division of Research, Kaiser Permanente Northern California, Oakland; Department of Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, CA; Departments of Epidemiology, Biostatistics and Medicine, University of California, San Francisco; Department of Medicine (Nephrology), Stanford University School of Medicine, Palo Alto, CA (A.S,G.)
| | - Orlando M Gutierrez
- Departments of Epidemiology and Medicine, University of Alabama at Birmingham (O.M.G.)
| | - Shih-Jen Hwang
- National Heart, Lung, and Blood Institute, Framingham, MA (S.-J.H.)
| | - Simerjot K Jassal
- Division of General Internal Medicine, University of California, San Diego and VA San Diego Healthcare, CA (S.K.J.)
| | - Csaba P Kovesdy
- Medicine-Nephrology, Memphis Veterans Affairs Medical Center and University of Tennessee Health Science Center, Memphis (C.P.K.)
| | - Donald M Lloyd-Jones
- Department of Preventive Medicine, Northwestern University, Chicago, IL (D.M.L.-J.)
| | - Michael G Shlipak
- Department of Medicine, Epidemiology, and Biostatistics, University of California, San Francisco, and San Francisco VA Medical Center (M.G.S.)
| | - Latha P Palaniappan
- Center for Asian Health Research and Education and the Department of Medicine, Stanford University School of Medicine, CA (L.P.P.)
| | | | - Salim S Virani
- Department of Medicine, The Aga Khan University, Karachi, Pakistan; Texas Heart Institute and Baylor College of Medicine, Houston (S.S.V.)
| | - Katherine Tuttle
- Providence Medical Research Center, Providence Inland Northwest Health, Spokane, WA; Kidney Research Institute and Institute of Translational Health Sciences, University of Washington, Seattle (K.T.)
| | - Ian J Neeland
- UH Center for Cardiovascular Prevention, Translational Science Unit, Center for Integrated and Novel Approaches in Vascular-Metabolic Disease (CINEMA), Harrington Heart and Vascular Institute, University Hospitals Cleveland Medical Center, Case Western Reserve University School of Medicine, OH (I.J.N.)
| | - Sheryl L Chow
- Department of Pharmacy Practice and Administration, College of Pharmacy, Western University of Health Sciences, Pomona, CA (S.L.C.)
| | - Janani Rangaswami
- Washington DC VA Medical Center and George Washington University School of Medicine (J.R.)
| | - Michael J Pencina
- Department of Biostatistics, Duke University Medical Center, Durham, NC (M.J.P.)
| | - Chiadi E Ndumele
- Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD (C.E.N.)
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (K.M., Y.S., S.H.B., J.C.)
- Department of Population Health, New York University Grossman School of Medicine, New York, NY (Y.S., S.H.B., J.C.)
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Sebastian SA, Padda I, Johal G. Cardiovascular-Kidney-Metabolic (CKM) syndrome: A state-of-the-art review. Curr Probl Cardiol 2024; 49:102344. [PMID: 38103820 DOI: 10.1016/j.cpcardiol.2023.102344] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 12/13/2023] [Indexed: 12/19/2023]
Abstract
The correlation between obesity, type 2 diabetes mellitus (DM), cardiovascular disease (CVD), and chronic kidney disease (CKD) is an escalating and widely acknowledged epidemic in industrialized nations. Recently, this complex web of interrelated health conditions has been collectively defined as the Cardiovascular-Kidney-Metabolic (CKM) syndrome by the American Heart Association (AHA). The molecular mechanisms underlying CKM disease contain a spectrum of interconnected factors, including hyperglycemia, insulin resistance, heightened activity of the renin-angiotensin-aldosterone system (RAAS), the generation of advanced glycation end-products, oxidative stress, lipotoxicity, endoplasmic reticulum stress, abnormalities in calcium handling, malfunctioning of mitochondria and impaired energy production, as well as persistent chronic inflammation. Addressing their prevention, management, and treatment is of paramount importance to promote better patient health outcomes. The objective of this review is to provide a comprehensive and critical examination of the current state-of-the-art regarding the recently defined CKM syndrome. This includes an exploration of epidemiological evidence establishing connections between cardio-renal-metabolic diseases, an examination of the underlying pathophysiological mechanisms, and a comprehensive overview of existing treatment modalities.
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Affiliation(s)
| | - Inderbir Padda
- Department of Internal Medicine, Richmond University Medical Center/Mount Sinai, Staten Island, NY, USA
| | - Gurpreet Johal
- Department of Cardiology, Valley Medical Center, University of Washington, Seattle, USA
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Kanaya AM. Diabetes in South Asians: Uncovering Novel Risk Factors With Longitudinal Epidemiologic Data: Kelly West Award Lecture 2023. Diabetes Care 2024; 47:7-16. [PMID: 38117990 PMCID: PMC10733655 DOI: 10.2337/dci23-0068] [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: 09/07/2023] [Accepted: 10/03/2023] [Indexed: 12/22/2023]
Abstract
South Asian populations have a higher prevalence and earlier age of onset of type 2 diabetes and atherosclerotic cardiovascular diseases than other race and ethnic groups. To better understand the pathophysiology and multilevel risk factors for diabetes and cardiovascular disease, we established the Mediators of Atherosclerosis in South Asians Living in America (MASALA) study in 2010. The original MASALA study cohort (n = 1,164) included 83% Asian Indian immigrants, with an ongoing expansion of the study to include individuals of Bangladeshi and Pakistani origin. We have found that South Asian Americans in the MASALA study had higher type 2 diabetes prevalence, lower insulin secretion, more insulin resistance, and an adverse body composition with higher liver and intermuscular fat and lower lean muscle mass compared with four other U.S. race and ethnic groups. MASALA study participants with diabetes were more likely to have the severe hyperglycemia subtype, characterized by β-cell dysfunction and lower body weight, and this subtype was associated with a higher incidence of subclinical atherosclerosis. We have found several modifiable factors for cardiometabolic disease among South Asians including diet and physical activity that can be influenced using specific social network members and with cultural adaptations to the U.S. context. Longitudinal data with repeat cardiometabolic measures that are supplemented with qualitative and mixed-method approaches enable a deeper understanding of disease risk and resilience factors. Studying and contrasting Asian American subgroups can uncover the causes for cardiometabolic disease heterogeneity and reveal novel methods for prevention and treatment.
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Affiliation(s)
- Alka M. Kanaya
- Division of General Internal Medicine, Departments of Medicine, Epidemiology, and Biostatistics, University of California, San Francisco, San Francisco, CA
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Ndumele CE, Neeland IJ, Tuttle KR, Chow SL, Mathew RO, Khan SS, Coresh J, Baker-Smith CM, Carnethon MR, Després JP, Ho JE, Joseph JJ, Kernan WN, Khera A, Kosiborod MN, Lekavich CL, Lewis EF, Lo KB, Ozkan B, Palaniappan LP, Patel SS, Pencina MJ, Powell-Wiley TM, Sperling LS, Virani SS, Wright JT, Rajgopal Singh R, Elkind MSV, Rangaswami J. A Synopsis of the Evidence for the Science and Clinical Management of Cardiovascular-Kidney-Metabolic (CKM) Syndrome: A Scientific Statement From the American Heart Association. Circulation 2023; 148:1636-1664. [PMID: 37807920 DOI: 10.1161/cir.0000000000001186] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
A growing appreciation of the pathophysiological interrelatedness of metabolic risk factors such as obesity and diabetes, chronic kidney disease, and cardiovascular disease has led to the conceptualization of cardiovascular-kidney-metabolic syndrome. The confluence of metabolic risk factors and chronic kidney disease within cardiovascular-kidney-metabolic syndrome is strongly linked to risk for adverse cardiovascular and kidney outcomes. In addition, there are unique management considerations for individuals with established cardiovascular disease and coexisting metabolic risk factors, chronic kidney disease, or both. An extensive body of literature supports our scientific understanding of, and approach to, prevention and management for individuals with cardiovascular-kidney-metabolic syndrome. However, there are critical gaps in knowledge related to cardiovascular-kidney-metabolic syndrome in terms of mechanisms of disease development, heterogeneity within clinical phenotypes, interplay between social determinants of health and biological risk factors, and accurate assessments of disease incidence in the context of competing risks. There are also key limitations in the data supporting the clinical care for cardiovascular-kidney-metabolic syndrome, particularly in terms of early-life prevention, screening for risk factors, interdisciplinary care models, optimal strategies for supporting lifestyle modification and weight loss, targeting of emerging cardioprotective and kidney-protective therapies, management of patients with both cardiovascular disease and chronic kidney disease, and the impact of systematically assessing and addressing social determinants of health. This scientific statement uses a crosswalk of major guidelines, in addition to a review of the scientific literature, to summarize the evidence and fundamental gaps related to the science, screening, prevention, and management of cardiovascular-kidney-metabolic syndrome.
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Araújo LR, Orefice JL, Gonçalves MA, Guimarães NS, Soares AN, Salomon T, de Souza AH. Use of digital retinography to detect vascular changes in pre-diabetic patients: a cross-sectional study. Diabetol Metab Syndr 2023; 15:225. [PMID: 37926814 PMCID: PMC10626765 DOI: 10.1186/s13098-023-01154-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Accepted: 08/22/2023] [Indexed: 11/07/2023] Open
Abstract
BACKGROUND Diabetic retinopathy (DR) is a common complication of DM and may go unnoticed until irreversible damage occurs. Its screening can contribute to the early detection. Although, there are no studies which investigate the ability of digital retinography to detect vascular changes in pre-diabetic patients. OBJECTIVE Identify the prevalence and severity of RD in patients with pre-diabetes. METHODS Cross-sectionalstudy carried out in a sample of patients with pre-diabetes and weight excess characterized from January 2020 to April 2023. Sociodemographic and clinical variables were collected, in addition to lifestyle habits. Retinographic evaluation was also performed using a Digital Retinography. For the analysis of all variables, the adopted significance level was 5%. The software used for the analysis was SPSS version 25.0. RESULTS Of 108 patients selected 7.1% have alteration in the exam indicating DR. Among the participants with diabetic retinopathy, four had the moderate form (50%), three the moderate form (37%) and only one participant had the severe form (13%). CONCLUSIONS Our findings highlight the importance of preventive measures and adequate control of these conditions in pre-diabetic patients, in order to prevent or delay the progression of diabetic retinopathy and, consequently, reduce the risk of blindness and other ocular complications.
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Affiliation(s)
- Levimar Rocha Araújo
- Faculdade de Ciências Médicas de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | | | | | | | - Aleida Nazareth Soares
- Faculdade de Ciências Médicas de Minas Gerais and Faculdade de Saúde Santa Casa BH, Belo Horizonte, Brazil
| | - Tassila Salomon
- Faculdade de Ciências Médicas de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
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O’Brien MJ, Zhang Y, Bailey SC, Khan SS, Ackermann RT, Ali MK, Bowen ME, Benoit SR, Imperatore G, Holliday CS, McKeever Bullard K. Clinical performance and health equity implications of the American Diabetes Association's 2023 screening recommendation for prediabetes and diabetes. Front Endocrinol (Lausanne) 2023; 14:1279348. [PMID: 37900145 PMCID: PMC10611495 DOI: 10.3389/fendo.2023.1279348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 09/21/2023] [Indexed: 10/31/2023] Open
Abstract
Introduction The American Diabetes Association (ADA) recommends screening for prediabetes and diabetes (dysglycemia) starting at age 35, or younger than 35 years among adults with overweight or obesity and other risk factors. Diabetes risk differs by sex, race, and ethnicity, but performance of the recommendation in these sociodemographic subgroups is unknown. Methods Nationally representative data from the National Health and Nutrition Examination Surveys (2015-March 2020) were analyzed from 5,287 nonpregnant US adults without diagnosed diabetes. Screening eligibility was based on age, measured body mass index, and the presence of diabetes risk factors. Dysglycemia was defined by fasting plasma glucose ≥100mg/dL (≥5.6 mmol/L) or haemoglobin A1c ≥5.7% (≥39mmol/mol). The sensitivity, specificity, and predictive values of the ADA screening criteria were examined by sex, race, and ethnicity. Results An estimated 83.1% (95% CI=81.2-84.7) of US adults were eligible for screening according to the 2023 ADA recommendation. Overall, ADA's screening criteria exhibited high sensitivity [95.0% (95% CI=92.7-96.6)] and low specificity [27.1% (95% CI=24.5-29.9)], which did not differ by race or ethnicity. Sensitivity was higher among women [97.8% (95% CI=96.6-98.6)] than men [92.4% (95% CI=88.3-95.1)]. Racial and ethnic differences in sensitivity and specificity among men were statistically significant (P=0.04 and P=0.02, respectively). Among women, guideline performance did not differ by race and ethnicity. Discussion The ADA screening criteria exhibited high sensitivity for all groups and was marginally higher in women than men. Racial and ethnic differences in guideline performance among men were small and unlikely to have a significant impact on health equity. Future research could examine adoption of this recommendation in practice and examine its effects on treatment and clinical outcomes by sex, race, and ethnicity.
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Affiliation(s)
- Matthew J. O’Brien
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
- Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
- Chicago Center for Diabetes Translation Research, Northwestern University Feinberg School of Medicine and University of Chicago Pritzker School of Medicine, Chicago, IL, United States
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
| | - Yan Zhang
- Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Stacy C. Bailey
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
- Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
| | - Sadiya S. Khan
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
| | - Ronald T. Ackermann
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
- Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
- Chicago Center for Diabetes Translation Research, Northwestern University Feinberg School of Medicine and University of Chicago Pritzker School of Medicine, Chicago, IL, United States
| | - Mohammed K. Ali
- Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, United States
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, United States
- Department of Family and Preventive Medicine, School of Medicine, Emory University, Atlanta, GA, United States
| | - Michael E. Bowen
- Division of General Internal Medicine, Department of Medicine, University of Texas Southwestern Medical Center, Dallas, TX, United States
- Peter O’Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Stephen R. Benoit
- Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Giuseppina Imperatore
- Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Christopher S. Holliday
- Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Kai McKeever Bullard
- Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, United States
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