1
|
Mohammedi K, Hess S, McQueen M, Pigeyre M, Lee SF, Pare G, Gerstein HC. Determinants of serious health outcome-free status in middle-aged and older people with dysglycaemia: Exploratory analysis of the ORIGIN trial. Diabetes Obes Metab 2024; 26:3272-3280. [PMID: 38747213 DOI: 10.1111/dom.15654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Revised: 04/25/2024] [Accepted: 04/29/2024] [Indexed: 07/10/2024]
Abstract
AIM To assess clinical and biochemical measurements that can identify people with dysglycaemia (i.e. diabetes or pre-diabetes) who remain free of serious outcomes during follow-up. MATERIALS AND METHODS We conducted exploratory analyses using data from the Outcomes Reduction with an Initial Glargine Intervention (ORIGIN) study to identify independent determinants of outcome-free status in 12 537 middle-aged and older adults with prediabetes and early type 2 diabetes from 40 countries. Serious outcome-free status was defined as the absence of major cardiovascular outcomes, kidney or retinal outcomes, peripheral artery disease, dementia, cancer, any hospitalization, or death during follow-up. RESULTS In total, 3328 (26.6%) participants remained free of serious outcomes during a median follow-up of 6.2 years (IQR 5.8, 6.7). Independent clinical determinants of outcome-free status included younger age, female sex, non-White ethnicity, shorter diabetes duration, absence of previous cardiovascular disease, current or former smokers, higher grip strength, Mini-Mental State Examination score, and ankle-brachial index, lower body mass index and kidney disease index, and non-use of renin-angiotensin system drugs and beta-blockers. In a subset of 8401 people with baseline measurements of 238 biomarkers, growth differentiation factor 15, kidney injury molecule-1, N-terminal pro-brain natriuretic peptide, uromodulin, C-reactive protein, factor VII and ferritin were independent determinants. The combination of clinical determinants and biomarkers best identified participants who remained outcome-free (C-statistics 0.71, 95% confidence interval 0.70-0.73; net reclassification improvement 0.55, 95% confidence interval 0.48-0.58). CONCLUSIONS A set of routinely measured clinical characteristics and seven protein biomarkers identify middle-aged and older people with prediabetes or early type 2 diabetes as least likely to experience serious outcomes during follow-up.
Collapse
Affiliation(s)
- Kamel Mohammedi
- Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton, Canada
- Université de Bordeaux, INSERM, BMC, U1034, Avenue de Magellan, Pessac, France
| | - Sibylle Hess
- Sanofi, Global Medical Diabetes, Frankfurt, Germany
| | - Matthew McQueen
- Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton, Canada
| | - Marie Pigeyre
- Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton, Canada
| | - Shun Fu Lee
- Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton, Canada
| | - Guillaume Pare
- Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton, Canada
| | - Hertzel C Gerstein
- Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton, Canada
| |
Collapse
|
2
|
Li H, Ren Y, Duan Y, Li P, Bian Y. Association of the longitudinal trajectory of urinary albumin/creatinine ratio in diabetic patients with adverse cardiac event risk: a retrospective cohort study. Front Endocrinol (Lausanne) 2024; 15:1355149. [PMID: 38745945 PMCID: PMC11091466 DOI: 10.3389/fendo.2024.1355149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Accepted: 02/26/2024] [Indexed: 05/16/2024] Open
Abstract
Objective The baseline urinary albumin/creatinine ratio (uACR) has been proven to be significantly associated with the risk of major adverse cardiac events (MACE). However, data on the association between the longitudinal trajectory patterns of uACR, changes in glycated hemoglobin A1c (HbA1c), and the subsequent risk of MACE in patients with diabetes are sparse. Methods This is a retrospective cohort study including 601 patients with type 2 diabetes mellitus (T2DM; uACR < 300 mg/g) admitted to The First Hospital of Shanxi Medical University and The Second Hospital of Shanxi Medical University from January 2015 to December 2018. The uACR index was calculated as urinary albumin (in milligrams)/creatinine (in grams), and latent mixed modeling was used to identify the longitudinal trajectory of uACR during the exposure period (2016-2020). The deadline for follow-up was December 31, 2021. The primary outcome was the MACE [a composite outcome of cardiogenic death, hospitalization related to heart failure (HHF), non-fatal acute myocardial infarction, non-fatal stroke, and acute renal injury/dialysis indications]. The Kaplan-Meier survival analysis curve was used to compare the risk of MACE among four groups, while univariate and multivariate Cox proportional hazards models were employed to calculate the hazard ratio (HR) and 95% confidence interval (CI) for MACE risk among different uACR or HbA1c trajectory groups. The predictive performance of the model, both before and after the inclusion of changes in the uACR and HbA1c, was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). Results Four distinct uACR trajectories were identified, namely, the low-stable group (uACR = 5.2-38.3 mg/g, n = 112), the moderate-stable group (uACR = 40.4-78.6 mg/g, n = 229), the high-stable group (uACR = 86.1-153.7 mg/g, n = 178), and the elevated-increasing group (uACR = 54.8-289.4 mg/g, n = 82). In addition, five distinct HbA1c trajectories were also identified: the low-stable group (HbA1c = 5.5%-6.8%, n = 113), the moderate-stable group (HbA1c = 6.0%-7.9%, n = 169), the moderate-decreasing group (HbA1c = 7.4%-6.1%, n = 67), the high-stable group (HbA1c = 7.7%-8.9%, n = 158), and the elevated-increasing group (HbA1c = 8.4%-10.3%, n = 94). Compared with the low-stable uACR group, patients in the high-stable and elevated-increasing uACR groups were more likely to be older, current smokers, and have a longer DM course, higher levels of 2-h plasma glucose (PG), HbA1c, N-terminal pro-B-type natriuretic peptide (NT-proBNP), uACR, and left ventricular mass index (LVMI), while featuring a higher prevalence of hypertension and a lower proportion of β-receptor blocker treatment (p < 0.05). During a median follow-up of 45 months (range, 24-57 months), 118 cases (19.6%) of MACE were identified, including 10 cases (1.7%) of cardiogenic death, 31 cases (5.2%) of HHF, 35 cases (5.8%) of non-fatal acute myocardial infarction (AMI), 18 cases (3.0%) of non-fatal stroke, and 24 cases (4.0%) of acute renal failure/dialysis. The Kaplan-Meier survival curve showed that, compared with that in the low-stable uACR group, the incidence of MACE in the high-stable (HR = 1.337, 95% CI = 1.083-1.652, p = 0.007) and elevated-increasing (HR = 1.648, 95% CI = 1.139-2.387, p = 0.009) uACR groups significantly increased. Similar results were observed for HHF, non-fatal AMI, and acute renal injury/dialysis indications (p < 0.05). The multivariate Cox proportional hazards models indicated that, after adjusting for potential confounders, the HRs for the risk of MACE were 1.145 (p = 0.132), 1.337 (p = 0.007), and 1.648 (p = 0.009) in the moderate-stable, high-stable, and elevated-increasing uACR groups, respectively. In addition, the HRs for the risk of MACE were 1.203 (p = 0.028), 0.872 (p = 0.024), 1.562 (p = 0.033), and 2.218 (p = 0.002) in the moderate-stable, moderate-decreasing, high-stable, and elevated-increasing groups, respectively. The ROC curve showed that, after adding uACR, HbA1c, or both, the AUCs were 0.773, 0.792, and 0.826, which all signified statistically significant improvements (p = 0.021, 0.035, and 0.019, respectively). Conclusion A long-term elevated uACR is associated with a significantly increased risk of MACE in patients with diabetes. This study implies that regular monitoring of uACR could be helpful in identifying diabetic patients with a higher risk of MACE.
Collapse
Affiliation(s)
- Hui Li
- Department of Cardiology, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Yajuan Ren
- Department of Cardiology, Second Hospital of Shanxi Medical University, Taiyuan, China
| | - Yongguang Duan
- Department of Cardiology, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Peng Li
- Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Yunfei Bian
- Department of Cardiology, Second Hospital of Shanxi Medical University, Taiyuan, China
| |
Collapse
|
3
|
Gerstein HC, Mian R, Ramasundarahettige C, Branch KRH, Del Prato S, Lam CSP, Lopes RD, Pratley R, Rosenstock J, Sattar N. Cardiovascular and renal outcomes with varying degrees of kidney disease in high-risk people with type 2 diabetes: An epidemiological analysis of data from the AMPLITUDE-O trial. Diabetes Obes Metab 2024; 26:1216-1223. [PMID: 38116691 DOI: 10.1111/dom.15417] [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: 10/10/2023] [Revised: 11/30/2023] [Accepted: 12/01/2023] [Indexed: 12/21/2023]
Abstract
AIMS To estimate the incidence of a major adverse cardiovascular event (MACE) and a composite kidney outcome across estimated glomerular filtration rate (eGFR) and urine albumin-to-creatinine ratio (UACR) levels, and to determine whether efpeglenatide's effect varies with these indices. MATERIALS AND METHODS AMPLITUDE-O trial data were used to estimate the relationship of eGFR, UACR, and Kidney Disease Improving Global Outcomes (KDIGO) category to the hazard of MACE and the kidney composite. Interactions on these outcomes between eGFR and the UACR, and between each of these variables and efpeglenatide were also assessed. RESULTS Baseline eGFR and UACR were available for 3983 participants (mean age 64.5 years). During a median follow-up of 1.8 years, the hazards of MACE and the kidney composite for the lowest versus highest eGFR third were 1.6 (95% confidence interval [CI] 1.2, 2.2) and 2.3 (95% CI 1.9, 2.8), respectively. The hazards for the highest versus the lowest UACR third were 2.3 (95% CI 1.8, 3.1) and 18.0 (95% CI 12.7, 25.5), respectively, and for the high- versus low-risk KDIGO categories the hazards were 2.4 (95% CI 1.8, 3.1) and 16.0 (95% CI 11.6, 22.0), respectively. eGFR and UACR were independent determinants of both outcomes, but negatively interacted with each other for the kidney outcome. Efpeglenatide's effect on both outcomes did not vary with any kidney disease measure (all interaction p values ≥0.26). CONCLUSIONS In high-risk people with diabetes, eGFR, UACR, and KDIGO category have different relationships to incident cardiovascular and kidney outcomes. The beneficial effect of efpeglenatide on these outcomes is independent of kidney-related risk category.
Collapse
Affiliation(s)
- Hertzel C Gerstein
- Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton, Ontario, Canada
- Department of Medicine, Master University, Hamilton, Ontario, Canada
| | - Rajibul Mian
- Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton, Ontario, Canada
| | | | - Kelley R H Branch
- Division of Cardiology, University of Washington, Seattle, Washington, USA
| | - Stefano Del Prato
- Interdisciplinary Research Center "Health Science" of the Sant'Anna School of Advanced Studies, Pisa, Italy
| | - Carolyn S P Lam
- National Heart Centre Singapore and Duke-National University of Singapore, Singapore, Singapore
| | - Renato D Lopes
- Duke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina, USA
| | - Richard Pratley
- AdventHealth Translational Research Institute, Orlando, Florida, USA
| | | | - Naveed Sattar
- School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK
| |
Collapse
|
4
|
Zeng C, Liu M, Zhang Y, Deng S, Xin Y, Hu X. Association of Urine Albumin to Creatinine Ratio With Cardiovascular Outcomes in Patients With Type 2 Diabetes Mellitus. J Clin Endocrinol Metab 2024; 109:1080-1093. [PMID: 37922304 PMCID: PMC10940266 DOI: 10.1210/clinem/dgad645] [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: 08/23/2023] [Revised: 10/13/2023] [Accepted: 10/27/2023] [Indexed: 11/05/2023]
Abstract
CONTEXT The urinary albumin to creatinine ratio (UACR) is a widely used indicator of albuminuria and has predictive value for adverse cardiovascular events. OBJECTIVE To evaluate the correlation between the UACR and the risk of developing major adverse cardiovascular events (MACEs) and total mortality in patients with type 2 diabetes mellitus (T2DM). METHODS This post hoc analysis included 10 171 participants from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study and the ACCORD follow-up study (ACCORDION) with baseline UACR data. The natural logarithm (ln) of each UACR measurement was calculated. Univariate and multivariate Cox proportional hazard regression analyses were conducted to examine the association between the UACR and the risk of MACEs and total mortality. The additional predictive value of UACR was further evaluated. Similar methods were used to analyze the correlation between the UACR and MACEs and total mortality within the normal range. RESULTS During a median follow-up period of 8.83 years, 1808 (17.78%) participants experienced MACEs, and there were 1934 (19.01%) total deaths. After adjusting for traditional cardiovascular risk factors, the multivariate analysis revealed a significant association between the UACR and the risk of MACEs and total mortality. The inclusion of UACR in the conventional risk model enhanced the predictive efficacy for MACEs and total mortality. CONCLUSION An elevated UACR is associated with a higher risk of MACEs and total mortality in patients with T2DM, even when it falls within the normal range. The UACR improves prediction of MACE and total mortality risk in patients with T2DM.
Collapse
Affiliation(s)
- Cheng Zeng
- Department of Cardiology, The Second Xiangya Hospital of Central South University, No. 139, Middle Ren-min Road, Changsha 410011, Hunan Province, People's Republic of China
| | - Maojun Liu
- Department of Cardiology, The Second Xiangya Hospital of Central South University, No. 139, Middle Ren-min Road, Changsha 410011, Hunan Province, People's Republic of China
| | - Yifeng Zhang
- Department of Cardiology, The Second Xiangya Hospital of Central South University, No. 139, Middle Ren-min Road, Changsha 410011, Hunan Province, People's Republic of China
| | - Simin Deng
- Department of Cardiology, The Second Xiangya Hospital of Central South University, No. 139, Middle Ren-min Road, Changsha 410011, Hunan Province, People's Republic of China
| | - Ying Xin
- Department of Cardiology, The Second Xiangya Hospital of Central South University, No. 139, Middle Ren-min Road, Changsha 410011, Hunan Province, People's Republic of China
| | - Xinqun Hu
- Department of Cardiology, The Second Xiangya Hospital of Central South University, No. 139, Middle Ren-min Road, Changsha 410011, Hunan Province, People's Republic of China
| |
Collapse
|
5
|
Lin W, Mousavi F, Blum BC, Heckendorf CF, Moore J, Lampl N, McComb M, Kotelnikov S, Yin W, Rabhi N, Layne MD, Kozakov D, Chitalia VC, Emili A. Integrated metabolomics and proteomics reveal biomarkers associated with hemodialysis in end-stage kidney disease. Front Pharmacol 2023; 14:1243505. [PMID: 38089059 PMCID: PMC10715419 DOI: 10.3389/fphar.2023.1243505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 11/13/2023] [Indexed: 02/25/2024] Open
Abstract
Background: We hypothesize that the poor survival outcomes of end-stage kidney disease (ESKD) patients undergoing hemodialysis are associated with a low filtering efficiency and selectivity. The current gold standard criteria using single or several markers show an inability to predict or disclose the treatment effect and disease progression accurately. Methods: We performed an integrated mass spectrometry-based metabolomic and proteomic workflow capable of detecting and quantifying circulating small molecules and proteins in the serum of ESKD patients. Markers linked to cardiovascular disease (CVD) were validated on human induced pluripotent stem cell (iPSC)-derived cardiomyocytes. Results: We identified dozens of elevated molecules in the serum of patients compared with healthy controls. Surprisingly, many metabolites, including lipids, remained at an elevated blood concentration despite dialysis. These molecules and their associated physical interaction networks are correlated with clinical complications in chronic kidney disease. This study confirmed two uremic toxins associated with CVD, a major risk for patients with ESKD. Conclusion: The retained molecules and metabolite-protein interaction network address a knowledge gap of candidate uremic toxins associated with clinical complications in patients undergoing dialysis, providing mechanistic insights and potential drug discovery strategies for ESKD.
Collapse
Affiliation(s)
- Weiwei Lin
- Center for Network Systems Biology, Boston University, Boston, MA, United States
- Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States
| | - Fatemeh Mousavi
- Center for Network Systems Biology, Boston University, Boston, MA, United States
| | - Benjamin C. Blum
- Center for Network Systems Biology, Boston University, Boston, MA, United States
- Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States
| | - Christian F. Heckendorf
- Center for Network Systems Biology, Boston University, Boston, MA, United States
- Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States
| | - Jarrod Moore
- Center for Network Systems Biology, Boston University, Boston, MA, United States
- Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States
| | - Noah Lampl
- Center for Network Systems Biology, Boston University, Boston, MA, United States
- Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States
| | - Mark McComb
- Center for Network Systems Biology, Boston University, Boston, MA, United States
- Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States
| | - Sergei Kotelnikov
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, United States
| | - Wenqing Yin
- Renal Section, Department of Medicine, Boston University School of Medicine, Boston, MA, United States
| | - Nabil Rabhi
- Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States
| | - Matthew D. Layne
- Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States
| | - Dima Kozakov
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, United States
| | - Vipul C. Chitalia
- Renal Section, Department of Medicine, Boston University School of Medicine, Boston, MA, United States
- Veterans Affairs Boston Healthcare System, Boston, MA, United States
- Institute of Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Andrew Emili
- Center for Network Systems Biology, Boston University, Boston, MA, United States
- Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States
- Department of Biology, Boston University, Boston, MA, United States
| |
Collapse
|
6
|
Fang S, Chen Y, Gao Q, Wei Q. Association of kidney disease index with all-cause and cardiovascular mortality among individuals with hypertension. Clin Cardiol 2023; 46:1442-1449. [PMID: 37605511 PMCID: PMC10642315 DOI: 10.1002/clc.24131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 07/31/2023] [Accepted: 08/10/2023] [Indexed: 08/23/2023] Open
Abstract
BACKGROUND This study aimed to investigate the association between a novel kidney disease index (KDI), which combines information from both estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (uACR), and all-cause and cardiovascular disease (CVD) mortality among individuals with hypertension. METHODS We analyzed data from 19 988 adults with hypertension who participated in the National Health and Nutrition Examination Survey from 1999 to 2018. Mortality outcomes were determined by linking to National Death Index records through December 31, 2019. Cox proportional hazards models were used to estimate hazard ratios and 95% confidence intervals for all-cause and CVD mortality. RESULTS Baseline KDI levels were positively associated with glucose, insulin resistance, hemoglobin A1c, triglycerides, and C-reactive protein (p value for trend <.05). During a follow-up period of 179 859 person-years, a total of 5069 deaths were documented, including 1741 from cardiovascular causes. After multivariable adjustment, each standard deviation increment in KDI level was associated with a 27% increased risk of all-cause mortality and a 31% increased risk of cardiovascular deaths (both p < .05). Further analysis showed a J-shaped association between KDI and mortality, with the risk increasing dramatically when KDI exceeded 0.27. CONCLUSION Elevated KDI levels were significantly associated with increased mortality from all causes and CVD among individuals with hypertension. We recommend routine testing of eGFR and uACR in hypertensive patients, and using KDI as a tool to identify individuals who are most likely to benefit from preventive therapies.
Collapse
Affiliation(s)
- Suxia Fang
- Department of Cardiology, Linping Campus, Second Affiliated HospitalZhejiang University School of MedicineHangzhouChina
| | - Yuwen Chen
- Department of Cardiology, Second Affiliated HospitalZhejiang University School of MedicineHangzhouChina
| | - Qiyue Gao
- Department of Cardiology, Second Affiliated HospitalZhejiang University School of MedicineHangzhouChina
| | - Qucheng Wei
- Department of Cardiology, Second Affiliated HospitalZhejiang University School of MedicineHangzhouChina
| |
Collapse
|
7
|
Lin X, Song W, Zhou Y, Gao Y, Wang Y, Wang Y, Liu Y, Deng L, Liao Y, Wu B, Chen S, Chen L, Fang Y. Elevated urine albumin creatinine ratio increases cardiovascular mortality in coronary artery disease patients with or without type 2 diabetes mellitus: a multicenter retrospective study. Cardiovasc Diabetol 2023; 22:203. [PMID: 37563647 PMCID: PMC10416404 DOI: 10.1186/s12933-023-01907-3] [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: 05/09/2023] [Accepted: 06/29/2023] [Indexed: 08/12/2023] Open
Abstract
BACKGROUND Albuminuria has been suggested as an atherosclerotic risk factor among the general population. However, whether this association will be amplified in patients with coronary artery disease (CAD) is unknown. It is also unknown whether diabetes mellitus confounds the association. We aim to analyse the prognosis of elevated urine albumin creatinine ratio (uACR) in the CAD population with or without type 2 diabetes mellitus (T2DM). METHODS This multi-center registry cohort study included 5,960 patients with CAD. Patients were divided into T2DM and non-T2DM group, and baseline uACR levels were assessed on three grades (low: uACR < 10 mg/g, middle: 10 mg/g ≤ uACR < 30 mg/g, and high: uACR ≥ 30 mg/g). The study endpoints were cardiovascular mortality and all-cause mortality. RESULTS During the median follow-up of 2.2 [1.2-3.1] years, 310 (5.2%) patients died, of which 236 (4.0%) patients died of cardiovascular disease. CAD patients with elevated uACR had a higher risk of cardiovascular mortality (middle: HR, 2.32; high: HR, 3.22) than those with low uACR, as well as all-cause mortality. Elevated uACR increased nearly 1.5-fold risk of cardiovascular mortality (middle: HR, 2.33; high: HR, 2.34) among patients without T2DM, and increased 1.5- fold to 3- fold risk of cardiovascular mortality in T2DM patients (middle: HR, 2.49; high: HR, 3.98). CONCLUSIONS Even mildly increased uACR could increase the risk of cardiovascular mortality in patients with CAD, especially when combined with T2DM.
Collapse
Affiliation(s)
- Xueqin Lin
- Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, China
| | - Wei Song
- Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, China
| | - Yang Zhou
- Department of Cardiology, Guangdong Provincial People's Hospital, Guangdong Cardiovascular Institute, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China
- Department of Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Cardiovascular Institute, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China
| | - Yuwei Gao
- Jinan university, Zhuhai people's hospital, Guangzhou, 510100, China
| | - Yani Wang
- Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, China
| | - Yun Wang
- Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, China
| | - Yuchen Liu
- Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, China
| | - Lin Deng
- Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, China
| | - Yin Liao
- Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, China
| | - Bo Wu
- Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, China
| | - Shiqun Chen
- Global Health Research Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Science, Guangzhou, 510100, China.
| | - Liling Chen
- Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, China.
| | - Yong Fang
- Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, China.
| |
Collapse
|