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Yu J, Zhang K, Chen T, Lin R, Chen Q, Chen C, Tong M, Chen J, Yu J, Lou Y, Xu P, Zhong C, Chen Q, Sun K, Liu L, Cao L, Zheng C, Wang P, Chen Q, Yang Q, Chen W, Wang X, Yan Z, Zhang X, Cui W, Chen L, Zhang Z, Zhang G. Temporal patterns of organ dysfunction in COVID-19 patients hospitalized in the intensive care unit: A group-based multitrajectory modeling analysis. Int J Infect Dis 2024; 144:107045. [PMID: 38604470 DOI: 10.1016/j.ijid.2024.107045] [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: 12/29/2023] [Revised: 03/19/2024] [Accepted: 04/07/2024] [Indexed: 04/13/2024] Open
Abstract
BACKGROUND The course of organ dysfunction (OD) in Corona Virus Disease 2019 (COVID-19) patients is unknown. Herein, we analyze the temporal patterns of OD in intensive care unit-admitted COVID-19 patients. METHODS Sequential organ failure assessment scores were evaluated daily within 2 weeks of admission to determine the temporal trajectory of OD using group-based multitrajectory modeling (GBMTM). RESULTS A total of 392 patients were enrolled with a 28-day mortality rate of 53.6%. GBMTM identified four distinct trajectories. Group 1 (mild OD, n = 64), with a median APACHE II score of 13 (IQR 9-21), had an early resolution of OD and a low mortality rate. Group 2 (moderate OD, n = 140), with a median APACHE II score of 18 (IQR 13-22), had a 28-day mortality rate of 30.0%. Group 3 (severe OD, n = 117), with a median APACHR II score of 20 (IQR 13-27), had a deterioration trend of respiratory dysfunction and a 28-day mortality rate of 69.2%. Group 4 (extremely severe OD, n = 71), with a median APACHE II score of 20 (IQR 17-27), had a significant and sustained OD affecting all organ systems and a 28-day mortality rate of 97.2%. CONCLUSIONS Four distinct trajectories of OD were identified, and respiratory dysfunction trajectory could predict nonpulmonary OD trajectories and patient prognosis.
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Affiliation(s)
- Jiafei Yu
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, China; Department of Critical Care Medicine, Haiyan People's Hospital, Zhejiang 314300, China
| | - Kai Zhang
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Tianqi Chen
- Department of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, 310016, China
| | - Ronghai Lin
- Department of Critical Care Medicine, Taizhou Municipal Hospital, Zhejiang, 318000, China
| | - Qijiang Chen
- Intensive Care Unit, Ninghai First Hospital, Zhejiang, 315600, China
| | - Chensong Chen
- Intensive Care Unit, Xiangshan First People's Hospital Medical and Health Group, Zhejiang, 315700, China
| | - Minfeng Tong
- Department of Neurosurgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Zhejiang, 321000, China
| | - Jianping Chen
- Department of Emergency Medicine, Dongyang People' Hospital of Wenzhou Medical University, Zhejiang, 322100, China
| | - Jianhua Yu
- Department of Critical Care Medicine, Longquan People's Hospital, Zhejiang, 323700, China
| | - Yuhang Lou
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Panpan Xu
- Department of Critical Care Medicine, Taizhou Municipal Hospital, Zhejiang, 318000, China
| | - Chao Zhong
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, China; Intensive Care Unit, Ninghai First Hospital, Zhejiang, 315600, China
| | - Qianfeng Chen
- Intensive Care Unit, Xiangshan First People's Hospital Medical and Health Group, Zhejiang, 315700, China
| | - Kangwei Sun
- Department of Emergency Medicine, Dongyang People' Hospital of Wenzhou Medical University, Zhejiang, 322100, China
| | - Liyuan Liu
- Department of Critical Care Medicine, Longquan People's Hospital, Zhejiang, 323700, China
| | - Lanxin Cao
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Cheng Zheng
- Department of Critical Care Medicine, Taizhou Municipal Hospital, Zhejiang, 318000, China
| | - Ping Wang
- Intensive Care Unit, Ninghai First Hospital, Zhejiang, 315600, China
| | - Qitao Chen
- Department of Neurosurgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Zhejiang, 321000, China
| | - Qianqian Yang
- Department of Neurosurgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Zhejiang, 321000, China
| | - Weiting Chen
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, China; Department of Emergency and Intensive Care Unit, The First People's Hospital of Linhai, Taizhou, Zhejiang 317000, China
| | - Xiaofang Wang
- Department of Cardiovascular Surgery, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Zuxi Yan
- Department of Critical Care Medicine, Haiyan People's Hospital, Zhejiang 314300, China
| | - Xuefeng Zhang
- Department of Critical Care Medicine, Second Affiliated Hospital, Jiaxing College School of Medicine, Jiaxing 314031, China
| | - Wei Cui
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Lin Chen
- Department of Neurosurgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Zhejiang, 321000, China
| | - Zhongheng Zhang
- Department of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, 310016, China
| | - Gensheng Zhang
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, China; Key Laboratory of Multiple Organ Failure (Zhejiang University), Ministry of Education, Hangzhou 310009, China.
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Seki M, Nakano T, Tanaka S, Kitamura H, Hiyamuta H, Ninomiya T, Tsuruya K, Kitazono T. Associations between the Serum Triglyceride Level and Kidney Outcome in Patients with Chronic Kidney Disease: The Fukuoka Kidney disease Registry Study. J Atheroscler Thromb 2024:64625. [PMID: 38735756 DOI: 10.5551/jat.64625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/14/2024] Open
Abstract
AIMS Hypertriglyceridemia is a risk factor for chronic kidney disease (CKD). However, whether or not it predicts the risk of CKD progression is unknown. This study evaluated the association between serum triglyceride (TG) levels and kidney disease progression in patients with non-dialysis-dependent CKD. METHODS The Fukuoka Kidney disease Registry (FKR) study was a multicenter, prospective longitudinal cohort study. In total, 4,100 patients with CKD were followed up for 5 years. The primary outcome was the incidence of CKD progression, defined as a ≥ 1.5-fold increase in serum creatinine level or the development of end-stage kidney disease. The patients were divided into quartiles according to baseline serum TG levels under non-fasting conditions: Q1 <87 mg/dL; Q2, 87-120 mg/dL; Q3, 121-170 mg/dL, and Q4 >170 mg/dL. RESULTS During the 5-year observation period, 1,410 patients met the criteria for CKD progression. The multivariable-adjusted Cox proportional hazards model showed a significant association between high serum TG level and the risk of CKD progression in the model without macroalbuminuria as a covariate (multivariable hazard ratio[HR] for Q4 versus Q1, 1.20; 95% CI, 1.03-1.41; P=0.022), but the significance disappeared after adjusting for macroalbuminuria (HR for Q4 versus Q1, 1.06; 95% CI, 0.90-1.24; P=0.507). CONCLUSIONS The present findings suggest that individuals with high serum TG levels are more likely to develop CKD progression than those without; however, whether or not higher serum TG levels reflect elevated macroalbuminuria or lead to CKD progression via elevated macroalbuminuria is unclear.
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Affiliation(s)
- Mai Seki
- Department of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University
| | - Toshiaki Nakano
- Department of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University
| | - Shigeru Tanaka
- Department of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University
| | | | - Hiroto Hiyamuta
- Department of Internal Medicine, Faculty of Medicine, Division of Nephrology and Rheumatology, Fukuoka University
| | - Toshiharu Ninomiya
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences Kyushu University
| | | | - Takanari Kitazono
- Department of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University
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Zhou H, Ding X, Lan Y, Chen S, Wu S, Wu D. Multi-trajectories of triglyceride-glucose index and lifestyle with Cardiovascular Disease: a cohort study. Cardiovasc Diabetol 2023; 22:341. [PMID: 38093279 PMCID: PMC10720233 DOI: 10.1186/s12933-023-02076-z] [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: 09/07/2023] [Accepted: 11/27/2023] [Indexed: 12/17/2023] Open
Abstract
BACKGROUND Previous studies using trajectory models focused on examining the longitudinal changes in triglyceride-glucose (TyG) levels and lifestyle scores separately, without exploring the joint evolution of these two factors. This study aimed to identify the multi-trajectories of TyG levels and lifestyle scores and assess their association with the risk of cardiovascular disease (CVD). METHODS The study enrolled 47,384 participants from three health surveys of the Kailuan Study. The TyG index was computed as Ln [fasting triglycerides (mg/dL) × fasting blood glucose (mg/dL)/2], and the lifestyle scores were derived from five factors, including smoking, alcohol consumption, physical activity, sedentary behaviors, and salt intake. A group-based multi-trajectory model was adopted to identify multi-trajectories of TyG levels and lifestyle scores. The association of identified multi-trajectories with incident CVD was examined using Cox proportional hazard model. RESULTS Five distinct multi-trajectories of TyG levels and lifestyle scores were identified. During a median follow-up period of 10.98 years, 3042 participants developed CVD events (2481 strokes, 616 myocardial infarctions, and 55 co-current stroke and myocardial infarctions). In comparison to group 3 with the lowest TyG levels and the best lifestyle scores, the highest CVD risk was observed in group 5 characterized by the highest TyG levels and moderate lifestyle scores (HR = 1.76, 95% CI: 1.50-2.05). Group 2 with higher TyG levels and the poorest lifestyle scores had a 1.45-fold (95% CI 1.26-1.66) risk of CVD, and group 1 with lower TyG levels and poorer lifestyle scores had a 1.33-fold (95% CI 1.17-1.50) risk of CVD. Group 4, with moderate TyG levels and better lifestyle scores, exhibited the lowest CVD risk (HR = 1.32, 95% CI: 1.18-1.47). CONCLUSIONS Distinct multi-trajectories of TyG levels and lifestyle scores corresponded to differing CVD risks. The CVD risk caused by a high level TyG trajectory remained increased despite adopting healthier lifestyles. These findings underscored the significance of evaluating the combined TyG and lifestyle patterns longitudinally, and implementing early interventions to reduce CVD risk by lowering TyG levels.
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Affiliation(s)
- Hui Zhou
- Nursing Department, The Third Xiangya Hospital, Central South University, Changsha, China
- Xiangya School of Nursing, Central South University, Changsha, China
| | - Xiong Ding
- School of Public Health, Wuhan University, Wuhan, China
- Global Heath Research Center, Duke Kunshan University, Kunshan, Jiangsu Province, China
| | - Yulong Lan
- Second Affiliated Hospital of Shantou University Medical College, Shantou, China
- Centre for Precision Health, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Shuohua Chen
- Department of Cardiology, Kailuan General Hospital, 57 Xinhua East Rd, Tangshan, China
| | - Shouling Wu
- Department of Cardiology, Kailuan General Hospital, 57 Xinhua East Rd, Tangshan, China.
| | - Dan Wu
- Second Affiliated Hospital of Shantou University Medical College, Shantou, China.
- Centre for Precision Health, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia.
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Xu X, Wang Z, Huang R, Guo Y, Xiong Z, Zhuang X, Liao X. Remnant Cholesterol in Young Adulthood Is Associated With Left Ventricular Remodeling and Dysfunction in Middle Age: The CARDIA Study. Circ Cardiovasc Imaging 2023; 16:e015589. [PMID: 37988449 PMCID: PMC10659242 DOI: 10.1161/circimaging.123.015589] [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: 04/13/2023] [Accepted: 10/12/2023] [Indexed: 11/23/2023]
Abstract
BACKGROUND Recent studies have shown that remnant cholesterol (RC) is associated with incident heart failure; however, its association with left ventricular (LV) structure and function is unclear. We aimed to evaluate the association between RC levels in young adulthood and LV structure and function in middle age. METHODS We included 3321 participants from the CARDIA study (Coronary Artery Risk Development in Young Adults) at baseline. RC was calculated as total cholesterol minus high-density lipoprotein cholesterol minus calculated low-density lipoprotein cholesterol, and the RC trajectories that followed a similar pattern of change over time were identified using the latent class growth mixture model. LV structure and function were assessed using echocardiography at CARDIA study year 25. Multivariable linear regression models were performed to assess the associations of both baseline and trajectories of RC levels with LV structure and function. RESULTS Among 3321 participants, the mean age was 24.99±3.62 years: 1450 (43.90%) were male, and 1561 (47.00%) were Black. After multivariate adjustment, higher baseline RC (per SD in log-transformed) was associated with higher LV mass index (β=1.29; P=0.004), worse global longitudinal strain (β=0.19; P<0.001), worse global circumferential strain (β=0.16; P=0.014), lower septal e' (β=-0.26; P<0.001), lower lateral e' (β=-0.18; P=0.003), and higher E/e' (β=0.15; P=0.003). Three RC trajectories were identified during follow-up: low increasing (42.4%), moderate increasing (45.5%), and high increasing (12.1%). Similarly, compared with the low-increasing group, the high-increasing RC trajectory group was related to higher LV mass index, worse global longitudinal strain, lower septal e', lower lateral e', and higher E/e'. CONCLUSIONS Elevated RC levels in young adulthood were related to adverse LV structural and functional alterations in midlife. Long-term trajectories of RC levels during young adulthood help identify individuals at a higher risk for adverse LV remodeling and dysfunction. REGISTRATION URL: https://www.clinicaltrials.gov; Unique identifier: NCT00005130.
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Affiliation(s)
- Xinghao Xu
- Department of Cardiology, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China (X.X., R.H., Y.G., Z.X., X.Z., X.L.)
- NHC Key Laboratory of Assisted Circulation, Sun Yat-Sen University, Guangzhou, China. (X.X., R.H., Y.G., Z.X., X.Z., X.L.)
| | - Zhaoyan Wang
- Department of Cardiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China (Z.W.)
| | - Rihua Huang
- Department of Cardiology, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China (X.X., R.H., Y.G., Z.X., X.Z., X.L.)
- NHC Key Laboratory of Assisted Circulation, Sun Yat-Sen University, Guangzhou, China. (X.X., R.H., Y.G., Z.X., X.Z., X.L.)
| | - Yue Guo
- Department of Cardiology, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China (X.X., R.H., Y.G., Z.X., X.Z., X.L.)
- NHC Key Laboratory of Assisted Circulation, Sun Yat-Sen University, Guangzhou, China. (X.X., R.H., Y.G., Z.X., X.Z., X.L.)
| | - Zhenyu Xiong
- Department of Cardiology, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China (X.X., R.H., Y.G., Z.X., X.Z., X.L.)
- NHC Key Laboratory of Assisted Circulation, Sun Yat-Sen University, Guangzhou, China. (X.X., R.H., Y.G., Z.X., X.Z., X.L.)
| | - Xiaodong Zhuang
- Department of Cardiology, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China (X.X., R.H., Y.G., Z.X., X.Z., X.L.)
- NHC Key Laboratory of Assisted Circulation, Sun Yat-Sen University, Guangzhou, China. (X.X., R.H., Y.G., Z.X., X.Z., X.L.)
| | - Xinxue Liao
- Department of Cardiology, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China (X.X., R.H., Y.G., Z.X., X.Z., X.L.)
- NHC Key Laboratory of Assisted Circulation, Sun Yat-Sen University, Guangzhou, China. (X.X., R.H., Y.G., Z.X., X.Z., X.L.)
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