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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] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [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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Wang J, Yang X, Li Y, Huang JA, Jiang J, Su N. Specific cytokines in the inflammatory cytokine storm of patients with COVID-19-associated acute respiratory distress syndrome and extrapulmonary multiple-organ dysfunction. Virol J 2021; 18:117. [PMID: 34088317 PMCID: PMC8177255 DOI: 10.1186/s12985-021-01588-y] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 05/27/2021] [Indexed: 02/18/2023] Open
Abstract
BACKGROUND To date, specific cytokines associated with development of acute respiratory distress syndrome (ARDS) and extrapulmonary multiple organ dysfunction (MOD) in COVID-19 patients have not been systematically described. We determined the levels of inflammatory cytokines in patients with COVID-19 and their relationships with ARDS and extrapulmonary MOD. METHODS The clinical and laboratory data of 94 COVID-19 patients with and without ARDS were analyzed. The levels of inflammatory cytokines (interleukin 6 [IL-6], IL-8, IL-10, and tumor necrosis factor α [TNF-α]) were measured on days 1, 3, and 5 following admission. Seventeen healthy volunteers were recruited as controls. Correlations in the levels of inflammatory cytokines with clinical and laboratory variables were analyzed, furthermore, we also explored the relationships of different cytokines with ARDS and extrapulmonary MOD. RESULTS The ARDS group had higher serum levels of all 4 inflammatory cytokines than the controls, and these levels steadily increased after admission. The ARDS group also had higher levels of IL-6, IL-8, and IL-10 than the non-ARDS group, and the levels of these cytokines correlated significantly with coagulation parameters and disseminated intravascular coagulation (DIC). The levels of IL-6 and TNF-α correlated with the levels of creatinine and urea nitrogen, and were also higher in ARDS patients with acute kidney injury (AKI). All 4 inflammatory cytokines had negative correlations with PaO2/FiO2. IL-6, IL-8, and TNF-α had positive correlations with the APACHE-II score. Relative to survivors, non-survivors had higher levels of IL-6 and IL-10 at admission, and increasing levels over time. CONCLUSIONS The cytokine storm apparently contributed to the development of ARDS and extrapulmonary MOD in COVID-19 patients. The levels of IL-6, IL-8, and IL-10 correlated with DIC, and the levels of IL-6 and TNF-α were associated with AKI. Relative to survivors, patients who died within 28 days had increased levels of IL-6 and IL-10.
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Affiliation(s)
- Jiajia Wang
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Soochow University, Pinghai Road No. 899, Suzhou, 215000, China
| | - Xinjing Yang
- Department of Emergency and Critical Care Medicine, The First Affiliated Hospital of Soochow University, Suzhou, 215000, China
| | - Yongsheng Li
- Department of Intensive Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Jian-An Huang
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Soochow University, Pinghai Road No. 899, Suzhou, 215000, China
| | - Junhong Jiang
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Soochow University, Pinghai Road No. 899, Suzhou, 215000, China. .,Department of Pulmonary and Critical Care Medicine, Dushu Lake Hospital, Affiliated to Soochow University, Chongwen Road No. 9, Suzhou, 215000, China.
| | - Nan Su
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Soochow University, Pinghai Road No. 899, Suzhou, 215000, China.
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Knox DB, Lanspa MJ, Pratt CM, Kuttler KG, Jones JP, Brown SM. Glasgow Coma Scale score dominates the association between admission Sequential Organ Failure Assessment score and 30-day mortality in a mixed intensive care unit population. J Crit Care 2014; 29:780-5. [PMID: 25012961 DOI: 10.1016/j.jcrc.2014.05.009] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2014] [Revised: 04/25/2014] [Accepted: 05/22/2014] [Indexed: 01/31/2023]
Abstract
OBJECTIVE The Sequential Organ Failure Assessment (SOFA) score, a measure of multiple-organ dysfunction syndrome, is used to predict mortality in critically ill patients by assigning equally weighted scores across 6 different organ systems. We hypothesized that specific organ systems would have a greater association with mortality than others. DESIGN We retrospectively studied patients admitted over a period of 4.2 years to a mixed-profile intensive care unit (ICU). We recorded age and comorbidities, and calculated SOFA organ scores. The primary outcome was 30-day all-cause mortality. We determined which organ subscores of the SOFA score were most associated with mortality using multiple analytic methods: random forests, conditional inference trees, distanced-based clustering techniques, and logistic regression. SETTING A 24-bed mixed-profile adult ICU that cares for medical, surgical, and trauma (level 1) patients at an academic referral center. PATIENTS All patients' first admission to the study ICU during the study period. MEASUREMENTS AND MAIN RESULTS We identified 9120 first admissions during the study period. Overall 30-day mortality was 12%. Multiple analytical methods all demonstrated that the best initial prediction variables were age and the central nervous system SOFA subscore, which is determined solely by Glasgow Coma Scale score. CONCLUSIONS In a mixed population of critically ill patients, the Glasgow Coma Scale score dominates the association between admission SOFA score and 30-day mortality. Future research into outcomes from multiple-organ dysfunction may benefit from new models for measuring organ dysfunction with special attention to neurologic dysfunction.
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