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Lin XM, Zhang LF, Wang YT, Huang T, Lin XF, Hong XY, Zheng HJ, Xie RC, Ma JF. Application of neutrophil-to-lymphocyte-to-monocyte ratio in predicting mortality risk in adult patients with septic shock: A retrospective cohort study conducted at a single center. Heliyon 2024; 10:e28809. [PMID: 38596065 PMCID: PMC11002270 DOI: 10.1016/j.heliyon.2024.e28809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 03/22/2024] [Accepted: 03/25/2024] [Indexed: 04/11/2024] Open
Abstract
Background Sepsis is a life-threatening condition characterized by an aberrant host response to infection, resulting in multi-organ dysfunction. The application of currently available prognostic indicators for sepsis in primary hospitals is challenging. In this retrospective study, we established a novel index, the neutrophil-to-lymphocyte-to-monocyte ratio (NLMR), based on routine blood examination upon admission, and assessed its prognostic value for early mortality risk in adult patients with septic shock. Methods This study included clinical data from adult patients with septic shock who were admitted to the hospital between January 1, 2018, and December 31, 2022. Training and validation sets were constructed, and patients were categorized into "survival" and "death" groups based on their survival status within the 28-day hospitalization period. Baseline data, including demographic characteristics and comorbidities, and laboratory results, such as complete blood count parameters, were collected for analysis. The Sequential Organ Failure Assessment (SOFA) and Acute Physiology and Chronic Health Evaluation II (APACHE II) scores were documented.The NLMR was determined through the utilization of multivariate binary logistic regression analysis, leading to the development of a risk model aimed at predicting early mortality in adult patients suffering from septic shock. Results Overall, 112 adult patients with septic shock were enrolled in this study, with 84 and 28 patients in the training and validation sets, respectively. Multivariate binary logistic analysis revealed that the neutrophil, lymphocyte, and monocyte counts independently contributed to the mortality risk (odds ratios = 1.22, 0.08, and 0.16, respectively). The NLMR demonstrated an area under the receiver operating characteristic curve (ROC-AUC) of 0.83 for internal validation in the training set and 0.97 for external validation in the validation set. Both overall model quality values were significantly high at 0.74 and 0.91, respectively (P < 0.05). NLMR exhibited a higher ROC-AUC value of 0.88 than quick SOFA (ROC-AUC = 0.71), SOFA (ROC-AUC = 0.83), and APACHE II (ROC-AUC = 0.78). Conclusion NLMR may be a potential marker for predicting the risk of early death in adult patients with septic shock, warranting further exploration and verification.
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Affiliation(s)
- Xiao-ming Lin
- Department of Critical Care Medicine, Zhongshan Hospital, Fudan University (Xiamen Branch), Xiamen 361015, Fujian province, PR China
| | - Lian-fang Zhang
- Department of Critical Care Medicine, Zhongshan Hospital, Fudan University (Xiamen Branch), Xiamen 361015, Fujian province, PR China
| | - Yu-ting Wang
- Department of Critical Care Medicine, Zhongshan Hospital, Fudan University (Xiamen Branch), Xiamen 361015, Fujian province, PR China
| | - Ting Huang
- Department of Critical Care Medicine, Zhongshan Hospital, Fudan University (Xiamen Branch), Xiamen 361015, Fujian province, PR China
| | - Xue-feng Lin
- Department of Critical Care Medicine, Zhongshan Hospital, Fudan University (Xiamen Branch), Xiamen 361015, Fujian province, PR China
| | - Xiang-yu Hong
- Department of Critical Care Medicine, Zhongshan Hospital, Fudan University (Xiamen Branch), Xiamen 361015, Fujian province, PR China
| | - Hong-jun Zheng
- Department of Critical Care Medicine, Zhongshan Hospital, Fudan University (Xiamen Branch), Xiamen 361015, Fujian province, PR China
| | - Rong-cheng Xie
- Department of Critical Care Medicine, Zhongshan Hospital, Fudan University (Xiamen Branch), Xiamen 361015, Fujian province, PR China
| | - Jie-fei Ma
- Department of Critical Care Medicine, Zhongshan Hospital, Fudan University (Xiamen Branch), Xiamen 361015, Fujian province, PR China
- Department of Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, PR China
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Zhang H, Dong N, Yao Y. Optimal strategy for treatment of sepsis based on the host inflammatory reaction and immune response. JOURNAL OF INTENSIVE MEDICINE 2024; 4:175-180. [PMID: 38681784 PMCID: PMC11043630 DOI: 10.1016/j.jointm.2023.10.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 09/20/2023] [Accepted: 10/16/2023] [Indexed: 05/01/2024]
Affiliation(s)
- Hui Zhang
- Translational Medicine Research Center, Medical Innovation Research Division and Fourth Medical Center of the Chinese PLA General Hospital, Beijing, China
| | - Ning Dong
- Translational Medicine Research Center, Medical Innovation Research Division and Fourth Medical Center of the Chinese PLA General Hospital, Beijing, China
| | - Yongming Yao
- Translational Medicine Research Center, Medical Innovation Research Division and Fourth Medical Center of the Chinese PLA General Hospital, Beijing, China
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Bonavia AS, Samuelsen A, Liang M, Hanson J, McKeone D, Chroneos ZC, Halstead ES. Comparison of whole blood cytokine immunoassays for rapid, functional immune phenotyping in critically ill patients with sepsis. Intensive Care Med Exp 2023; 11:70. [PMID: 37831231 PMCID: PMC10575832 DOI: 10.1186/s40635-023-00556-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 10/04/2023] [Indexed: 10/14/2023] Open
Abstract
BACKGROUND Sepsis is characterized by highly heterogeneous immune responses associated with a spectrum of disease severity. Methods that rapidly and sensitively profile these immune responses can potentially personalize immune-adjuvant therapies for sepsis. We hypothesized that the ELLA microfluidic approach to measure cytokine production from the whole blood of septic and critically ill patients would deliver faster, more precise results than the existing optic-driven ELISpot quantification. We tested our hypothesis by measuring ex vivo-stimulated production of TNF and IFNγ in critically ill and septic patients (n = 22), critically ill and non-septic patients (n = 10), and healthy volunteers (n = 10) through both ELLA and ELISpot immunoassays. Blood samples were subjected to one of three stimulants for 4 h or 18 h durations during days 1, 7-10, and 14 of critical illness. Stimulants for lymphocytes included anti-CD3/anti-CD28 and phorbol 12-myristate 13-acetate (PMA), whereas LPS was used for monocytes. Stimulated TNF and IFNγ concentrations were then associated with 30-day mortality. RESULTS Both ELISpot and ELLA immunoassays showed substantial agreement in TNF concentrations post 4 h and 18 h LPS stimulation, with concordance correlation coefficients at 0.62 and 0.60, respectively. ELLA had a broad dynamic measurement range and provided accurate TNF and IFNγ readings at both minimal and elevated cytokine concentrations (with mean coefficients of variation between triplicate readings at 2.1 ± 1.4% and 4.9 ± 7.2%, respectively). However, there was no association between the ELLA-determined cytokine concentrations on the first day of critical illness and 30-day mortality rate. In contrast, using the ELISpot for cytokine quantification revealed that non-survivors had reduced baseline TNF levels at 18 h, decreased LPS-induced TNF levels at 18 h, and diminished TNF levels post 4 h/18 h anti-CD3/28 stimulation. CONCLUSIONS Our study affirms the feasibility of obtaining dependable immune phenotyping data within 6 h of blood collection from critically ill patients, both septic and non-septic, using the ELLA immunoassay. Both ELLA and ELISpot can offer valuable insights into prognosis, therapeutic strategies, and the underlying mechanisms of sepsis development.
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Affiliation(s)
- Anthony S Bonavia
- Department of Anesthesiology and Perioperative Medicine, Penn State Milton S. Hershey Medical Center, Hershey, PA, USA.
| | - Abigail Samuelsen
- Department of Anesthesiology and Perioperative Medicine, Penn State Milton S. Hershey Medical Center, Hershey, PA, USA
| | - Menglu Liang
- Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, Baltimore, MD, USA
| | - Jodi Hanson
- Cellular Technology, Shaker Heights, OH, USA
| | - Daniel McKeone
- Department of Pediatrics, Penn State Milton S. Hershey Medical Center, Hershey, PA, USA
| | - Zissis C Chroneos
- Department of Pediatrics, Penn State Milton S. Hershey Medical Center, Hershey, PA, USA
| | - E Scott Halstead
- Department of Pediatrics, Penn State Milton S. Hershey Medical Center, Hershey, PA, USA
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Wang B, Zhu L, Jia B, Zhao C, Zhang J, Li F, Li J, Ding N, Zhang C, Hao Y, Tong S, Wang J, Li G, Fan Y, Zhang H, Li R, Du J, Kong Y, Zhang Y, Yang X, Han J, Yu Z, Du Z, Zheng H, Kosan C, Li A, Chen C, Ma Y, Zeng H. Sepsis induces non-classic innate immune memory in granulocytes. Cell Rep 2023; 42:113044. [PMID: 37643085 DOI: 10.1016/j.celrep.2023.113044] [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: 01/13/2023] [Revised: 07/14/2023] [Accepted: 08/14/2023] [Indexed: 08/31/2023] Open
Abstract
Secondary infection in patients with sepsis triggers a new wave of inflammatory response, which aggravates organ injury and increases mortality. Trained immunity boosts a potent and nonspecific response to the secondary challenge and has been considered beneficial for the host. Here, using a murine model of polymicrobial infection, we find that the primary infection reprograms granulocytes to boost enhanced inflammatory responses to the secondary infection, including the excessive production of inflammatory cytokines, respiratory burst, and augmented phagocytosis capacity. However, these reprogramed granulocytes exhibit "non-classic" characteristics of innate immune memory. Two mechanisms are independently involved in the innate immune memory of granulocytes: a metabolic shift in favor of glycolysis and fatty acid synthesis and chromatin remodeling leading to the transcriptional inactivity of genes encoding inhibitors of TLR4-initiated signaling pathways. Counteracting the deleterious effects of stressed granulocytes on anti-infection immunity might provide a strategy to fight secondary infections during sepsis.
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Affiliation(s)
- Beibei Wang
- Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China; Beijing Key Laboratory of Emerging Infectious Diseases, Beijing 100015, China
| | - Liuluan Zhu
- Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China; Beijing Key Laboratory of Emerging Infectious Diseases, Beijing 100015, China
| | - Bei Jia
- Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China; Beijing Key Laboratory of Emerging Infectious Diseases, Beijing 100015, China
| | - Chenchen Zhao
- Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China; Beijing Key Laboratory of Emerging Infectious Diseases, Beijing 100015, China
| | - Ju Zhang
- Biomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China; Beijing Key Laboratory for Therapeutic Cancer Vaccines, Beijing 100038, China
| | - Fangyuan Li
- Biomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China; Beijing Key Laboratory for Therapeutic Cancer Vaccines, Beijing 100038, China
| | - Jiarui Li
- Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China; Beijing Key Laboratory of Emerging Infectious Diseases, Beijing 100015, China
| | - Nan Ding
- Biomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China; Beijing Key Laboratory for Therapeutic Cancer Vaccines, Beijing 100038, China
| | - Can Zhang
- Biomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China; Beijing Key Laboratory for Therapeutic Cancer Vaccines, Beijing 100038, China
| | - Yu Hao
- Biomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China; Beijing Key Laboratory for Therapeutic Cancer Vaccines, Beijing 100038, China
| | - Shuai Tong
- Biomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China; Beijing Key Laboratory for Therapeutic Cancer Vaccines, Beijing 100038, China
| | - Jiajia Wang
- Biomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China; Beijing Key Laboratory for Therapeutic Cancer Vaccines, Beijing 100038, China
| | - Guoli Li
- Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China; Beijing Key Laboratory of Emerging Infectious Diseases, Beijing 100015, China
| | - Yang Fan
- Biomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China; Beijing Key Laboratory for Therapeutic Cancer Vaccines, Beijing 100038, China
| | - Henghui Zhang
- Biomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China; Beijing Key Laboratory for Therapeutic Cancer Vaccines, Beijing 100038, China
| | - Rui Li
- Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China; Beijing Key Laboratory of Emerging Infectious Diseases, Beijing 100015, China
| | - Juan Du
- Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China; Beijing Key Laboratory of Emerging Infectious Diseases, Beijing 100015, China
| | - Yaxian Kong
- Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China; Beijing Key Laboratory of Emerging Infectious Diseases, Beijing 100015, China
| | - Yue Zhang
- Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China; Beijing Key Laboratory of Emerging Infectious Diseases, Beijing 100015, China
| | - Xiaoyu Yang
- Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China; Beijing Key Laboratory of Emerging Infectious Diseases, Beijing 100015, China
| | - Junyan Han
- Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China; Beijing Key Laboratory of Emerging Infectious Diseases, Beijing 100015, China
| | - Zhengya Yu
- Department of Vascular Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing 100015, China
| | - Zhongtao Du
- Department of Vascular Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing 100015, China
| | - Hong Zheng
- Penn State Hershey Cancer Institute, Penn State University College of Medicine, Hershey, PA 17033, USA
| | - Christian Kosan
- Department of Biochemistry, Center for Molecular Biomedicine (CMB), Friedrich- Schiller-University, 07743 Jena, Germany
| | - Ang Li
- Intensive Care Unit, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
| | - Chen Chen
- Biomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China; Beijing Key Laboratory for Therapeutic Cancer Vaccines, Beijing 100038, China
| | - Yaluan Ma
- The Institute of Basic Medical Theory of Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China.
| | - Hui Zeng
- Biomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China; Beijing Key Laboratory for Therapeutic Cancer Vaccines, Beijing 100038, China.
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Hu F, Zhu J, Zhang S, Wang C, Zhang L, Zhou H, Shi H. A predictive model for the risk of sepsis within 30 days of admission in patients with traumatic brain injury in the intensive care unit: a retrospective analysis based on MIMIC-IV database. Eur J Med Res 2023; 28:290. [PMID: 37596695 PMCID: PMC10436454 DOI: 10.1186/s40001-023-01255-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 07/30/2023] [Indexed: 08/20/2023] Open
Abstract
PURPOSE Traumatic brain injury (TBI) patients admitted to the intensive care unit (ICU) are at a high risk of infection and sepsis. However, there are few studies on predicting secondary sepsis in TBI patients in the ICU. This study aimed to build a prediction model for the risk of secondary sepsis in TBI patients in the ICU, and provide effective information for clinical diagnosis and treatment. METHODS Using the MIMIC IV database version 2.0 (Medical Information Mart for Intensive Care IV), we searched data on TBI patients admitted to ICU and considered them as a study cohort. The extracted data included patient demographic information, laboratory indicators, complications, and other clinical data. The study cohort was divided into a training cohort and a validation cohort. In the training cohort, variables were screened by LASSO (Least absolute shrinkage and selection operator) regression and stepwise Logistic regression to assess the predictive ability of each feature on the incidence of patients. The screened variables were included in the final Logistic regression model. Finally, the decision curve, calibration curve, and receiver operating character (ROC) were used to test the performance of the model. RESULTS Finally, a total of 1167 patients were included in the study, and these patients were randomly divided into the training (N = 817) and validation (N = 350) cohorts at a ratio of 7:3. In the training cohort, seven features were identified as key predictors of secondary sepsis in TBI patients in the ICU, including acute kidney injury (AKI), anemia, invasive ventilation, GCS (Glasgow Coma Scale) score, lactic acid, and blood calcium level, which were included in the final model. The areas under the ROC curve in the training cohort and the validation cohort were 0.756 and 0.711, respectively. The calibration curve and ROC curve show that the model has favorable predictive accuracy, while the decision curve shows that the model has favorable clinical benefits with good and robust predictive efficiency. CONCLUSION We have developed a nomogram model for predicting secondary sepsis in TBI patients admitted to the ICU, which can provide useful predictive information for clinical decision-making.
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Affiliation(s)
- Fangqi Hu
- Department of Neurosurgery, Lianyungang Clinical Medical College, Nanjing Medical University, Lianyungang, 222000, Jiangsu, China
| | - Jiaqiu Zhu
- Department of Neurosurgery, The Second People's Hospital of Lianyungang City, Lianyungang, 222000, Jiangsu, China
| | - Sheng Zhang
- Department of Neurosurgery, Huzhou Central Hospital, Huzhou, 313000, Zhejiang, China
| | - Cheng Wang
- Department of Neurosurgery, Lianyungang Clinical Medical College, Nanjing Medical University, Lianyungang, 222000, Jiangsu, China
| | - Liangjia Zhang
- Department of Neurosurgery, Lianyungang Clinical Medical College, Nanjing Medical University, Lianyungang, 222000, Jiangsu, China
| | - Hui Zhou
- Department of Neurosurgery, Lianyungang Clinical Medical College, Nanjing Medical University, Lianyungang, 222000, Jiangsu, China.
| | - Hui Shi
- Department of Neurosurgery, Lianyungang Clinical Medical College, Nanjing Medical University, Lianyungang, 222000, Jiangsu, China
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6
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Joshi I, Carney WP, Rock EP. Utility of monocyte HLA-DR and rationale for therapeutic GM-CSF in sepsis immunoparalysis. Front Immunol 2023; 14:1130214. [PMID: 36825018 PMCID: PMC9942705 DOI: 10.3389/fimmu.2023.1130214] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Accepted: 01/16/2023] [Indexed: 02/09/2023] Open
Abstract
Sepsis, a heterogeneous clinical syndrome, features a systemic inflammatory response to tissue injury or infection, followed by a state of reduced immune responsiveness. Measurable alterations occur in both the innate and adaptive immune systems. Immunoparalysis, an immunosuppressed state, associates with worsened outcomes, including multiple organ dysfunction syndrome, secondary infections, and increased mortality. Multiple immune markers to identify sepsis immunoparalysis have been proposed, and some might offer clinical utility. Sepsis immunoparalysis is characterized by reduced lymphocyte numbers and downregulation of class II human leukocyte antigens (HLA) on innate immune monocytes. Class II HLA proteins present peptide antigens for recognition by and activation of antigen-specific T lymphocytes. One monocyte class II protein, mHLA-DR, can be measured by flow cytometry. Downregulated mHLA-DR indicates reduced monocyte responsiveness, as measured by ex-vivo cytokine production in response to endotoxin stimulation. Our literature survey reveals low mHLA-DR expression on peripheral blood monocytes correlates with increased risks for infection and death. For mHLA-DR, 15,000 antibodies/cell appears clinically acceptable as the lower limit of immunocompetence. Values less than 15,000 antibodies/cell are correlated with sepsis severity; and values at or less than 8000 antibodies/cell are identified as severe immunoparalysis. Several experimental immunotherapies have been evaluated for reversal of sepsis immunoparalysis. In particular, sargramostim, a recombinant human granulocyte-macrophage colony-stimulating factor (rhu GM-CSF), has demonstrated clinical benefit by reducing hospitalization duration and lowering secondary infection risk. Lowered infection risk correlates with increased mHLA-DR expression on peripheral blood monocytes in these patients. Although mHLA-DR has shown promising utility for identifying sepsis immunoparalysis, absence of a standardized, analytically validated method has thus far prevented widespread adoption. A clinically useful approach for patient inclusion and identification of clinically correlated output parameters could address the persistent high unmet medical need for effective targeted therapies in sepsis.
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Affiliation(s)
- Ila Joshi
- Development and Regulatory Department, Partner Therapeutics, Inc., Lexington, MA, United States,*Correspondence: Ila Joshi,
| | - Walter P. Carney
- Walt Carney Biomarkers Consulting, LLC., North Andover, MA, United States
| | - Edwin P. Rock
- Development and Regulatory Department, Partner Therapeutics, Inc., Lexington, MA, United States
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He Y, Xu J, Shang X, Fang X, Gao C, Sun D, Yao L, Zhou T, Pan S, Zou X, Shu H, Yang X, Shang Y. Clinical characteristics and risk factors associated with ICU-acquired infections in sepsis: A retrospective cohort study. Front Cell Infect Microbiol 2022; 12:962470. [PMID: 35967847 PMCID: PMC9366915 DOI: 10.3389/fcimb.2022.962470] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 06/27/2022] [Indexed: 11/13/2022] Open
Abstract
Intensive care unit (ICU)-acquired infection is a common cause of poor prognosis of sepsis in the ICU. However, sepsis-associated ICU-acquired infections have not been fully characterized. The study aims to assess the risk factors and develop a model that predicts the risk of ICU-acquired infections in patients with sepsis.
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Affiliation(s)
- Yajun He
- Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Institute of Anesthesiology and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiqian Xu
- Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Institute of Anesthesiology and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaopu Shang
- Department of Information Management, Beijing Jiaotong University, Beijing, China
| | - Xiangzhi Fang
- Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Chenggang Gao
- Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Institute of Anesthesiology and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Deyi Sun
- Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Institute of Anesthesiology and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lu Yao
- Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Institute of Anesthesiology and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ting Zhou
- Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shangwen Pan
- Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaojing Zou
- Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Huaqing Shu
- Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaobo Yang
- Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - You Shang
- Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Institute of Anesthesiology and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- *Correspondence: You Shang,
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Abstract
BACKGROUND Sepsis is a leading cause of mortality in patients with neutropenia; however, data on whether neutropenic sepsis is associated with distinct clinical characteristics and outcomes are limited. Thus, this study was designed to clarify the clinical characteristics and outcomes of patients with neutropenic sepsis compared with those of patients without neutropenic sepsis diagnosed based on the Third International Consensus Definitions for Sepsis and Septic Shock criteria. METHODS We analyzed data from the Korean Sepsis Alliance, a nationwide prospective multicenter cohort study evaluating the clinical characteristics, management, and outcomes of patients with sepsis from September 2019 to February 2020. Eligible patients were divided into the neutropenic (absolute neutrophil count of less than 1,500/mL) and non-neutropenic groups. The characteristics and outcomes were compared between the two groups. RESULTS During the study period, 2,074 patients were enrolled from 16 tertiary referral or university-affiliated hospitals. Of them, 218 (10.5%) had neutropenia. The neutropenia group was younger and had a lower proportion of patients with chronic diseases compared to the non-neutropenia group. However, solid tumors (50.0% vs. 34.1%; P > 0.001) and hematological malignancies (40.8% vs. 3.8%; P < 0.001) were more common in the neutropenia group. The neutropenia group had a higher incidence of septic shock (43.6% vs. 22.9%; P < 0.001) and higher Sequential Organ Failure Assessment score (7 vs. 5; P < 0.001) than the non-neutropenia group. However, no significant differences in microbiologically confirmed infections and its pathogen distribution and the incidence of multidrug resistance were observed between the two groups. The neutropenic group had a higher hospital mortality than the non-neutropenic group (42.2% vs. 26.3%; P < 0.001), and the Kaplan-Meier survival curve demonstrated a significant difference in survival within 1 week after diagnosing sepsis (log-rank test, P = 0.002). The incidence of adverse events during intensive care unit admission was not different between the two groups. Among hospital survivors, the neutropenic group was more frequently discharged to home (72.2% vs. 57.8%; P = 0.002). CONCLUSIONS Neutropenic sepsis is associated with a higher-grade organ dysfunction during the diagnosis of sepsis and higher mortality without difference in the pathogen isolated.
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Gillis A, Ben Yaacov A, Agur Z. A New Method for Optimizing Sepsis Therapy by Nivolumab and Meropenem Combination: Importance of Early Intervention and CTL Reinvigoration Rate as a Response Marker. Front Immunol 2021; 12:616881. [PMID: 33732241 PMCID: PMC7959825 DOI: 10.3389/fimmu.2021.616881] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Accepted: 02/05/2021] [Indexed: 11/22/2022] Open
Abstract
Background: Recently, there has been a growing interest in applying immune checkpoint blockers (ICBs), so far used to treat cancer, to patients with bacterial sepsis. We aimed to develop a method for predicting the personal benefit of potential treatments for sepsis, and to apply it to therapy by meropenem, an antibiotic drug, and nivolumab, a programmed cell death-1 (PD-1) pathway inhibitor. Methods: We defined an optimization problem as a concise framework of treatment aims and formulated a fitness function for grading sepsis treatments according to their success in accomplishing the pre-defined aims. We developed a mathematical model for the interactions between the pathogen, the cellular immune system and the drugs, whose simulations under diverse combined meropenem and nivolumab schedules, and calculation of the fitness function for each schedule served to plot the fitness landscapes for each set of treatments and personal patient parameters. Results: Results show that treatment by meropenem and nivolumab has maximum benefit if the interval between the onset of the two drugs does not exceed a dose-dependent threshold, beyond which the benefit drops sharply. However, a second nivolumab application, within 7–10 days after the first, can extinguish a pathogen which the first nivolumab application failed to remove. The utility of increasing nivolumab total dose above 6 mg/kg is contingent on the patient's personal immune attributes, notably, the reinvigoration rate of exhausted CTLs and the overall suppression rates of functional CTLs. A baseline pathogen load, higher than 5,000 CFU/μL, precludes successful nivolumab and meropenem combination therapy, whereas when the initial load is lower than 3,000 CFU/μL, meropenem monotherapy suffices for removing the pathogen. Discussion: Our study shows that early administration of nivolumab, 6 mg/kg, in combination with antibiotics, can alleviate bacterial sepsis in cases where antibiotics alone are insufficient and the initial pathogen load is not too high. The study pinpoints the role of precision medicine in sepsis, suggesting that personalized therapy by ICBs can improve pathogen elimination and dampen immunosuppression. Our results highlight the importance in using reliable markers for classifying patients according to their predicted response and provides a valuable tool in personalizing the drug regimens for patients with sepsis.
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Affiliation(s)
- Avi Gillis
- Institute for Medical Biomathematics (IMBM), Bene Ataroth, Israel
| | - Anat Ben Yaacov
- Institute for Medical Biomathematics (IMBM), Bene Ataroth, Israel
| | - Zvia Agur
- Institute for Medical Biomathematics (IMBM), Bene Ataroth, Israel
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Yin J, Chen Y, Huang JL, Yan L, Kuang ZS, Xue MM, Sun S, Xiang H, Hu YY, Dong ZM, Tong CY, Bai CX, Song ZJ. Prognosis-related classification and dynamic monitoring of immune status in patients with sepsis: A prospective observational study. World J Emerg Med 2021; 12:185-191. [PMID: 34141032 DOI: 10.5847/wjem.j.1920-8642.2021.03.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND The dynamic monitoring of immune status is crucial to the precise and individualized treatment of sepsis. In this study, we aim to introduce a model to describe and monitor the immune status of sepsis and to explore its prognostic value. METHODS A prospective observational study was carried out in Zhongshan Hospital, Fudan University, enrolling septic patients admitted between July 2016 and December 2018. Blood samples were collected at days 1 and 3. Serum cytokine levels (e.g., tumor necrosis factor-α [TNF-α], interleukin-10 [IL-10]) and CD14+ monocyte human leukocyte antigen-D-related (HLA-DR) expression were measured to serve as immune markers. Classification of each immune status, namely systemic inflammatory response syndrome (SIRS), compensatory anti-inflammatory response syndrome (CARS), and mixed antagonistic response syndrome (MARS), was defined based on levels of immune markers. Changes of immune status were classified into four groups which were stabilization (SB), deterioration (DT), remission (RM), and non-remission (NR). RESULTS A total of 174 septic patients were enrolled including 50 non-survivors. Multivariate analysis discovered that IL-10 and HLA-DR expression levels at day 3 were independent prognostic factors. Patients with MARS had the highest mortality rate. Immune status of 46.1% patients changed from day 1 to day 3. Among four groups of immune status changes, DT had the highest mortality rate, followed by NR, RM, and SB with mortality rates of 64.7%, 42.9%, and 11.2%, respectively. CONCLUSIONS Severe immune disorder defined as MARS or deterioration of immune status defined as DT lead to the worst outcomes. The preliminary model of the classification and dynamic monitoring of immune status based on immune markers has prognostic values and is worthy of further investigation.
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Affiliation(s)
- Jun Yin
- Department of Emergency Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Yao Chen
- Department of Emergency Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Jun-Ling Huang
- Department of Emergency Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Lei Yan
- Department of Emergency Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Zhong-Shu Kuang
- Department of Emergency Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Ming-Ming Xue
- Department of Emergency Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Si Sun
- Department of Emergency Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Hao Xiang
- Department of Emergency Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Yan-Yan Hu
- Department of Emergency Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Zhi-Min Dong
- Department of Emergency Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Chao-Yang Tong
- Department of Emergency Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Chun-Xue Bai
- Department of Respiratory and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Zhen-Ju Song
- Department of Emergency Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
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