1
|
Hao W, Liu M, Bai C, Liu X, Niu S, Chen X. Increased inflammatory mediators levels are associated with clinical outcomes and prolonged illness in severe COVID-19 patients. Int Immunopharmacol 2023; 123:110762. [PMID: 37562295 DOI: 10.1016/j.intimp.2023.110762] [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: 04/27/2023] [Revised: 07/31/2023] [Accepted: 08/01/2023] [Indexed: 08/12/2023]
Abstract
OBJECTIVE The purpose of this study was to identify potential predictors of clinical outcome in severe COVID-19 patients and to investigate the relationship between immunological parameters and duration of illness. METHODS This single-center study retrospectively recruited 73 patients with severe or critical COVID-19. Immunological indicators include white blood cell count, neutrophil count, lymphocyte count, neutrophil-to-lymphocyte ratio, and circulating inflammatory mediators were observed for their association with disease severity, mortality and duration of illness of COVID-19. RESULTS Serum inflammatory mediators levels of C-reactive protein (P = 0.015), interleukin 6 (IL-6) (P < 0.001), CX3CL1 (P < 0.001), D-dimer (P < 0.001) and procalcitonin (PCT) (P < 0.001) were increased in critical illness patients compared to those severe COVID-19 patients. CX3CL1 has the highest C-index (0.75) to predict in-hospital mortality in patients with COVID-19. Furthermore, this study shows for the first time that the duration of illness in severe COVID-19 patients is associated with serum levels of CX3CL1 (P = 0.037) and D-dimer (P = 0.014). CONCLUSION CX3CL1, D-dimer, PCT, and IL-6 could effectively predict mortality in severe COVID-19 patients. In addition, only the circulating levels of CX3CL1 and D-dimer were significantly associated with duration of illness.
Collapse
Affiliation(s)
- Wendong Hao
- Department of Allergy, Yulin Hospital, the First Affiliated Hospital of Xi'an Jiaotong University, Yulin 719000, Shaanxi province, PR China; Department of Respiratory and Critical Care Medicine, Yulin Hospital, the First Affiliated Hospital of Xi'an Jiaotong University, Yulin 719000, Shaanxi province, PR China.
| | - Meimei Liu
- Department of Allergy, Yulin Hospital, the First Affiliated Hospital of Xi'an Jiaotong University, Yulin 719000, Shaanxi province, PR China; Department of Respiratory and Critical Care Medicine, Yulin Hospital, the First Affiliated Hospital of Xi'an Jiaotong University, Yulin 719000, Shaanxi province, PR China
| | - Cairong Bai
- Department of Allergy, Yulin Hospital, the First Affiliated Hospital of Xi'an Jiaotong University, Yulin 719000, Shaanxi province, PR China
| | - Xin Liu
- Department of Allergy, Yulin Hospital, the First Affiliated Hospital of Xi'an Jiaotong University, Yulin 719000, Shaanxi province, PR China; Department of Respiratory and Critical Care Medicine, Yulin Hospital, the First Affiliated Hospital of Xi'an Jiaotong University, Yulin 719000, Shaanxi province, PR China
| | - Siqian Niu
- Department of Respiratory and Critical Care Medicine, Yulin Hospital, the First Affiliated Hospital of Xi'an Jiaotong University, Yulin 719000, Shaanxi province, PR China
| | - Xiushan Chen
- Department of Respiratory and Critical Care Medicine, Yulin Hospital, the First Affiliated Hospital of Xi'an Jiaotong University, Yulin 719000, Shaanxi province, PR China
| |
Collapse
|
2
|
Li J, Luo H, Chen Y, Wu B, Han M, Jia W, Wu Y, Cheng R, Wang X, Ke J, Xian H, Liu J, Yu P, Tu J, Yi Y. Comparison of the Predictive Value of Inflammatory Biomarkers for the Risk of Stroke-Associated Pneumonia in Patients with Acute Ischemic Stroke. Clin Interv Aging 2023; 18:1477-1490. [PMID: 37720840 PMCID: PMC10503514 DOI: 10.2147/cia.s425393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Accepted: 09/03/2023] [Indexed: 09/19/2023] Open
Abstract
Purpose To investigate the predictive value of various inflammatory biomarkers in patients with acute ischemic stroke (AIS) and evaluate the relationship between stroke-associated pneumonia (SAP) and the best predictive index. Patients and Methods We calculated the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), prognostic nutritional index (PNI), systemic inflammation response index (SIRI), systemic immune inflammation index (SII), Glasgow prognostic score (GPS), modified Glasgow prognostic score (mGPS), and prognostic index (PI). Variables were selectively included in the logistic regression analysis to explore the associations of NLR, PLR, MLR, PNI, SIRI, SII, GPS, mGPS, and PI with SAP. We assessed the predictive performance of biomarkers by analyzing receiver operating characteristic (ROC) curves. We further used restricted cubic splines (RCS) to investigate the association. Next, we conducted subgroup analyses to investigate whether specific populations were more susceptible to NLR. Results NLR, PLR, MLR, SIRI, SII, GPS, mGPS, and PI increased significantly in SAP patients, and PNI was significantly decreased. After adjustment for potential confounders, the association of inflammatory biomarkers with SAP persisted. NLR showed the most favorable discriminative performance and was an independent risk factor predicting SAP. The RCS showed an increasing nonlinear trend of SAP risk with increasing NLR. The AUC of the combined indicator of NLR and C-reactive protein (CRP) was significantly higher than those of NLR and CRP alone (DeLong test, P<0.001). Subgroup analyses suggested good generalizability of the predictive effect. Conclusion NLR, PLR, MLR, PNI, SIRI, SII, GPS, mGPS, and PI can predict the occurrence of SAP. Among the indices, the NLR was the best predictor of SAP occurrence. It can therefore be used for the early identification of SAP.
Collapse
Affiliation(s)
- Jingyi Li
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital of Nanchang University, Nanchang, People’s Republic of China
- School of Public Health, Nanchang University, Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang, People’s Republic of China
| | - Haowen Luo
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital of Nanchang University, Nanchang, People’s Republic of China
| | - Yongsen Chen
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital of Nanchang University, Nanchang, People’s Republic of China
- School of Public Health, Nanchang University, Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang, People’s Republic of China
| | - Bin Wu
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital of Nanchang University, Nanchang, People’s Republic of China
- School of Public Health, Nanchang University, Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang, People’s Republic of China
| | - Mengqi Han
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital of Nanchang University, Nanchang, People’s Republic of China
- School of Public Health, Nanchang University, Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang, People’s Republic of China
| | - Weijie Jia
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital of Nanchang University, Nanchang, People’s Republic of China
- School of Public Health, Nanchang University, Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang, People’s Republic of China
| | - Yifan Wu
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital of Nanchang University, Nanchang, People’s Republic of China
- School of Public Health, Nanchang University, Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang, People’s Republic of China
| | - Rui Cheng
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital of Nanchang University, Nanchang, People’s Republic of China
- School of Public Health, Nanchang University, Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang, People’s Republic of China
| | - Xiaoman Wang
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital of Nanchang University, Nanchang, People’s Republic of China
- School of Public Health, Nanchang University, Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang, People’s Republic of China
| | - Jingyao Ke
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital of Nanchang University, Nanchang, People’s Republic of China
- School of Public Health, Nanchang University, Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang, People’s Republic of China
| | - Hongfei Xian
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital of Nanchang University, Nanchang, People’s Republic of China
- School of Public Health, Nanchang University, Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang, People’s Republic of China
| | - JianMo Liu
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital of Nanchang University, Nanchang, People’s Republic of China
| | - Pengfei Yu
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital of Nanchang University, Nanchang, People’s Republic of China
| | - Jianglong Tu
- Department of Neurology, The Second Affiliated Hospital of Nanchang University, Nanchang, People’s Republic of China
| | - Yingping Yi
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital of Nanchang University, Nanchang, People’s Republic of China
| |
Collapse
|
3
|
Zinellu A, Zinellu E, Mangoni AA, Pau MC, Carru C, Pirina P, Fois AG. Clinical significance of the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in acute exacerbations of COPD: present and future. Eur Respir Rev 2022; 31:31/166/220095. [DOI: 10.1183/16000617.0095-2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 07/22/2022] [Indexed: 11/30/2022] Open
Abstract
Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are a leading cause of hospitalisation and death in COPD patients. In addition to the identification of better strategies to prevent AECOPD, there is an intense focus on discovering novel markers of disease severity that enhance risk stratification on hospital admission for the targeted institution of aggressiveversussupportive treatments. In the quest for such biomarkers, an increasing body of evidence suggests that specific indexes derived from routine complete blood counts,i.e.the neutrophil-to-lymphocyte ratio (NLR) and the platelet-to-lymphocyte ratio (PLR), can significantly predict adverse outcomes in AECOPD. This narrative review discusses the current evidence regarding the association between the NLR and the PLR on admission and several clinical end-points (need for invasive ventilation, noninvasive mechanical ventilation failure, admission to an intensive care unit, pulmonary hypertension, length of hospitalisation, and mortality) in AECOPD. Future research directions and potential clinical applications of these haematological indexes in this patient group are also discussed.
Collapse
|
4
|
Liu H, Tang HY, Xu JY, Pang ZG. Small airway immunoglobulin A profile in emphysema-predominant chronic obstructive pulmonary disease. Chin Med J (Engl) 2020; 133:1915-1921. [PMID: 32826454 PMCID: PMC7462224 DOI: 10.1097/cm9.0000000000000863] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Due to airway remodeling and emphysematous destruction in the lung, the two classical clinical phenotypes of chronic obstructive pulmonary disease (COPD) are emphysema and bronchiolitis. The present study was designed to investigate the levels of small airway immunoglobulin A (IgA) in COPD with "emphysema phenotype." The study also evaluated the associations between the small airway IgA levels and the severity of disease by the extent of emphysema versus airflow limitation. METHODS Thirty patients (20 with COPD and ten healthy smokers) undergoing lung resection surgery for a solitary peripheral nodule were included. The study was conducted from January 2015 to December 2018 in the Shanxi Dayi Hospital. The presence of small airway IgA expression was determined in the lung by immunohistochemistry. In vivo, Wistar rats were exposed to silica by intratracheal instillation. Rats were sacrificed at 15 and 30 days after exposure of silica (n = 10 for each group). We also evaluated airway IgA from rats. RESULTS Small airway secretory IgA (sIgA), dimeric IgA (dIgA), and dIgA/sIgA of Global Initiative for Chronic Obstructive Lung Disease grade 1-2 COPD patients showed no difference compared with smoking control subjects (5.15 ± 1.53 vs. 6.03 ± 0.85; 1.94 ± 0.66 vs. 1.67 ± 0.04; 41.69 ± 21.02 vs. 28.44 ± 9.45, all P > 0.05). dIgA/sIgA level in the lung of COPD patients with emphysema showed higher levels than that of COPD patients without emphysema (51.89 ± 24.81 vs. 31.49 ± 9.28, P = 0.03). The percentage of low-attenuation area below 950 Hounsfield units was positively correlated with dIgA/sIgA levels (r = 0.45, P = 0.047), but not associated with the severity of disease by spirometric measurements (forced expiratory volume in the first second %pred, P > 0.05). Likewise, in the rat study, significant differences in sIgA, dIgA, dIgA/sIgA, mean linear intercept, mean alveoli number, and mean airway thickness of bronchioles (VV airway, all P < 0.01) were only observed between control rats and those exposed for 30 days. However, in the group exposed for 15 days, although the VV airway was higher than that in normal rats (27.61 ± 2.26 vs. 20.39 ± 1.99, P < 0.01), there were no significant differences in IgA and emphysema parameters between the two groups (all P > 0.05). CONCLUSION Airway IgA concentrations in mild and moderate COPD patients are directly associated with the severity of COPD with "emphysema phenotype" preceding severe airway limitation. This finding suggests that small airway IgA might play an important role in the pathophysiology of COPD, especially emphysema phenotype.
Collapse
Affiliation(s)
- Hu Liu
- Department of Respiratory Medicine, Shanxi Bethune Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi 030032, China
| | - Huo-Yan Tang
- Shanxi Medical University, Taiyuan, Shanxi 030001, China
| | - Jian-Ying Xu
- Department of Respiratory Medicine, Shanxi Bethune Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi 030032, China
| | - Zhi-Gang Pang
- Department of Respiratory Medicine, Shanxi Bethune Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi 030032, China
| |
Collapse
|