Combination of lymphocyte number and function in evaluating host immunity

The association of prealbumin, transferrin, and albumin with immunosenescence among elderly males

OBJECTIVE

As people get older, the innate and acquired immunity of the elderly are affected, resulting in immunosenescence. Prealbumin (PAB), transferrin (TRF), and albumin (ALB) are commonly used markers to monitor protein energy malnutrition (PEM). However, their relationship with the immune system has not been fully explored.

METHODS

In our study, a total of 93 subjects (≥65 years) were recruited from Tongji Hospital between January 2015 and February 2017. According to the serum levels of these proteins (PAB, TRF, and ALB), we divided the patients into the high serum protein group and the low serum protein group. Then, we compared the percent expression of lymphocyte subsets between two groups.

RESULTS

All the low serum protein groups (PAB, TRF, and ALB) had significant decreases in the percentage of CD4+ cells, CD3+CD28+ cells, CD4+CD28+ cells and significant increases in the percentage of CD8+ cells, CD8+CD28- cells. PAB, TRF, and ALB levels revealed positive correlations with CD4/CD8 ratio, proportions of CD4+ cells, CD3+CD28+ cells, CD4+CD28+ cells, and negative correlation with proportions of CD8+ cells, CD8+CD28- cells.

CONCLUSIONS

This study suggested PAB, TRF, and ALB could be used as immunosenescence indicators. PEM might accelerate the process of immunosenescence in elderly males.

COVID-19 in pulmonary critically ill patients: metagenomic identification of fungi and characterization of pathogenic microorganisms

Background

Fungal co-infection is prevalent in critically ill patients with COVID-19. The conventional approach applied to fungal identification has relatively low sensitivity and is time-consuming. The metagenomic next-generation sequencing (mNGS) technology can simultaneously detect a variety of microorganisms, and is increasingly being used for the rapid detection and diagnosis of pathogens.

Methods

In this single-center retrospective study, we described the clinical presentation and outcomes of COVID-19 and mNGS positive for fungi in pulmonary critically ill patients during the outbreak of Omicron infection from December 2022 to January 2023.

Results

Among 43 COVID-19 patients with acute respiratory distress syndrome (ARDS) on a single intensive care unit (ICU), 10 were reported to be fungal positive using the mNGS test. The number of pathogenic microorganisms detected by mNGS was significantly higher than that via traditional methods, especially in the detection of fungi and viruses. Aspergillus infection was dominant, and most of these patients also had concurrent bacterial or viral infections. Probable or possible COVID-19-associated pulmonary aspergillosis (CAPA) was diagnosed in all 10 patients, and the prognosis was poor.

Conclusion

Patients with COVID-19 may be at increased risk of developing fungal infections as well as concurrent bacterial or viral infections, and mNGS can be a powerful tool in identifying these infections. Clinicians should be aware of the increased risk of fungal infections in COVID-19 patients, particularly those who have underlying immunocompromising conditions, and should monitor for early signs of infection.

The Systemic Immune-Inflammation Index and Predicting Cardiac Implantable Electronic Device Infections

This study aimed to evaluate the utility of the systemic immune-inflammation index (SII) in predicting the development of Cardiac Implantable Electronic Device (CIED) infections. A retrospective analysis was performed using the medical records of 2185 patients who underwent CIED (including de novo, revision, or upgrade) implantation at our institution from January 2012 to December 2019. We recorded CIED infections and risk factors according to the patient, device, and procedural characteristics during the median 28.7 months (6.2-56.8) follow-up. CIED infections were identified in 52 patients. Diabetes, chronic renal disease, SII before implantation, new cardiac resynchronization therapy (CRT) implantation, CRT-battery replacement, revision or upgrade, and the number of previous procedures were independent predictors of CIED infections. The area under the curve (AUC) of SII to predict CIED infection was .733 (95% CI: .654-.811). A raised SII may be a useful predictor of CIED infection.

A score-based method of immune status evaluation for healthy individuals with complete blood cell counts

BACKGROUND

With the COVID-19 outbreak, an increasing number of individuals are concerned about their health, particularly their immune status. However, as of now, there is no available algorithm that effectively assesses the immune status of normal, healthy individuals. In response to this, a new score-based method is proposed that utilizes complete blood cell counts (CBC) to provide early warning of disease risks, such as COVID-19.

METHODS

First, data on immune-related CBC measurements from 16,715 healthy individuals were collected. Then, a three-platform model was developed to normalize the data, and a Gaussian mixture model was optimized with expectation maximization (EM-GMM) to cluster the immune status of healthy individuals. Based on the results, Random Forest (RF), Light Gradient Boosting Machine (LightGBM) and Extreme Gradient Boosting (XGBoost) were used to determine the correlation of each CBC index with the immune status. Consequently, a weighted sum model was constructed to calculate a continuous immunity score, enabling the evaluation of immune status.

RESULTS

The results demonstrated a significant negative correlation between the immunity score and the age of healthy individuals, thereby validating the effectiveness of the proposed method. In addition, a nonlinear polynomial regression model was developed to depict this trend. By comparing an individual's immune status with the reference value corresponding to their age, their immune status can be evaluated.

CONCLUSION

In summary, this study has established a novel model for evaluating the immune status of healthy individuals, providing a good approach for early detection of abnormal immune status in healthy individuals. It is helpful in early warning of the risk of infectious diseases and of significant importance.

Epidemiological Characteristics and Outcomes Predictors for Intensive Care Unit COVID-19 Patients in Al-Madinah, Saudi Arabia. Retrospective Cohort Study

Introduction

The global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) increased the demand for intensive care unit (ICU) services. Mortality and morbidity rates among ICU COVID-19 patients are affected by several factors, such as severity, comorbidities, and coinfections. In this study, we describe the demographic characteristics of COVID-19 patients admitted to an ICU in Saudi Arabia, and we determined the predictors for mortality and prolonged ICU length of stay. Additionally, we determined the prevalence of bacterial coinfection and its effect on the outcomes for ICU COVID-19 patients.

Methods

We retrospectively studied the medical records of 142 COVID-19 patients admitted to the ICU at a tertiary hospital in Madinah, Saudi Arabia. Data on demographics, medical history, mortality, length of stay, and presence of coinfection were collected for each patient.

Results

Neutrophil-to-Lymphocyte ratio (NLR) and intubation were reliable predictors of mortality and ICU length of stay among these ICU COVID-19 patients. Moreover, bacterial coinfections were detected in 23.2% of the patients and significantly (p < 0.001) prolonged their ICU length of stay, explaining the 10% increase in the length of stay for these patients. Furthermore, mortality reached 70% among the coinfected patients, and 60.8% of the isolated coinfecting pathogens were multidrug-resistant (MDR) strains of Klebsiella pneumoniae, Acinetobacter baumannii, and Staphylococcus aureus.

Conclusion

Increased NLR and intubation are predictors of mortality and prolonged length of stay in COVID-19 patients admitted to the ICU. Coinfection with MDR bacterial strains potentially results in complications and is a high-risk factor for prolonged ICU length of stay.

Comparative Analysis of Hematological and Immunological Parameters in Patients with Primary Sjögren's Syndrome and Peripheral Neuropathy

BACKGROUND

Primary Sjögren syndrome (pSS) is a multisystem disorder of autoimmune etiology, frequently involving peripheral nerves. Early detection of peripheral neuropathy (PN) manifestations might improve prognosis and disease control. The purpose of the study was to evaluate the predictive potential of hematological and immunological parameters associated with PN development in pSS patients.

METHODS

This single-center retrospective study included patients with pSS who were divided into two groups, according to the occurrence of neurological manifestations throughout the follow-up period.

RESULTS

From the total of 121 pSS patients included in the study, 31 (25.61%) developed neurological manifestations (PN+ group) during the follow-up period. At the moment of pSS diagnosis, 80.64% of PN+ patients exhibited increased disease activity, with ESSDAI scores above 14 (p = 0.001), and significantly higher values for VASp score (p = 0.001), with a mean value of 4.90 ± 2.45, compared to 1.27 ± 1.32 in the PN- group. The hematological assessment at the moment of pSS diagnosis revealed that neutrophils and neutrophil-to-lymphocyte ratio (NLR) were significantly higher in the PN+ group (p = 0.001), while lymphocytes, monocytes and monocyte-to-lymphocyte ratio (MLR) were significantly lower (p = 0.025, p = 0.13 and p = 0.003, respectively). Immuno-inflammatory parameters-gammaglobulins, complement fractions C3, C4, total proteins and vitamin D were significantly lower in the PN+ patients' group. In multivariate analysis, the independent predictive character for PN development in pSS patients was confirmed for NLR (95% CI 0.033 to 0.263, p = 0.012), MLR (95% CI -1.289 to -0.194, p = 0.008), gammaglobulins (95% CI -0.426 to -0.088, p < 0.003), complement fraction C4 (95% CI -0.018 to -0.001, p < 0.030) and vitamin D (95% CI -0.017 to -0.003, p < 0.009).

CONCLUSIONS

Readily available and frequently used hematological and immunological markers, such as NLR, MLR, gammaglobulins, C4 and vitamin D could be helpful in predicting the neurological involvement in pSS patients. These biological parameters might become useful tools for clinicians to monitor disease progression and identify potentially severe extraglandular manifestations in pSS patients.

A case report of necrotizing fasciitis caused by Haemophilus influenzae co-infection in the setting of COVID-19 pneumonia

INTRODUCTION AND IMPORTANCE

Necrotizing fasciitis is an aggressive skin and soft tissue infection that is a surgical emergency, and Haemophilus influenzae (H. flu) is a rare cause. We present a case of H. flu co-infection causing necrotizing fasciitis in the setting of COVID-19 pneumonia.

CASE PRESENTATION

A 56-year-old male presented with 2 weeks of upper respiratory symptoms. He was unvaccinated against COVID-19 and tested positive for COVID-19 five days prior. He developed respiratory failure requiring intubation, and was treated with dexamethasone, remdesivir, and tocilizumab for COVID-19 pneumonia. On hospital day 2, he was hypotensive with new rapidly evolving erythematous lesions with crepitus of his lower extremities suspicious for necrotizing fasciitis. He underwent wide excision and debridement with significant hemodynamic improvements. H. flu co-infection was identified from blood cultures. Aberrant cells with 94 % lymphocytes were noted and suggested chronic lymphocytic leukemia (CLL) that was not previously known. He developed progressive lesions globally, concerning for purpura fulminans with clinical disseminated intravascular coagulation and neurological decline ultimately leading to withdrawal of care.

CLINICAL DISCUSSION

COVID-19 infection is often associated with concomitant opportunistic infections. Our patient was also immunocompromised by CLL, diabetes, chronic steroids, and initial appropriate COVID-19 treatments. Despite appropriate treatments, he could not overcome his medical comorbidities and multiple infections.

CONCLUSION

Necrotizing fasciitis caused by H. flu is rare, and we present the first case as a co-infection in the setting of COVID-19 pneumonia. Due to the patient's immunocompromised state with underlying CLL, this proved to be fatal.

Distinct Immune Reconstitution Profiles Captured by Immune Functional Assays at 6 Months Post Allogeneic Hematopoietic Stem Cell Transplantation

Immune reconstitution after allogeneic-hematopoietic-stem-cell transplantation (allo-HSCT) is a complex and individual process. In this cross-sectional study, whole-blood (WB) immune functional assay (IFA) was used to characterize immune function by assessing immune-related gene/pathway alterations. The usefulness of this tool in the context of infection, 6 months after transplantation, was evaluated. Sixty allo-HSCT recipients at 6 months after transplantation and 10 healthy volunteers (HV) were included. WB was stimulated in standardized TruCulture tubes using lipopolysaccharides and Staphylococcal enterotoxin B. Gene expression was quantified using a custom 144-gene panel using NanoString nCounter technology and analyzed using Ingenuity Pathway Analysis. The relationships between immune function and clinical characteristics, immune cell counts, and post-transplantation infections were assessed. Allo-HSCT recipients were able to activate similar networks of the innate and adaptive immune response compared to HV, with, nevertheless, a lower intensity. A reduced number and a lower expression of genes associated with immunoregulatory and inflammatory processes were observed in allo-HSCT recipients. The use of immunosuppressive treatments was associated with a protracted immune reconstitution revealed by transcriptomic immunoprofiling. No difference in immune cell counts was observed among patients receiving or not receiving immunosuppressive treatments using a large immunophenotyping panel. Moreover, the expression of a set of genes, including CCL3/CCL4, was significantly lower in patients with Herpesviridae reactivation (32%, 19/60), which once again was not identified using classical immune cell counts. Transcriptional IFA revealed the heterogeneity among allo-HSCT recipients with a reduced immune function, a result that could not be captured by circulating immune cell counts. This highlights the potential added value of this tool for the personalized care of immunocompromised patients.

Development of diagnostic algorithm using machine learning for distinguishing between active tuberculosis and latent tuberculosis infection

BACKGROUND

The discrimination between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains challenging. The present study aims to investigate the value of diagnostic models established by machine learning based on multiple laboratory data for distinguishing Mycobacterium tuberculosis (Mtb) infection status.

METHODS

T-SPOT, lymphocyte characteristic detection, and routine laboratory tests were performed on participants. Diagnostic models were built according to various algorithms.

RESULTS

A total of 892 participants (468 ATB and 424 LTBI) and another 263 participants (125 ATB and 138 LTBI), were respectively enrolled at Tongji Hospital (discovery cohort) and Sino-French New City Hospital (validation cohort). Receiver operating characteristic (ROC) curve analysis showed that the value of individual indicator for differentiating ATB from LTBI was limited (area under the ROC curve (AUC) < 0.8). A total of 28 models were successfully established using machine learning. Among them, the AUCs of 25 models were more than 0.9 in test set. It was found that conditional random forests (cforest) model, based on the implementation of the random forest and bagging ensemble algorithms utilizing conditional inference trees as base learners, presented best discriminative power in segregating ATB from LTBI. Specially, cforest model presented an AUC of 0.978, with the sensitivity of 93.39% and the specificity of 91.18%. Mtb-specific response represented by early secreted antigenic target 6 (ESAT-6) and culture filtrate protein 10 (CFP-10) spot-forming cell (SFC) in T-SPOT assay, as well as global adaptive immunity assessed by CD4 cell IFN-γ secretion, CD8 cell IFN-γ secretion, and CD4 cell number, were found to contribute greatly to the cforest model. Superior performance obtained in the discovery cohort was further confirmed in the validation cohort. The sensitivity and specificity of cforest model in validation set were 92.80% and 89.86%, respectively.

CONCLUSIONS

Cforest model developed upon machine learning could serve as a valuable and prospective tool for identifying Mtb infection status. The present study provided a novel and viable idea for realizing the clinical diagnostic application of the combination of machine learning and laboratory findings.

Problems Associated with Co-Infection by Multidrug-Resistant Klebsiella pneumoniae in COVID-19 Patients: A Review

To date, coronavirus disease 2019 (COVID-19) and its variants have been reported as a novel public health concern threatening us worldwide. The presence of Klebsiella pneumoniae in COVID-19-infected patients is a major problem due to its resistance to multiple antibiotics, and it can possibly make the management of COVID-19 in patients more problematic. The impact of co-infection by K. pneumoniae on COVID-19 patients was explored in the current review. The spread of K. pneumoniae as a co-infection among critically ill COVID-19 patients, particularly throughout hospitalization, was identified and recorded via numerous reports. Alarmingly, the extensive application of antibiotics in the initial diagnosis of COVID-19 infection may reduce bacterial co-infection, but it increases the antibiotic resistance of bacteria such as the strains of K. pneumoniae. The correct detection of multidrug-resistant K. pneumoniae can offer a supportive reference for the diagnosis and therapeutic management of COVID-19 patients. Furthermore, the prevention and control of K. pneumoniae are required to minimize the risk of COVID-19. The aim of the present review is, therefore, to report on the virulence factors of the K. pneumonia genotypes, the drug resistance of K. pneumonia, and the impact of K. pneumoniae co-infection with COVID-19 on patients through a study of the published scientific papers, reports, and case studies.

Biomarkers of sequela in adult patients convalescing from COVID-19

Different biomarkers for SARS-CoV-2 have been linked to detection, diagnosis, treatment, disease progression, and development of new drugs and vaccines. The objective of this research was to evaluate various hematological, biochemicals, immunological, radiological and spirometric parameters in 20 adult patients convalescing from COVID-19 and their possible relationship with the clinical course of the disease. The frequencies of categorical variables were compared using the chi-square and Fisher's exact test. The levels of statistical significance were denoted in each figure legend. Two-dimensional clustering analysis was performed using MeV software from TIGR. The tests with P value of ≤ 0.05 were considered statistically significant. Most of the patients studied presented alterations in dissimilar laboratory, radiological and spirometric parameters, which were related to the clinical evolution of the disease. The results obtained show that certain hematological, biochemical, immunological and radiological parameters can be considered as biomarkers of sequela in adult COVID-19 patients, which allows their stratification, according to the degree of involvement or sequela, into three groups: I (mild degree of involvement or sequela), without lung lesions on computerized axial tomography (CT scan) and high values of IgG, C3 and hemoglobin, II (moderate degree of involvement or sequel), without lung lesions on CT scan, characterized by high levels of CD3+/CD4+ T lymphocytes and the rest of the variables with low values and III (severe degree of involvement or sequela), with lung lesions on CT scan and high values of erythrocyte sedimentation rate, monocytes and neutrophils, associated with lymphopenia and decreased concentrations of IgG and C3.

Characteristics of circulating adaptive immune cells in patients with colorectal cancer

Adaptive immune cells prevent solid tumor progression by targeting and killing tumor cells. However, there are no comprehensive studies on peripheral circulating adaptive immune cell characterization in colorectal cancer (CRC) patients or the effect of tumor-node-metastasis (TNM) stages on these cells. In this study, the number, phenotype, and function of different subsets of circulating adaptive immune cells in peripheral blood of CRC patients were analyzed. We found remarkable differences in CRC patients compared with those in healthy controls, including reduced absolute counts of total T cells, helper T lymphocytes (Th), cytotoxic T lymphocytes (Tc), and double-negative T lymphocytes, a decreased proportion of INF-γ⁺ cells in total T cells and Th, and increased percentages of B cells, plasmablasts, and activated T cells. Compared with early-stage CRC patients, advanced-stage CRC patients showed more severe immunosenescence, which manifested as decreased proportions of CD8⁺ naive T cells with strong proliferative ability and CD8⁺ central memory T cells with immune surveillance function. Proportions and absolute counts of CD8⁺ and CD4⁺ terminally differentiated effector memory T cells were increased, indicating immunosenescence. The immune cell characteristics analyzed in this study serve as a starting point for further research to determine potential clinical implications.

The reference ranges and characteristics of lymphocyte parameters and the correlation between lymphocyte parameters and routine health indicators in adults from China

Background

Assessment of immune function is of key importance in recognition of disease or healthy status, which still faces challenge in clinical practice. We conducted a 10-center study to investigate lymphocyte parameters including the number, phenotype and IFN-γ-producing ability, and routine laboratory indicators by using the standard method.

Results

Although the heterogeneity of lymphocyte parameters was widely found, we have established the normal ranges of these parameters by using pooled data which showed no significant difference among centers. Cluster analysis of 35 parameters found 3 interesting clusters which represented different immunological status. Cluster 1 (parameters: IFN-γ⁺CD4⁺ T cell percentage and IFN-γ⁺CD8⁺ T cell percentage) represented current lymphocyte function, which was associated with indicators such as body mass index and red blood cell; Cluster 2 (parameters: NK cell number and CD45RA⁺CD4⁺ T cell percentage) represented potential of lymphocytes, which was associated with indicators such as albumin and high-density lipoprotein. Cluster 3 (parameters: HLA-DR⁺CD8⁺ T cell percentage) represented inflammatory status, which was associated with indicators such as low-density lipoprotein, globulin and age. Correlation analysis found that nutritional indicator albumin is significantly positively correlated with lymphocyte potential. Triglyceride and body mass index were positively correlated with current lymphocyte function rather than lymphocyte potential. The loss of CD8⁺ T cells was extremely pronounced with increasing age and was one of the most important factors to cause immunosenescence, which may be associated with increased glucose.

Conclusions

We have established the normal ranges of lymphocyte parameters in different areas. This study elucidates the key indicators used to reflect the current function or potential of lymphocytes, which may provide a valuable clue for how to keep immunity healthy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12979-022-00298-5.

Bacterial co-infections and antimicrobial resistance associated with the Coronavirus Disease 2019 infection

Bacterial co-infections are typically associated with viral respiratory tract infections and pose a significant public health problem around the world. COVID-19 infection damages tissues lining the respiratory track and regulates immune cells/cytokines leading to microbiome dysbiosis and facilitating the area to be colonized by pathogenic bacterial agents. There have been reports of different types of bacterial co-infection in COVID-19 patients. Some of these reports showed despite geographical differences and differences in hospital settings, bacterial co-infections are a major cause of morbidity and mortality in COVID-19 patients. The inappropriate use of antibiotics for bacterial infections, particularly broad-spectrum antibiotics, can also further complicate the infection process, often leading to multi drug resistance, clinical deterioration, poor prognosis, and eventually death. To this end, researchers must establish a new therapeutic approach to control SARS-CoV-2 and the associated microbial coinfections. Hence, the aim of this review is to highlight the bacterial co-infection that has been recorded in COVID-19 patients and the status of antimicrobial resistance associated with the dual infections.

Prognostic Nutritional Index in Hepatocellular Carcinoma Patients With Hepatitis B Following US-Guided Percutaneous Microwave Ablation: A Retrospective Study With 1,047 Patients

Objective

Several studies have revealed that the prognostic nutritional index (PNI) was associated with survival in several cancers. However, the prognostic value of PNI in hepatocellular carcinoma (HCC) patients following ultrasound-guided percutaneous microwave ablation (US-PMWA) remains unknown, especially in patients with hepatitis B virus (HBV) infection. Therefore, the present study aimed to evaluate the potential prognostic value of PNI in these patients.

Materials

The medical records of 1,047 HCC patients with HBV infection following US-PMWA were retrospectively reviewed. The association between preoperative PNI and overall survival (OS), as well as other clinical characteristics of HCC, were analyzed using the Kaplan–Meier plot, log-rank test, multi-parameter Cox proportional hazards model, restricted cubic spline (RCS), and time-dependent receiver operating characteristic (ROC) curve analyses.

Results

Patients with a preoperative PNI more than 45 were verified to have better OS than patients with a PNI less than 45. In the multi-parameter Cox proportional hazards models, the log-transformed PNI was verified as an independent prognostic factor for OS. The result of the RCS analysis revealed that there was a nearly linear relationship between PNI and OS. The area under the time-dependent ROC curve for PNI in predicting OS was 0.56, which is relatively stable.

Conclusion

Preoperative PNI represents a convenient, noninvasive, and independent prognostic indicator in HCC patients with HBV infection following US-PMWA.

The Aging Features of Thyrotoxicosis Mice: Malnutrition, Immunosenescence and Lipotoxicity

The problem of aging is mainly the increase of age-related diseases, and elderly patients have longer hospitalization and worse prognosis. Poorer nutritional status and immunosenescence may be predisposing and severe factors. The mechanism of the high incidence of diseases and poor prognosis behind aging is complex. Finding suitable aging models is of great significance to find strategies to prevent aging related events. In this study, the relationship between thyrotoxicosis and aging was investigated in mice. The results of routine blood tests and flow cytometry showed that immunosenescence occurred in thyrotoxicosis mice, which was characterized by a significant decrease in neutrophils, lymphocytes, CD4+/CD8+ and CD4+IFN-γ+ lymphocytes. Biochemical examination results showed that there were hypocholesterolemia, hypolipoproteinemia, and hyperlipidemia in thyrotoxicosis mice. Serum proteomics analysis showed that the downregulation of complement and coagulation proteins was another manifestation of declined immunity. Moreover, proteomics analysis showed that many downregulated proteins were related to homeostasis, mainly transport proteins. Their downregulation led to the disturbance of osmotic pressure, ion homeostasis, vitamin utilization, lipid transport, hyaluronic acid processing, and pH maintenance. Serum metabolomics analysis provided more detailed evidence of homeostasis disturbance, especially lipid metabolism disorder, including the downregulation of cholesterol, vitamin D, bile acids, docosanoids, and the upregulation of glucocorticoids, triglycerides, sphingolipids, and free fatty acids. The upregulated lipid metabolites were related to lipotoxicity, which might be one cause of immunosenescence and many aging related syndromes. This study provides evidence for the aging model of thyrotoxicosis mice, which can be used for exploring anti-aging drugs and strategies.

The association between systemic inflammatory response index and in-hospital mortality in patients with infective endocarditis

Background

Infective endocarditis (IE) has a significant mortality, and early identification of high‐risk patients and prediction of poor outcomes is of great significance. In recent years, increasing research has revealed the predictors associated with infective endocarditis prognosis. Systemic inflammatory response index (SIRI) is an important new indicator of inflammation. So far, there have been no reports on the relationship between SIRI and the prognosis of IE patients.

Hypothesis

The purpose of this study was to explore the value of SIRI in predicting in‐hospital death for patients with infective endocarditis (IE), so as to provide reference for improving the prognosis of patients with IE.

Method

A retrospective analysis was performed on the clinical data of patients with IE admitted to the First Affiliated Hospital of Nanjing Medical University from January 2017 to December 2019. SIRI was calculated according to the blood routine results of patients at admission; receiver operating characteristic curve was employed to determined the optimal cutoff value of SIRI. Patients were divided into groups (low SIRI group and high SIRI group; nonsurvivor group and survivor group) according to the levels of SIRI or their prognosis, and the general clinical features of the two groups were compared. Univariate and multivariate logistic regression analysis were performed to analyze the independent prognostic factors of in‐hospital death in IE patients.

Results

A total of 147 IE patients meeting the diagnostic criteria were included, including 102 males (69.4%) and 45 females (30.6%). There was statistically significant difference in SIRI level between nonsurvivor group and survivor group (p < .05). After adjusting for the related factors, the risk of in‐hospital death in the high SIRI was still a risk of in‐hospital death with statistical significance (hazard ratio = 5.053, 95% confidence interval: 1.426‒17.905, p = .012).

Conclusions

Higher SIRI level is independently associated with the risk of in‐hospital death in IE patients, and can be an independent predictor of poor outcome in IE patients.

Risk factors for <em>Herpes simplex</em> virus (HSV) and <em>Cytomegalovirus</em> (CMV) infections in critically-ill COVID-19 patients

Background

To assess the prevalence of Herpes simplex and Cytomegalovirus infection in respiratory samples of critically-ill COVID-19 patients, its role in outcome and mortality and the influence of dexamethasone treatment in the early stage of SARS-CoV-2 infection.

Methods

All mechanically ventilated COVID-19 patients treated on ICU between March 2020 and January 2021 were included. Respiratory specimens were tested for Herpes simplex virus (HSV) type 1, 2 and Cytomegalovirus (CMV) by quantitative real-time PCR. Clinical parameters were compared in the cohorts with and without HSV-1- infection.

Results

134 patients with a median age of 72.5 years (73.0% male, n=98) were included. HSV-1 reactivation occurred in 61 patients (45.5%), after median 9 (7-13) days of mechanical ventilation. The main factor for reactivation was length of stay on ICU (24 days vs 13 days, p<0.001) and duration of mechanical ventilation (417 vs 214 hours, p<0.001). Treatment with dexamethasone and a history of immunosuppression did not associate with HSV-infection in the univariate analysis (39 vs 41, p=0.462 and 27.9% vs 23.3%, p=0.561, respectively). Both ICU and hospital mortality were not significantly different in the cohorts with and without HSV-infection (57.4% vs 45.2%, p=0.219).

Conclusions

Our study shows a high prevalence of HSV-infection in critically-ill COVID-19 patients which was unexpectedly higher than the prevalence of CMV-infections and unrelated to dexamethasone treatment. The main risk factors for HSV and CMV in the studied cohorts were the length of ICU stay and duration of mechanical ventilation. Therefore, we recommend routine monitoring of critically ill COVID-19 patients for these viral co-infections and consider treatment in those patients.

Clinical Characteristics, Diagnosis, Treatment, and Mortality Rate of TB/COVID-19 Coinfectetd Patients: A Systematic Review

Introduction: Novel coronavirus (COVID-19) and tuberculosis (TB) are the newest and one of the oldest global threats, respectively. In the COVID-19 era, due to the health system's focus on the COVID-19 epidemic, the national TB control program received less attention, leading to a worsening of the global TB epidemic. In this study, we will review the characteristics of TB patients coinfected with COVID-19.

Material and Methods: Using Scopus, PubMed/Medline, Embase, and Web of Science databases, a systematic search was performed. Case reports and case series on TB/COVID-19 coinfection published from January 1, 2019 to February 24, 2021 were collected. There were no limitations regarding publication language.

Results: Eleven case series and 20 case reports were identified from 18 countries, with the majority them being from India (N = 6) and China (N = 4). Overall, 146 patients (114 men and 32 women) coinfected with TB and COVID-19 enrolled. Smoking (15.1%), diabetes (14.4%), and hypertension (8.9%) were the most frequent comorbidities among these patients. The COVID-19 patients with TB mainly suffered fever (78.8%), cough (63.7%), and respiratory distress (22.6%). Hydroxychloroquine (64.0%) and lopinavir/ritonavir (39.5%) were the most common treatments for them. The mortality rate was 13.0% and the rate of discharged patients was 87.0%.

Conclusion: Global prevalence of COVID-19-related deaths is 6.6%. Our results showed that 13.0% of patients with TB/COVID-19 died. Thus, this study indicated that coinfection of TB and COVID-19 can increase the mortality. The respiratory symptoms of TB and COVID-19 are very similar, and this causes them to be misdiagnosed. In addition, TB is sometimes diagnosed later than COVID-19 and the severity of the disease worsens, especially in patients with underlying conditions. Therefore, patients with TB should be screened regularly in the COVID-19 era to prevent the spread of the TB/COVID-19 coinfection.

Innate and Adaptive Immunity Imbalance With Severe COVID-19 Pneumonia in Children and Adults

Introduction: Little is known about the laboratory and radiological characteristics and clinical significance of peripheral immune alterations in patients with coronavirus disease 2019 (COVID-19). This study aims to clarify these aspects in children and adults with COVID-19. Methods: In this consecutive pilot study, COVID-19 patients with the confirmed pneumonia and real-time RT-PCR were recruited prospectively in June 2020. The clinical, chest CT, and laboratory features, such as lymphocyte subpopulations, were analyzed for each individual. Results: Forty confirmed COVID-19 patients, 11 severe children, 12 severe adults, and 17 critical adult patients, besides 20 healthy pediatrics and 14 healthy adults as controls, were enrolled prospectively. Adult patients, especially critical ones, had a much higher prevalence of laboratory and chest CT abnormalities. Data regarding immune cell subsets in children patients, compared with matched controls, had higher CD3+ CD8+ T cells (p = 0.004) and lower CD4+/CD8+ ratio (p = 0.042), while adult patients, compared with matched controls, had lower CD14+ monocytes (p = 0.032). Adult patients were also categorized as experiencing critical or severe illness on admission and, compared with severe patients, had lower total lymphocytes (p < 0.047), CD3+ T-lymphocytes (p < 0.002), and CD3+ CD8+ T cells (p = 0.001) and, on the other hand, had higher CD3+ CD4+ T cells (p = 0.012) and CD4+/CD8+ ratio (p = 0.003). Non survived adults, compared with survived patients, had significantly lower CD3+ T-lymphocyte (p = 0.005). Conclusion: Unlike adult patients, who compared with matched controls and had more comorbidities, higher frequency of severe clinical symptoms, laboratory abnormalities, and immune cells alteration, clinical manifestations of COVID-19 in children (compared with matched controls) were relatively mild, and fewer clinical complications were seen either, perhaps because of a milder inflammatory response following their peripheral innate and adaptive immune cell alteration pattern.

The Dynamic Immunological Parameter Landscape in Coronavirus Disease 2019 Patients With Different Outcomes

Objectives

The longitudinal and systematic evaluation of immunity in coronavirus disease 2019 (COVID-19) patients is rarely reported.

Methods

Parameters involved in innate, adaptive, and humoral immunity were continuously monitored in COVID-19 patients from onset of illness until 45 days after symptom onset.

Results

This study enrolled 27 mild, 47 severe, and 46 deceased COVID-19 patients. Generally, deceased patients demonstrated a gradual increase of neutrophils and IL-6 but a decrease of lymphocytes and platelets after the onset of illness. Specifically, sustained low numbers of CD8⁺ T cells, NK cells, and dendritic cells were noted in deceased patients, while these cells gradually restored in mild and severe patients. Furthermore, deceased patients displayed a rapid increase of HLA-DR expression on CD4⁺ T cells in the early phase, but with a low level of overall CD45RO and HLA-DR expressions on CD4⁺ and CD8⁺ T cells, respectively. Notably, in the early phase, deceased patients showed a lower level of plasma cells and antigen-specific IgG, but higher expansion of CD16⁺CD14⁺ proinflammatory monocytes and HLA-DR⁻CD14⁺ monocytic-myeloid-derived suppressor cells (M-MDSCs) than mild or severe patients. Among these immunological parameters, M-MDSCs showed the best performance in predicting COVID-19 mortality, when using a cutoff value of ≥10%. Cluster analysis found a typical immunological pattern in deceased patients on day 9 after onset, which was characterized as the increase of inflammatory markers (M-MDSCs, neutrophils, CD16⁺CD14⁺ monocytes, and IL-6) but a decrease of host immunity markers.

Conclusions

This study systemically characterizes the kinetics of immunity of COVID-19, highlighting the importance of immunity in patient prognosis.

Bacterial infections and death among patients with Covid-19 versus non Covid-19 patients with pneumonia

Background

Many patients with Coronavirus disease-2019 (Covid-19) present with radiological evidence of pneumonia. Because it is difficult to determine co-existence of bacterial pneumonia, many of these patients are initially treated with antibiotics. We compared the rates of bacterial infections and mortality in Covid-19 patients with pulmonary infiltrates versus patients diagnosed with ‘pneumonia’ the year previously.

Methods

We conducted a medical record review of patients admitted with Covid-19 and a pulmonary infiltrate and compared them with patients diagnosed with pneumonia admitted in the prior year before the pandemic. Data abstracted included baseline demographics, comorbidities, signs and symptoms, laboratory and microbiological results, and imaging findings. Outcomes were bacterial infections and mortality. Patients presenting with and without Covid-19 were compared using univariable and multivariable analyses.

Results

There were 1398 and 1001 patients admitted through the emergency department (ED) with and without Covid-19 respectively. Compared with non-Covid-19 patients, those with Covid-19 were younger (61±18 vs. 65±25 years, P < 0.001) and had a lower Charlson Comorbidity Index (0.7 vs. 1.2, P < 0.001). Bacterial infections were present in fewer Covid-19 than non-Covid-19 patients (8% vs. 13%, P < 0.001), and most infections in Covid-19 were nosocomial as opposed to community acquired in non-Covid-19 patients. CXR was more often read as abnormal and with bilateral infiltrates in patients with Covid-19 (82% vs. 70%, P < 0.001 and 81% vs. 48%, P < 0.001, respectively). Mortality was higher in patients with Covid-19 vs. those without (15% vs. 9%, P < 0.001). Multivariable predictors (OR [95%CI]) of mortality were age (1.04 [1.03–1.05]/year), tachypnea (1.55 [1.12–2.14]), hypoxemia (2.98 [2.04–4.34]), and bacterial infection (2.80 [1.95–4.02]). Compared with non-Covid-19 patients with pneumonia, patients with Covid-19 were more likely to die (2.68 [1.97–3.63]).

Conclusions

The rate of bacterial infections is lower in Covid-19 patients with pulmonary infiltrates compared with patients diagnosed with pneumonia prior to the pandemic and most are nosocomial. Mortality was higher in Covid-19 than non-Covid-19 patients even after adjusting for age, tachypnea, hypoxemia, and bacterial infection.

Lymphocyte function based on IFN-γ secretion assay may be a promising indicator for assessing different immune status in renal transplant recipients

BACKGROUND

Immunological monitoring plays a crucial role in organ recipients for allowing tailoring of immunosuppression. However, there is still a paucity of promising indicators for detecting immune status in recipients.

METHODS

We conducted a prospective study to characterize the immune status by detecting dynamically lymphocyte subsets and function (represented by the abilities to secrete IFN-γ) in the first 6 months posttransplant in renal recipients. Participants were classified into an immune stable group, infected group, and rejected group.

RESULTS

In the stable group, our study suggested that the counts and function of CD4+ T, CD8+ T, and NK lymphocytes decreased to their nadir at week 2, and thereafter these indicators were gradually restored. The counts exceeded pre-operative levels, whereas function did not reach the pre-transplant levels by 6 months. We demonstrated that function of lymphocytes was considerably decreased in infected recipients compared with the stable group when infection occurred. By contrast, the function of lymphocytes was obviously increased at the point of rejection. Receiver operating characteristic (ROC) analysis in the combination of subsets and function of lymphocytes presented a superior clinical value with an area under the curve (AUC) of 0.903 in the diagnosis of infected receivers, and IFN-γ+CD8+ T cells% is the highest indicator with the auROC curve of 0.862. Another ROC analysis confirmed that IFN-γ+CD4  T cells% presented a preferable diagnostic value with an area of 0.887 for rejected recipients.

CONCLUSIONS

In conclusion, the ability of lymphocyte subsets secreting IFN-γ may provide a promising assessment of immune status in recipients and allow timely modifying immunosuppression.

A systematic review on SARS-CoV-2-associated fungal coinfections

A severe pandemic of Coronavirus Disease (COVID‐19) has been sweeping the globe since 2019, and this time, it did not stop, with frequent mutations transforming into virulent strains, for instance, B.1.1.7, B.1.351, and B.1.427. In recent months, a fungal infection, mucormycosis has emerged with more fatal responses and significantly increased mortality rate. To measure the severity and potential alternative approaches against black fungus coinfection in COVID‐19 patients, PubMed, Google Scholar, World Health Organization (WHO) newsletters, and other online resources, based on the cases reported and retrospective observational analysis were searched from the years 2015–2021. The studies reporting mucormycosis with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS‐CoV‐2) coinfection and/or demonstrating potential risk factors, such as a history of diabetes mellitus or suppressed immune system were included, and reports published in non‐English language were excluded. More than 20 case reports and observational studies on black fungus coinfection in COVID‐19 patients were eligible for inclusion. The results indicated that diabetes mellitus, hyperglycemic, and immunocompromised COVID‐19 patients with mucormycosis were at a higher risk. We found that it was prudent to assess the potential risk factors and severity of invasive mycosis via standardized diagnostic and clinical settings. Large‐scale studies need to be conducted to identify early biomarkers and optimization of diagnostic methods has to be established per population and geographical variation. This will not only help clinicians around the world to detect the coinfection in time but also will prepare them for future outbreaks of other potential pandemics.

Observational studies and case reports of Post‐COVID black fungus co‐infection highlighted in review.

Along with risk factors, radiological interventions of black fungus co‐infection in COVID‐19 patients and challenges for accurate diagnosis were elaborated.

The review discusses interconnection between fungus and SARS‐CoV‐2 co‐infection of mechanism to identify potential biomarkers.

Our conclusion will contribute to motivate researchers to design follow‐up plans for black fungus infection in COVID‐19.

Activation Phenotype of Mycobacterium tuberculosis-Specific CD4+ T Cells Promoting the Discrimination Between Active Tuberculosis and Latent Tuberculosis Infection

Background

Rapid and effective discrimination between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains a challenge. There is an urgent need for developing practical and affordable approaches targeting this issue.

Methods

Participants with ATB and LTBI were recruited at Tongji Hospital (Qiaokou cohort) and Sino-French New City Hospital (Caidian cohort) based on positive T-SPOT results from June 2020 to January 2021. The expression of activation markers including HLA-DR, CD38, CD69, and CD25 was examined on Mycobacterium tuberculosis (MTB)-specific CD4⁺ T cells defined by IFN-γ, TNF-α, and IL-2 expression upon MTB antigen stimulation.

Results

A total of 90 (40 ATB and 50 LTBI) and another 64 (29 ATB and 35 LTBI) subjects were recruited from the Qiaokou cohort and Caidian cohort, respectively. The expression patterns of Th1 cytokines including IFN-γ, TNF-α, and IL-2 upon MTB antigen stimulation could not differentiate ATB patients from LTBI individuals well. However, both HLA-DR and CD38 on MTB-specific cells showed discriminatory value in distinguishing between ATB patients and LTBI individuals. As for developing a single candidate biomarker, HLA-DR had the advantage over CD38. Moreover, HLA-DR on TNF-α⁺ or IL-2⁺ cells had superiority over that on IFN-γ⁺ cells in differentiating ATB patients from LTBI individuals. Besides, HLA-DR on MTB-specific cells defined by multiple cytokine co-expression had a higher ability to discriminate patients with ATB from LTBI individuals than that of MTB-specific cells defined by one kind of cytokine expression. Specially, HLA-DR on TNF-α⁺IL-2⁺ cells produced an AUC of 0.901 (95% CI, 0.833–0.969), with a sensitivity of 93.75% (95% CI, 79.85–98.27%) and specificity of 72.97% (95% CI, 57.02–84.60%) as a threshold of 44% was used. Furthermore, the performance of HLA-DR on TNF-α⁺IL-2⁺ cells for differential diagnosis was obtained with validation cohort data: 90.91% (95% CI, 72.19–97.47%) sensitivity and 68.97% (95% CI, 50.77–82.73%) specificity.

Conclusions

We demonstrated that HLA-DR on MTB-specific cells was a potentially useful biomarker for accurate discrimination between ATB and LTBI.

Clinical Presentations, Management and Outcomes of Rhino-Orbital-Cerebral Mucormycosis (ROCM) Following COVID-19: A Multi-Centric Study

PURPOSE

To report clinical presentations and factors affecting outcomes in rhino-orbital-cerebral mucormycosis following COVID-19.

METHODS

Retrospective multi-centric interventional case series of 58 eyes with rhino-orbital-cerebral mucormycosis. Demography, clinical parameters and management outcomes were noted. Factors affecting outcome and mortality were analyzed. Outcome was defined as favorable when complete resolution or stabilization without further progression of the infection was noted at last visit.

RESULTS

Mean age was 55 ± 11 years (median 56). The mean HbA1c value was 10.44 ± 2.84 mg% (median 10.5). The duration between the diagnosis of COVID-19 and rhino-orbital-cerebral mucormycosis was 16 ± 21 days (median: 8 days). Thirty-six eyes (62%) had no vision at presentation. Imaging revealed paranasal sinus involvement (100%), orbital apex involvement (41%), cavernous sinus involvement (30%), and central nervous system (CNS) involvement (33%). All the patients were treated with systemic Liposomal amphotericin-B and sinus debridement. Twenty-two eyes (38%) underwent exenteration. One eye underwent transcutaneous retrobulbar amphotericin-B. The mean follow-up duration was 5.62 ± 0.78 months (median 6). Favorable outcome was seen in 35 (60%) cases. Presence of uncontrolled diabetes (p = 0.001), orbital apex involvement (p = 0.04), CNS involvement (p = 0.04), and history of steroid use (p < 0.0001) resulted in unfavorable outcome. CNS involvement was the only factor predicting mortality (p = 0.03). Mortality was seen in 20 (34%) patients.

CONCLUSION

Over a third of patients with rhino-orbital-cerebral mucormycosis following COVID-19 have an unfavorable clinical outcome. Uncontrolled diabetes mellitus at presentation, involvement of the orbital apex, CNS, and the usage of steroids were associated with poorer outcomes. CNS involvement was a factor determining mortality.

Comparison of the Prognostic Value of Inflammation-Based Scores in Patients with Hepatocellular Carcinoma After Anti-PD-1 Therapy

Background

Inflammatory response is related to cancer progression and patient survival. However, the value in predicting survival in hepatocellular carcinoma (HCC) patients who received anti-PD-1 therapy has not been elucidated. This study aimed to compare the predictive ability of inflammation-based scores for the prognosis of HCC patients after anti-PD-1 therapy.

Methods

A total of 442 patients who received anti-PD-1 therapy were included in the study. Representative inflammation-based prognostic scores, including the platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-C-reactive protein (CRP) ratio (LCR), lymphocyte-to-monocyte ratio (LMR), systemic immune inflammation index (SII), CRP-to-albumin ratio (CAR), prognostic nutritional index (PNI), Glasgow Prognostic Score (GPS), modified Glasgow Prognostic Score (mGPS), and prognostic index (PI), were assessed for prediction accuracy using Kaplan–Meier survival curves, time-dependent receiver operating characteristic (ROC) and Harrell’s concordance index (C-index) analyses.

Results

All the inflammation-based prognostic scores exhibited good discriminatory ability in overall survival (OS) (all P < 0.01), while the PNI score was a unique independent predictor for OS in multivariate analysis (hazard ratio, 1.770; confidence interval, 1.309–2.393; P < 0.001). The areas under the ROC curves at 6, 12, 18 and 24 months and the C-index (0.65) demonstrated that the predictive accuracy of the PNI score was superior to that of the other inflammation-based scores.

Conclusion

The PNI score is a discriminatory prognostic indicator for OS in HCC patients with anti-PD-1 therapy and is superior to the other inflammation-based prognostic scores in terms of predictive ability.

Microbial co-infections in COVID-19: Associated microbiota and underlying mechanisms of pathogenesis

The novel coronavirus infectious disease-2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has traumatized the whole world with the ongoing devastating pandemic. A plethora of microbial domains including viruses (other than SARS-CoV-2), bacteria, archaea and fungi have evolved together, and interact in complex molecular pathogenesis along with SARS-CoV-2. However, the involvement of other microbial co-pathogens and underlying molecular mechanisms leading to extortionate ailment in critically ill COVID-19 patients has yet not been extensively reviewed. Although, the incidence of co-infections could be up to 94.2% in laboratory-confirmed COVID-19 cases, the fate of co-infections among SARS-CoV-2 infected hosts often depends on the balance between the host's protective immunity and immunopathology. Predominantly identified co-pathogens of SARS-CoV-2 are bacteria such as Streptococcus pneumoniae, Staphylococcus aureus, Klebsiella pneumoniae, Haemophilus influenzae, Mycoplasma pneumoniae, Acinetobacter baumannii, Legionella pneumophila and Clamydia pneumoniae followed by viruses including influenza, coronavirus, rhinovirus/enterovirus, parainfluenza, metapneumovirus, influenza B virus, and human immunodeficiency virus. The cross-talk between co-pathogens (especially lung microbiomes), SARS-CoV-2 and host is an important factor that ultimately increases the difficulty of diagnosis, treatment, and prognosis of COVID-19. Simultaneously, co-infecting microbiotas may use new strategies to escape host defense mechanisms by altering both innate and adaptive immune responses to further aggravate SARS-CoV-2 pathogenesis. Better understanding of co-infections in COVID-19 is critical for the effective patient management, treatment and containment of SARS-CoV-2. This review therefore necessitates the comprehensive investigation of commonly reported microbial co-pathogens amid COVID-19, their transmission pattern along with the possible mechanism of co-infections and outcomes. Thus, identifying the possible co-pathogens and their underlying molecular mechanisms during SARS-CoV-2 pathogenesis may shed light in developing diagnostics, appropriate curative and preventive interventions for suspected SARS-CoV-2 respiratory infections in the current pandemic.

Lymphocyte-Related Immunological Indicators for Stratifying Mycobacterium tuberculosis Infection

Background

Easily accessible tools that reliably stratify Mycobacterium tuberculosis (MTB) infection are needed to facilitate the improvement of clinical management. The current study attempts to reveal lymphocyte-related immune characteristics of active tuberculosis (ATB) patients and establish immunodiagnostic model for discriminating ATB from latent tuberculosis infection (LTBI) and healthy controls (HC).

Methods

A total of 171 subjects consisted of 54 ATB, 57 LTBI, and 60 HC were consecutively recruited at Tongji hospital from January 2019 to January 2021. All participants were tested for lymphocyte subsets, phenotype, and function. Other examination including T-SPOT and microbiological detection for MTB were performed simultaneously.

Results

Compared with LTBI and HC, ATB patients exhibited significantly lower number and function of lymphocytes including CD4⁺ T cells, CD8⁺ T cells and NK cells, and significantly higher T cell activation represented by HLA-DR and proportion of immunosuppressive cells represented by Treg. An immunodiagnostic model based on the combination of NK cell number, HLA-DR⁺CD3⁺ T cells, Treg, CD4⁺ T cell function, and NK cell function was built using logistic regression. Based on receiver operating characteristic curve analysis, the area under the curve (AUC) of the diagnostic model was 0.920 (95% CI, 0.867-0.973) in distinguishing ATB from LTBI, while the cut-off value of 0.676 produced a sensitivity of 81.48% (95% CI, 69.16%-89.62%) and specificity of 91.23% (95% CI, 81.06%-96.20%). Meanwhile, AUC analysis between ATB and HC according to the diagnostic model was 0.911 (95% CI, 0.855-0.967), with a sensitivity of 81.48% (95% CI, 69.16%-89.62%) and a specificity of 90.00% (95% CI, 79.85%-95.34%).

Conclusions

Our study demonstrated that the immunodiagnostic model established by the combination of lymphocyte-related indicators could facilitate the status differentiation of MTB infection.

Lymphocyte Non-Specific Function Detection Facilitating the Stratification of Mycobacterium tuberculosis Infection

Background

Inadequate tuberculosis (TB) diagnostics, especially for discrimination between active TB (ATB) and latent TB infection (LTBI), are major hurdle in the reduction of the disease burden. The present study aims to investigate the role of lymphocyte non-specific function detection for TB diagnosis in clinical practice.

Methods

A total of 208 participants including 49 ATB patients, 64 LTBI individuals, and 95 healthy controls were recruited at Tongji hospital from January 2019 to October 2020. All subjects were tested with lymphocyte non-specific function detection and T-SPOT assay.

Results

Significantly positive correlation existed between lymphocyte non-specific function and phytohemagglutinin (PHA) spot number. CD4⁺ T cell non-specific function showed the potential for differentiating patients with negative T-SPOT results from those with positive T-SPOT results with an area under the curve (AUC) of 0.732 (95% CI, 0.572-0.893). The non-specific function of CD4⁺ T cells, CD8⁺ T cells, and NK cells was found significantly lower in ATB patients than in LTBI individuals. The AUCs presented by CD4⁺ T cell non-specific function, CD8⁺ T cell non-specific function, and NK cell non-specific function for discriminating ATB patients from LTBI individuals were 0.845 (95% CI, 0.767-0.925), 0.770 (95% CI, 0.683-0.857), and 0.691 (95% CI, 0.593-0.789), respectively. Application of multivariable logistic regression resulted in the combination of CD4⁺ T cell non-specific function, NK cell non-specific function, and culture filtrate protein-10 (CFP-10) spot number as the optimally diagnostic model for differentiating ATB from LTBI. The AUC of the model in distinguishing between ATB and LTBI was 0.939 (95% CI, 0.898-0.981). The sensitivity and specificity were 83.67% (95% CI, 70.96%-91.49%) and 90.63% (95% CI, 81.02%-95.63%) with the threshold as 0.57. Our established model showed superior performance to TB-specific antigen (TBAg)/PHA ratio in stratifying TB infection status.

Conclusions

Lymphocyte non-specific function detection offers an attractive alternative to facilitate TB diagnosis. The three-index diagnostic model was proved to be a potent tool for the identification of different events involved in TB infection, which is helpful for the treatment and management of patients.

Confronting the threat of SARS-CoV-2: Realities, challenges and therapeutic strategies (Review)

The novel coronavirus (SARS-CoV-2) appeared in2019 in Wuhan, China, and rapidly developed into a global pandemic. The disease has affected not only health care systems and economies worldwide but has also changed the lifestyles and habits of the majority of the world's population. Among the potential targets for SARS-CoV-2 therapy, the viral spike glycoprotein has been studied most intensely, due to its key role in mediating viral entry into target cells and inducing a protective antibody response in infected individuals. In the present manuscript the molecular mechanisms that are responsible for SARS-CoV-2 infection are described and a progress report on the status of SARS-CoV-2 research is provided. A brief review of the clinical symptoms of the condition and current diagnostic methods and treatment plans for SARS-CoV-2 are also presented and the progress of preclinical research into medical intervention against SARS-CoV-2 infection are discussed.

[Analysis of the correlation between lymphocyte subsets and severity of corona virus disease 19]

OBJECTIVE

To understand the differences in lymphocyte subsets in patients with different clinical classifications of corona virus disease 19 (COVID-19).

METHODS

Eighty-one patients with COVID-19 who were admitted to the isolation ward under the responsibility of three medical aid teams in the Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, from February 8, 2020 to March 28, 2020, were selected to collect clinical data. According to the relevant diagnostic criteria, the disease status of the patients was classified into moderate cases (n=35), severe cases (n=39) and critical cases (n=7) when lymphocyte subset testing was performed. Their blood routine tests, lymphocyte subsets and other indicators were tested to compare whether there were differences in each indicator between the patients of different clinical classification groups.

RESULTS

The differences in the absolute count of total lymphocytes, T-lymphocytes, CD4⁺T-lymphocytes, CD8⁺T-lymphocytes and natural killer (NK) cells among the three groups of patients were all statistically significant (P < 0.05), and the critical cases were significantly lower than the moderate and severe cases in the above indicators, and the indicators showed a decreasing trend with the severity of the disease. In 22 patients, the six indicators of the absolute count of T-lymphocytes, B-lymphocytes, CD4⁺T-lymphocytes, CD8⁺T-lymphocytes and NK cells, CD4⁺/CD8⁺ ratio were all within the normal reference range in the first test, and 59 patients had abnormalities of the above indicators, with the absolute count of NK cells and CD8⁺ T lymphocytes decreasing most frequently (61%, 56%). The patients with the absolute count of NK cells and CD8⁺ T lymphocytes below the normal reference range were one group, and the remaining abnormal patients were the other group. There were more critical cases in the former group (moderate : severe : critical cases were 4 : 8 : 7 vs. 19 : 21 : 0, respectively, P=0.001), and all the deaths were in this group (6 cases vs. 0 case, P=0.001). The absolute B lymphocyte count was below the normal reference range in 15 patients, and the remaining 64 cases were within the normal range. The ratio of moderate, severe and critical cases in the reduced group was 4 : 7 : 4, and the ratio of critical cases was more in normal group which was 30 : 31 : 3, and the difference between the two groups was statistically significant (P=0.043).

CONCLUSION

The more critical the clinical subtype of patients with COVID-19, the lower the absolute count of each subset of lymphocytes.

[Analysis of the correlation between lymphocyte subsets and severity of corona virus disease 19]

OBJECTIVE

To understand the differences in lymphocyte subsets in patients with different clinical classifications of corona virus disease 19 (COVID-19).

METHODS

Eighty-one patients with COVID-19 who were admitted to the isolation ward under the responsibility of three medical aid teams in the Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, from February 8, 2020 to March 28, 2020, were selected to collect clinical data. According to the relevant diagnostic criteria, the disease status of the patients was classified into moderate cases (n=35), severe cases (n=39) and critical cases (n=7) when lymphocyte subset testing was performed. Their blood routine tests, lymphocyte subsets and other indicators were tested to compare whether there were differences in each indicator between the patients of different clinical classification groups.

RESULTS

The differences in the absolute count of total lymphocytes, T-lymphocytes, CD4+T-lymphocytes, CD8+T-lymphocytes and natural killer (NK) cells among the three groups of patients were all statistically significant (P < 0.05), and the critical cases were significantly lower than the moderate and severe cases in the above indicators, and the indicators showed a decreasing trend with the severity of the disease. In 22 patients, the six indicators of the absolute count of T-lymphocytes, B-lymphocytes, CD4+T-lymphocytes, CD8+T-lymphocytes and NK cells, CD4+/CD8+ ratio were all within the normal reference range in the first test, and 59 patients had abnormalities of the above indicators, with the absolute count of NK cells and CD8+ T lymphocytes decreasing most frequently (61%, 56%). The patients with the absolute count of NK cells and CD8+ T lymphocytes below the normal reference range were one group, and the remaining abnormal patients were the other group. There were more critical cases in the former group (moderate : severe : critical cases were 4 : 8 : 7 vs. 19 : 21 : 0, respectively, P=0.001), and all the deaths were in this group (6 cases vs. 0 case, P=0.001). The absolute B lymphocyte count was below the normal reference range in 15 patients, and the remaining 64 cases were within the normal range. The ratio of moderate, severe and critical cases in the reduced group was 4 : 7 : 4, and the ratio of critical cases was more in normal group which was 30 : 31 : 3, and the difference between the two groups was statistically significant (P=0.043).

CONCLUSION

The more critical the clinical subtype of patients with COVID-19, the lower the absolute count of each subset of lymphocytes.

Torque Teno Virus Viral Load as a Marker of Immune Function in Allogeneic Haematopoietic Stem Cell Transplantation Recipients

Torque teno virus (TTV) has been proposed as a surrogate biomarker of T-cell function in allogeneic–haematopoietic–stem-cell transplantation (allo-HSCT). Conflicting data exists regarding the value of TTV to assess the degree of immunosuppression. The aim of the present study was to investigate the correlation between TTV viral load and immune function. Using samples from a prospective cohort composed of healthy-volunteers (HV) and allo-HSCT recipients at 6 months post-transplantation, we assessed the correlation between TTV viraemia and immune cell counts or T-cell proliferation capacity post-phytohaemagglutinin stimulation. TTV viraemia was detected in 68% of HV (n = 80) and 100% of allo-HSCT recipients (n = 41; p < 0.001); it was significantly higher in allo-HSCT recipients (3.9 vs. 2.1 Log copies/mL, p < 0.001). There was no correlation between T-cell function and CD3⁺T-cell count (rho: 0.002) suggesting that T-cell count can normalise without full functional recovery. Furthermore, no significant correlation was observed between TTV viraemia and absolute total/subset lymphocyte counts (rho: <0.13). The highest correlation was observed between TTV viral load and T-cell proliferation capacity (rho: −0.39). We therefore report an inverse correlation between T-cell function and TTV viraemia that is independent of T-cell count. Monitoring of TTV viraemia could be a fast suitable option to objectively assess the competence of immune function in at-risk populations.

The study of the association between immune monitoring and pneumonia in kidney transplant recipients through machine learning models

Background

Kidney transplantation is the optimal treatment to cure the patients with end-stage renal disease (ESRD). However, the infectious complication, especially pneumonia, is the main cause of mortality in the early stage. Immune monitoring by relevant biomarkers provides direct evidence of immune status. We aimed to study the association between immune monitoring and pneumonia in kidney transplant patients through machine learning models.

Methods

A total of 146 patients receiving the immune monitoring panel in our center, including 46 pneumonia recipients and 100 stable recipients, were retrospectively reviewed to develop the models. All the models were validated by external data containing 10 pneumonia recipients and 32 stable recipients. The immune monitoring panel consisted of the percentages and absolute cell counts of CD3⁺CD4⁺ T cells, CD3⁺CD8⁺ T cells, CD19⁺ B cells and natural killer (NK) cells, and median fluorescence intensity (MFI) of human leukocyte antigen (HLA)-DR on monocytes and CD64 on neutrophils. The machine learning models including support vector machine (SVM), logistic regression (LR), multi-layer perceptron (MLP) and random forest (RF) were applied for analysis.

Results

The pneumonia and stable groups showed significant difference in cell counts of each subpopulation and MFI of monocyte HLA-DR and neutrophil CD64. The SVM model by monocyte HLA-DR (MFI), neutrophil CD64 (MFI), CD8⁺ T cells (cells/μl), NK cells (cell/μl) and TBNK (T cells, B cells and NK cells, cells/μl) had the best performance with the average area under the curve (AUC) of 0.940. The RF model best predicted the patients who would progress into severe pneumonia, with the average AUC of 0.760. All the models had good performance validated by external data.

Conclusions

The immune monitoring panel was tightly associated with pneumonia in kidney transplant recipients. The models developed by machine learning techniques identified patients at risk and predicted the prognosis. Based on the results of immune monitoring, better individualized therapy might be achieved.

The Effect of Host Immunity on Predicting the Mortality of Carbapenem-Resistant Organism Infection

Carbapenem-resistant organisms (CROs) are associated with considerable mortality clinically. There is a lack of effective tool to predict individual prognosis. We aim to determine if host immunity can be utilized to predict the prognosis of patients infected with CRO. From December 2018 to August 2019, we recruited CRO-infected patients to evaluate risk factors for 30-day mortality. Clinical, routine laboratory, immune and microbiological features were investigated and subjected to univariate and multivariate analyses. The final predictive models were established based on the regression coefficients of multivariate logistic regression. A total of 127 CRO-infected patients were enrolled in our study, including 85 survivors and 42 non-survivors. The number and IFN-γ producing ability of lymphocytes were remarkably decreased in non-survivors. The number of IFN-γ⁺CD4⁺ T cells could effectively predict 30-day mortality of CRO infection. Its area under the receiver operating characteristic (ROC) curve, sensitivity, specificity and accuracy, were 0.889 (95% confidence interval [CI], 0.834-0.945), 81.0, 80.0, and 80.3%, respectively. In multivariate analysis of laboratory parameters, IFN-γ⁺CD4⁺ T cell number and creatinine concentration were selected for the 2-marker model to predict prognosis fleetly. Its area under the ROC curve, sensitivity, specificity and accuracy were 0.894 (95% CI, 0.841-0.947), 83.3, 82.4, and 82.7%, respectively. Impaired lymphocyte function was an important factor to affect the outcome of CRO-infected patients. A 2-marker model based on the combination of IFN-γ⁺CD4⁺ T cell number and creatinine showed good performance in predicting the prognosis of CRO infection.

The microbial coinfection in COVID-19

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel β-coronavirus, is the main pathogenic agent of the rapidly spreading pneumonia called coronavirus disease 2019 (COVID-19). SARS-CoV-2 infects much more people, especially the elder population, around the world than other coronavirus, such as SARS-CoV and MERS-CoV, which is challenging current global public health system. Beyond the pathogenesis of SARS-CoV-2, microbial coinfection plays an important role in the occurrence and development of SARS-CoV-2 infection by raising the difficulties of diagnosis, treatment, prognosis of COVID-19, and even increasing the disease symptom and mortality. We summarize the coinfection of virus, bacteria and fungi with SARS-CoV-2, their effects on COVID-19, the reasons of coinfection, and the diagnosis to emphasize the importance of microbial coinfection in COVID-19. KEY POINTS: • Microbial coinfection is a nonnegligible factor in COVID-19. • Microbial coinfection exacerbates the processes of the occurrence, development and prognosis of COVID-19, and the difficulties of clinical diagnosis and treatment. • Different virus, bacteria, and fungi contributed to the coinfection with SARS-CoV-2.

Dysregulation of Immune Response in Patients With Coronavirus 2019 (COVID-19) in Wuhan, China

BACKGROUND

In December 2019, coronavirus 2019 (COVID-19) emerged in Wuhan and rapidly spread throughout China.

METHODS

Demographic and clinical data of all confirmed cases with COVID-19 on admission at Tongji Hospital from 10 January to 12 February 2020 were collected and analyzed. The data on laboratory examinations, including peripheral lymphocyte subsets, were analyzed and compared between patients with severe and nonsevere infection.

RESULTS

Of the 452 patients with COVID-19 recruited, 286 were diagnosed as having severe infection. The median age was 58 years and 235 were male. The most common symptoms were fever, shortness of breath, expectoration, fatigue, dry cough, and myalgia. Severe cases tend to have lower lymphocyte counts, higher leukocyte counts and neutrophil-lymphocyte ratio (NLR), as well as lower percentages of monocytes, eosinophils, and basophils. Most severe cases demonstrated elevated levels of infection-related biomarkers and inflammatory cytokines. The number of T cells significantly decreased, and were more impaired in severe cases. Both helper T (Th) cells and suppressor T cells in patients with COVID-19 were below normal levels, with lower levels of Th cells in the severe group. The percentage of naive Th cells increased and memory Th cells decreased in severe cases. Patients with COVID-19 also have lower levels of regulatory T cells, which are more obviously decreased in severe cases.

CONCLUSIONS

The novel coronavirus might mainly act on lymphocytes, especially T lymphocytes. Surveillance of NLR and lymphocyte subsets is helpful in the early screening of critical illness, diagnosis, and treatment of COVID-19.

Prediction Model Based on the Combination of Cytokines and Lymphocyte Subsets for Prognosis of SARS-CoV-2 Infection

BACKGROUND

There are currently rare satisfactory markers for predicting the death of patients with coronavirus disease 2019 (COVID-19). The aim of this study is to establish a model based on the combination of serum cytokines and lymphocyte subsets for predicting the prognosis of the disease.

METHODS

A total of 739 participants with COVID-19 were enrolled at Tongji Hospital from February to April 2020 and classified into fatal (n = 51) and survived (n = 688) groups according to the patient's outcome. Cytokine profile and lymphocyte subset analysis was performed simultaneously.

RESULTS

The fatal patients exhibited a significant lower number of lymphocytes including B cells, CD4⁺ T cells, CD8⁺ T cells, and NK cells and remarkably higher concentrations of cytokines including interleukin-2 receptor, interleukin-6, interleukin-8, and tumor necrosis factor-α on admission compared with the survived subjects. A model based on the combination of interleukin-8 and the numbers of CD4⁺ T cells and NK cells showed a good performance in predicting the death of patients with COVID-19. When the threshold of 0.075 was used, the sensitivity and specificity of the prediction model were 90.20% and 90.26%, respectively. Meanwhile, interleukin-8 was found to have a potential value in predicting the length of hospital stay until death.

CONCLUSIONS

Significant increase of cytokines and decrease of lymphocyte subsets are found positively correlated with in-hospital death. A model based on the combination of three markers provides an attractive approach to predict the prognosis of COVID-19.

Prealbumin as a Predictor of Prognosis in Patients With Coronavirus Disease 2019

Background: The predictive value of prealbumin for the prognosis of coronavirus disease 2019 (COVID-19) has not been extensively investigated.

Methods: A total of 1,115 patients with laboratory-confirmed COVID-19 were enrolled at Tongji hospital from February to April 2020 and classified into fatal (n = 129) and recovered (n = 986) groups according to the patient's outcome. Prealbumin and other routine laboratory indicators were measured simultaneously.

Results: The level of prealbumin on admission was significantly lower in fatal patients than in recovered patients. For predicting the prognosis of COVID-19, the performance of prealbumin was better than most routine laboratory indicators, such as albumin, lymphocyte count, neutrophil count, hypersensitive C-reactive protein, d-dimer, lactate dehydrogenase, creatinine, and hypersensitive cardiac troponin I. When a threshold of 126 mg/L was used to discriminate between fatal and recovered patients, the sensitivity and specificity of prealbumin were, respectively, 78.29 and 90.06%. Furthermore, a model based on the combination of nine indexes showed an improved performance in predicting the death of patients with COVID-19. Using a cut-off value of 0.19, the prediction model was able to distinguish between fatal and recovered individuals with a sensitivity of 86.82% and a specificity of 90.37%.

Conclusions: A lower level of prealbumin on admission may indicate a worse outcome of COVID-19. Immune and nutritional status may be vital factors for predicting disease progression in the early stage of COVID-19.

Characteristics of inflammatory factors and lymphocyte subsets in patients with severe COVID-19

To investigate the inflammatory factors and lymphocyte subsets which play an important role in the course of severe coronavirus disease 2019 (COVID-19). A total of 27 patients with severe COVID-19 who were admitted to Tongji Hospital in Wuhan from 1 to 21 February 2020 were recruited to the study. The characteristics of interleukin-1β (IL-1β), IL-2 receptor (IL-2R), IL-6, IL-8, IL-10, tumor necrosis factor-α (TNF)-α, C-reactive protein (CRP), serum ferritin and procalcitonin (PCT), and lymphocyte subsets of these patients were retrospectively compared before and after treatment. Before treatment, there was no significant difference in most inflammatory factors (IL-1β, IL-2R, IL-6, IL-8, IL-10, CRP, and serum ferritin) between male and female patients. Levels of IL-2R, IL-6, TNF-α, and CRP decreased significantly after treatment, followed by IL-8, IL-10, and PCT. Serum ferritin was increased in all patients before treatment but did not decrease significantly after treatment. IL-1β was normal in most patients before treatment. Lymphopenia was common among these patients with severe COVID-19. Analysis of lymphocyte subsets showed that CD4+ and particularly CD8+ T lymphocytes increased significantly after treatment. However, B lymphocytes and natural killer cells showed no significant changes after treatment. A pro-inflammatory response and decreased level of T lymphocytes were associated with severe COVID-19.

Establishing a model for predicting the outcome of COVID-19 based on combination of laboratory tests

Introduction

There are currently no satisfactory methods for predicting the outcome of Coronavirus Disease-2019 (COVID-19). The aim of this study is to establish a model for predicting the prognosis of the disease.

Methods

The laboratory results were collected from 54 deceased COVID-19 patients on admission and before death. Another 54 recovered COVID-19 patients were enrolled as control cases.

Results

Many laboratory indicators, such as neutrophils, AST, γ-GT, ALP, LDH, NT-proBNP, Hs-cTnT, PT, APTT, D-dimer, IL-2R, IL-6, IL-8, IL-10, TNF-α, CRP, ferritin and procalcitonin, were all significantly increased in deceased patients compared with recovered patients on admission. In contrast, other indicators such as lymphocytes, platelets, total protein and albumin were significantly decreased in deceased patients on admission. Some indicators such as neutrophils and procalcitonin, others such as lymphocytes and platelets, continuously increased or decreased from admission to death in deceased patients respectively. Using these indicators alone had moderate performance in differentiating between recovered and deceased COVID-19 patients. A model based on combination of four indicators (P = 1/[1 + e^{−(−2.658+0.587×neutrophils – 2.087×lymphocytes – 0.01×platelets+0.004×IL−2R)}]) showed good performance in predicting the death of COVID-19 patients. When cutoff value of 0.572 was used, the sensitivity and specificity of the prediction model were 90.74% and 94.44%, respectively.

Conclusions

Using the current indicators alone is of modest value in differentiating between recovered and deceased COVID-19 patients. A prediction model based on combination of neutrophils, lymphocytes, platelets and IL-2R shows good performance in predicting the outcome of COVID-19.

The laboratory tests and host immunity of COVID-19 patients with different severity of illness

BACKGROUNDThe coronavirus disease 2019 (COVID-19), infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a severe outbreak throughout the world. The host immunity of COVID-19 patients is unknown.METHODSThe routine laboratory tests and host immunity in COVID-19 patients with different severity of illness were compared after patient admission.RESULTSA total of 65 SARS-CoV-2-positive patients were classified as having mild (n = 30), severe (n = 20), and extremely severe (n = 15) illness. Many routine laboratory tests, such as ferritin, lactate dehydrogenase, and D-dimer, were increased in severe and extremely severe patients. The absolute numbers of CD4+ T cells, CD8+ T cells, and B cells were gradually decreased with increased severity of illness. The activation markers such as HLA-DR and CD45RO expressed on CD4+ and CD8+ T cells were increased in severe and extremely severe patients compared with mild patients. The costimulatory molecule CD28 had opposite results. The percentage of natural Tregs was decreased in extremely severe patients. The percentage of IFN-γ-producing CD8+ T cells was increased in both severe and extremely severe patients compared with mild patients. The percentage of IFN-γ-producing CD4+ T cells was increased in extremely severe patients. IL-2R, IL-6, and IL-10 were all increased in extremely severe patients. The activation of DC and B cells was decreased in extremely severe patients.CONCLUSIONThe number and function of T cells are inconsistent in COVID-19 patients. The hyperfunction of CD4+ and CD8+ T cells is associated with the pathogenesis of extremely severe SARS-CoV-2 infection.FUNDINGThis work was funded by the National Mega Project on Major Infectious Disease Prevention (2017ZX10103005-007) and the Fundamental Research Funds for the Central Universities (2019kfyRCPY098).