Application value of P-selectin and Clara cell secretory protein 16 expression in children with severe adenovirus pneumonia.

This study investigated the roles of P-selectin and Clara cell secretory protein 16 (CC16) levels in the pathogenesis of severe adenovirus (ADV) pneumonia in children and evaluated their ability to predict disease. Fifty-one children (age, 1-5 years) with ADV pneumonia who were admitted to Xiamen Children's Hospital were included in this study and divided into the mild group (24 patients) and severe group (27 patients). A control group comprising healthy children of the same age who underwent routine physical examinations during the same period (30 patients) was also included. The univariate analysis demonstrated that the levels of the white blood cell count and C-reactive protein, procalcitonin, d-dimer, and P-selectin were increased in a severe group compared with a mild group, while CC16 levels were significantly decreased (p < 0.05). The logistic regression analysis revealed that P-selectin and CC16 levels were independent risk factors for severe ADV pneumonia in children. The areas under the ROC curves suggested that P-selectin and CC16 exhibited high predictive value for severe ADV pneumonia. P-selectin values more than 898.58 pg/mL and CC16 values less than 11.355 ng/mL predicted severe ADV pneumonia. P-selectin and CC16 levels are correlated with the severity of ADV pneumonia in children.

Serum metabolomics profile identifies patients with community-acquired pneumonia infected by bacteria, fungi, and viruses.

PURPOSE: Patients with bacterial, fungal, and viral community-acquired pneumonia (CAP) were studied to determine their metabolic profiles. METHODS: Loop-mediated isothermal amplification technology and nucleic acid sequence-dependent amplification combined with microfluidic chip technology were applied to screen multiple pathogens from respiratory tract samples. Eighteen patients with single bacterial infection (B-CAP), fifteen with single virus infection (V-CAP), twenty with single fungal infection (F-CAP), and twenty controls were enrolled. UHPLC-MS/MS analysis of untargeted serum samples for metabolic profiles. Multiple linear regression and Spearman's rank correlation analysis were used to determine associations between metabolites and clinical parameters. The sensitivity and specificity of the screened metabolites were also examined, along with their area under the curve. RESULTS: The metabolic signatures of patients with CAP infected by bacteria, viruses, and fungi were markedly different from those of controls. The abundances of 45, 56, and 79 metabolites were significantly unbalanced. Among these differential metabolites, 11, 13, and 29 were unique to the B-CAP, V-CAP, and F-CAP groups, respectively. Bacterial infections were the only known causes of disturbances in the pentose and glucuronate and aldarate and ascorbate metabolism interconversions metabolic pathway. CONCLUSIONS: Serum metabolomic techniques based on UHPLC-MS/MS may identify differences between individuals with CAP who have been infected by various pathogens, and they can also build a metabolite signature for early detection of the origin of infection and prompt care.

Predictive signature of murine and human host response to typical and atypical pneumonia.

BACKGROUND: Pneumonia due to typical bacterial, atypical bacterial and viral pathogens can be difficult to clinically differentiate. Host response-based diagnostics are emerging as a complementary diagnostic strategy to pathogen detection. METHODS: We used murine models of typical bacterial, atypical bacterial and viral pneumonia to develop diagnostic signatures and understand the host's response to these types of infections. Mice were intranasally inoculated with Streptococcus pneumoniae, Mycoplasma pneumoniae, influenza or saline as a control. Peripheral blood gene expression analysis was performed at multiple time points. Differentially expressed genes were used to perform gene set enrichment analysis and generate diagnostic signatures. These murine-derived signatures were externally validated in silico using human gene expression data. The response to S. pneumoniae was the most rapid and robust. RESULTS: Mice infected with M. pneumoniae had a delayed response more similar to influenza-infected animals. Diagnostic signatures for the three types of infection had 0.94-1.00 area under the receiver operator curve (auROC). Validation in five human gene expression datasets revealed auROC of 0.82-0.96. DISCUSSION: This study identified discrete host responses to typical bacterial, atypical bacterial and viral aetiologies of pneumonia in mice. These signatures validated well in humans, highlighting the conserved nature of the host response to these pathogen classes.

Cytomegalovirus Pneumonia in Patients with Severe COVID-19.

Severe pneumonia accounts for 15% of the total severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections, and the affected patients require hospitalization and oxygen support. In addition, 5% of patients with severe coronavirus disease 2019 (COVID-19) experience acute respiratory distress syndrome and sepsis, which contributes to the high mortality rate. Moreover, the risk of severe COVID-19 increases with age and is the highest among elderly people over 70 years of age. Notably, these pneumonia cases can be attributed to the reactivation of latent cytomegalovirus (CMV). We hereby report two cases of patients with COVID-19 who required prolonged mechanical ventilation and were later diagnosed with secondary CMV pneumonia. These cases support the theory that in some patients with severe COVID-19, there is a possibility of CMV reactivation, contributing to the disease's severity and pathogenesis. These cases also highlight the risk involved in using steroids for a long time and the requirement of routine evaluation for CMV infection in patients with COVID-19 who require prolonged mechanical ventilation or have difficulty weaning off from the ventilator support.

Virtual physical examination in teleconsultation: A scoping review.

BACKGROUND: The conduct of virtual physical examination has provided significant information for the diagnosis during a teleconsultation session, especially during the COVID-19 pandemic, where in-person physical examinations have been greatly compromised. OBJECTIVE: The aim of this scoping review was to provide a comprehensive overview of the available evidence concerning virtual physical examination (VPE) in all healthcare settings during the COVID-19 pandemic. The review focuses on types of VPE, technological and non-technological approaches, patient and clinician experiences, as well as barriers and facilitators of VPE. METHODS: A literature search was conducted across three databases, namely MEDLINE, Embase, and Scopus. Only studies in the English language with primary research data collected from December 2019 to January 2023 were included. A narrative analysis, highlighting patients' and clinicians' experiences, was conducted on the included studies. This scoping review was reported using The PRISMA extension for scoping reviews (PRISMA-ScR) Checklist. RESULTS: A total of 25 articles meeting eligibility criteria were identified. Three major types of VPE included were musculoskeletal, head and neck, and chest exams. Sixteen studies involved specific technological aids, while three studies involved non-technological aids. Patients found VPE helped them to better assess their disease conditions, or aided their clinicians' understanding of their conditions. Clinicians also reported that VPE had provided enough clinically relevant information for decision-making in 2 neurological evaluations. Barriers to conducting VPE included technological challenges, efficacy concerns, confidence level of assistants, as well as patient health conditions, health literacy, safety, and privacy. CONCLUSIONS: Patients found virtual physical examination (VPE) helpful in understanding their own conditions, and clinicians found it useful for better assessing patient's conditions. From the clinicians' point of view, VPE provided sufficient clinically relevant information for decision-making in neurological evaluations. Major barriers identified for VPE included technological issues, patient's health conditions, and their health literacy.

Clinical findings and electrocardiography predicted mortality among COVID-19 patients with pre-existing hypertension: A cross-sectional study of East Java Province, Indonesia.

OBJECTIVE: To evaluate the factors associated with mortality among coronavirus disease-2019 patients with preexisting hypertension. METHODS: The retrospective, cross-sectional study was conducted from June 15 to July 7, 2021, after approval from Dr Soetomo General Province Hospital, Indonesia, and comprised data from the coronavirus disease-2019 registry in the East Java province of Indonesia from March 2020 to June 2021. Data was collected for adult patients infected by coronavirus disease-2019 with pre-existing hypertension Data was analysed using SPSS 23. RESULTS: Of the 2,732 patients in the registry, 425(15.6%) with median age 56.5 years (interquartile range: 50-64 years) had pre-existing hypertension. Of them, 251(59.06%) were males, and 110(25.9%) had died while in hospital. Mortality was associated with older age; higher white blood cell counts at admission and lower platelet count (p<0.05). In addition, electrocardiogram parameters associated with mortality were faster heart rate and ST abnormality (p<0.05). CONCLUSIONS: Older age, high white blood cell level, lower platelet count, faster heart rate, and ST abnormality at admission were found to be the predictors of mortality among hospitalised coronavirus disease-2019 patients with pre-existing hypertension.

Respiratory syncytial virus-associated pneumonia in primary care in Malawi.

OBJECTIVE: To identify the prevalence of respiratory syncytial virus (RSV) in a cohort of children under 5 years of age with World Health Organization (WHO)-defined pneumonia and the factors associated with developing severe RSV-associated community-acquired pneumonia (CAP) in primary care in a single centre in Northern Malawi. METHODS: The BIOmarkers TO diagnose PnEumonia (BIOTOPE) study was a prospective cohort study conducted from March to June 2016 that took place in a primary care centre in Northern Malawi. Data from this study was used to identify the characteristics of children under 5 years of age who presented with RSV and WHO-defined CAP. Means, standard deviations, medians and ranges were calculated for continuous variables. A univariate logistic regression was performed to examine the potential predictor variables. RESULTS: Four hundred and ninety-four infants presented with CAP and were eligible for inclusion in the study; RSV infection was detected in 205 (41.6%) of the infants. Eight factors were associated with increased risk for RSV CAP in the univariate model: age, born at term, presenting for care in June, crowded living environment, not being exclusively breastfed, not having received zinc or vitamin A supplementation in the last six months. Infants with RSV were more likely to have an oxygen saturation ≤92% compared to infants with other causes of pneumonia and more likely to have severe pneumonia as defined by the WHO. CONCLUSION: This study supports that RSV-associated CAP is linked to modifiable and non-modifiable risk factors; further research is indicated to determine which interventions would be most impactful. Developing and implementing an infant or maternal vaccine could be a cost-effective way to prevent RSV-associated CAP and mortality in developing nations. More research is needed to understand seasonal patterns of CAP and research over extended periods can offer valuable insights on host, environmental and pathogen-specific factors that contribute to RSV-associated CAP.

Lobar pneumonia due to human metapneumovirus: a case report.

Human metapneumovirus (hMPV) is a respiratory pathogen that can cause lower respiratory tract infections and pneumonia in immunocompetent adults. Pneumonia caused by hMPV is reportedly more likely to cause bronchial wall thickening and ground-glass opacity (GGO). A 44-year-old woman with no significant medical history developed fever, cough, and nausea. Computed tomography of the chest showed scattered GGOs in the right upper lobe and infiltrating shadows with air bronchograms in the left lingual and bilateral lower lobes. The patient was admitted to our hospital for further evaluation. Atypical pneumonia was suspected and lascufloxacin (LSFX) was started. Multiplex polymerase chain reaction (PCR) detected hMPV on hospital day 2 using the FilmArray Respiratory Panel 2.1. Pneumonia due to hMPV was suspected and LSFX was discontinued. The patient subsequently showed spontaneous improvement and was discharged on hospital day 6 after admission. After discharge, pneumonia continued to improve. Early detection of respiratory pathogens using multiplex PCR can help determine the appropriate treatment strategy. As hMPV can also cause lobar pneumonia, we should consider pneumonia due to hMPV in the differential diagnosis of lobar pneumonia.

Clinical significance of lower respiratory tract culture within 48 h of admission in patients with viral pneumonia: an observational study.

BACKGROUND: The aim of this retrospective study was to examine the risk factors of positive lower respiratory tract cultures and to investigate whether nosocomial infections are common in patients with positive lower respiratory tract cultures. METHODS: We enrolled 86 patients diagnosed with influenza A-related critical illness who were treated at Fuzhou Pulmonary Hospital of Fujian in China between 1st October 2013 and 31st March 2019. The of admission were used to divide the enrolled patients into two groups. Sputum and bronchoalveolar lavage fluid specimens were collected within 48 h after admission for culture. All samples were cultured immediately after sampling. Nosocomial infections are defined as any symptom or sign of pulmonary infiltration, confirmed by X-ray, after 5 days of admission and positive results from one or more cultures. RESULTS: The average age of this cohort was (54.13 ± 16.52) years. Based on the culture results, Staphylococcus aureus and Candida albicans had the highest positive rates (3.40% (3/86) and 20.90% (18/86), respectively). In patients with positive lower respiratory tract cultures, the incidence of nosocomial infection was 73.30% (22/30) five days after admission. However, the incidence of nosocomial infection was lower (42.80%, 24/56) in patients with negative lower respiratory tract cultures. Hemoptysis, systolic pressure at admission, and blood urea nitrogen level at admission were all independent risk factors for positive lower respiratory tract cultures within 48 h of admission. CONCLUSION: Our data showed that a significant proportion of patients with pneumonia exhibited co-infections with bacteria or fungi within five days of hospital admission. Hemoptysis, systolic pressure, and blood urea nitrogen levels at admission emerged as the key risk factors. These findings underscore the necessity of closely monitoring patients with influenza infection, particularly for positive bacterial or fungal cultures within the initial 48 h of admission.

Haemolysis index conundrum in a COVID-19 patient.

In this study, we report a preanalytical challenge noted in our laboratory on plasma samples from a critically ill COVID-19 patient treated with hydroxychloroquine. This is significant because, in critically ill COVID-19 patients on hydroxychloroquine, plasma samples can have a high measured haemolysis index in the absence of haemolysis, with the impact on reporting the results for potassium and other analytes.

Value of a secretomic approach for distinguishing patients with COVID-19 viral pneumonia among patients with respiratory distress admitted to intensive care unit.

In intensive care units, COVID-19 viral pneumonia patients (VPP) present symptoms similar to those of other patients with Nonviral infection (NV-ICU). To better manage VPP, it is therefore interesting to better understand the molecular pathophysiology of viral pneumonia and to search for biomarkers that may clarify the diagnosis. The secretome being a set of proteins secreted by cells in response to stimuli represents an opportunity to discover new biomarkers. The objective of this study is to identify the secretomic signatures of VPP with those of NV-ICU. Plasma samples and clinical data from NV-ICU (n = 104), VPP (n = 30) or healthy donors (HD, n = 20) were collected at Nantes Hospital (France) upon admission. Samples were enriched for the low-abundant proteins and analyzed using nontarget mass spectrometry. Specifically deregulated proteins (DEP) in VPP versus NV-ICU were selected. Combinations of 2 to 4 DEPs were established. The differences in secretome profiles of the VPP and NV-ICU groups were highlighted. Forty-one DEPs were specifically identified in VPP compared to NV-ICU. We describe five of the best combinations of 3 proteins (complement component C9, Ficolin-3, Galectin-3-binding protein, Fibrinogen alpha, gamma and beta chain, Proteoglycan 4, Coagulation factor IX and Cdc42 effector protein 4) that show a characteristic receptor function curve with an area under the curve of 95.0%. This study identifies five combinations of candidate biomarkers in VPP compared to NV-ICU that may help distinguish the underlying causal molecular alterations.

Cytomegalovirus pneumonia with intermittent pulmonary hemorrhage leading to asphyxia death: a case report and literature review.

Neonatal pulmonary hemorrhage is a late manifestation of various diseases. Premature delivery and low body weight are frequently observed as high-risk factors, characterized by acute onset, rapid progression, and high mortality rates. Pulmonary hemorrhage caused by cytomegalovirus infection in newborns with normal immune function is a rare occurrence. This case report focuses on a term neonate with normal birth weight who presented solely with nasal obstruction shortly after birth. However, 4 days after birth, the newborn experienced a sudden onset of blood gushing from both the mouth and nasal cavity. The patient was diagnosed with gastrointestinal bleeding, neonatal pneumonia and neonatal lung consolidation. And he was discharged after ten days of symptomatic treatment. However, upon returning home, the patient experienced a sudden onset of bleeding from the mouth and nose, leading to his untimely demise. Subsequent autopsy revealed the presence of pulmonary hemorrhage in newborn, which presented as interstitial pneumonia. The cause of pulmonary hemorrhage is cytomegalovirus infection. This case emphasizes the importance of pediatricians enhancing their skills in differentiating pulmonary hemorrhage, especially from cytomegalovirus pneumonia.

Expression and significance of procalcitonin, leukotriene B4, serum amyloid A, and C-reactive protein in children with different types of pneumonia: An observational study.

This study aimed to investigate the expression and significance of serum procalcitonin (PCT), leukotriene B4 (LTB4), Serum amyloid A (SAA), and C-reactive protein (CRP) in children with different types of pneumonia caused by different pathogenic infections. One hundred and one children with pneumonia admitted to The Fifth People Hospital of Zhuhai from July 2019 to June 2020 were enrolled and divided into 38 cases in the bacterial group, 30 cases in the mycoplasma group, and 33 cases in the virus group according to the different types of pathogens. The patients were divided into 42 cases in the noncritical group, 33 cases in the critical group, and 26 cases in the very critical group according to the pediatric clinical illness score (PCIS), and 30 healthy children were selected as the control group during the same period. Comparison of serum PCT, SAA: bacterial group > mycoplasma group > viral group > control group with significant differences (P < .05). Receiver operator characteristic (ROC) analysis showed that the area under the curves (AUCs) of serum PCT, LTB4, SAA, and CRP for the diagnosis of bacterial pneumonia were 1.000, 0.531, 0.969, and 0.833, respectively, and the AUCs for the diagnosis of mycoplasma pneumonia were 0.653, 0.609, 0.547, and 0.652, respectively, and the AUCs for the diagnosis of viral pneumonia were 0.888, 0.570, 0.955, and 1.000, respectively. Comparison of serum PCT, LTB4, SAA: very critical group > critical group > noncritical group > control group, with significant differences (P < .05). Serum PCT, LTB4, and SAA were negatively correlated with PCIS score by Pearson analysis (P < .05). Serum PCT and SAA showed diagnostic value for bacterial pneumonia, and serum SAA and CRP showed diagnostic value for viral pneumonia; serum PCT, LTB4, and SAA correlate with severity of disease and show higher expression with worsening of the condition.

Desorption Separation Ionization Mass Spectrometry (DSI-MS) for Rapid Analysis of COVID-19.

During the coronavirus disease 2019 (COVID-19) pandemic, which has witnessed over 772 million confirmed cases and over 6 million deaths globally, the outbreak of COVID-19 has emerged as a significant medical challenge affecting both affluent and impoverished nations. Therefore, there is an urgent need to explore the disease mechanism and to implement rapid detection methods. To address this, we employed the desorption separation ionization (DSI) device in conjunction with a mass spectrometer for the efficient detection and screening of COVID-19 urine samples. The study encompassed patients with COVID-19, healthy controls (HC), and patients with other types of pneumonia (OP) to evaluate their urine metabolomic profiles. Subsequently, we identified the differentially expressed metabolites in the COVID-19 patients and recognized amino acid metabolism as the predominant metabolic pathway involved. Furthermore, multiple established machine learning algorithms validated the exceptional performance of the metabolites in discriminating the COVID-19 group from healthy subjects, with an area under the curve of 0.932 in the blind test set. This study collectively suggests that the small-molecule metabolites detected from urine using the DSI device allow for rapid screening of COVID-19, taking just three minutes per sample. This approach has the potential to expand our understanding of the pathophysiological mechanisms of COVID-19 and offers a way to rapidly screen patients with COVID-19 through the utilization of machine learning algorithms.

COVID­19 detection from chest X-ray images using transfer learning.

COVID-19 is a kind of coronavirus that appeared in China in the Province of Wuhan in December 2019. The most significant influence of this virus is its very highly contagious characteristic which may lead to death. The standard diagnosis of COVID-19 is based on swabs from the throat and nose, their sensitivity is not high enough and so they are prone to errors. Early diagnosis of COVID-19 disease is important to provide the chance of quick isolation of the suspected cases and to decrease the opportunity of infection in healthy people. In this research, a framework for chest X-ray image classification tasks based on deep learning is proposed to help in early diagnosis of COVID-19. The proposed framework contains two phases which are the pre-processing phase and classification phase which uses pre-trained convolution neural network models based on transfer learning. In the pre-processing phase, different image enhancements have been applied to full and segmented X-ray images to improve the classification performance of the CNN models. Two CNN pre-trained models have been used for classification which are VGG19 and EfficientNetB0. From experimental results, the best model achieved a sensitivity of 0.96, specificity of 0.94, precision of 0.9412, F1 score of 0.9505 and accuracy of 0.95 using enhanced full X-ray images for binary classification of chest X-ray images into COVID-19 or normal with VGG19. The proposed framework is promising and achieved a classification accuracy of 0.935 for 4-class classification.

Thorax computed tomography (CTX) guided ground truth annotation of CHEST radiographs (CXR) for improved classification and detection of COVID-19.

Several data sets have been collected and various artificial intelligence models have been developed for COVID-19 classification and detection from both chest radiography (CXR) and thorax computed tomography (CTX) images. However, the pitfalls and shortcomings of these systems significantly limit their clinical use. In this respect, improving the weaknesses of advanced models can be very effective besides developing new ones. The inability to diagnose ground-glass opacities by conventional CXR has limited the use of this modality in the diagnostic work-up of COVID-19. In our study, we investigated whether we could increase the diagnostic efficiency by collecting a novel CXR data set, which contains pneumonic regions that are not visible to the experts and can only be annotated under CTX guidance. We develop an ensemble methodology of well-established deep CXR models for this new data set and develop a machine learning-based non-maximum suppression strategy to boost the performance for challenging CXR images. CTX and CXR images of 379 patients who applied to our hospital with suspected COVID-19 were evaluated with consensus by seven radiologists. Among these, CXR images of 161 patients who also have had a CTX examination on the same day or until the day before or after and whose CTX findings are compatible with COVID-19 pneumonia, are selected for annotating. CTX images are arranged in the main section passing through the anterior, middle, and posterior according to the sagittal plane with the reformed maximum intensity projection (MIP) method in the coronal plane. Based on the analysis of coronal MIP reconstructed CTX images, the regions corresponding to the pneumonia foci are annotated manually in CXR images. Radiologically classified posterior to anterior (PA) CXR of 218 patients with negative thorax CTX imaging were classified as COVID-19 pneumonia negative group. Accordingly, we have collected a new data set using anonymized CXR (JPEG) and CT (DICOM) images, where the PA CXRs contain pneumonic regions that are hidden or not easily recognized and annotated under CTX guidance. The reference finding was the presence of pneumonic infiltration consistent with COVID-19 on chest CTX examination. COVID-Net, a specially designed convolutional neural network, was used to detect cases of COVID-19 among CXRs. Diagnostic performances were evaluated by ROC analysis by applying six COVID-Net variants (COVIDNet-CXR3-A, -B, -C/COVIDNet-CXR4-A, -B, -C) to the defined data set and combining these models in various ways via ensemble strategies. Finally, a convex optimization strategy is carried out to find the outperforming weighted ensemble of individual models. The mean age of 161 patients with pneumonia was 49.31 ± 15.12, and the median age was 48 years. The mean age of 218 patients without signs of pneumonia in thorax CTX examination was 40.04 ± 14.46, and the median was 38. When working with different combinations of COVID-Net's six variants, the area under the curve (AUC) using the ensemble COVID-Net CXR 4A-4B-3C was .78, sensitivity 67%, specificity 95%; COVID-Net CXR 4a-3b-3c was .79, sensitivity 69% and specificity 94%. When diverse and complementary COVID-Net models are used together through an ensemble, it has been determined that the AUC values are close to other studies, and the specificity is significantly higher than other studies in the literature.

Platelet and Monocyte Microvesicles as Potential Biomarkers of COVID-19 Severity: A Cross-Sectional Analysis.

Background: Coronavirus disease (COVID-19) induces inflammation, coagulopathy following platelet and monocyte activation, and fibrinolysis, resulting in elevated D-dimer levels. Activated platelets and monocytes produce microvesicles (MVs). We analyzed the differences in platelet and monocyte MV counts in mild, moderate, and severe COVID-19, as well as their correlation with D-dimer levels. Methods: In this cross-sectional study, blood specimens were collected from 90 COVID-19 patients and analyzed for D-dimers using SYSMEX CS-2500. Platelet MVs (PMVs; PMVCD42b+ and PMVCD41a+), monocyte MVs (MMVs; MMVCD14+), and phosphatidylserine-binding annexin V (PS, AnnV+) were analyzed using a BD FACSCalibur instrument. Results: PMV and MMV counts were significantly increased in COVID-19 patients. AnnV+ PMVCD42b+ and AnnV+ PMVCD41a+ cell counts were higher in patients with severe COVID-19 than in those with moderate clinical symptoms. The median (range) of AnnV+ PMVCD42b+ (MV/µL) in mild, moderate, and severe COVID-19 was 1,118.3 (328.1-1,910.5), 937.4 (311.4-2,909.5), and 1,298.8 (458.2-9,703.5), respectively (P =0.009). The median (range) for AnnV+ PMVCD41a+ (MV/µL) in mild, moderate, and severe disease was 885.5 (346.3-1,682.7), 663.5 (233.8-2,081.5), and 1,146.3 (333.3-10,296.6), respectively (P =0.007). D-dimer levels (ng/mL) weak correlated with AnnV+ PMVCD41a+ (P =0.047, r=0.258). Conclusions: PMV PMVCD42b+ and PMVCD41a+ counts were significantly increased in patients with severe clinical symptoms, and PMVCD41a+ counts correlated with D-dimer levels. Therefore, MV counts can be used as a potential biomarker of COVID-19 severity.

Prolonged viral pneumonia and high mortality in COVID-19 patients on anti-CD20 monoclonal antibody therapy.

PURPOSE: In clinical practice, we observed an apparent overrepresentation of COVID-19 patients on anti-CD20 monoclonal antibody therapy. The aim of this study was to characterize the clinical picture of COVID-19 in these patients. METHODS: All adult patients from Turku University Hospital, Turku, Finland, with COVID-19 diagnosis and/or positive SARS-CoV-2 PCR test result up to March 2023, and with anti-CD20 therapy within 12 months before COVID-19 were included. Data was retrospectively obtained from electronic patient records. RESULTS: Ninety-eight patients were identified. 44/93 patients (47.3%) were hospitalized due to COVID-19. Patients with demyelinating disorder (n = 20) were youngest (median age 36.5 years, interquartile range 33-45 years), had less comorbidities, and were least likely to be hospitalized (2/20; 10.0%) or die (n = 0). COVID-19 mortality was 13.3% in the whole group, with age and male sex as independent risk factors. Persistent symptoms were documented in 33/94 patients (35.1%) alive by day 30, in 21/89 patients (23.6%) after 60 days, and in 15/85 after 90 days (17.6%), mostly in patients with haematological malignancy or connective tissue disease. Prolonged symptoms after 60 days predisposed to persistent radiological findings (odds ratio 64.0; 95% confidence interval 6.3-711; p < 0.0001) and persistently positive PCR (odds ratio 45.5, 95% confidence interval 4.0-535; p < 0.0001). Several patients displayed rapid response to late antiviral therapy. CONCLUSION: Anti-CD20 monoclonal antibody therapy is associated with high COVID-19 mortality and with a phenotype consistent with prolonged viral pneumonia. Our study provides rationale for retesting of immunocompromised patients with prolonged COVID-19 symptoms and considering antiviral therapy.