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Introduction: Severe COVID-19 is associated with reduced absolute lymphocyte counts, suggesting that lymphocyte subsets may serve as predictors of clinical outcomes in affected patients. Early identification of patients at risk for severe disease is crucial for optimizing care, accurately informing patients and their families, guiding therapeutic interventions, and improving patient flow in the ED. Given that immunosuppressive drugs significantly impact lymphocyte profiles, we aimed to determine the association between prior use of immunosuppressive drugs, lymphocyte subsets, and COVID-19 severity in our population with a high prevalence of immunosuppression., Methods: In 2021, suspected COVID-19 patients were included in the ED. Lymphocyte subsets were determined in peripheral blood within 24 hours after presentation and comparative analyses was performed between SARS-CoV-2 negative and positive patients, mild versus severe disease and patients with and without prior immunosuppressive drug use. Mild cases were patients discharged home or admitted to a general ward, severe cases were patients with COVID-19-related mortality or necessitating ICU admission. Logistic regression analysis was performed to assess the association between lymphocyte subsets and COVID-19 severity, and between prior immunosuppressive drug use and COVID-19 severity., Results: Twenty-five SARS-CoV-2 negative and 77 SARS-CoV-2 positive patients were included, whereof 57 (74%) had mild and 20 (26%) severe COVID-19. No significant differences were observed in the absolute counts of CD3+, CD4+, and CD8+ T-lymphocytes, B-lymphocytes, and NK-cells between SARS-CoV-2 negative and positive patients or between mild and severe cases. The 36 patients with prior use of immunosuppressive drugs had significantly lower CD4+ T-lymphocytes (p<0.01). Prior use of immunosuppressive drugs was not associated with COVID-19 severity (adjusted OR 1.074, 0.355-3.194)., Conclusion: Lymphocyte subsets were not significantly different between SARS-CoV-2 negative and positive patients and between mild versus severe cases. Neither lymphocyte subsets nor prior immunosuppressive drug use were associated with COVID-19 severity., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Daenen, van Hooijdonk, Tong-Minh, Dik, van Hagen, Huijben, Gommers, van Gorp, Endeman and Dalm.)

FebriDx is a rapid point-of-care test combining qualitative measurements of C-reactive protein (CRP) and Myxovirus Resistance Protein A (MxA) using a disposable test device to detect and differentiate acute bacterial from viral respiratory tract infections. The goal of this study was to investigate the diagnostic accuracy of FebriDx in patients with suspected respiratory tract infections in the emergency department (ED). This was an observational cohort study, performed in the ED of an academic hospital. Patients were included if they had a suspected infection. The primary outcome was the presence of a bacterial or viral infection, determined by clinical adjudication by an expert panel. The sensitivity, specificity, and positive and negative predictive value of FebriDx for the presence of bacterial versus non-bacterial infections, and viral versus non-viral infections were calculated. Between March 2019 and November 2020, 244 patients were included. A bacterial infection was present in 41%, viral infection was present in 24%, and 4% of the patients had both viral and bacterial pathogens. FebriDx demonstrated high sensitivity in the detection of bacterial infection (87%), high NPV (91%) to rule out bacterial infection, and high specificity (94%) for viral infection in patients with a suspected infection in the ED.

The prediction of disease outcomes in COVID-19 patients in the ICU is of critical importance, and the examination of host gene expressions is a promising tool. The 29-host mRNA Inflam-matix-Severity-3b (IMX-SEV-3b) classifier has been reported to predict mortality in emergency department COVID-19 patients and surgical ICU patients. The accuracy of the IMX-SEV-3b in predicting mortality in COVID-19 patients admitted to the ICU is yet unknown. Our aim was to investigate the accuracy of the IMX-SEV-3b in predicting the ICU mortality of COVID-19 patients. In addition, we assessed the predictive performance of routinely measured biomarkers and the Sequential Organ Failure Assessment (SOFA) score as well. This was a prospective observational study enrolling COVID-19 patients who received mechanical ventilation on the ICU of the Erasmus MC, the Netherlands. The IMX-SEV-3b scores were generated by amplifying 29 host response genes from blood collected in PAXgene ® Blood RNA tubes. A severity score was provided, ranging from 0 to 1 for increasing disease severity. The primary outcome was the accuracy of the IMX-SEV-3b in predicting ICU mortality, and we calculated the AUROC of the IMX-SEV-3b score, the biomarkers C-reactive protein (CRP), D-dimer, ferritin, leukocyte count, interleukin-6 (IL-6), lactate dehydrogenase (LDH), neutrophil-to-lymphocyte ratio (NLR), procalcitonin (PCT) and the SOFA score. A total of 53 patients were included between 1 March and 30 April 2020, with 47 of them being included within 72 h of their admission to the ICU. Of these, 18 (34%) patients died during their ICU stay, and the IMX-SEV-3b scores were significantly higher in non-survivors compared to survivors (0.65 versus 0.57, p = 0.05). The Area Under the Receiver Operating Characteristic Curve (AUROC) for prediction of ICU mortality by the IMX-SEV-3b was 0.65 (0.48-0.82). The AUROCs of the biomarkers ranged from 0.52 to 0.66, and the SOFA score had an AUROC of 0.81 (0.69-0.93). The AUROC of the pooled biomarkers CRP, D-dimer, ferritin, leukocyte count, IL-6, LDH, NLR and PCT for prediction of ICU mortality was 0.81 (IQR 0.69-0.93). Further validation in a larger interventional trial of a point-of-care version of the IMX-SEV-3b classifier is warranted to determine its value for patient management.

Introduction: Predicting disease severity is important for treatment decisions in patients with COVID-19 in the intensive care unit (ICU). Different biomarkers have been investigated in COVID-19 as predictor of mortality, including C-reactive protein (CRP), procalcitonin (PCT), interleukin-6 (IL-6), and soluble urokinase-type plasminogen activator receptor (suPAR). Using repeated measurements in a prediction model may result in a more accurate risk prediction than the use of single point measurements. The goal of this study is to investigate the predictive value of trends in repeated measurements of CRP, PCT, IL-6, and suPAR on mortality in patients admitted to the ICU with COVID-19., Methods: This was a retrospective single center cohort study. Patients were included if they tested positive for SARS-CoV-2 by PCR test and if IL-6, PCT, suPAR was measured during any of the ICU admission days. There were no exclusion criteria for this study. We used joint models to predict ICU-mortality. This analysis was done using the framework of joint models for longitudinal and survival data. The reported hazard ratios express the relative change in the risk of death resulting from a doubling or 20% increase of the biomarker's value in a day compared to no change in the same period., Results: A total of 107 patients were included, of which 26 died during ICU admission. Adjusted for sex and age, a doubling in the next day in either levels of PCT, IL-6, and suPAR were significantly predictive of in-hospital mortality with HRs of 1.523 (1.012-6.540), 75.25 (1.116-6247), and 24.45 (1.696-1057) respectively. With a 20% increase in biomarker value in a subsequent day, the HR of PCT, IL-6, and suPAR were 1.117 (1.03-1.639), 3.116 (1.029-9.963), and 2.319 (1.149-6.243) respectively., Conclusion: Joint models for the analysis of repeated measurements of PCT, suPAR, and IL-6 are a useful method for predicting mortality in COVID-19 patients in the ICU. Patients with an increasing trend of biomarker levels in consecutive days are at increased risk for mortality., Competing Interests: Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2022.)

Introduction: Myxovirus resistance protein 1 (MxA) is a biomarker that is elevated in patients with viral infections. The goal of this study was to evaluate the diagnostic value of MxA in diagnosing COVID-19 infections in the emergency department (ED) patients., Methods: This was a single-center prospective observational cohort study including patients with a suspected COVID-19 infection. The primary outcome of this study was a confirmed COVID-19 infection by RT-PCR test. MxA was assessed using an enzyme immunoassay on whole blood and receiver operating chart and area under the curve (AUC) analysis was conducted. Sensitivity, specificity, negative predictive value, and positive predictive value of MxA on diagnosing COVID-19 at the optimal cut-off of MxA was determined., Results: In 2021, 100 patients were included. Of these patients, 77 patients had COVID-19 infection and 23 were non-COVID-19. Median MxA level was significantly higher (p < .001) in COVID-19 patients compared to non-COVID-19 patients, respectively 1933 and 0.1 ng/ml. The AUC of MxA on a confirmed COVID-19 infection was 0.941 (95% CI: 0.867-1.000). The optimal cut-off point of MxA was 252 ng/ml. At this cut-off point, the sensitivity of MxA on a confirmed COVID-19 infection was 94% (95% CI: 85%-98%) and the specificity was 91% (95% CI: 72%-99%)., Conclusion: MxA accurately distinguishes COVID-19 infections from bacterial infections and noninfectious diagnoses in the ED in patients with a suspected COVID-19 infection. If the results can be validated, MxA could improve the diagnostic workup and patient flow in the ED., (© 2022 The Authors. Immunity, Inflammation and Disease published by John Wiley & Sons Ltd.)

Background: Patients with a severe COVID-19 infection often require admission at an intensive care unit (ICU) when they develop acute respiratory distress syndrome (ARDS). Hyperinflammation plays an important role in the development of ARDS in COVID-19. Procalcitonin (PCT) is a biomarker which may be a predictor of hyperinflammation. When patients with COVID-19 are in the emergency department (ED), elevated PCT levels could be associated with severe COVID-19 infections. The goal of this study is to investigate the association between PCT levels and severe COVID-19 infections in the ED., Methods: This was a retrospective cohort study including patients with a confirmed COVID-19 infection who visited the ED of Erasmus Medical Center in Rotterdam, the Netherlands, between March and December 2020. The primary outcome was a severe COVID-19 infection, which was defined as patients who required ICU admission, all cause in-hospital mortality and mortality within 30 days after hospital discharge. PCT levels were measured during the ED visit. We used logistic regression to calculate the odds ratio (OR) with 95% confidence interval (95% CI) and corresponding area under the curve (AUC) of PCT on a severe COVID-19 infection, adjusting for bacterial coinfections, age, sex, comorbidities, C-reactive protein (CRP) and D-dimer., Results: A total of 332 patients were included in the final analysis of this study, of which 105 patients reached the composite outcome of a severe COVID-19 infection. PCT showed an unadjusted OR of 4.19 (95%CI: 2.52-7.69) on a severe COVID-19 infection with an AUC of 0.82 (95% CI: 0.76-0.87). Corrected for bacterial coinfection, the OR of PCT was 4.05 (95% CI: 2.45-7.41). Adjusted for sex, bacterial coinfection, age any comorbidity, CRP and D-dimer, elevated PCT levels were still significantly associated with a severe COVID-19 infection with an adjusted OR of 2.11 (95% CI: 1.36-3.61). The AUC of this multivariable model was 0.85 (95%CI: 0.81-0.90)., Conclusion: High PCT levels are associated with high rates of severe COVID-19 infections in patients with a COVID-19 infection in the ED. The routine measurement of PCT in patients with a COVID-19 infection in the ED may assist physicians in the clinical decision making process regarding ICU disposition., (© 2022. The Author(s).)

Background: Sepsis can be detected in an early stage in the emergency department (ED) by biomarkers and clinical scoring systems. A combination of multiple biomarkers or biomarker with clinical scoring system might result in a higher predictive value on mortality. The goal of this systematic review is to evaluate the available literature on combinations of biomarkers and clinical scoring systems on 1-month mortality in patients with sepsis in the ED., Methods: We performed a systematic search using MEDLINE, EMBASE and Google Scholar. Articles were included if they evaluated at least one biomarker combined with another biomarker or clinical scoring system and reported the prognostic accuracy on 28 or 30 day mortality by area under the curve (AUC) in patients with sepsis. We did not define biomarker cut-off values in advance., Results: We included 18 articles in which a total of 35 combinations of biomarkers and clinical scoring systems were studied, of which 33 unique combinations. In total, seven different clinical scoring systems and 21 different biomarkers were investigated. The combination of procalcitonin (PCT), lactate, interleukin-6 (IL-6) and Simplified Acute Physiology Score-2 (SAPS-2) resulted in the highest AUC on 1-month mortality., Conclusion: The studies we found in this systematic review were too heterogeneous to conclude that a certain combination it should be used in the ED to predict 1-month mortality in patients with sepsis. Future studies should focus on clinical scoring systems which require a limited amount of clinical parameters, such as the qSOFA score in combination with a biomarker that is already routinely available in the ED.

Background: Cystic fibrosis (CF) caregivers focus on correct inhalation technique for nebulisers as this is essential to optimize efficacy of inhaled drugs. However, little is known on this nebuliser technique of patients at home., Methods: Three "hidden" video registrations were made of 32 children with CF (6-18years) nebulising at home. Videos were randomly scored on inhalation technique items using nebuliser-specific checklists and a total score was calculated., Results: Median nebuliser technique was 91.9% of max score. Nebuliser technique was perfect (score 100%) in 23.3% of the patients and incorrect (score 0%) in 13.3%. Most mistakes were made in the required optimal breathing pattern., Conclusion: Most CF patients had good nebuliser technique on a day-to-day basis. However, errors observed likely resulted in reduced treatment efficacy and, in 13%, no treatment at all. Regular "real life" evaluation by the CF-team can improve inhaled therapy substantially., (Copyright © 2016 European Cystic Fibrosis Society. Published by Elsevier B.V. All rights reserved.)