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SARS-CoV-2 antigen rapid diagnostic tests (Ag-RDTs) are increasingly being integrated in testing strategies around the world. Studies of the Ag-RDTs have shown variable performance. In this systematic review and meta-analysis, we assessed the clinical accuracy (sensitivity and specificity) of commercially available Ag-RDTs. We registered the review on PROSPERO (registration number: CRD42020225140). We systematically searched multiple databases (PubMed, Web of Science Core Collection, medRvix, bioRvix, and FIND) for publications evaluating the accuracy of Ag-RDTs for SARS-CoV-2 up until 30 April 2021. Descriptive analyses of all studies were performed, and when more than 4 studies were available, a random-effects meta-analysis was used to estimate pooled sensitivity and specificity in comparison to reverse transcription polymerase chain reaction (RT-PCR) testing. We assessed heterogeneity by subgroup analyses, and rated study quality and risk of bias using the QUADAS-2 assessment tool. From a total of 14,254 articles, we included 133 analytical and clinical studies resulting in 214 clinical accuracy datasets with 112,323 samples. Across all meta-analyzed samples, the pooled Ag-RDT sensitivity and specificity were 71.2% (95% CI 68.2% to 74.0%) and 98.9% (95% CI 98.6% to 99.1%), respectively. Sensitivity increased to 76.3% (95% CI 73.1% to 79.2%) if analysis was restricted to studies that followed the Ag-RDT manufacturers' instructions. LumiraDx showed the highest sensitivity, with 88.2% (95% CI 59.0% to 97.5%). Of instrument-free Ag-RDTs, Standard Q nasal performed best, with 80.2% sensitivity (95% CI 70.3% to 87.4%). Across all Ag-RDTs, sensitivity was markedly better on samples with lower RT-PCR cycle threshold (Ct) values, i.e., <20 (96.5%, 95% CI 92.6% to 98.4%) and <25 (95.8%, 95% CI 92.3% to 97.8%), in comparison to those with Ct ≥ 25 (50.7%, 95% CI 35.6% to 65.8%) and ≥30 (20.9%, 95% CI 12.5% to 32.8%). Testing in the first week from symptom onset resulted in substantially higher sensitivity (83.8%, 95% CI 76.3% to 89.2%) compared to testing after 1 week (61.5%, 95% CI 52.2% to 70.0%). The best Ag-RDT sensitivity was found with anterior nasal sampling (75.5%, 95% CI 70.4% to 79.9%), in comparison to other sample types (e.g., nasopharyngeal, 71.6%, 95% CI 68.1% to 74.9%), although CIs were overlapping. Concerns of bias were raised across all datasets, and financial support from the manufacturer was reported in 24.1% of datasets. Our analysis was limited by the included studies' heterogeneity in design and reporting. In this study we found that Ag-RDTs detect the vast majority of SARS-CoV-2-infected persons within the first week of symptom onset and those with high viral load. Thus, they can have high utility for diagnostic purposes in the early phase of disease, making them a valuable tool to fight the spread of SARS-CoV-2. Standardization in conduct and reporting of clinical accuracy studies would improve comparability and use of data.

COVID-19 has been reported in over 40million people globally with variable clinical outcomes. In this systematic review and meta-analysis, we assessed demographic, laboratory and clinical indicators as predictors for severe courses of COVID-19. This systematic review was registered at PROSPERO under CRD42020177154. We systematically searched multiple databases (PubMed, Web of Science Core Collection, MedRvix and bioRvix) for publications from December 2019 to May 31st 2020. Random-effects meta-analyses were used to calculate pooled odds ratios and differences of medians between (1) patients admitted to ICU versus non-ICU patients and (2) patients who died versus those who survived. We adapted an existing Cochrane risk-of-bias assessment tool for outcome studies. Of 6,702 unique citations, we included 88 articles with 69,762 patients. There was concern for bias across all articles included. Age was strongly associated with mortality with a difference of medians (DoM) of 13.15 years (95% confidence interval (CI) 11.37 to 14.94) between those who died and those who survived. We found a clinically relevant difference between non-survivors and survivors for C-reactive protein (CRP; DoM 69.10 mg/L, CI 50.43 to 87.77), lactate dehydrogenase (LDH; DoM 189.49 U/L, CI 155.00 to 223.98), cardiac troponin I (cTnI; DoM 21.88 pg/mL, CI 9.78 to 33.99) and D-Dimer (DoM 1.29mg/L, CI 0.9 to 1.69). Furthermore, cerebrovascular disease was the co-morbidity most strongly associated with mortality (Odds Ratio 3.45, CI 2.42 to 4.91) and ICU admission (Odds Ratio 5.88, CI 2.35 to 14.73). This comprehensive meta-analysis found age, cerebrovascular disease, CRP, LDH and cTnI to be the most important risk-factors that predict severe COVID-19 outcomes and will inform clinical scores to support early decision-making.

We investigate the feasibility of molecular-level sample classification of sepsis using microarray gene expression data merged by in silico meta-analysis. Publicly available data series were extracted from NCBI Gene Expression Omnibus and EMBL-EBI ArrayExpress to create a comprehensive meta-analysis microarray expression set (meta-expression set). Measurements had to be obtained via microarray-technique from whole blood samples of adult or pediatric patients with sepsis diagnosed based on international consensus definition immediately after admission to the intensive care unit. We aggregate trauma patients, systemic inflammatory response syndrome (SIRS) patients, and healthy controls in a non-septic entity. Differential expression (DE) analysis is compared with machine-learning-based solutions like decision tree (DT), random forest (RF), support vector machine (SVM), and deep-learning neural networks (DNNs). We evaluated classifier training and discrimination performance in 100 independent iterations. To test diagnostic resilience, we gradually degraded expression data in multiple levels. Clustering of expression values based on DE genes results in partial identification of sepsis samples. In contrast, RF, SVM, and DNN provide excellent diagnostic performance measured in terms of accuracy and area under the curve (>0.96 and >0.99, respectively). We prove DNNs as the most resilient methodology, virtually unaffected by targeted removal of DE genes. By surpassing most other published solutions, the presented approach substantially augments current diagnostic capability in intensive care medicine.

Background Bloodstream infections remain one of the major challenges in intensive care units, leading to sepsis or even septic shock in many cases. Due to the lack of timely diagnostic approaches with sufficient sensitivity, mortality rates of sepsis are still unacceptably high. However a prompt diagnosis of the causative microorganism is critical to significantly improve outcome of bloodstream infections. Although various targeted molecular tests for blood samples are available, time-consuming blood culture-based approaches still represent the standard of care for the identification of bacteria. Methods Here we describe the establishment of a complete diagnostic workflow for the identification of infectious microorganisms from seven septic patients based on unbiased sequence analyses of free circulating DNA from plasma by next-generation sequencing. Results We found significant levels of DNA fragments derived from pathogenic bacteria in samples from septic patients. Quantitative evaluation of normalized read counts and introduction of a sepsis indicating quantifier (SIQ) score allowed for an unambiguous identification of Gram-positive as well as Gram-negative bacteria that exactly matched with blood cultures from corresponding patient samples. In addition, we also identified species from samples where blood cultures were negative. Reads of non-human origin also comprised fragments derived from antimicrobial resistance genes, showing that, in principle, prediction of specific types of resistance might be possible. Conclusions The complete workflow from sample preparation to species identification report could be accomplished in roughly 30 h, thus making this approach a promising diagnostic platform for critically ill patients suffering from bloodstream infections.

Here we report on five COVID-19 patients with a median age of 67 years who were admitted to the medical intensive care unit of Heidelberg University Hospital due to respiratory failure. [...]all patients had multi-organ failure with acute respiratory distress syndrome (ARDS, 4 severe, 1 moderate) and acute kidney injury of at least KDIGO stage 2. During the PE, striking reduction of inflammatory markers C-reactive protein (− 47%, P = 0.0078) and interleukin 6 (− 74%, P = 0.0078), as well as significant reduction of ferritin (− 49%, P = 0.0078), LDH (− 41%, P = 0.0078), and D-dimer (− 47%, P = 0.016) were observed (Fig. 1a–e).

Sepsis is a frequently fatal condition characterized by an uncontrolled and harmful host reaction to microbial infection. Despite the prevalence and severity of sepsis, we lack a fundamental grasp of its pathophysiology. Here we report that the cytokine interleukin-3 (IL-3) potentiates inflammation in sepsis. Using a mouse model of abdominal sepsis, we showed that innate response activator B cells produce IL-3, which induces myelopoiesis of Ly-6Chigh monocytes and neutrophils and fuels a cytokine storm. IL-3 deficiency protects mice against sepsis. In humans with sepsis, high plasma IL-3 levels are associated with high mortality even after adjusting for prognostic indicators. This study deepens our understanding of immune activation, identifies IL-3 as an orchestrator of emergency myelopoiesis, and reveals a new therapeutic target for treating sepsis.

Hypercoagulability and thrombo-inflammation are the main reasons for death in COVID-19 patients. It is unclear whether there is a difference between D-dimer levels in patients without or with COVID-19 acute respiratory distress syndrome (ARDS). We searched PubMed, EMBASE, and ClinicalTrails.gov databases looking for studies reporting D-dimer levels in patients without or with COVID-19 ARDS. Secondary endpoints included length of hospital stay, and mortality data at the longest follow-up available. We included 12 retrospective and 3 prospective studies with overall 2,828 patients, of whom 1,404 (49.6%) had non-COVID-19 ARDS and 1,424 had COVID-19 ARDS. D-dimer levels were not significantly higher in non-COVID-19 ARDS than in COVID-19 ARDS patients (mean 7.65 mg/L vs. mean 6.20 mg/L MD 0.88 [CI: -0.61 to 2.38] p = 0.25; I² = 85%) while the length of hospital stay was shorter (non-COVID-19 mean 37.4 days vs. COVID-19 mean 48.5 days, MD -10.92 [CI: -16.71 to -5.14] p < 0.001; I² = 44%). No difference in mortality was observed: non-COVID-19 ARDS 418/1167 (35.8%) vs. COVID-19 ARDS 467/1201 (38.8%). We found no difference in the mean D-dimer levels between non-COVID-19 ARDS and COVID-19 ARDS patients.

Background Preoperative risk prediction in patients at elevated cardiovascular risk shows limited accuracy. Platelet to lymphocyte ratio (PLR) and neutrophil to lymphocyte ratio (NLR) indicate systemic inflammation. Both have been investigated for outcome prediction in the field of oncology and cardiovascular medicine, as well as risk prediction of adverse cardiovascular events in non-surgical patients at increased cardiovascular risk. Methods For this post-hoc analysis, we included all 38 coronary heart disease patients from the Leukocytes and Cardiovascular Perioperative Events cohort-1 study scheduled for elective non-cardiac surgery. We evaluated preoperative differential blood counts for association with major adverse cardiovascular and cerebrovascular events (MACCE) defined as the composite endpoint of death, myocardial ischemia, myocardial infarction, myocardial injury after non-cardiac surgery, or embolic or thrombotic stroke within 30 days after surgery. We used Youden’s index to calculate cut-off values for PLR and NLR. Additive risk-predictive values were assessed using receiver operating characteristic curve and net reclassification (NRI) improvement analyses. Results Patients with the composite endpoint MACCE had higher PLR and NLR (309 [206; 380] vs. 160 [132; 203], p  = 0.001; 4.9 [3.5; 8.1] vs. 2.6 [2.2; 3.4]), p  = 0.001). Calculated cut-offs for PLR > 204.4 and NLR > 3.1 were associated with increased risk of 30-day MACCE (OR 7, 95% CI [1.2; 44.7], p  = 0.034; OR 36, 95% CI [1.8; 686.6], p  = 0.001). Furthermore, NLR improved risk prediction in coronary heart disease patients undergoing non-cardiac surgery when combined with hs-cTnT or NT-proBNP (NRI total  = 0.23, p  = 0.008, NRI total  = 0.26, p  = 0.005). Conclusions Both PLR and NLR were associated with perioperative cardiovascular adverse events in coronary heart disease patients. NLR proved to be of additional value for preoperative risk stratification. Both PLR and NLR could be used as inexpensive and broadly available tools for perioperative risk assessment. Trial registration NCT02874508 , August 22, 2016.

Aim This work provides an epidemiological overview of out-of-hospital cardiac arrest (OHCA) in children in Germany between 2007 and 2021. We wanted to identify modifiable factors associated with survival. Methods Data from the German Resuscitation Registry (GRR) were used, and we included patients registered between 1st January 2007 and 31st December 2021. We included children aged between > 7 days and 17 years, where cardiopulmonary resuscitation (CPR) was started, and treatment was continued by emergency medical services (EMS). Incidences and descriptive analyses are presented for the overall cohort and each age group. Multivariate binary logistic regression was performed on the whole cohort to determine the influence of (1) CPR with/without ventilation started by bystander, (2) OHCA witnessed status and (3) night-time on the outcome hospital admission with return of spontaneous circulation (ROSC). Results OHCA in children aged < 1 year had the highest incidence of the same age group, with 23.42 per 100 000. Overall, hypoxia was the leading presumed cause of OHCA, whereas trauma and drowning accounted for a high proportion in children aged > 1 year. Bystander-witnessed OHCA and bystander CPR rate were highest in children aged 1–4 years, with 43.9% and 62.3%, respectively. In reference to EMS-started CPR, bystander CPR with ventilation were associated with an increased odds ratio for ROSC at hospital admission after adjusting for age, sex, year of OHCA and location of OHCA. Conclusion This study provides an epidemiological overview of OHCA in children in Germany and identifies bystander CPR with ventilation as one primary factor for survival. Trial registrations German Clinical Trial Register: DRKS00030989, December 28th 2022. Graphical Abstract

With more than 18 million annual new cases, cancer belongs to the major challenges of modern healthcare. Surgical resection of solid tumours under general anaesthesia is the prime therapy. Different aspects of anaesthesia are under discussion to independently influence the long-term outcome of cancer patients. Most recently, the commonly used volatile anaesthetics like sevoflurane have entered the spotlight, as retrospective studies suggest a detrimental outcome in certain cancer aetiologies with sparse mechanistic understanding. Our objective was to investigate this concept in a murine melanoma model, herein comparing the consequence of inhalative and injection anesthesia on tumour composition and growth. We used a murine model of malignant melanoma in male, adult C57BL/6 mice (n = 92), induced by the subcutaneous injection of B16-F10 cells. We either exposed the melanoma cells to sevoflurane before implantation or subjected the animals to single or double anaesthesia with either volatile or injection drugs. After a maximum follow-up of 4 weeks, leucocytes within the tumour microenvironment (TME) were comprehensively analysed by flow cytometry with focus on tumor-associated macrophages (TAM). We found that exposure of melanoma cells to sevoflurane before implantation induced long-lasting transcriptome changes and aggravated tumour growth, without extensive changes of the TME. Contrastingly, both a single and double anaesthesia with sevoflurane led to a significant reduction of TAMs (injection vs. sevoflurane: 2,0 vs. 0.3% and 1.2 vs. 0.6%, respectively), whilst increasing PD-L1 expression on the remaining cells (mean fluorescent intensity injection vs. sevoflurane: 3,804 vs. 7,143 and 9,090 vs. 32,228, respectively). No changes in tumour growth were observed in these groups. In sharp contrast to the detrimental impact of sevoflurane on patients' outcome reported in retrospective clinical studies, we propose here that sevoflurane might actually exert a beneficial effect by decreasing TAMs within the TME, rendering the tumour again susceptible for cytotoxic T cells and immunotherapies. Further research is warranted to delineate, how these results translate into the clinic.