Altered DNA methylation underlies monocyte dysregulation and innate exhaustion memory in sepsis (preprint)

Innate immune memory is the process by which pathogen exposure elicits cell-intrinsic states to alter the strength of future immune challenges. Such altered memory states drive monocyte dysregulation during sepsis, promoting pathogenic behavior characterized by pro-inflammatory, immunosuppressive gene expression in concert with emergency hematopoiesis. Epigenetic changes, notably in the form of histone modifications, have been shown to underlie innate immune memory, but the contribution of DNA methylation to this process remains poorly understood. Using an ex vivo sepsis model, we discovered broad changes in DNA methylation throughout the genome of exhausted monocytes, including at several genes previously implicated as major drivers of immune dysregulation during sepsis and Covid-19 infection (e.g. Plac8). Methylome alterations are driven in part by Wnt signaling inhibition in exhausted monocytes, and can be reversed through treatment with DNA methyltransferase inhibitors, Wnt agonists, or immune training molecules. Importantly, these changes are recapitulated in septic mice following cecal slurry injection, resulting in stable changes at critical immune genes that support the involvement of DNA methylation in acute and long-term monocyte dysregulation during sepsis.

Community-onset urinary tract infection in females in the context of COVID-19: a longitudinal population cohort study exploring case presentation, management, and outcomes (preprint)

Background COVID-19 affected the epidemiology of other infectious diseases and how they were managed. Urinary tract infection (UTI) is one of the most common infections treated in the community in England. We investigated the impact of the COVID-19 pandemic on UTI primary care consultations and outcomes in female patients. Methods and findings We analysed General Practice (GP) consultation and hospital admission records using the Whole Systems Integrated Care (WSIC) data in North West London between 2016 and 2021. We quantified the changes in UTI GP consultation rates using time series analysis before and during the pandemic. We assessed the outcomes of UTI, measured by subsequent bacteraemia and sepsis within 60 days, for consultations delivered face-to-face or remotely, with or without diagnostic tests recommended by the national guidelines, and with or without antibiotic treatment. Between January 2016 and December 2021, we identified 375,859 UTI episodes in 233,450 female patients. Before the COVID-19 pandemic (January 2016-February 2020), the UTI GP consultation rate stayed level at 522.8 cases per 100,000 population per month, with a seasonal pattern of peaking in October. Since COVID-19, (March 2020-December 2021), monthly UTI GP consultations declined when COVID-19 cases surged and rose when COVID-19 case fell. During the pandemic, the UTI consultations delivered face-to-face reduced from 72.0% to 29.4%, the UTI consultations with appropriate diagnostic tests, including urine culture and urinalysis, reduced from 17.3% to 10.4%, and the UTI cases treated with antibiotics reduced from 52.0% to 47.8%. The likelihood of antibiotics being prescribed was not affected by whether the consultation was delivered face-to-face or remotely but associated with whether there was a diagnostic test. Regardless of whether the UTI consultation occurred before or during the pandemic, the absence of antibiotic treatment for UTI is associated with a 10-fold increase in the risk of having bacteraemia or sepsis within 60 days, though the patients who consulted GPs for UTI during the pandemic were older and more co-morbid. Across the study period (January 2016-December 2021), nitrofurantoin remained the first-line antibiotic option for UTI. The percentage of non-prophylactic acute UTI antibiotic prescriptions with durations that exceeded the guideline recommendations was 58.7% before the pandemic, and 49.4% since. This led to 830,522 total excess days of treatment, account for 63.3% of all non-prophylactic acute antibiotics prescribed for UTI. Before the pandemic, excess antibiotic days of UTI drugs had been reducing consistently. However, this decline slowed down during the pandemic. Having a diagnostic test was associated with 0.6 less excess days of antibiotic treatment. Conclusions This analysis provides a comprehensive examination of management and outcomes of community-onset UTI in female patients, considering the changes in GP consultations during the COVID-19 pandemic. Our findings highlighted the importance of appropriate urine testing to support UTI diagnosis in symptomatic patients and initiation of antibiotic treatment with appropriate course duration. Continued monitoring is required to assess the overall impact on patients and health systems from the changed landscape of primary care delivery.

Accuracy of automated computer-aided risk scoring systems to estimate the risk of COVID-19: a retrospective cohort study (preprint)

Background: In the UK National Health Service (NHS), the patient’s vital signs are monitored and summarised into a National Early Warning Score (NEWS) score. A set of computer-aided risk scoring systems (CARSS) was developed and validated for predicting in-hospital mortality and sepsis in unplanned admission to hospital using NEWS and routine blood tests results. We sought to assess the accuracy of these models to predict the risk of COVID-19 in unplanned admisisons during the first phase of the pandemic. Methods: Adult (>=18 years) non-elective admissions discharged (alive/deceased) between 11-March-2020 to 13-June-2020 from two acute hospitals with an index NEWS electronically recorded within ±24 hours of admission. We identified COVID-19 admission based on ICD-10 code ‘U071’ which was determined by COVID-19 swab test results (hospital or community). We assessed the performance of CARSS (CARS_N, CARS_NB, CARM_N, CARM_NB) for predicting the risk of COVID-19 in terms of discrimination (c-statistic) and calibration (graphically). Results: The risk of in-hospital mortality following emergency medical admission was 8.4% (500/6444) and 9.6% (620/6444) had a diagnosis of COVID-19. For predicting COVID-19 admissions, the CARS_N model had the highest discrimination 0.73 (0.71 to 0.75) and calibration slope 0.81 (0.72 to 0.89) compared to other CARSS models: CARM_N (discrimination:0.68 (0.66 to 0.70) and calibration slope 0.47 (0.41 to 0.54)), CARM_NB (discrimination:0.68 (0.65 to 0.70) and calibration slope 0.37 (0.31 to 0.43)), and CARS_NB (discrimination:0.68 (0.66 to 0.70) and calibration slope 0.56 (0.47 to 0.64)). Conclusions: The CARS_N model is reasonably accurate for predicting the risk of COVID-19. It may be clinically useful as an early warning system at the time of admission especially to triage large numbers of unplanned hospital admissions because requires no additional data collection and is readily automated.

Long-term outcomes of hospitalized SARS-CoV-2/COVID-19 patients with and without neurological involvement: 3-year follow-up assessment (preprint)

Background and ObjectivesAcute neurological manifestations are a common complication of acute COVID-19 disease. This study investigated the 3-year outcomes of patients with and without significant neurological manifestations during initial COVID-19 hospitalization. MethodsPatients infected by SARS-CoV-2 between March 1 and April 16, 2020 and hospitalized in the Montefiore Health System in the Bronx, an epicenter of the early pandemic, were included. Follow-up data was captured up to January 23, 2023 (3 years post COVID-19). This cohort consisted of 414 COVID-19 patients with significant neurological manifestations and 1199 propensity-matched COVID- 19 patients without neurological manifestations. Primary outcomes were mortality, stroke, heart attack, major adverse cardiovascular events (MACE), reinfection, and hospital readmission post-discharge. Secondary outcomes were clinical neuroimaging findings (hemorrhage, active stroke, prior stroke, mass effect, and microhemorrhage, white-matter changes, microvascular disease, and volume loss). Predictive models were used to identify risk factors of mortality post-discharge. ResultsMore patients in the neurological cohort were discharged to acute rehabilitation (10.54% vs 3.68%, p<0.0001), skilled nursing facilities (30.67% vs 20.78%, p=0.0002) and fewer to home (55.27% vs 70.21%, p<0.0001) compared to the matched controls. Incidence of readmission for any medical reason (65.70% vs 60.72%, p=0.036), stroke (6.28% vs 2.34%, p<0.0001), and MACE (20.53% vs 16.51%, p=0.032) was higher in the neurological cohort post-discharge. Neurological patients were more likely to die post-discharge (58 (14.01%) vs 94 (7.84%), p=0.0001) compared to controls (HR=2.346, 95% CI=(1.586, 3.470), p<0.0001). The major causes of death post-discharge were heart disease (14.47%), sepsis (13.82%), influenza and pneumonia (11.18%), COVID-19 (8.55%) and acute respiratory distress syndrome (7.89%). Factors associated with mortality after leaving the hospital were belonging to the neurological cohort (OR=1.802 (1.237, 2.608), p=0.002), discharge disposition (OR=1.508, 95% CI=(1.276, 1.775), p<0.0001), congestive heart failure (OR=2.281 (1.429, 3.593), p=0.0004), higher COVID-19 severity score (OR=1.177 (1.062, 1.304), p=0.002), and older age (OR=1.027 (1.010, 1.044), p=0.002). There were no group differences in gross radiological findings, except the neurological cohort showed significantly more age-adjusted brain volume loss (p<0.05) compared to controls. DiscussionCOVID-19 patients with neurological manifestations have worse long-term outcomes compared to matched controls. These findings raise awareness and the need for closer monitoring and timely interventions for COVID-19 patients with neurological manifestations.

[Informativeness estimation for the main clinical and laboratory parameters in patients with severe COVID-19].

AIM: To conduct a retrospective assessment of the clinical and laboratory data of patients with severe forms of COVID-19 hospitalized in the intensive care and intensive care unit, in order to assess the contribution of various indicators to the likelihood of death. MATERIALS AND METHODS: A retrospective assessment of data on 224 patients with severe COVID-19 admitted to the intensive care unit was carried out. The analysis included the data of biochemical, clinical blood tests, coagulograms, indicators of the inflammatory response. When transferring to the intensive care units (ICU), the indicators of the formalized SOFA and APACHE scales were recorded. Anthropometric and demographic data were downloaded separately. RESULTS: Analysis of obtained data, showed that only one demographic feature (age) and a fairly large number of laboratory parameters can serve as possible markers of an unfavorable prognosis. We identified 12 laboratory features the best in terms of prediction: procalcitonin, lymphocytes (absolute value), sodium (ABS), creatinine, lactate (ABS), D-dimer, oxygenation index, direct bilirubin, urea, hemoglobin, C-reactive protein, age, LDH. The combination of these features allows to provide the quality of the forecast at the level of AUC=0.85, while the known scales provided less efficiency (APACHE: AUC=0.78, SOFA: AUC=0.74). CONCLUSION: Forecasting the outcome of the course of COVID-19 in patients in ICU is relevant not only from the position of adequate distribution of treatment measures, but also from the point of view of understanding the pathogenetic mechanisms of the development of the disease.

Early plasma angiopoietin-2 is prognostic for ARDS and mortality among critically ill patients with sepsis.

Angiopoietin-2 (Ang-2) is associated with vascular endothelial injury and permeability in the acute respiratory distress syndrome (ARDS) and sepsis. Elevated circulating Ang-2 levels may identify critically ill patients with distinct pathobiology amenable to targeted therapy. We hypothesized that plasma Ang-2 measured shortly after hospitalization among patients with sepsis would be associated with the development of ARDS and poor clinical outcomes. To test this hypothesis, we measured plasma Ang-2 in a cohort of 757 patients with sepsis, including 267 with ARDS, enrolled in the emergency department or early in their ICU course before the COVID-19 pandemic. Multivariable models were used to test the association of Ang-2 with the development of ARDS and 30-day morality. We found that early plasma Ang-2 in sepsis was associated with higher baseline severity of illness, the development of ARDS, and mortality risk. The association between Ang-2 and mortality was strongest among patients with ARDS and sepsis as compared to those with sepsis alone (OR 1.81 vs. 1.52 per log Ang-2 increase). These findings might inform models testing patient risk prediction and strengthen the evidence for Ang-2 as an appealing biomarker for patient selection for novel therapeutic agents to target vascular injury in sepsis and ARDS.

Bioinformatics and system biology approach to identify the influences among COVID-19, ARDS and sepsis.

Background Severe coronavirus disease 2019 (COVID -19) has led to severe pneumonia or acute respiratory distress syndrome (ARDS) worldwide. we have noted that many critically ill patients with COVID-19 present with typical sepsis-related clinical manifestations, including multiple organ dysfunction syndrome, coagulopathy, and septic shock. The molecular mechanisms that underlie COVID-19, ARDS and sepsis are not well understood. The objectives of this study were to analyze potential molecular mechanisms and identify potential drugs for the treatment of COVID-19, ARDS and sepsis using bioinformatics and a systems biology approach. Methods Three RNA-seq datasets (GSE171110, GSE76293 and GSE137342) from Gene Expression Omnibus (GEO) were employed to detect mutual differentially expressed genes (DEGs) for the patients with the COVID-19, ARDS and sepsis for functional enrichment, pathway analysis, and candidate drugs analysis. Results We obtained 110 common DEGs among COVID-19, ARDS and sepsis. ARG1, FCGR1A, MPO, and TLR5 are the most influential hub genes. The infection and immune-related pathways and functions are the main pathways and molecular functions of these three diseases. FOXC1, YY1, GATA2, FOXL, STAT1 and STAT3 are important TFs for COVID-19. mir-335-5p, miR-335-5p and hsa-mir-26a-5p were associated with COVID-19. Finally, the hub genes retrieved from the DSigDB database indicate multiple drug molecules and drug-targets interaction. Conclusion We performed a functional analysis under ontology terms and pathway analysis and found some common associations among COVID-19, ARDS and sepsis. Transcription factors-genes interaction, protein-drug interactions, and DEGs-miRNAs coregulatory network with common DEGs were also identified on the datasets. We believe that the candidate drugs obtained in this study may contribute to the effective treatment of COVID-19.

Neutrophils and emergency granulopoiesis drive immune suppression and an extreme response endotype during sepsis.

Sepsis arises from diverse and incompletely understood dysregulated host response processes following infection that leads to life-threatening organ dysfunction. Here we showed that neutrophils and emergency granulopoiesis drove a maladaptive response during sepsis. We generated a whole-blood single-cell multiomic atlas (272,993 cells, n = 39 individuals) of the sepsis immune response that identified populations of immunosuppressive mature and immature neutrophils. In co-culture, CD66b+ sepsis neutrophils inhibited proliferation and activation of CD4+ T cells. Single-cell multiomic mapping of circulating hematopoietic stem and progenitor cells (HSPCs) (29,366 cells, n = 27) indicated altered granulopoiesis in patients with sepsis. These features were enriched in a patient subset with poor outcome and a specific sepsis response signature that displayed higher frequencies of IL1R2+ immature neutrophils, epigenetic and transcriptomic signatures of emergency granulopoiesis in HSPCs and STAT3-mediated gene regulation across different infectious etiologies and syndromes. Our findings offer potential therapeutic targets and opportunities for stratified medicine in severe infection.

Facilitating systems-level analyses of all-cause and Covid-mediated sepsis through SeptiSearch, a manually-curated compendium of dysregulated gene sets.

Background: Sepsis is a dysfunctional host response to infection. The syndrome leads to millions of deaths annually (19.7% of all deaths in 2017) and is the cause of most deaths from severe Covid infections. High throughput sequencing or 'omics' experiments in molecular and clinical sepsis research have been widely utilized to identify new diagnostics and therapies. Transcriptomics, quantifying gene expression, has dominated these studies, due to the efficiency of measuring gene expression in tissues and the technical accuracy of technologies like RNA-Seq. Objective: Most of these studies seek to uncover novel mechanistic insights into sepsis pathogenesis and diagnostic gene signatures by identifying genes differentially expressed between two or more relevant conditions. However, little effort has been made, to date, to aggregate this knowledge from such studies. In this study we sought to build a compendium of previously described gene sets that combines knowledge gained from sepsis-associated studies. This would enable the identification of genes most associated with sepsis pathogenesis, and the description of the molecular pathways commonly associated with sepsis. Methods: PubMed was searched for studies using transcriptomics to characterize acute infection/sepsis and severe sepsis (i.e., sepsis combined with organ failure). Several studies were identified that used transcriptomics to identify differentially expressed (DE) genes, predictive/prognostic signatures, and underlying molecular responses and pathways. The molecules included in each gene set were collected, in addition to the relevant study metadata (e.g., patient groups used for comparison, sample collection time point, tissue type, etc.). Results: After performing extensive literature curation of 74 sepsis-related publications involving transcriptomics, 103 unique gene sets (comprising 20,899 unique genes) from thousands of patients were collated together with associated metadata. Frequently described genes included in gene sets as well as the molecular mechanisms they were involved in were identified. These mechanisms included neutrophil degranulation, generation of second messenger molecules, IL-4 and -13 signaling, and IL-10 signaling among many others. The database, which we named SeptiSearch, is made available in a web application created using the Shiny framework in R, (available at https://septisearch.ca). Conclusions: SeptiSearch provides members of the sepsis community the bioinformatic tools needed to leverage and explore the gene sets contained in the database. This will allow the gene sets to be further scrutinized and analyzed for their enrichment in user-submitted gene expression data and used for validation of in-house gene sets/signatures.

Epidemiology and risk factors of 28-day mortality of hospital-acquired bloodstream infection in Turkish intensive care units: a prospective observational cohort study.

OBJECTIVES: To uncover clinical epidemiology, microbiological characteristics and outcome determinants of hospital-acquired bloodstream infections (HA-BSIs) in Turkish ICU patients. METHODS: The EUROBACT II was a prospective observational multicontinental cohort study. We performed a subanalysis of patients from 24 Turkish ICUs included in this study. Risk factors for mortality were identified using multivariable Cox frailty models. RESULTS: Of 547 patients, 58.7% were male with a median [IQR] age of 68 [55-78]. Most frequent sources of HA-BSIs were intravascular catheter [182, (33.3%)] and lower respiratory tract [175, (32.0%)]. Among isolated pathogens (n = 599), 67.1% were Gram-negative, 21.5% Gram-positive and 11.2% due to fungi. Carbapenem resistance was present in 90.4% of Acinetobacter spp., 53.1% of Klebsiella spp. and 48.8% of Pseudomonas spp. In monobacterial Gram-negative HA-BSIs (n = 329), SOFA score (aHR 1.20, 95% CI 1.14-1.27), carbapenem resistance (aHR 2.46, 95% CI 1.58-3.84), previous myocardial infarction (aHR 1.86, 95% CI 1.12-3.08), COVID-19 admission diagnosis (aHR 2.95, 95% CI 1.25-6.95) and not achieving source control (aHR 2.02, 95% CI 1.15-3.54) were associated with mortality. However, availability of clinical pharmacists (aHR 0.23, 95% CI 0.06-0.90) and source control (aHR 0.46, 95% CI 0.28-0.77) were associated with survival. In monobacterial Gram-positive HA-BSIs (n = 93), SOFA score (aHR 1.29, 95% CI 1.17-1.43) and age (aHR 1.05, 95% CI 1.03-1.08) were associated with mortality, whereas source control (aHR 0.41, 95% CI 0.20-0.87) was associated with survival. CONCLUSIONS: Considering high antimicrobial resistance rate, importance of source control and availability of clinical pharmacists, a multifaceted management programme should be adopted in Turkish ICUs.

Kinome and phosphoproteome reprogramming underlies the aberrant immune responses in critically ill COVID-19 patients (preprint)

The SARS-CoV-2 infection elicits comprehensive host immune reactions and causes severe diseases in some individuals. However, the molecular basis underlying the excessive, yet non-productive immune responses in severe COVID-19 is not fully understood. To address this, we compared the peripheral blood mononuclear cell (PBMC) proteome and phosphoproteome of sepsis patients positive or negative for SARS-CoV-2 and healthy subjects by quantitative mass spectrometry. We show here that the COVID-19 PBMC proteome and phosphoproteome undergo dynamic changes during disease progression, and the corresponding protein or phosphoprotein signatures can distinguish longitudinal disease states. Furthermore, SARS-CoV-2 infection leads to a global reprogramming of the kinome and the phosphoproteome, resulting in defective adaptive immune response mediated by B and T lymphocytes, compromised innate immune responses involving the SIGLEC and SLAM family of immunoreceptors, and excessive cytokine-JAK-STAT signaling. Besides uncovering the host proteome and phosphoproteome aberrations caused by SARS-CoV-2, our work has recapitulated several reported therapeutic targets for COVID-19 and identified numerous new ones, including the kinases PKG1, CK2, ROCK1/2, GRK2, SYK, JAK2/3, TYK2, DNA-PK and the cytokine IL-12. FUNDING. Ontario Research Fund (ORF)-COVID-19 Rapid Research Fund.

Pathological Effects of SARS-CoV-19 Associated With Hematological Abnormalities (preprint)

The SARS coronavirus 2 (SARS-CoV-2) is the causative agent of the 2019 coronavirus disease (COVID-19) pandemic that has executed 6.9 million people and infected over 765 million. It’s become a major worldwide health alarm and is also known to cause abnormalities in various systems, including the hematologic system. COVID-19 infection primarily affects the lower res-piratory tract and can lead to a cascade of events, including a cytokine storm, intravascular thrombosis, and subsequent complications such as arterial and venous thromboses. COVID-19 can cause thrombocytopenia, lymphopenia, and neutrophilia, which are associated with worse out-comes. Prophylactic anticoagulation is essential to prevent complication and death rate associated with the virus's effect on the coagulation system. It is crucial to recognize these complications early and promptly start therapeutic anticoagulation to improve patient outcomes. While rare, COVID-19-induced disseminated intravascular coagulation exhibits some similarities to DIC induced by sepsis. LDH, D-dimer, ferritin, and CRP biomarker are often increase in serious COVID-19 cases and poor prognosis. Understanding the pathophysiology of the disease and identifying risk factors for adverse outcomes is critical for effective management of COVID-19.

Deep Phenotyping of the Lipidomic Response in COVID and non-COVID Sepsis (preprint)

Lipids may influence cellular penetrance by pathogens and the immune response that they evoke. Here we find broad based lipidomic storm driven predominantly by secretory (s) phospholipase A2 (sPLA2) dependent eicosanoid production occurs in patients with sepsis of viral and bacterial origin and relates to disease severity in COVID-19. Elevations in the cyclooxygenase (COX) products of arachidonic acid (AA), PGD2 and PGI2, and the AA lipoxygenase (LOX) product, 12-HETE, and a reduction in the high abundance lipids, ChoE 18:3, LPC O-16:0 and PC-O-30:0 exhibit relative specificity for COVID-19 amongst such patients, correlate with the inflammatory response and link to disease severity. Linoleic acid (LA) binds directly to SARS-CoV-2 and both LA and its di-HOME products reflect disease severity in COVID-19. AA and LA metabolites and LPC-O-16:0 linked variably to the immune response. These studies yield prognostic biomarkers and therapeutic targets for patients with sepsis, including COVID-19. An interactive purpose built interactive network analysis tool was developed, allowing the community to interrogate connections across these multiomic data and generate novel hypotheses.

Identification of a sub-group of critically ill patients with high risk of intensive care unit-acquired infections and poor clinical course using a transcriptomic score.

BACKGROUND: The development of stratification tools based on the assessment of circulating mRNA of genes involved in the immune response is constrained by the heterogeneity of septic patients. The aim of this study is to develop a transcriptomic score based on a pragmatic combination of immune-related genes detected with a prototype multiplex PCR tool. METHODS: As training cohort, we used the gene expression dataset obtained from 176 critically ill patients enrolled in the REALISM study (NCT02638779) with various etiologies and still hospitalized in intensive care unit (ICU) at day 5-7. Based on the performances of each gene taken independently to identify patients developing ICU-acquired infections (ICU-AI) after day 5-7, we built an unweighted score assuming the independence of each gene. We then determined the performances of this score to identify a subgroup of patients at high risk to develop ICU-AI, and both longer ICU length of stay and mortality of this high-risk group were assessed. Finally, we validated the effectiveness of this score in a retrospective cohort of 257 septic patients. RESULTS: This transcriptomic score (TScore) enabled the identification of a high-risk group of patients (49%) with an increased rate of ICU-AI when compared to the low-risk group (49% vs. 4%, respectively), with longer ICU length of stay (13 days [95% CI 8-30] vs. 7 days [95% CI 6-9], p < 0.001) and higher ICU mortality (15% vs. 2%). High-risk patients exhibited biological features of immune suppression with low monocytic HLA-DR levels, higher immature neutrophils rates and higher IL10 concentrations. Using the TScore, we identified 160 high-risk patients (62%) in the validation cohort, with 30% of ICU-AI (vs. 18% in the low-risk group, p = 0.06), and significantly higher mortality and longer ICU length of stay. CONCLUSIONS: The transcriptomic score provides a useful and reliable companion diagnostic tool to further develop immune modulating drugs in sepsis in the context of personalized medicine.

Abnormal glucose metabolism in virus associated sepsis.

Sepsis is identified as a potentially lethal organ impairment triggered by an inadequate host reaction to infection (Sepsis-3). Viral sepsis is a potentially deadly organ impairment state caused by the host's inappropriate reaction to a viral infection. However, when a viral infection occurs, the metabolism of the infected cell undergoes a variety of changes that cause the host to respond to the infection. But, until now, little has been known about the challenges faced by cellular metabolic alterations that occur during viral infection and how these changes modulate infection. This study concentrates on the alterations in glucose metabolism during viral sepsis and their impact on viral infection, with a view to exploring new potential therapeutic targets for viral sepsis.

COVID-19 associated infections in the ICU setting: A retrospective analysis in a tertiary-care hospital.

INTRODUCTION: Our work describes the frequency of superinfections in COVID-19 ICU patients and identifies risk factors for its appearance. Second, we evaluated ICU length of stay, in-hospital mortality and analyzed a subgroup of multidrug-resistant microorganisms (MDROs) infections. METHODS: Retrospective study conducted between March and June 2020. Superinfections were defined as appeared ≥48h. Bacterial and fungal infections were included, and sources were ventilator-associated lower respiratory tract infection (VA-LRTI), primary bloodstream infection (BSI), secondary BSI, and urinary tract infection (UTI). We performed a univariate analysis and a multivariate analysis of the risk factors. RESULTS: Two-hundred thirteen patients were included. We documented 174 episodes in 95 (44.6%) patients: 78 VA-LRTI, 66 primary BSI, 9 secondary BSI and 21 UTI. MDROs caused 29.3% of the episodes. The median time from admission to the first episode was 18 days and was longer in MDROs than in non-MDROs (28 vs. 16 days, p<0.01). In multivariate analysis use of corticosteroids (OR 4.9, 95% CI 1.4-16.9, p 0.01), tocilizumab (OR 2.4, 95% CI 1.1-5.9, p 0.03) and broad-spectrum antibiotics within first 7 days of admission (OR 2.5, 95% CI 1.2-5.1, p<0.01) were associated with superinfections. Patients with superinfections presented respect to controls prolonged ICU stay (35 vs. 12 days, p<0.01) but not higher in-hospital mortality (45.3% vs. 39.7%, p 0.13). CONCLUSIONS: Superinfections in ICU patients are frequent in late course of admission. Corticosteroids, tocilizumab, and previous broad-spectrum antibiotics are identified as risk factors for its development.

An observational study on factors associated with ICU mortality in Covid-19 patients and critical review of the literature.

The novel pandemic caused by SARS-CoV-2 has been associated with increased burden on healthcare system. Recognizing the variables that independently predict death in COVID-19 is of great importance. The study was carried out prospectively in a single ICU in northern Greece. It was based on the collection of data during clinical practice in 375 adult patients who were tested positive for SARS-CoV-2 between April 2020 and February 2022. All patients were intubated due to acute respiratory insufficiency and received Invasive Mechanical Ventilation. The primary outcome was ICU mortality. Secondary outcomes were 28-day mortality and independent predictors of mortality at 28 days and during ICU hospitalization. For continuous variables with normal distribution, t-test was used for means comparison between two groups and one-way ANOVA for multiple comparisons. When the distribution was not normal, comparisons were performed using the Mann-Whitney test. Comparisons between discrete variables were made using the x2 test, whereas the binary logistic regression was employed for the definition of factors affecting survival inside the ICU and after 28 days. Of the total number of patients intubated due to COVID-19 during the study period, 239 (63.7%) were male. Overall, the ICU survival was 49.6%, whereas the 28-day survival reached 46.9%. The survival rates inside the ICU for the four main viral variants were 54.9%, 50.3%, 39.7% and 50% for the Alpha, Beta, Delta and Omicron variants, respectively. Logistic regressions for outcome revealed that the following parameters were independently associated with ICU survival: wave, SOFA @day1, Remdesivir use, AKI, Sepsis, Enteral Insufficiency, Duration of ICU stay and WBC. Similarly, the parameters affecting the 28-days survival were: duration of stay in ICU, SOFA @day1, WBC, Wave, AKI and Enteral Insufficiency. In this observational cohort study of critically ill COVID-19 patients we report an association between mortality and the wave sequence, SOFA score on admission, the use of Remdesivir, presence of AKI, presence of gastrointestinal failure, sepsis and WBC levels. Strengths of this study are the large number of critically ill COVID-19 patients included, and the comparison of the adjusted mortality rates between pandemic waves within a two year-study period.