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2.
Front Immunol ; 13: 830061, 2022.
Article in English | MEDLINE | ID: covidwho-2198803

ABSTRACT

Introduction: Resistin is reported to form a cytokine network and cause endothelial damage. The pathogenesis of coronavirus disease 2019 (COVID-19) remains unknown, but the association between cytokine storm and endothelial damage is crucial. This study aimed to evaluate resistin in COVID-19 pathogenesis compared with sepsis. Materials and Methods: First, we evaluated the association of plasma resistin levels and disease severity and clinical outcome in two large cohorts: a publicly available cohort including 306 COVID-19 patients in the United States (MGH cohort) and our original cohort including only intubated 113 patients in Japan (Osaka cohort 1). Second, to understand pathogenesis, we evaluate resistin, cytokines and endothelial cell adhesion molecules in COVID-19 compared with sepsis. Blood samples were collected from 62 ICU-treated COVID-19 patients and 38 sepsis patients on day 1 (day of ICU admission), days 2-3, days 6-8, and from 18 healthy controls (Osaka cohort 2). The plasma resistin, inflammatory cytokines (IL-6, IL-8, MCP-1 and IL-10) and endothelial cell adhesion molecules (ICAM-1 and VCAM-1) were compared between patients and control. Correlations among resistin, inflammatory cytokines and endothelial cell adhesion molecules were evaluated in COVID-19 and sepsis. Results: In the MGH cohort, the day 1 resistin levels were associated with disease severity score. The non-survivors showed significantly greater resistin levels than survivors on days 1, 4 and 8. In the Osaka cohort 1, 28-day non-survivors showed significantly higher resistin levels than 28-day survivors on days 6-8. Patients with late recovery (defined as the day of weaning off mechanical ventilation >12 or death) had significantly higher resistin levels than those with early recovery on day 1 and days 6-8. In the Osaka cohort 2, plasma resistin levels were elevated in COVID-19 and sepsis patients compared to controls at all measurement points and were associated with inflammatory cytokines and endothelial cell adhesion molecules. Conclusion: Resistin was elevated in COVID-19 patients and was associated with cytokines and endothelial cell adhesion molecules. Higher resistin levels were related to worse outcome.


Subject(s)
COVID-19 , Sepsis , Cytokines , Humans , Resistin , Sepsis/metabolism , Vascular Cell Adhesion Molecule-1
3.
researchsquare; 2023.
Preprint in English | PREPRINT-RESEARCHSQUARE | ID: ppzbmed-10.21203.rs.3.rs-2451901.v1

ABSTRACT

Introduction Sepsis is a disease with high mortality and morbidity. Despite advances in diagnosis and therapeutic packages, many gaps remain. This study aimed to evaluate the profile and outcomes of out-of-hospital sepsis. Methods This was a retrospective study, multicenter study including five basic health Unit. The study period was from January 2018 to December 2021.Patients diagnosed with sepsis or septic shock according to the Sepsis 3.0 criterion. Results A total 2630 patients were included with a diagnosis of sepsis 68.4% (1800) or septic shock 31.6% (830) in the emergency care units. The comorbidities that were independent predictors of septic shock were chronic kidney disease on dialysis (CKD-d), bone marrow transplantation and neoplasia; CKD and neoplasia were also independent predictors of mortality, with ORs of 2.00 (CI 1.10–3.68) p = 0.023 and 1.74 (CI 1.319–2.298) p = < 0.0001, respectively. Mortality according to the focus of primary infection was as follows: pulmonary 40.1%; COVID-19 35.7%; abdominal 8.1% and urinary 6.2%. Mortality due to the COVID-19 outbreak had an OR of 4.94 (CI 3.08–8.13) p ≤ 0.0001. Conclusions The following are risk factors associated with mortality in nonhospitalized sepsis: comorbidities (d-CKD and neoplasia) and the primary focus of COVID-19 infection.


Subject(s)
Sepsis , Shock, Septic , Renal Insufficiency, Chronic , COVID-19 , Neoplasms
4.
researchsquare; 2022.
Preprint in English | PREPRINT-RESEARCHSQUARE | ID: ppzbmed-10.21203.rs.3.rs-2427684.v1

ABSTRACT

Background Annually, more than 313 million procedures are conducted worldwide. However, only 6% are conducted in the low-income countries where a third of the world population lives. In Low- and Middle-Income Countries (LMICs) only, more than 143 million additional surgeries are needed to save lives and avoid disability. Overall global postoperative mortality is 7.7%, and half of these deaths occur in LMICs. In Ethiopia, about 250,000 procedures are being conducted annually. This is less than 5% of what is actually needed according to recommendation of 5000 procedures per 100,000 population per year.Methods This study is a retrospective review of surgical services, including surgical admissions, procedures, and outpatient visits. The study encompassed surgical activities from January 1, 2021 to December 30, 2021 and was conducted in Tikur Anbessa Specialized hospital. Data were collected from operative logbooks, clinic registrars, liaison office, ward registries and from monthly audit reports of each division.Results The majority of the admissions were elective, constituting 2589 (64.1%). The most frequent elective surgeries performed in the study year were great saphenous interposition graft (bypass) consisting of 12.4% of elective surgeries. Emergency admissions constitute 1449 (35.9%) of all admissions. The most frequent emergency procedures performed in the previous year were tracheostomy (35.7%). Mortality rate was available only from the general surgery division. Average mortality rates were was 0.07% for elective procedures and 2.1% for emergency procedures. Most common causes of mortality were septicemia and anastomotic leak. There were 508 cancellations in the one-year study period with lack of oxygen, Covid and lack of investigations being main reasons.Conclusion This study showed most of surgical procedures were done on elective basis. The most commonly performed procedures also are relatively more complex than previous report from the same country, reflecting the tertiary nature of the hospital. Overall, the outcome of both elective and emergency surgeries was favorable. However, all divisions should report morbidity and mortality, preferably with similar format. The cancellation rate is also high and needs intervention from the hospital and department leaders.


Subject(s)
Sepsis
5.
BMC Geriatr ; 22(1): 552, 2022 07 01.
Article in English | MEDLINE | ID: covidwho-1913453

ABSTRACT

BACKGROUND: Infection is more frequent, and serious in people aged > 65 as they experience non-specific signs and symptoms delaying diagnosis and prompt treatment. Monitoring signs and symptoms using decision support tools (DST) is one approach that could help improve early detection ensuring timely treatment and effective care. OBJECTIVE: To identify and analyse decision support tools available to support detection of infection in older people (> 65 years). METHODS: A scoping review of the literature 2010-2021 following Arksey and O'Malley (2005) framework and PRISMA-ScR guidelines. A search of MEDLINE, Cochrane, EMBASE, PubMed, CINAHL, Scopus and PsycINFO using terms to identify decision support tools for detection of infection in people > 65 years was conducted, supplemented with manual searches. RESULTS: Seventeen papers, reporting varying stages of development of different DSTs were analysed. DSTs largely focussed on specific types of infection i.e. urine, respiratory, sepsis and were frequently hospital based (n = 9) for use by physicians. Four DSTs had been developed in nursing homes and one a care home, two of which explored detection of non- specific infection. CONCLUSIONS: DSTs provide an opportunity to ensure a consistent approach to early detection of infection supporting prompt action and treatment, thus avoiding emergency hospital admissions. A lack of consideration regarding their implementation in practice means that any attempt to create an optimal validated and tested DST for infection detection will be impeded. This absence may ultimately affect the ability of the workforce to provide more effective and timely care, particularly during the current covid-19 pandemic.


Subject(s)
COVID-19 , Sepsis , Aged , COVID-19/diagnosis , COVID-19/epidemiology , Dietary Supplements , Early Diagnosis , Humans , Pandemics
6.
Front Immunol ; 13: 975848, 2022.
Article in English | MEDLINE | ID: covidwho-2142004

ABSTRACT

Corona Virus Disease 2019 (COVID-19), an acute respiratory infectious disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has spread rapidly worldwide, resulting in a pandemic with a high mortality rate. In clinical practice, we have noted that many critically ill or critically ill patients with COVID-19 present with typical sepsis-related clinical manifestations, including multiple organ dysfunction syndrome, coagulopathy, and septic shock. In addition, it has been demonstrated that severe COVID-19 has some pathological similarities with sepsis, such as cytokine storm, hypercoagulable state after blood balance is disrupted and neutrophil dysfunction. Considering the parallels between COVID-19 and non-SARS-CoV-2 induced sepsis (hereafter referred to as sepsis), the aim of this study was to analyze the underlying molecular mechanisms between these two diseases by bioinformatics and a systems biology approach, providing new insights into the pathogenesis of COVID-19 and the development of new treatments. Specifically, the gene expression profiles of COVID-19 and sepsis patients were obtained from the Gene Expression Omnibus (GEO) database and compared to extract common differentially expressed genes (DEGs). Subsequently, common DEGs were used to investigate the genetic links between COVID-19 and sepsis. Based on enrichment analysis of common DEGs, many pathways closely related to inflammatory response were observed, such as Cytokine-cytokine receptor interaction pathway and NF-kappa B signaling pathway. In addition, protein-protein interaction networks and gene regulatory networks of common DEGs were constructed, and the analysis results showed that ITGAM may be a potential key biomarker base on regulatory analysis. Furthermore, a disease diagnostic model and risk prediction nomogram for COVID-19 were constructed using machine learning methods. Finally, potential therapeutic agents, including progesterone and emetine, were screened through drug-protein interaction networks and molecular docking simulations. We hope to provide new strategies for future research and treatment related to COVID-19 by elucidating the pathogenesis and genetic mechanisms between COVID-19 and sepsis.


Subject(s)
COVID-19 , Sepsis , Biomarkers , Computational Biology/methods , Critical Illness , Cytokines/genetics , Emetine , Gene Expression Profiling/methods , Humans , Molecular Docking Simulation , NF-kappa B/genetics , Progesterone , Receptors, Cytokine/genetics , SARS-CoV-2 , Sepsis/genetics , Sepsis/metabolism
7.
Rev Assoc Med Bras (1992) ; 68(10): 1458-1463, 2022.
Article in English | MEDLINE | ID: covidwho-2140983

ABSTRACT

OBJECTIVE: This study aimed to describe sepsis progression in critical COVID-19 patients using the SOFA score and investigate its relationship with mortality. METHODS: Three researchers collected and analyzed retrospective clinical and laboratory data found in electronic health records from all patients admitted to a severe COVID-19 exclusive intensive care unit from March 2020 to October 2020. Mixed-effect logistic regression was used to evaluate SOFA (Sepsis-3) score variables as mortality prediction markers, while Kaplan-Meier survival curves were used to compare mortality between groups of patients. Cox proportional hazard models were used to further stratify mortality association between variants. RESULTS: A total of 73 patients were included. Temporal COVID-19-related sepsis progression analysis indicates difference in degrees and timing between different organ dysfunction over time. Sepsis-3 Cardiovascular Dysfunction characterized by severe hypotension added to the use of any vasopressor drugs was the only parameter associated with in-hospital death during the first 5 days of hospital admission (OR 2.19; 95%CI 1.14-4.20; p=0.01). CONCLUSION: Increased Sepsis-3 Cardiovascular Dysfunction score, characterized as hypotension associated with the use of vasopressor drugs in the first days of intensive care unit stay, is related to higher mortality in COVID-19 patients and may be a useful prognostic prediction tool.


Subject(s)
COVID-19 , Hypotension , Sepsis , Humans , COVID-19/complications , Retrospective Studies , Hospital Mortality , Critical Care
8.
Virol J ; 19(1): 198, 2022 Nov 28.
Article in English | MEDLINE | ID: covidwho-2139350

ABSTRACT

BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2, has led to major public health crises worldwide. Several studies have reported the comprehensive mRNA expression analysis of immune-related genes in patients with COVID-19, using blood samples, to understand its pathogenesis; however, the characteristics of RNA expression in COVID-19 and bacterial sepsis have not been compared. The current study aimed to address this gap. METHODS: RNA-sequencing and bioinformatics analyses were used to compare the transcriptome expression of whole blood samples from patients with COVID-19 and patients with sepsis who were admitted to the intensive care unit of Osaka University Graduate School of Medicine. RESULTS: The COVID-19 and sepsis cohorts showed upregulation of mitochondrial- and neutrophil-related transcripts, respectively. Compared with that in the control cohort, neutrophil-related transcripts were upregulated in both the COVID-19 and sepsis cohorts. In contrast, mitochondrial-related transcripts were upregulated in the COVID-19 cohort and downregulated in the sepsis cohort, compared to those in the control cohort. Moreover, transcript levels of the pro-apoptotic genes BAK1, CYCS, BBC3, CASP7, and CASP8 were upregulated in the COVID-19 cohort, whereas those of anti-apoptotic genes, such as BCL2L11 and BCL2L1, were upregulated in the sepsis cohort. CONCLUSIONS: This study clarified the differential expression of transcripts related to neutrophils and mitochondria in sepsis and COVID-19 conditions. Mitochondrial-related transcripts were downregulated in sepsis than in COVID-19 conditions, and our results indicated suboptimal intrinsic apoptotic features in sepsis samples compared with that in COVID-19 samples. This study is expected to contribute to the development of specific treatments for COVID-19.


Subject(s)
COVID-19 , Sepsis , Humans , COVID-19/genetics , Sepsis/genetics , SARS-CoV-2 , Intensive Care Units , RNA
9.
Immunol Rev ; 312(1): 61-75, 2022 11.
Article in English | MEDLINE | ID: covidwho-2136897

ABSTRACT

Tissue factor (TF) is a procoagulant protein released from activated host cells, such as monocytes, and tumor cells on extracellular vesicles (EVs). TF + EVs are observed in the circulation of patients with various types of diseases. In this review, we will summarize the association between TF + EVs and activation of coagulation and survival in different types of diseases, including cancer, sepsis, and infections with different viruses, such as human immunodeficiency virus (HIV), influenza A virus (IAV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We will also discuss the source of TF + EVs in various diseases. EVTF activity is associated with thrombosis in pancreatic cancer patients and coronavirus disease 2019 patients (COVID-19) and with disseminated intravascular coagulation in cancer patients. EVTF activity is also associated with worse survival in patients with cancer and COVID-19. Monocytes are the major sources of TF + EVs in sepsis, and viral infections, such as HIV, Ebola virus, and SARS-CoV-2. In contrast, alveolar epithelial cells are the major source of TF + EVs in bronchoalveolar lavage fluid in COVID-19 and influenza A patients. These studies indicate that EVTF activity could be used as a biomarker to identify patients that have an increased risk of coagulopathy and mortality.


Subject(s)
COVID-19 , Extracellular Vesicles , Pancreatic Neoplasms , Sepsis , Thrombosis , Biomarkers/metabolism , Extracellular Vesicles/metabolism , Extracellular Vesicles/pathology , Humans , Pancreatic Neoplasms/complications , Pancreatic Neoplasms/metabolism , Pancreatic Neoplasms/pathology , SARS-CoV-2 , Thromboplastin/metabolism
11.
Int J Infect Dis ; 111: 31-36, 2021 Oct.
Article in English | MEDLINE | ID: covidwho-2113701

ABSTRACT

BACKGROUND: Correlation between coronavirus disease 2019 (COVID-19) and superinfections has been investigated, but remains to be fully assessed. This multi-centre study reports the impact of the pandemic on bloodstream infections (BSIs). METHODS: This study included all patients with BSIs admitted to four Italian hospitals between 1 January and 30 June 2020. Clinical, demographic and microbiologic data were compared with data for patients hospitalized during the same period in 2019. RESULTS: Among 26,012 patients admitted between 1 January and 30 June 2020, 1182 had COVID-19. Among the patients with COVID-19, 107 BSIs were observed, with an incidence rate of 8.19 episodes per 1000 patient-days. The incidence of BSI was significantly higher in these patients compared with patients without COVID-19 (2.72/1000 patient-days) and patients admitted in 2019 (2.76/1000 patient-days). In comparison with patients without COVID-19, BSI onset in patients with COVID-19 was delayed during the course of hospitalization (16.0 vs 5 days, respectively). Thirty-day mortality among patients with COVID-19 was 40.2%, which was significantly higher compared with patients without COVID-19 (23.7%). BSIs in patients with COVID-19 were frequently caused by multi-drug-resistant pathogens, which were often centre-dependent. CONCLUSIONS: BSIs are a common secondary infection in patients with COVID-19, characterized by increased risk during hospitalization and potentially burdened with high mortality.


Subject(s)
COVID-19 , Coinfection , Sepsis , Humans , Italy/epidemiology , SARS-CoV-2 , Sepsis/epidemiology
12.
J Nippon Med Sch ; 89(5): 479-486, 2022 Nov 09.
Article in English | MEDLINE | ID: covidwho-2117787

ABSTRACT

BACKGROUND: Patients with coronavirus disease 2019 (COVID-19) occasionally develop respiratory failure and coagulopathy. We aimed to determine whether coagulation abnormalities at admission and during the course of hospitalization can predict the liberation from respiratory support in critically ill patients with COVID-19 by combining the results of rotational thromboelastometry (ROTEM) with standard laboratory tests. METHODS: This single-center, retrospective, observational study included 31 consecutive adult patients with COVID-19 who were admitted to the intensive care unit (ICU) and who required respiratory support between April 2021 and August 2021. We divided the patients into two groups according to the liberation from respiratory support and analyzed the differences between the groups. RESULTS: There were 20 patients in the liberation group and 11 in the non-liberation group. There were no significant differences in the overt disseminated intravascular coagulation scores or abnormal counts in the ROTEM parameters at admission between groups, although there was a significant difference in the highest score in the ICU. The Sequential Organ Failure Assessment and sepsis-induced coagulopathy scores were significantly different between both groups at admission and at the time when the highest values were reported during the ICU stay. CONCLUSIONS: High sepsis-induced coagulopathy scores at admission to the ICU were found to be useful predictors of difficulties in the liberation from respiratory support in patients with severe COVID-19. However, increased overt disseminated intravascular coagulation scores and abnormal counts in the ROTEM parameters during the ICU stay were associated with difficulties in the liberation from respiratory support.


Subject(s)
Blood Coagulation Disorders , COVID-19 , Disseminated Intravascular Coagulation , Sepsis , Adult , Humans , COVID-19/complications , Retrospective Studies , Disseminated Intravascular Coagulation/complications , Intensive Care Units , Blood Coagulation Disorders/etiology
13.
Euro Surveill ; 27(46)2022 11.
Article in English | MEDLINE | ID: covidwho-2115722

ABSTRACT

Recent data from the European Antimicrobial Resistance Surveillance Network (EARS-Net) show a large increase of +57% in Acinetobacter species bloodstream infections in the European Union and European Economic Area in the first years of the COVID-19 pandemic (2020-2021) compared with 2018-2019. Most were resistant to carbapenems, from intensive care units, and in countries with ≥ 50% carbapenem resistance in Acinetobacter spp. in 2018-2019. This highlights the requirement for reinforced Acinetobacter preparedness and infection prevention and control in Europe.


Subject(s)
Acinetobacter , COVID-19 , Sepsis , Humans , Drug Resistance, Bacterial , Pandemics , Anti-Bacterial Agents/pharmacology , Anti-Bacterial Agents/therapeutic use , Carbapenems/pharmacology , Carbapenems/therapeutic use , Sepsis/drug therapy
14.
Antimicrob Resist Infect Control ; 11(1): 73, 2022 05 19.
Article in English | MEDLINE | ID: covidwho-2115294

ABSTRACT

BACKGROUND: There is a paucity of data regarding blood culture utilization and antimicrobial-resistant (AMR) infections in low and middle-income countries (LMICs). In addition, there has been a concern for increasing AMR infections among COVID-19 cases in LMICs. Here, we investigated epidemiology of AMR bloodstream infections (BSI) before and during the COVID-19 pandemic in the Indonesian national referral hospital. METHODS: We evaluated blood culture utilization rate, and proportion and incidence rate of AMR-BSI caused by WHO-defined priority bacteria using routine hospital databases from 2019 to 2020. A patient was classified as a COVID-19 case if their SARS-CoV-2 RT-PCR result was positive. The proportion of resistance was defined as the ratio of the number of patients having a positive blood culture for a WHO global priority resistant pathogen per the total number of patients having a positive blood culture for the given pathogen. Poisson regression models were used to assess changes in rate over time. RESULTS: Of 60,228 in-hospital patients, 8,175 had at least one blood culture taken (total 17,819 blood cultures), giving a blood culture utilization rate of 30.6 per 1,000 patient-days. A total of 1,311 patients were COVID-19 cases. Blood culture utilization rate had been increasing before and during the COVID-19 pandemic (both p < 0.001), and was higher among COVID-19 cases than non-COVID-19 cases (43.5 vs. 30.2 per 1,000 patient-days, p < 0.001). The most common pathogens identified were K. pneumoniae (23.3%), Acinetobacter spp. (13.9%) and E. coli (13.1%). The proportion of resistance for each bacterial pathogen was similar between COVID-19 and non-COVID-19 cases (all p > 0.10). Incidence rate of hospital-origin AMR-BSI increased from 130.1 cases per 100,000 patient-days in 2019 to 165.5 in 2020 (incidence rate ratio 1.016 per month, 95%CI:1.016-1.017, p < 0.001), and was not associated with COVID-19 (p = 0.96). CONCLUSIONS: In our setting, AMR-BSI incidence and etiology were similar between COVID-19 and non-COVID-19 cases. Incidence rates of hospital-origin AMR-BSI increased in 2020, which was likely due to increased blood culture utilization. We recommend increasing blood culture utilization and generating AMR surveillance reports in LMICs to inform local health care providers and policy makers.


Subject(s)
COVID-19 , Cross Infection , Sepsis , Anti-Bacterial Agents/pharmacology , Anti-Bacterial Agents/therapeutic use , Bacteria , Blood Culture , COVID-19/epidemiology , Cross Infection/microbiology , Escherichia coli , Hospitals , Humans , Indonesia/epidemiology , Klebsiella pneumoniae , Pandemics , Referral and Consultation , SARS-CoV-2/genetics , Sepsis/microbiology
15.
medrxiv; 2022.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2022.12.06.22282077

ABSTRACT

Resolving chromatin remodeling-linked gene expression changes at cell type resolution is important for understanding disease states. We describe MAGICAL, a hierarchical Bayesian approach that leverages paired scRNA-seq and scATAC-seq data from different conditions to map disease-associated transcription factors, chromatin sites, and genes as regulatory circuits. By simultaneously modeling signal variation across cells and conditions in both omics data types, MAGICAL achieved high accuracy on circuit inference. We applied MAGICAL to study Staphylococcus aureus sepsis from peripheral blood mononuclear single-cell data that we generated from infected subjects with bloodstream infection and from uninfected controls. MAGICAL identified sepsis-associated regulatory circuits predominantly in CD14 monocytes, known to be activated by bacterial sepsis. We addressed the challenging problem of distinguishing host regulatory circuit responses to methicillin-resistant- (MRSA) and methicillin-susceptible Staphylococcus aureus (MSSA) infections. While differential expression analysis failed to show predictive value, MAGICAL identified epigenetic circuit biomarkers that distinguished MRSA from MSSA.


Subject(s)
Sepsis
16.
authorea preprints; 2022.
Preprint in English | PREPRINT-AUTHOREA PREPRINTS | ID: ppzbmed-10.22541.au.166979176.66104074.v1

ABSTRACT

AIMS: To analyze the clinical spectrum in Neonates with MIS-N based on the time of presentation and also to assess the use of immunomodulator therapy in MIS-N. SUBJECTS AND METHODS: We studied 100 neonates, delivered at BLDE (DU) Shri B M Patil Medical College Hospital admitted to Level III-A NICU from JULY 2020 to MAY 2021. 98 neonates had high titers of Ig G antibodies and negative for COVID Antigen. We categorized the cohorts into EARLY MIS-N (<72 hrs) and LATE MIS-N (>72 hrs). RESULTS: 58 presented as EARLY MIS-N with Respiratory Distress in 40 (70%), cardiac dysfunction 34 (60%), PPHN 12(20%), Fever 12(20%), seizures 12(20%), encephalopathy in 6(10%), sepsis-like features 6(10%), had elevated inflammatory markers like CRP (30%), D-Dimer (70%), Ferritin (30%), cardiac biomarkers like BNP (60%), LDH (30%) and ECHO showing LV dysfunction in 50%. LATE MIS-N presented mostly with fever 28(70%), sepsis-like features 24(60%), Respiratory Distress in 16(40%), cardiac dysfunction 12 (30%), hypoglycemia 4(10%) parotitis 4(10%), had significantly elevated inflammatory markers like CRP (70%), D-Dimer (50%), Ferritin (70%), cardiac biomarkers like BNP (40%), LDH (20%) and ECHO showing LV dysfunction in 20%, dilated coronaries in 20 %, PPHN in 10%. Oxygen and respiratory support requirement was more in EARLY presenters and IVIG and steroid requirement was more in LATE presenters. CONCLUSION: We observed that maternal SARS COV2 antibodies transferred transplacentally and neonatal antibodies acquired after COVID 19 infection can cause MIS-N in neonates. The immunomodulator therapy is required in severe cases of MIS-N only.


Subject(s)
Sepsis , Respiratory Distress Syndrome , Sexual Dysfunction, Physiological , Heart Diseases , Parotitis , Dementia, Multi-Infarct , Fever , Seizures , Hypoglycemia , Brain Diseases
17.
Immunobiology ; 227(6): 152288, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-2105124

ABSTRACT

The clinical presentation of coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), ranges between mild respiratory symptoms and a severe disease that shares many of the features of sepsis. Sepsis is a deregulated response to infection that causes life-threatening organ failure. During sepsis, the intestinal epithelial cells are affected, causing an increase in intestinal permeability and allowing microbial translocation from the intestine to the circulation, which exacerbates the inflammatory response. Here we studied patients with moderate, severe and critical COVID-19 by measuring a panel of molecules representative of the innate and adaptive immune responses to SARS-CoV-2, which also reflect the presence of systemic inflammation and the state of the intestinal barrier. We found that non-surviving COVID-19 patients had higher levels of low-affinity anti-RBD IgA antibodies than surviving patients, which may be a response to increased microbial translocation. We identified sFas and granulysin, in addition to IL-6 and IL-10, as possible early biomarkers with high sensitivity (>73 %) and specificity (>51 %) to discriminate between surviving and non-surviving COVID-19 patients. Finally, we found that the microbial metabolite d-lactate and the tight junction regulator zonulin were increased in the serum of patients with severe COVID-19 and in COVID-19 patients with secondary infections, suggesting that increased intestinal permeability may be a source of secondary infections in these patients. COVID-19 patients with secondary infections had higher disease severity and mortality than patients without these infections, indicating that intestinal permeability markers could provide complementary information to the serum cytokines for the early identification of COVID-19 patients with a high risk of a fatal outcome.


Subject(s)
COVID-19 , Coinfection , Sepsis , Humans , COVID-19/diagnosis , SARS-CoV-2 , Interleukin-6 , Interleukin-10 , Permeability , Biomarkers , Intestines
18.
Scand J Trauma Resusc Emerg Med ; 29(1): 145, 2021 Oct 03.
Article in English | MEDLINE | ID: covidwho-2098399

ABSTRACT

BACKGROUND: Sepsis is a life-threatening organ dysfunction and a major healthcare burden worldwide. Although sepsis is a medical emergency that requires immediate management, screening for the occurrence of sepsis is difficult. Herein, we propose a deep learning-based model (DLM) for screening sepsis using electrocardiography (ECG). METHODS: This retrospective cohort study included 46,017 patients who were admitted to two hospitals. A total of 1,548 and 639 patients had sepsis and septic shock, respectively. The DLM was developed using 73,727 ECGs from 18,142 patients, and internal validation was conducted using 7774 ECGs from 7,774 patients. Furthermore, we conducted an external validation with 20,101 ECGs from 20,101 patients from another hospital to verify the applicability of the DLM across centers. RESULTS: During the internal and external validations, the area under the receiver operating characteristic curve (AUC) of the DLM using 12-lead ECG was 0.901 (95% confidence interval, 0.882-0.920) and 0.863 (0.846-0.879), respectively, for screening sepsis and 0.906 (95% confidence interval (CI), 0.877-0.936) and 0.899 (95% CI, 0.872-0.925), respectively, for detecting septic shock. The AUC of the DLM for detecting sepsis using 6-lead and single-lead ECGs was 0.845-0.882. A sensitivity map revealed that the QRS complex and T waves were associated with sepsis. Subgroup analysis was conducted using ECGs from 4,609 patients who were admitted with an infectious disease, and the AUC of the DLM for predicting in-hospital mortality was 0.817 (0.793-0.840). There was a significant difference in the prediction score of DLM using ECG according to the presence of infection in the validation dataset (0.277 vs. 0.574, p < 0.001), including severe acute respiratory syndrome coronavirus 2 (0.260 vs. 0.725, p = 0.018). CONCLUSIONS: The DLM delivered reasonable performance for sepsis screening using 12-, 6-, and single-lead ECGs. The results suggest that sepsis can be screened using not only conventional ECG devices but also diverse life-type ECG machines employing the DLM, thereby preventing irreversible disease progression and mortality.


Subject(s)
COVID-19 , Deep Learning , Sepsis , Electrocardiography , Humans , Retrospective Studies , SARS-CoV-2 , Sepsis/diagnosis
19.
PLoS One ; 17(11): e0275358, 2022.
Article in English | MEDLINE | ID: covidwho-2098742

ABSTRACT

We present a novel setup for treating sepsis using distributional reinforcement learning (RL). Sepsis is a life-threatening medical emergency. Its treatment is considered to be a challenging high-stakes decision-making problem, which has to procedurally account for risk. Treating sepsis by machine learning algorithms is difficult due to a couple of reasons: There is limited and error-afflicted initial data in a highly complex biological system combined with the need to make robust, transparent and safe decisions. We demonstrate a suitable method that combines data imputation by a kNN model using a custom distance with state representation by discretization using clustering, and that enables superhuman decision-making using speedy Q-learning in the framework of distributional RL. Compared to clinicians, the recovery rate is increased by more than 3% on the test data set. Our results illustrate how risk-aware RL agents can play a decisive role in critical situations such as the treatment of sepsis patients, a situation acerbated due to the COVID-19 pandemic (Martineau 2020). In addition, we emphasize the tractability of the methodology and the learning behavior while addressing some criticisms of the previous work (Komorowski et al. 2018) on this topic.


Subject(s)
COVID-19 , Sepsis , Humans , Pandemics , Reinforcement, Psychology , Algorithms , Sepsis/diagnosis
20.
Nihon Yakurigaku Zasshi ; 157(6): 422-425, 2022.
Article in Japanese | MEDLINE | ID: covidwho-2098631

ABSTRACT

Sepsis is one of the leading cause of death worldwide. Recently, several studies suggested that free-hemoglobin and heme derived from hemolysis are important factors which may be associated with severity of septic patients including COVID-19. In other words, hemolysis-derived products enhance the inflammatory responses as damage-associated molecular patterns (DAMPs) in both intravascular and extravascular space. In addition, hemoglobin has vasoconstrictive activity by depleting nitric oxide, whereas heme or Fe2+ produce reactive oxygen species (ROS) through Fenton reaction leading to tissue injury. At present, we have no therapeutic options against sepsis-related hemolysis in clinical settings, however, there might be two therapeutic strategies in this regard. One is supplemental therapy of depleted scavenging proteins such as haptoglobin and hemopexin, the other is activation of the internal scavenging system including macrophage-CD163 pathway. These novel targets against sepsis are also critical for the next pandemic. In this review, we summarize the current issues regarding sepsis-related hemolysis including COVID-19, as well as for future perspectives.


Subject(s)
COVID-19 , Sepsis , Humans , Hemolysis , COVID-19/complications , Hemoglobins/metabolism , Alarmins , Heme/metabolism
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