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Abstract Purpose Six to 19% of critically ill COVID-19 patients display circulating auto-antibodies against type I interferons (IFN-AABs). Here, we establish a clinically applicable strategy for early identification of IFN-AAB-positive patients for potential subsequent clinical interventions. Methods We analyzed sera of 430 COVID-19 patients from four hospitals for presence of IFN-AABs by ELISA. Binding specificity and neutralizing activity were evaluated via competition assay and virus-infection-based neutralization assay. We defined clinical parameters associated with IFN-AAB positivity. In a subgroup of critically ill patients, we analyzed effects of therapeutic plasma exchange (TPE) on the levels of IFN-AABs, SARS-CoV-2 antibodies and clinical outcome. Results The prevalence of neutralizing AABs to IFN-α and IFN-ω in COVID-19 patients from all cohorts was 4.2% (18/430), while being undetectable in an uninfected control cohort. Neutralizing IFN-AABs were detectable exclusively in critically affected (max. WHO score 6–8), predominantly male (83%) patients (7.6%, 18/237 for IFN-α-AABs and 4.6%, 11/237 for IFN-ω-AABs in 237 patients with critical COVID-19). IFN-AABs were present early post-symptom onset and at the peak of disease. Fever and oxygen requirement at hospital admission co-presented with neutralizing IFN-AAB positivity. IFN-AABs were associated with lower probability of survival (7.7% versus 80.9% in patients without IFN-AABs). TPE reduced levels of IFN-AABs in three of five patients and may increase survival of IFN-AAB-positive patients compared to those not undergoing TPE. Conclusion IFN-AABs may serve as early biomarker for the development of severe COVID-19. We propose to implement routine screening of hospitalized COVID-19 patients for rapid identification of patients with IFN-AABs who most likely benefit from specific therapies.

For psoriasis, which affects up to 2% of the population and adalimumab is approved from the age of 4 years. Here, we present a middle-aged Italian man with long-term history of plaque psoriasis and psoriasis arthropathica and adalimumab therapy. He developed ulcers or nodules within the psoriatic plaques, resembling cutaneous infection with Leishmania infantum. TNF and other cytokines such as IL-12 and IFN-γ are central in the early control of the infection. Discontinuation of the anti-TNF-treatment resolved the infection without specific therapy.

Funder: Charité - Universitätsmedizin Berlin, PURPOSE: Six to 19% of critically ill COVID-19 patients display circulating auto-antibodies against type I interferons (IFN-AABs). Here, we establish a clinically applicable strategy for early identification of IFN-AAB-positive patients for potential subsequent clinical interventions. METHODS: We analyzed sera of 430 COVID-19 patients from four hospitals for presence of IFN-AABs by ELISA. Binding specificity and neutralizing activity were evaluated via competition assay and virus-infection-based neutralization assay. We defined clinical parameters associated with IFN-AAB positivity. In a subgroup of critically ill patients, we analyzed effects of therapeutic plasma exchange (TPE) on the levels of IFN-AABs, SARS-CoV-2 antibodies and clinical outcome. RESULTS: The prevalence of neutralizing AABs to IFN-α and IFN-ω in COVID-19 patients from all cohorts was 4.2% (18/430), while being undetectable in an uninfected control cohort. Neutralizing IFN-AABs were detectable exclusively in critically affected (max. WHO score 6-8), predominantly male (83%) patients (7.6%, 18/237 for IFN-α-AABs and 4.6%, 11/237 for IFN-ω-AABs in 237 patients with critical COVID-19). IFN-AABs were present early post-symptom onset and at the peak of disease. Fever and oxygen requirement at hospital admission co-presented with neutralizing IFN-AAB positivity. IFN-AABs were associated with lower probability of survival (7.7% versus 80.9% in patients without IFN-AABs). TPE reduced levels of IFN-AABs in three of five patients and may increase survival of IFN-AAB-positive patients compared to those not undergoing TPE. CONCLUSION: IFN-AABs may serve as early biomarker for the development of severe COVID-19. We propose to implement routine screening of hospitalized COVID-19 patients for rapid identification of patients with IFN-AABs who most likely benefit from specific therapies.

BackgroundEstablishing the optimal treatment for COVID-19 patients remains challenging. Specifically, immunocompromised and pre-diseased patients are at high risk for severe disease course and face limited therapeutic options. Convalescent plasma has been considered as therapeutic approach, but reliable data are lacking, especially for high-risk patients.MethodsWe performed a retrospective analysis of 55 hospitalized COVID-19 patients with high risk for disease progression, primarily due to immunosuppression from cancer, solid organ transplantation, autoimmune disease, dialysis. A matched-pairs analysis (1:4) was performed with 220 patients from the Lean European Open Survey on SARS-CoV-2-infected Patients (LEOSS) who were treated or not treated with convalescent plasma. ResultsBoth cohorts, had high mortality (UKD 41.8%, LEOSS 34.1%). A matched-pairs analysis showed no significant effect on mortality. CP administration before the formation of pulmonary infiltrates showed the lowest mortality in both cohorts (10%), whereas mortality in the complicated phase was 27.8%. CP administration during the critical phase revealed the highest mortality; UKD 60.9%, LEOSS 48.3%. ConclusionIn our cohort of SARS-CoV-2 infected patients with severe comorbidities CP did not significantly reduce mortality in a retrospective matched pairs analysis. However, our data supports the concept that a reduction in mortality is achievable when CP is administered early.

PurposeIn Germany, the incidence of bacterial sexual transmitted infections (STI) is on the rise and still high for HIV infections. The Center for Sexual Health Freiburg (CSHF) was established to offer low threshold access for STI/HIV counseling, testing, HIV pre-exposure prophylaxis (PrEP), and on-site treatment. The objective of this study was to analyze the performance of CSHF.MethodsLongitudinal study that includes all clients presenting between 1 May 2020 and 28 February 2021 at CSHF and willing to sign informed consent.ResultsIn the study period, 536 clients presented at CSHF of whom 417 clients were included in the study resulting in 668 client contacts. Clients' median age was 28.1 years (range: 18.0–73.1), 55.9% were men, 42.0% were women, 0.3% were transman, and 1.7% were not binary. Clients' sexual orientation was heterosexual (56.6%), homosexual men (26.2%), and bisexual (13.6%). STI screening resulted in the detection of any STI in 3.4% (95% confidence interval (CI): 0.7–6.1) of women, in 3.1% (95% CI: 0.0–6.5) of heterosexual men, and in 22.2% (95% CI: 13.0–31.5) of men having sex with men (MSM) not taking PrEP. Eighty-one MSM received PrEP with a total follow-up of 57.3 person-years and 0.44 STIs per person-year.ConclusionThe substantial burden of STI in the study population emphasizes the need for regular and low threshold STI screening services. The concept of CSHF may facilitate access to STI/HIV counseling, testing, and PrEP for a wide spectrum of people and may prove to be an important contribution to the efforts to reduce STI and HIV incidence in Germany.

Made available in DSpace on 2022-04-29T08:35:59Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-12-01 Division of Intramural Research, National Institute of Allergy and Infectious Diseases Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases National Institute of Allergy and Infectious Diseases National Center for Advancing Translational Sciences National Heart, Lung, and Blood Institute National Institute of Environmental Health Sciences U.S. National Library of Medicine National Institute of Neurological Disorders and Stroke Division of Cancer Prevention, National Cancer Institute Neurological complications worsen outcomes in COVID-19. To define the prevalence of neurological conditions among hospitalized patients with a positive SARS-CoV-2 reverse transcription polymerase chain reaction test in geographically diverse multinational populations during early pandemic, we used electronic health records (EHR) from 338 participating hospitals across 6 countries and 3 continents (January–September 2020) for a cross-sectional analysis. We assessed the frequency of International Classification of Disease code of neurological conditions by countries, healthcare systems, time before and after admission for COVID-19 and COVID-19 severity. Among 35,177 hospitalized patients with SARS-CoV-2 infection, there was an increase in the proportion with disorders of consciousness (5.8%, 95% confidence interval [CI] 3.7–7.8%, pFDR < 0.001) and unspecified disorders of the brain (8.1%, 5.7–10.5%, pFDR < 0.001) when compared to the pre-admission proportion. During hospitalization, the relative risk of disorders of consciousness (22%, 19–25%), cerebrovascular diseases (24%, 13–35%), nontraumatic intracranial hemorrhage (34%, 20–50%), encephalitis and/or myelitis (37%, 17–60%) and myopathy (72%, 67–77%) were higher for patients with severe COVID-19 when compared to those who never experienced severe COVID-19. Leveraging a multinational network to capture standardized EHR data, we highlighted the increased prevalence of central and peripheral neurological phenotypes in patients hospitalized with COVID-19, particularly among those with severe disease. Department of Biostatistics Epidemiology and Informatics University of Pennsylvania Perelman School of Medicine Department of Biomedical Informatics Harvard Medical School Department of Neurology University of Pittsburgh, Biomedical Science Tower 3, Suite 7014, 3501 5th Avenue Department of Pediatrics Wake Forest School of Medicine Department of Critical Care National University Health Systems Department of Preventive Medicine Northwestern University Department of Biomedical Informatics University of Pittsburgh Department of Surgery National University Health Systems Department of Internal Medicine University of Kansas Medical Center Data Analytics Center University of Pennsylvania Health System Department of Computational Medicine and Bioinformatics University of Michigan Department of Biomedical Informatics University of Kentucky Department of Legal Economic and Social Sciences University Magna Graecia of Catanzaro Health Catalyst INC. Department of Surgery ASST Pavia Lombardia Region Health System Clinical Research Unit of Botucatu Medical School São Paulo State University Pediatric Emergency Department Hôpital Necker-Enfants Malades Assistance Publique-Hôpitaux de Paris National Center for Infectious Diseases Tan Tock Seng Hospital Departments of Biomedical Informatics Pediatrics Cincinnati Children’s Hospital Medical Center University of Cincinnati Department of Pediatrics Medical University of South Carolina Department of Surgery St. Luke’s University Health Network Department of Medicine David Geffen School of Medicine at UCLA UOC Ricerca Innovazione e Brand Reputation ASST Papa Giovanni XXIII Department of Electrical Computer and Biomedical Engineering University of Pavia IT Department Innovation & Data APHP Greater Paris University Hospital I.T. Department ASST Pavia Health Informatics Hospital Universitario, 12 de Octubre Strategy and Transformation Department APHP Greater Paris University Hospital Faculty of Medicine and Medical Center University of Freiburg Digital Research Informatics and Virtual Environments (DRIVE), Great Ormond Street Hospital for Children Scientific Direction IRCCS Ca’ Granda Ospedale Maggiore Policlinico di Milano North Carolina Translational and Clinical Sciences (NC TraCS) Institute University of North Carolina BIOMERIS (BIOMedical Research Informatics Solutions) Department of Biomedical Informatics HEGP APHP Greater Paris University Hospital Department of Medical and Surgical Sciences Data Analytics Research Center University Magna Graecia of Catanzaro Department of Anesthesia St. Luke’s University Health Network Université Paris-Saclay Inria CEA INRIA Sophia-Antipolis–ZENITH Team LIRMM Computational Health Informatics Program Boston Children’s Hospital Department of Internal Medicine University of Kentucky Unit of Internal Medicine and Endocrinology Istituti Clinici Scientifici Maugeri SpA SB IRCCS Department of Internal Medicine and Therapeutics University of Pavia Informatics Institute University of Alabama at Birmingham IAM Unit Bordeaux University Hospital/ERIAS-Inserm U1219 BPH Biomedical Informatics Center Medical University of South Carolina Clinical Research Informatics Boston Children’s Hospital Department of Biomedical and Health Informatics Children’s Hospital of Philadelphia SED/SIERRA Inria Centre de Paris Health Information Technology & Services University of Michigan Internal Medicine Department Botucatu Medical School São Paulo State University Heinrich-Lanz-Center for Digital Health University Medicine Mannheim Heidelberg University Department of Anesthesiology Critical Care and Pain Medicine Boston Children’s Hospital Department of Learning Health Sciences University of Michigan Medical School MSHI Medical University of South Carolina Department of Medicine Massachusetts General Hospital Division of Human Genetics Department of Pediatrics The Children’s Hospital of Philadelphia Center for Medical Information and Communication Technology University Hospital Renaissance Computing Institute/Department of Computer Science University of North Carolina Clinical Research Unit Saint Antoine Hospital APHP Greater Paris University Hospital Clevy.io Department of Biostatistics Harvard T.H. Chan School of Public Health VA Informatics and Computing Infrastructure VA Salt Lake City Health Care System MICHR Informatics University of Michigan Laboratory of Informatics and Systems Engineering for Clinical Research Istituti Clinici Scientifici Maugeri SpA SB IRCCS Harvard Catalyst Harvard Medical School Clinical Research Unit Paris Saclay APHP Greater Paris University Hospital Department of Anesthesiology and Critical Care Children’s Hospital of Philadelphia VA Informatics and Computing Infrastructure Tennessee Valley Healthcare System Veterans Affairs Medical Center École Normale Supérieure PSL Université Paris BIG-ARC The University of Texas Health Science Center at Houston School of Biomedical Informatics Pediatric Infectious Disease Department Hospital Universitario, 12 de Octubre Department of Infectious Diseases Great Ormond Street Hospital for Children Department of Neurology Massachusetts General Hospital Internal Medicine Department of Botucatu Medical School São Paulo State University Department of Pediatrics Boston Children’s Hospital Center for Biomedical Informatics Wake Forest School of Medicine Department of Medical Informatics University of Erlangen-Nürnberg Department of Veterans Affairs Office of Research and Development Biomedical Data Science Lab ITACA Institute Universitat Politècnica de València Nurse Department of FMB-Medicine School of Botucatu Management Engineering ASST Pavia Lombardia Region Health System Department of Anesthesiology University Hospital Erlangen FAU Erlangen-Nürnberg Critical Care Medicine Department of Medicine St. Luke’s University Health Network Department of Medicine National University Hospital Department of Information Management Chang Gung University Clinical & Translational Science Institute Medical College of Wisconsin Montréal Neurological Institute McGill University SequeL Inria Lille Respiratory Department ICS S Maugeri IRCCS Department of Health Management and Informatics University of Missouri Department of Oncology ASST Papa Giovanni XXIII Clinical Research Unit of Botucatu Medical School São Paulo State University Internal Medicine Department Botucatu Medical School São Paulo State University Internal Medicine Department of Botucatu Medical School São Paulo State University Division of Intramural Research, National Institute of Allergy and Infectious Diseases: AI11679 Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases: AI11679 National Institute of Allergy and Infectious Diseases: AI11679 National Center for Advancing Translational Sciences: CTSA Award #UL1TR001878 National Center for Advancing Translational Sciences: CTSA Award #UL1TR002366 National Heart, Lung, and Blood Institute: K23HL148394 National Institute of Environmental Health Sciences: P30ES017885 U.S. National Library of Medicine: R01LM012095 National Institute of Neurological Disorders and Stroke: R01NS098023 Division of Cancer Prevention, National Cancer Institute: U24CA210967 National Center for Advancing Translational Sciences: UL1TR001420 National Center for Advancing Translational Sciences: UL1TR001857

ObjectiveThe Consortium for Clinical Characterization of COVID-19 by EHR (4CE) is an international collaboration addressing coronavirus disease 2019 (COVID-19) with federated analyses of electronic health record (EHR) data. We sought to develop and validate a computable phenotype for COVID-19 severity.Materials and methodsTwelve 4CE sites participated. First, we developed an EHR-based severity phenotype consisting of 6 code classes, and we validated it on patient hospitalization data from the 12 4CE clinical sites against the outcomes of intensive care unit (ICU) admission and/or death. We also piloted an alternative machine learning approach and compared selected predictors of severity with the 4CE phenotype at 1 site.ResultsThe full 4CE severity phenotype had pooled sensitivity of 0.73 and specificity 0.83 for the combined outcome of ICU admission and/or death. The sensitivity of individual code categories for acuity had high variability-up to 0.65 across sites. At one pilot site, the expert-derived phenotype had mean area under the curve of 0.903 (95% confidence interval, 0.886-0.921), compared with an area under the curve of 0.956 (95% confidence interval, 0.952-0.959) for the machine learning approach. Billing codes were poor proxies of ICU admission, with as low as 49% precision and recall compared with chart review.DiscussionWe developed a severity phenotype using 6 code classes that proved resilient to coding variability across international institutions. In contrast, machine learning approaches may overfit hospital-specific orders. Manual chart review revealed discrepancies even in the gold-standard outcomes, possibly owing to heterogeneous pandemic conditions.ConclusionsWe developed an EHR-based severity phenotype for COVID-19 in hospitalized patients and validated it at 12 international sites.

[Objectives] This study aimed to investigate whether neutropenia influenced mortality and long-term outcomes of Staphylococcus aureus bloodstream (SAB) infection., [Methods] Data from two prospective, multicentre cohort studies (INSTINCT and ISAC) conducted at 20 tertiary care hospitals in six countries between 2006 and 2015 were analyzed. Neutropenic and severely neutropenic patients (defined by proxy of total white blood cell count, [Results] Of the 3187 included patients, 102 were neutropenic and 70 severely neutropenic at the time of SAB infection onset. Applying overlap weights yielded two groups of 83 neutropenic and 220 nonneutropenic patients, respectively. The baseline characteristics of these groups were exactly balanced. In the Cox regression analysis, we observed no significant difference in survival between the two groups (death during follow up: 36.1% in neutropenic vs. 30.6% in nonneutropenic patients; hazard ratio (HR): 1.21; 95% CI, 0.79–1.83). This finding remained unchanged when we considered severely neutropenic patients (HR: 1.08; 95% CI, 0.60–1.94). A competing risk analysis showed a cause-specific HR of 0.39 (95% CI, 0.11–1.39) for SAB infection-related late complications in neutropenic patients., [Discussion] Neutropenia was not associated with a higher survival rate during follow up. The lower rate of SAB infection-related late complications in neutropenic patients should be validated in other cohorts.

Additional file 2. Data extraction spreadsheet.

Additional file 1. Included countries.

Additional file 3. Full search strategy.

Additional file 1. Health Care Questionnaire.

Additional file 1. Medical Alert Card Asplenia.

Additional file 3: Table S3. Operationalization of the PrePSS-score parameters after weighting of the parameters.

Additional file 2: Table S2. Results of the expert survey.

Additional file 1: Fig. S1. Intensive care and renal replacement therapy in COVID-19 cases at the University of Freiburg Medical Center 02/26/2020–05/21/2020 (85 d). Table S1. COVID-19 and influenza patients treated on ICU. Fig. S2. RRT and mortality in critically ill COVID-19 and influenza patients. Table S2. Thromboembolic events and prothrombotic markers. Fig. S3. Distribution of prothrombotic markers in COVID-19 RRT- and Non-RRT-cohort. Table S3. Baseline characteristics according to anticoagulatory regimen during CVVHD. Table S4. Baseline characteristics according to anticoagulatory regimen during SLEDD

ObjectivesCoronaviruses (CoVs) have a neuroinvasive propensity, and the frequently reported symptoms of smelling and taste dysfunction in many COVID-19 patients may be related to the respective capability of SARS-CoV2, the cause of the current pandemic. In this study we objectified and quantified the magnitude and underreporting of the smelling dysfunction caused by COVID-19 using a standardized test.MethodsWe conducted a prospective cross-sectional study comparing the proportion of anosmia using Sniffin-sticks in those reporting a loss of smell, in those who did not as well as in uninfected controls. The outcome of anosmic versus not anosmic patients were recorded during hospital stay and at day 15 on a six-category ordinal scale. The study was approved by the institutional review board, all participants consented to the study.Results40% of 45 consecutive hospitalized COVID-19 patients and 0% of 45 uninfected controls consenting were diagnosed with anosmia. 44% of anosmic and 50% of hyposmic patients did not report having smelling problems. Anosmia or hyposmia was not predictive of a severe COVID-19 manifestation.ConclusionsThe majority of COVID-19 patients have an objective anosmia and hyposmia, which often occurs unnoticed. These symptoms may be related to the neuroinvasive propensity of SARS-COV-2 and the unusual presentation of COVID-19 disease manifestations.

List of Ethics Committees and Competent Authorities that approved the trial. (PDF 190 kb)