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Im E, Kim H, Lee H, Jiang X, Kim JH. Exploring the tradeoff between data privacy and utility with a clinical data analysis use case. BMC Med Inform Decis Mak 2024; 24:147. [PMID: 38816848 PMCID: PMC11137882 DOI: 10.1186/s12911-024-02545-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 05/21/2024] [Indexed: 06/01/2024] Open
Abstract
BACKGROUND Securing adequate data privacy is critical for the productive utilization of data. De-identification, involving masking or replacing specific values in a dataset, could damage the dataset's utility. However, finding a reasonable balance between data privacy and utility is not straightforward. Nonetheless, few studies investigated how data de-identification efforts affect data analysis results. This study aimed to demonstrate the effect of different de-identification methods on a dataset's utility with a clinical analytic use case and assess the feasibility of finding a workable tradeoff between data privacy and utility. METHODS Predictive modeling of emergency department length of stay was used as a data analysis use case. A logistic regression model was developed with 1155 patient cases extracted from a clinical data warehouse of an academic medical center located in Seoul, South Korea. Nineteen de-identified datasets were generated based on various de-identification configurations using ARX, an open-source software for anonymizing sensitive personal data. The variable distributions and prediction results were compared between the de-identified datasets and the original dataset. We examined the association between data privacy and utility to determine whether it is feasible to identify a viable tradeoff between the two. RESULTS All 19 de-identification scenarios significantly decreased re-identification risk. Nevertheless, the de-identification processes resulted in record suppression and complete masking of variables used as predictors, thereby compromising dataset utility. A significant correlation was observed only between the re-identification reduction rates and the ARX utility scores. CONCLUSIONS As the importance of health data analysis increases, so does the need for effective privacy protection methods. While existing guidelines provide a basis for de-identifying datasets, achieving a balance between high privacy and utility is a complex task that requires understanding the data's intended use and involving input from data users. This approach could help find a suitable compromise between data privacy and utility.
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Affiliation(s)
- Eunyoung Im
- College of Nursing, Seoul National University, Seoul, South Korea
- Center for World-leading Human-care Nurse Leaders for the Future by Brain Korea 21 (BK 21) four project, College of Nursing, Seoul National University, Seoul, South Korea
| | - Hyeoneui Kim
- College of Nursing, Seoul National University, Seoul, South Korea.
- Center for World-leading Human-care Nurse Leaders for the Future by Brain Korea 21 (BK 21) four project, College of Nursing, Seoul National University, Seoul, South Korea.
- The Research Institute of Nursing Science, Seoul National University, Seoul, South Korea.
| | - Hyungbok Lee
- College of Nursing, Seoul National University, Seoul, South Korea
- Seoul National University Hospital, Seoul, South Korea
| | - Xiaoqian Jiang
- School of Biomedical Informatics, UTHealth, Houston, TX, USA
| | - Ju Han Kim
- Seoul National University Hospital, Seoul, South Korea
- College of Medicine, Seoul National University, Seoul, South Korea
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2
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Pilgram L, Meurers T, Malin B, Schaeffner E, Eckardt KU, Prasser F. The Costs of Anonymization: Case Study Using Clinical Data. J Med Internet Res 2024; 26:e49445. [PMID: 38657232 PMCID: PMC11079766 DOI: 10.2196/49445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 01/14/2024] [Accepted: 02/13/2024] [Indexed: 04/26/2024] Open
Abstract
BACKGROUND Sharing data from clinical studies can accelerate scientific progress, improve transparency, and increase the potential for innovation and collaboration. However, privacy concerns remain a barrier to data sharing. Certain concerns, such as reidentification risk, can be addressed through the application of anonymization algorithms, whereby data are altered so that it is no longer reasonably related to a person. Yet, such alterations have the potential to influence the data set's statistical properties, such that the privacy-utility trade-off must be considered. This has been studied in theory, but evidence based on real-world individual-level clinical data is rare, and anonymization has not broadly been adopted in clinical practice. OBJECTIVE The goal of this study is to contribute to a better understanding of anonymization in the real world by comprehensively evaluating the privacy-utility trade-off of differently anonymized data using data and scientific results from the German Chronic Kidney Disease (GCKD) study. METHODS The GCKD data set extracted for this study consists of 5217 records and 70 variables. A 2-step procedure was followed to determine which variables constituted reidentification risks. To capture a large portion of the risk-utility space, we decided on risk thresholds ranging from 0.02 to 1. The data were then transformed via generalization and suppression, and the anonymization process was varied using a generic and a use case-specific configuration. To assess the utility of the anonymized GCKD data, general-purpose metrics (ie, data granularity and entropy), as well as use case-specific metrics (ie, reproducibility), were applied. Reproducibility was assessed by measuring the overlap of the 95% CI lengths between anonymized and original results. RESULTS Reproducibility measured by 95% CI overlap was higher than utility obtained from general-purpose metrics. For example, granularity varied between 68.2% and 87.6%, and entropy varied between 25.5% and 46.2%, whereas the average 95% CI overlap was above 90% for all risk thresholds applied. A nonoverlapping 95% CI was detected in 6 estimates across all analyses, but the overwhelming majority of estimates exhibited an overlap over 50%. The use case-specific configuration outperformed the generic one in terms of actual utility (ie, reproducibility) at the same level of privacy. CONCLUSIONS Our results illustrate the challenges that anonymization faces when aiming to support multiple likely and possibly competing uses, while use case-specific anonymization can provide greater utility. This aspect should be taken into account when evaluating the associated costs of anonymized data and attempting to maintain sufficiently high levels of privacy for anonymized data. TRIAL REGISTRATION German Clinical Trials Register DRKS00003971; https://drks.de/search/en/trial/DRKS00003971. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) RR2-10.1093/ndt/gfr456.
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Affiliation(s)
- Lisa Pilgram
- Junior Digital Clinician Scientist Program, Biomedical Innovation Academy, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
- Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Thierry Meurers
- Medical Informatics Group, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Bradley Malin
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Elke Schaeffner
- Institute of Public Health, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Department of Nephrology and Hypertension, Universitätsklinikum Erlangen, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Fabian Prasser
- Medical Informatics Group, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
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Mehtälä J, Ali M, Miettinen T, Partanen L, Laapas K, Niemelä PT, Khorlo I, Ström S, Kurki S, Vapalahti J, Abdelgawwad K, Leinonen JV. Utilization of anonymization techniques to create an external control arm for clinical trial data. BMC Med Res Methodol 2023; 23:258. [PMID: 37925415 PMCID: PMC10625188 DOI: 10.1186/s12874-023-02082-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 10/26/2023] [Indexed: 11/06/2023] Open
Abstract
BACKGROUND Subject-level real-world data (RWD) collected during daily healthcare practices are increasingly used in medical research to assess questions that cannot be addressed in the context of a randomized controlled trial (RCT). A novel application of RWD arises from the need to create external control arms (ECAs) for single-arm RCTs. In the analysis of ECAs against RCT data, there is an evident need to manage and analyze RCT data and RWD in the same technical environment. In the Nordic countries, legal requirements may require that the original subject-level data be anonymized, i.e., modified so that the risk to identify any individual is minimal. The aim of this study was to conduct initial exploration on how well pseudonymized and anonymized RWD perform in the creation of an ECA for an RCT. METHODS This was a hybrid observational cohort study using clinical data from the control arm of the completed randomized phase II clinical trial (PACIFIC-AF) and RWD cohort from Finnish healthcare data sources. The initial pseudonymized RWD were anonymized within the (k, ε)-anonymity framework (a model for protecting individuals against identification). Propensity score matching and weighting methods were applied to the anonymized and pseudonymized RWD, to balance potential confounders against the RCT data. Descriptive statistics for the potential confounders and overall survival analyses were conducted prior to and after matching and weighting, using both the pseudonymized and anonymized RWD sets. RESULTS Anonymization affected the baseline characteristics of potential confounders only marginally. The greatest difference was in the prevalence of chronic obstructive pulmonary disease (4.6% vs. 5.4% in the pseudonymized compared to the anonymized data, respectively). Moreover, the overall survival changed in anonymization by only 8% (95% CI 4-22%). Both the pseudonymized and anonymized RWD were able to produce matched ECAs for the RCT data. Anonymization after matching impacted overall survival analysis by 22% (95% CI -21-87%). CONCLUSIONS Anonymization may be a viable technique for cases where flexible data transfer and sharing are required. As anonymization necessarily affects some aspects of the original data, further research and careful consideration of anonymization strategies are needed.
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Affiliation(s)
| | - Mehreen Ali
- Veil.ai Oy, Helsinki, Finland
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Timo Miettinen
- Veil.ai Oy, Helsinki, Finland
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
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Bartenschlager CC, Grieger M, Erber J, Neidel T, Borgmann S, Vehreschild JJ, Steinbrecher M, Rieg S, Stecher M, Dhillon C, Ruethrich MM, Jakob CEM, Hower M, Heller AR, Vehreschild M, Wyen C, Messmann H, Piepel C, Brunner JO, Hanses F, Römmele C. Covid-19 triage in the emergency department 2.0: how analytics and AI transform a human-made algorithm for the prediction of clinical pathways. Health Care Manag Sci 2023; 26:412-429. [PMID: 37428304 PMCID: PMC10485125 DOI: 10.1007/s10729-023-09647-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 06/01/2023] [Indexed: 07/11/2023]
Abstract
The Covid-19 pandemic has pushed many hospitals to their capacity limits. Therefore, a triage of patients has been discussed controversially primarily through an ethical perspective. The term triage contains many aspects such as urgency of treatment, severity of the disease and pre-existing conditions, access to critical care, or the classification of patients regarding subsequent clinical pathways starting from the emergency department. The determination of the pathways is important not only for patient care, but also for capacity planning in hospitals. We examine the performance of a human-made triage algorithm for clinical pathways which is considered a guideline for emergency departments in Germany based on a large multicenter dataset with over 4,000 European Covid-19 patients from the LEOSS registry. We find an accuracy of 28 percent and approximately 15 percent sensitivity for the ward class. The results serve as a benchmark for our extensions including an additional category of palliative care as a new label, analytics, AI, XAI, and interactive techniques. We find significant potential of analytics and AI in Covid-19 triage regarding accuracy, sensitivity, and other performance metrics whilst our interactive human-AI algorithm shows superior performance with approximately 73 percent accuracy and up to 76 percent sensitivity. The results are independent of the data preparation process regarding the imputation of missing values or grouping of comorbidities. In addition, we find that the consideration of an additional label palliative care does not improve the results.
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Affiliation(s)
- Christina C Bartenschlager
- Health Care Operations/Health Information Management, Faculty of Business and Economics, Faculty of Medicine, University of Augsburg, Universitätsstraße 16, 86159, Augsburg, Germany
- Professor of Applied Data Science in Health Care, Nürnberg School of Health, Ohm University of Applied Sciences Nuremberg, Nuremberg, Germany
- Anaesthesiology and Operative Intensive Care Medicine, Faculty of Medicine, University of Augsburg, Stenglinstrasse 2, 86156, Augsburg, Germany
| | - Milena Grieger
- Health Care Operations/Health Information Management, Faculty of Business and Economics, Faculty of Medicine, University of Augsburg, Universitätsstraße 16, 86159, Augsburg, Germany
| | - Johanna Erber
- Department of Internal Medicine II, Technical University of Munich, School of Medicine, University Hospital Rechts Der Isar, Munich, Germany
| | - Tobias Neidel
- Anaesthesiology and Operative Intensive Care Medicine, Faculty of Medicine, University of Augsburg, Stenglinstrasse 2, 86156, Augsburg, Germany
| | - Stefan Borgmann
- Hygiene and Infectiology, Klinikum Ingolstadt, Ingolstadt, Germany
| | - Jörg J Vehreschild
- Department of Internal Medicine, Hematology and Oncology, Goethe University Frankfurt, Frankfurt Am Main, Germany
- Department I of Internal Medicine, University of Cologne, University Hospital of Cologne, Cologne, Germany
- German Center for Infection Research, Partner Site Bonn-Cologne, Cologne, Germany
| | - Markus Steinbrecher
- Clinic for Internal Medicine III - Gastroenterology and Infectious Diseases, University Hospital Augsburg, Stenglinstraße 2, 86156, Augsburg, Germany
| | - Siegbert Rieg
- Clinic for Internal Medicine II - Infectiology, University Hospital Freiburg, Freiburg, Germany
| | - Melanie Stecher
- Department I of Internal Medicine, University of Cologne, University Hospital of Cologne, Cologne, Germany
- German Center for Infection Research, Partner Site Bonn-Cologne, Cologne, Germany
| | - Christine Dhillon
- COVID-19 Task Force, University Hospital Augsburg, Stenglinstraße 2, 86156, Augsburg, Germany
| | - Maria M Ruethrich
- Hematology and Internal Oncology, University Hospital Jena, Jena, Germany
| | - Carolin E M Jakob
- Department I of Internal Medicine, University of Cologne, University Hospital of Cologne, Cologne, Germany
- German Center for Infection Research, Partner Site Bonn-Cologne, Cologne, Germany
| | - Martin Hower
- Pneumology, Infectiology and Internal Intensive Care Medicine, Klinikum Dortmund, Germany
| | - Axel R Heller
- Anaesthesiology and Operative Intensive Care Medicine, Faculty of Medicine, University of Augsburg, Stenglinstrasse 2, 86156, Augsburg, Germany
| | - Maria Vehreschild
- Department of Internal Medicine, Infectious Diseases, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt Am Main, Germany
| | - Christoph Wyen
- Praxis am Ebertplatz, Cologne, Germany
- Department of Medicine I, University Hospital of Cologne, Cologne, Germany
| | - Helmut Messmann
- Clinic for Internal Medicine III - Gastroenterology and Infectious Diseases, University Hospital Augsburg, Stenglinstraße 2, 86156, Augsburg, Germany
| | - Christiane Piepel
- Department of Hemato-Oncology and Infectious Diseases, Klinikum Bremen-Mitte, Bremen, Germany
| | - Jens O Brunner
- Health Care Operations/Health Information Management, Faculty of Business and Economics, Faculty of Medicine, University of Augsburg, Universitätsstraße 16, 86159, Augsburg, Germany.
- Department of Technology, Management, and Economics, Technical University of Denmark, Hovedstaden, Denmark.
- Data and Development Support, Region Zealand, Denmark.
| | - Frank Hanses
- Internal Medicine and Infectious Diseases, University Hospital Regensburg, Regensburg, Germany
| | - Christoph Römmele
- Clinic for Internal Medicine III - Gastroenterology and Infectious Diseases, University Hospital Augsburg, Stenglinstraße 2, 86156, Augsburg, Germany
- COVID-19 Task Force, University Hospital Augsburg, Stenglinstraße 2, 86156, Augsburg, Germany
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5
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de Hesselle ML, Borgmann S, Rieg S, Vehreschild JJ, Rasch S, Koll CEM, Hower M, Stecher M, Ebert D, Hanses F, Schumann J. Age and Comorbidity Burden of Patients Critically Ill with COVID-19 Affect Both Access to and Outcome of Ventilation Therapy in Intensive Care Units. J Clin Med 2023; 12:jcm12072469. [PMID: 37048553 PMCID: PMC10095412 DOI: 10.3390/jcm12072469] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 03/20/2023] [Indexed: 04/14/2023] Open
Abstract
During the COVID-19 pandemic, large numbers of elderly, multimorbid people required treatment in intensive care units. This study investigated how the inherent patient factors age and comorbidity burden affected the treatment strategy and the outcome achieved. Retrospective analysis of data from intensive care patients enrolled in the Lean European Open Survey on SARS-CoV2-Infected Patients (LEOSS) cohort found that a patient's age and comorbidity burden in fact influenced their mortality rate and the use of ventilation therapy. Evidence showed that advanced age and multimorbidity were associated with the restrictive use of invasive ventilation therapies, particularly ECMO. Geriatric patients with a high comorbidity burden were clustered in the sub-cohort of non-ventilated ICU patients characterized by a high mortality rate. The risk of death generally increased with older age and accumulating comorbidity burden. Here, the more aggressive an applied procedure, the younger the age in which a majority of patients died. Clearly, geriatric, multimorbid COVID-19 patients benefit less from invasive ventilation therapies. This implies the need for a holistic approach to therapy decisions, taking into account the patient's wishes.
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Affiliation(s)
- Marie Louise de Hesselle
- University Clinic and Outpatient Clinic for Anesthesiology and Operative Intensive Care, University Medicine Halle (Saale), 06112 Halle (Saale), Germany
| | - Stefan Borgmann
- Department of Infectious Diseases and Infection Control, Ingolstadt Hospital, 85049 Ingolstadt, Germany
| | - Siegbert Rieg
- Department of Medicine II, University of Freiburg, 79106 Freiburg, Germany
| | - Jörg Janne Vehreschild
- Department II of Internal Medicine, Hematology/Oncology, Goethe University Frankfurt, 60323 Frankfurt, Germany
- Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany
- German Center for Infection Research (DZIF), Partner Site Bonn-Cologne, 50937 Cologne, Germany
| | - Sebastian Rasch
- Department of Internal Medicine II, University Hospital Rechts der Isar, School of Medicine, Technical University of Munich, 81675 Munich, Germany
| | - Carolin E M Koll
- Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany
- German Center for Infection Research (DZIF), Partner Site Bonn-Cologne, 50937 Cologne, Germany
| | - Martin Hower
- Department of Pneumology, Infectious Diseases, Internal Medicine and Intensive Care, Klinikum Dortmund GmbH, 44137 Dortmund, Germany
| | - Melanie Stecher
- Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany
- German Center for Infection Research (DZIF), Partner Site Bonn-Cologne, 50937 Cologne, Germany
| | - Daniel Ebert
- University Clinic and Outpatient Clinic for Anesthesiology and Operative Intensive Care, University Medicine Halle (Saale), 06112 Halle (Saale), Germany
| | - Frank Hanses
- Emergency Department and Department for Infection Control and Infectious Diseases, University Hospital Regensburg, 93053 Regensburg, Germany
| | - Julia Schumann
- University Clinic and Outpatient Clinic for Anesthesiology and Operative Intensive Care, University Medicine Halle (Saale), 06112 Halle (Saale), Germany
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Schmidt-Hellerau K, Raichle C, Ruethrich MM, Vehreschild JJ, Lanznaster J, Nunes de Miranda SM, Bausewein C, Vehreschild MJGT, Koll CEM, Simon ST, Hellwig K, Jensen BEO, Jung N. Specialized palliative care for hospitalized patients with SARS-CoV-2 infection: an analysis of the LEOSS registry. Infection 2023:10.1007/s15010-023-02020-z. [PMID: 36952127 PMCID: PMC10034879 DOI: 10.1007/s15010-023-02020-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 03/11/2023] [Indexed: 03/24/2023]
Abstract
PURPOSE Symptom control for patients who were severely ill or dying from COVID-19 was paramount while resources were strained and infection control measures were in place. We aimed to describe the characteristics of SARS-CoV-2 infected patients who received specialized palliative care (SPC) and the type of SPC provided in a larger cohort. METHODS From the multi-centre cohort study Lean European Open Survey on SARS-CoV-2 infected patients (LEOSS), data of patients hospitalized with SARS-CoV-2 infection documented between July 2020 and October 2021 were analysed. RESULTS 273/7292 patients (3.7%) received SPC. Those receiving SPC were older and suffered more often from comorbidities, but 59% presented with an estimated life expectancy > 1 year. Main symptoms were dyspnoea, delirium, and excessive tiredness. 224/273 patients (82%) died during the hospital stay compared to 789/7019 (11%) without SPC. Symptom control was provided most common (223/273; 95%), followed by family and psychological support (50% resp. 43%). Personal contact with friends or relatives before or during the dying phase was more often documented in patients receiving SPC compared to patients without SPC (52% vs. 30%). CONCLUSION In 3.7% of SARS-CoV-2 infected hospitalized patients, the burden of the acute infection triggered palliative care involvement. Besides complex symptom management, SPC professionals also focused on psychosocial and family issues and aimed to enable personal contacts of dying patients with their family. The data underpin the need for further involvement of SPC in SARS-CoV-2 infected patients but also in other severe chronic infectious diseases.
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Affiliation(s)
- Kirsten Schmidt-Hellerau
- Department I of Internal Medicine, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany.
| | - Claudia Raichle
- Department of Geriatric and Palliative Medicine, Tropenklinik Paul-Lechler Hospital, Tuebingen, Germany
| | - Maria M Ruethrich
- Department of Internal Medicine II, Haematology and Medical Oncology, University Hospital Jena, Jena, Germany
| | - Jörg J Vehreschild
- Department I of Internal Medicine, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
- Department II of Internal Medicine, Haematology/Oncology, Goethe University, Frankfurt, Frankfurt Am Main, Germany
- German Centre for Infection Research (DZIF), Partner Site Bonn-Cologne, Cologne, Germany
| | - Julia Lanznaster
- Department II of Internal Medicine, Hospital Passau, Passau, Germany
| | - Susana M Nunes de Miranda
- Department I of Internal Medicine, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
| | - Claudia Bausewein
- Department of Palliative Medicine, LMU University Hospital Munich, LMU Munich, Munich, Germany
| | - Maria J G T Vehreschild
- German Centre for Infection Research (DZIF), Partner Site Bonn-Cologne, Cologne, Germany
- Department of Internal Medicine II, Infectious Diseases, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt Am Main, Germany
| | - Carolin E M Koll
- Department I of Internal Medicine, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
| | - Steffen T Simon
- Department of Palliative Medicine, Faculty of Medicine, University of Cologne, Cologne, Germany
| | - Kerstin Hellwig
- Department of Neurology, St. Josef-Hospital Bochum, Ruhr University Bochum, Bochum, Germany
| | - Björn-Erik O Jensen
- Department of Gastroenterology, Hepatology and Infectious Diseases, Medical Faculty, University Hospital Duesseldorf, Heinrich Heine University, Düsseldorf, Germany
| | - Norma Jung
- Department I of Internal Medicine, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
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7
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Koppe U, Schilling J, Stecher M, Rüthrich MM, Marquis A, Diercke M, Haselberger M, Koll CEM, Niebank M, Ruehe B, Borgmann S, Grabenhenrich L, Hellwig K, Pilgram L, Spinner CD, Paerisch T. Disease severity in hospitalized COVID-19 patients: comparing routine surveillance with cohort data from the LEOSS study in 2020 in Germany. BMC Infect Dis 2023; 23:89. [PMID: 36765274 PMCID: PMC9912207 DOI: 10.1186/s12879-023-08035-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 01/27/2023] [Indexed: 02/12/2023] Open
Abstract
INTRODUCTION Studies investigating risk factors for severe COVID-19 often lack information on the representativeness of the study population. Here, we investigate factors associated with severe COVID-19 and compare the representativeness of the dataset to the general population. METHODS We used data from the Lean European Open Survey on SARS-CoV-2 infected patients (LEOSS) of hospitalized COVID-19 patients diagnosed in 2020 in Germany to identify associated factors for severe COVID-19, defined as progressing to a critical disease stage or death. To assess the representativeness, we compared the LEOSS cohort to cases of hospitalized patients in the German statutory notification data of the same time period. Descriptive methods and Poisson regression models were used. RESULTS Overall, 6672 hospitalized patients from LEOSS and 132,943 hospitalized cases from the German statutory notification data were included. In LEOSS, patients above 76 years were less likely represented (34.3% vs. 44.1%). Moreover, mortality was lower (14.3% vs. 21.5%) especially among age groups above 66 years. Factors associated with a severe COVID-19 disease course in LEOSS included increasing age, male sex (adjusted risk ratio (aRR) 1.69, 95% confidence interval (CI) 1.53-1.86), prior stem cell transplantation (aRR 2.27, 95% CI 1.53-3.38), and an elevated C-reactive protein at day of diagnosis (aRR 2.30, 95% CI 2.03-2.62). CONCLUSION We identified a broad range of factors associated with severe COVID-19 progression. However, the results may be less applicable for persons above 66 years since they experienced lower mortality in the LEOSS dataset compared to the statutory notification data.
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Affiliation(s)
- Uwe Koppe
- Department of Infectious Disease Epidemiology, Robert Koch-Institute, Berlin, Germany.
| | - Julia Schilling
- grid.13652.330000 0001 0940 3744Department of Infectious Disease Epidemiology, Robert Koch-Institute, Berlin, Germany
| | - Melanie Stecher
- grid.6190.e0000 0000 8580 3777Department I of Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany ,grid.452463.2German Centre for Infection Research (DZIF), Partner Site Bonn-Cologne, Cologne, Germany
| | - Maria Madeleine Rüthrich
- grid.275559.90000 0000 8517 6224Centre for Emergency Medicine, University Hospital Jena, Jena, Germany
| | - Adine Marquis
- grid.13652.330000 0001 0940 3744Department of Infectious Disease Epidemiology, Robert Koch-Institute, Berlin, Germany
| | - Michaela Diercke
- grid.13652.330000 0001 0940 3744Department of Infectious Disease Epidemiology, Robert Koch-Institute, Berlin, Germany
| | | | - Carolin E. M. Koll
- grid.6190.e0000 0000 8580 3777Department I of Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany ,grid.452463.2German Centre for Infection Research (DZIF), Partner Site Bonn-Cologne, Cologne, Germany
| | - Michaela Niebank
- grid.13652.330000 0001 0940 3744Centre for Biological Threats and Special Pathogens, Robert Koch-Institute, Berlin, Germany
| | - Bettina Ruehe
- grid.13652.330000 0001 0940 3744Centre for Biological Threats and Special Pathogens, Robert Koch-Institute, Berlin, Germany
| | - Stefan Borgmann
- grid.492033.f0000 0001 0058 5377Department of Infectious Diseases and Infection Control, Ingolstadt Hospital, Ingolstadt, Germany
| | - Linus Grabenhenrich
- grid.13652.330000 0001 0940 3744Department for Methods Development, Research Infrastructure and Information Technology, Robert Koch Institute, Berlin, Germany
| | - Kerstin Hellwig
- grid.5570.70000 0004 0490 981XDepartment of Neurology, Catholic Hospital Bochum St. Josef-Hospital Bochum, Ruhr University Bochum, Bochum, Germany
| | - Lisa Pilgram
- grid.6363.00000 0001 2218 4662Department of Nephrology and Medical Intensive Care, Charité, Universitätsmedizin Berlin, Berlin, Germany ,grid.7839.50000 0004 1936 9721Department of Internal Medicine, Hematology and Oncology, Goethe University, Frankfurt, Frankfurt, Germany
| | - Christoph D. Spinner
- grid.6936.a0000000123222966Department of Internal Medicine II, School of Medicine, University Hospital Rechts Der Isar, Technical University of Munich, Munich, Germany
| | - Thomas Paerisch
- grid.13652.330000 0001 0940 3744Centre for Biological Threats and Special Pathogens, Robert Koch-Institute, Berlin, Germany
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Use and effectiveness of remdesivir for the treatment of patients with covid-19 using data from the Lean European Open Survey on SARS-CoV-2 infected patients (LEOSS): a multicentre cohort study. Infection 2023:10.1007/s15010-023-01994-0. [PMID: 36763285 PMCID: PMC9913009 DOI: 10.1007/s15010-023-01994-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 01/30/2023] [Indexed: 02/11/2023]
Abstract
OBJECTIVES The use of remdesivir (RDV) as the first drug approved for coronavirus disease 2019 (COVID-19) remains controversial. Based on the Lean European Open Survey on severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infected patients (LEOSS), we aim to contribute timing-focused complementary real-world insights to its evaluation. METHODS SARS-CoV-2 infected patients between January 2020 and December 2021 treated with RDV were matched 1:1 to controls considering sociodemographics, comorbidities and clinical status. Multiple imputations were used to account for missing data. Effects on fatal outcome were estimated using uni- and multivariable Cox regression models. RESULTS We included 9,687 patients. For those starting RDV administration in the complicated phase, Cox regression for fatal outcome showed an adjusted hazard ratio (aHR) of 0.59 (95%CI 0.41-0.83). Positive trends could be obtained for further scenarios: an aHR of 0.51 (95%CI 0.16-1.68) when RDV was initiated in uncomplicated and of 0.76 (95% CI 0.55-1.04) in a critical phase of disease. Patients receiving RDV with concomitant steroids exhibited a further reduction in aHR in both, the complicated (aHR 0.50, 95%CI 0.29-0.88) and critical phase (aHR 0.63, 95%CI 0.39-1.02). CONCLUSION Our study results elucidate that RDV use, in particular when initiated in the complicated phase and accompanied by steroids is associated with improved mortality. However, given the limitations of non-randomized trials in estimating the magnitude of the benefit of an intervention, further randomized trials focusing on the timing of therapy initiation seem warranted.
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Pilgram L, Eberwein L, Jensen BEO, Jakob CEM, Koehler FC, Hower M, Kielstein JT, Stecher M, Hohenstein B, Prasser F, Westhoff T, de Miranda SMN, Vehreschild MJGT, Lanznaster J, Dolff S. SARS-CoV-2 infection in chronic kidney disease patients with pre-existing dialysis: description across different pandemic intervals and effect on disease course (mortality). Infection 2023; 51:71-81. [PMID: 35486356 PMCID: PMC9052729 DOI: 10.1007/s15010-022-01826-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2021] [Accepted: 04/03/2022] [Indexed: 01/31/2023]
Abstract
PURPOSE Patients suffering from chronic kidney disease (CKD) are in general at high risk for severe coronavirus disease (COVID-19) but dialysis-dependency (CKD5D) is poorly understood. We aimed to describe CKD5D patients in the different intervals of the pandemic and to evaluate pre-existing dialysis dependency as a potential risk factor for mortality. METHODS In this multicentre cohort study, data from German study sites of the Lean European Open Survey on SARS-CoV-2-infected patients (LEOSS) were used. We multiply imputed missing data, performed subsequent analyses in each of the imputed data sets and pooled the results. Cases (CKD5D) and controls (CKD not requiring dialysis) were matched 1:1 by propensity-scoring. Effects on fatal outcome were calculated by multivariable logistic regression. RESULTS The cohort consisted of 207 patients suffering from CKD5D and 964 potential controls. Multivariable regression of the whole cohort identified age (> 85 years adjusted odds ratio (aOR) 7.34, 95% CI 2.45-21.99), chronic heart failure (aOR 1.67, 95% CI 1.25-2.23), coronary artery disease (aOR 1.41, 95% CI 1.05-1.89) and active oncological disease (aOR 1.73, 95% CI 1.07-2.80) as risk factors for fatal outcome. Dialysis-dependency was not associated with a fatal outcome-neither in this analysis (aOR 1.08, 95% CI 0.75-1.54) nor in the conditional multivariable regression after matching (aOR 1.34, 95% CI 0.70-2.59). CONCLUSIONS In the present multicentre German cohort, dialysis dependency is not linked to fatal outcome in SARS-CoV-2-infected CKD patients. However, the mortality rate of 26% demonstrates that CKD patients are an extreme vulnerable population, irrespective of pre-existing dialysis-dependency.
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Affiliation(s)
- Lisa Pilgram
- Department of Nephrology and Medical Intensive Care, Charité, Universitätsmedizin Berlin, Berlin, Germany
- Department of Internal Medicine, Hematology and Oncology, Goethe University Frankfurt, Frankfurt, Germany
| | - Lukas Eberwein
- 4th Department of Internal Medicine, Klinikum Leverkusen gGmbH, Leverkusen, Germany
| | - Bjoern-Erik O Jensen
- Department of Gastroenterology, Hepatology and Infectious Diseases, Heinrich Heine University, Düsseldorf, Germany
| | - Carolin E M Jakob
- Department I of Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- German Centre for Infection Research (DZIF), Partner Site Bonn-Cologne, Cologne, Germany
| | - Felix C Koehler
- Department II of Internal Medicine and Center for Molecular Medicine Cologne, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Faculty of Medicine and University Hospital Cologne, CECAD, University of Cologne, Cologne, Germany
| | - Martin Hower
- Department of Pneumology, Infectiology, Internal Medicine and Intensive Care, Klinikum Dortmund gGmbH, Dortmund, Hospital of University Witten/Herdecke, Dortmund, Germany
| | - Jan T Kielstein
- Medical Clinic V, Nephrology|Rheumatology|Blood Purification, Academic Teaching Hospital Braunschweig, Braunschweig, Germany
| | - Melanie Stecher
- Department I of Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- German Centre for Infection Research (DZIF), Partner Site Bonn-Cologne, Cologne, Germany
| | - Bernd Hohenstein
- Nephrological Centre Villingen-Schwenningen, Villingen-Schwenningen, Germany
| | - Fabian Prasser
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Timm Westhoff
- Department of Internal Medicine I, Marien Hospital Herne Ruhr University Bochum, Herne, Germany
| | - Susana M Nunes de Miranda
- Department I of Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Maria J G T Vehreschild
- Department of Internal Medicine, Infectious Diseases, Goethe University Frankfurt, Frankfurt, Germany
| | - Julia Lanznaster
- Department of Internal Medicine 2, Klinikum Passau, Passau, Germany
| | - Sebastian Dolff
- Department of Infectious Diseases, West German Centre of Infectious Diseases, University Hospital Essen, University Duisburg-Essen, Hufelandstr. 55, 45122, Essen, Germany.
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Sáinz-Pardo Díaz J, López García Á. A Python library to check the level of anonymity of a dataset. Sci Data 2022; 9:785. [PMID: 36572676 PMCID: PMC9791635 DOI: 10.1038/s41597-022-01894-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 12/08/2022] [Indexed: 12/28/2022] Open
Abstract
Openly sharing data with sensitive attributes and privacy restrictions is a challenging task. In this document we present the implementation of pyCANON, a Python library and command line interface (CLI) to check and assess the level of anonymity of a dataset through some of the most common anonymization techniques: k-anonymity, (α,k)-anonymity, ℓ-diversity, entropy ℓ-diversity, recursive (c,ℓ)-diversity, t-closeness, basic β-likeness, enhanced β-likeness and δ-disclosure privacy. For the case of more than one sensitive attribute, two approaches are proposed for evaluating these techniques. The main strength of this library is to obtain a full report of the parameters that are fulfilled for each of the techniques mentioned above, with the unique requirement of the set of quasi-identifiers and sensitive attributes. The methods implemented are presented together with the attacks they prevent, the description of the library, examples of the different functions' usage, as well as the impact and the possible applications that can be developed. Finally, some possible aspects to be incorporated in future updates are proposed.
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Affiliation(s)
- Judith Sáinz-Pardo Díaz
- grid.469953.40000 0004 1757 2371Instituto de Física de Cantabria (IFCA), CSIC-UC, Avda. los Castros s/n, 39005 Santander, Spain
| | - Álvaro López García
- grid.469953.40000 0004 1757 2371Instituto de Física de Cantabria (IFCA), CSIC-UC, Avda. los Castros s/n, 39005 Santander, Spain
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11
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Bartenschlager CC, Ebel SS, Kling S, Vehreschild J, Zabel LT, Spinner CD, Schuler A, Heller AR, Borgmann S, Hoffmann R, Rieg S, Messmann H, Hower M, Brunner JO, Hanses F, Römmele C. COVIDAL: A machine learning classifier for digital COVID-19 diagnosis in German hospitals. ACM TRANSACTIONS ON MANAGEMENT INFORMATION SYSTEMS 2022. [DOI: 10.1145/3567431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
For the fight against the COVID-19 pandemic, it is particularly important to map the course of infection, in terms of patients who have currently tested SARS-CoV-2 positive, as accurately as possible. In hospitals, this is even more important because resources have become scarce. Although polymerase chain reaction (PCR) and point of care (POC) antigen testing capacities have been massively expanded, they are often very time-consuming and cost-intensive and, in some cases, lack appropriate performance. To meet these challenges, we propose the COVIDAL classifier for AI-based diagnosis of symptomatic COVID-19 subjects in hospitals based on laboratory parameters. We evaluate the algorithm's performance by unique multicenter data with approx. 4,000 patients and an extraordinary high ratio of SARS-CoV-2 positive patients. We analyze the influence of data preparation, flexibility in optimization targets as well as the selection of the test set on the COVIDAL outcome. The algorithm is compared with standard AI, PCR, POC antigen testing and manual classifications of seven physicians by a decision theoretic scoring model including performance metrics, turnaround times and cost. Thereby, we define health care settings in which a certain classifier for COVID-19 diagnosis is to be applied. We find sensitivities, specificities and accuracies of the COVIDAL algorithm of up to 90 percent. Our scoring model suggests using PCR testing for a focus on performance metrics. For turnaround times, POC antigen testing should be used. If balancing performance, turnaround times and cost is of interest, as, for example, in the emergency department, COVIDAL is superior based on the scoring model.
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Affiliation(s)
- Christina C. Bartenschlager
- Chair of Health Care Operations/Health Information Management, Faculty of Business and Economics, Faculty of Medicine, University of Augsburg, Universitätsstraße 16, 86159 Augsburg, Germany
| | - Stefanie S. Ebel
- Chair of Health Care Operations/Health Information Management, Faculty of Business and Economics, Faculty of Medicine, University of Augsburg, Universitätsstraße 16, 86159 Augsburg, Germany
| | - Sebastian Kling
- Chair of Health Care Operations/Health Information Management, Faculty of Business and Economics, Faculty of Medicine, University of Augsburg, Universitätsstraße 16, 86159 Augsburg, Germany
| | - Janne Vehreschild
- Department II of Internal Medicine, Hematology/Oncology, Goethe University, Frankfurt, Frankfurt am Main, Germany; Department I of Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany; German Centre for Infection Research (DZIF), partner site Bonn-Cologne, Cologne, Germany
| | - Lutz T. Zabel
- Laboratory Medicine, Alb Fils Kliniken GmbH, Eichertstraße 3, 73035 Göppingen, Germany
| | - Christoph D. Spinner
- Technical University of Munich, School of Medicine, University Hospital rechts der Isar, Department of Internal Medicine II, Ismaninger Str. 22, 81675 Munich, Germany
| | - Andreas Schuler
- Gastroenterology, Alb Fils Kliniken GmbH, Eichertstraße 3, 73035 Göppingen, Germany
| | - Axel R. Heller
- Anaesthesiology and Operative Intensive Care Medicine, Medical Faculty, University of Augsburg, Stenglinstrasse 2, 86156 Augsburg, Germany
| | | | - Reinhard Hoffmann
- Laboratory Medicine and Microbiology, Medical Faculty, University of Augsburg, Stenglinstrasse 2, 86156 Augsburg, Germany
| | - Siegbert Rieg
- Clinic for Internal Medicine II - Infectiology, University Hospital Freiburg, Germany
| | - Helmut Messmann
- Clinic for Internal Medicine III - Gastroenterology and Infectious Diseases, University Hospital Augsburg, Stenglinstraße 2, 86156 Augsburg, Germany
| | - Martin Hower
- Department of Pneumology, Infectious Diseases and Intensive Care, Klinikum Dortmund gGmbH, Hospital of University Witten / Herdecke, 44137 Dortmund, Germany
| | - Jens O. Brunner
- Chair of Health Care Operations/Health Information Management, Faculty of Business and Economics, Faculty of Medicine, University of Augsburg, Universitätsstraße 16, 86159 Augsburg, Germany
| | - Frank Hanses
- Emergency Department, University Hospital Regensburg, Germany; Department for Infection Control and Infectious Diseases, University Hospital Regensburg, Germany
| | - Christoph Römmele
- Clinic for Internal Medicine III - Gastroenterology and Infectious Diseases, University Hospital Augsburg, Stenglinstraße 2, 86156 Augsburg, Germany
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12
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Statistical biases due to anonymization evaluated in an open clinical dataset from COVID-19 patients. Sci Data 2022; 9:776. [PMID: 36543828 PMCID: PMC9769467 DOI: 10.1038/s41597-022-01669-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 08/30/2022] [Indexed: 12/24/2022] Open
Abstract
Anonymization has the potential to foster the sharing of medical data. State-of-the-art methods use mathematical models to modify data to reduce privacy risks. However, the degree of protection must be balanced against the impact on statistical properties. We studied an extreme case of this trade-off: the statistical validity of an open medical dataset based on the German National Pandemic Cohort Network (NAPKON), which was prepared for publication using a strong anonymization procedure. Descriptive statistics and results of regression analyses were compared before and after anonymization of multiple variants of the original dataset. Despite significant differences in value distributions, the statistical bias was found to be small in all cases. In the regression analyses, the median absolute deviations of the estimated adjusted odds ratios for different sample sizes ranged from 0.01 [minimum = 0, maximum = 0.58] to 0.52 [minimum = 0.25, maximum = 0.91]. Disproportionate impact on the statistical properties of data is a common argument against the use of anonymization. Our analysis demonstrates that anonymization can actually preserve validity of statistical results in relatively low-dimensional data.
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13
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Heissig B, Salama Y, Iakoubov R, Vehreschild JJ, Rios R, Nogueira T, Vehreschild MJGT, Stecher M, Mori H, Lanznaster J, Adachi E, Jakob C, Tabe Y, Ruethrich M, Borgmann S, Naito T, Wille K, Valenti S, Hower M, Hattori N, Rieg S, Nagaoka T, Jensen BE, Yotsuyanagi H, Hertenstein B, Ogawa H, Wyen C, Kominami E, Roemmele C, Takahashi S, Rupp J, Takahashi K, Hanses F, Hattori K. COVID-19 Severity and Thrombo-Inflammatory Response Linked to Ethnicity. Biomedicines 2022; 10:biomedicines10102549. [PMID: 36289811 PMCID: PMC9599040 DOI: 10.3390/biomedicines10102549] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Revised: 10/03/2022] [Accepted: 10/08/2022] [Indexed: 01/08/2023] Open
Abstract
Although there is strong evidence that SARS-CoV-2 infection is associated with adverse outcomes in certain ethnic groups, the association of disease severity and risk factors such as comorbidities and biomarkers with racial disparities remains undefined. This retrospective study between March 2020 and February 2021 explores COVID-19 risk factors as predictors for patients’ disease progression through country comparison. Disease severity predictors in Germany and Japan were cardiovascular-associated comorbidities, dementia, and age. We adjusted age, sex, body mass index, and history of cardiovascular disease comorbidity in the country cohorts using a propensity score matching (PSM) technique to reduce the influence of differences in sample size and the surprisingly young, lean Japanese cohort. Analysis of the 170 PSM pairs confirmed that 65.29% of German and 85.29% of Japanese patients were in the uncomplicated phase. More German than Japanese patients were admitted in the complicated and critical phase. Ethnic differences were identified in patients without cardiovascular comorbidities. Japanese patients in the uncomplicated phase presented a suppressed inflammatory response and coagulopathy with hypocoagulation. In contrast, German patients exhibited a hyperactive inflammatory response and coagulopathy with hypercoagulation. These differences were less pronounced in patients in the complicated phase or with cardiovascular diseases. Coagulation/fibrinolysis-associated biomarkers rather than inflammatory-related biomarkers predicted disease severity in patients with cardiovascular comorbidities: platelet counts were associated with severe illness in German patients. In contrast, high D-dimer and fibrinogen levels predicted disease severity in Japanese patients. Our comparative study indicates that ethnicity influences COVID-19-associated biomarker expression linked to the inflammatory and coagulation (thrombo-inflammatory) response. Future studies will be necessary to determine whether these differences contributed to the less severe disease progression observed in Japanese COVID-19 patients compared with those in Germany.
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Affiliation(s)
- Beate Heissig
- School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan
| | - Yousef Salama
- An-Najah Center for Cancer and Stem Cell Research, Faculty of Medicine and Health Sciences, An-Najah National University, P.O. Box 7, Nablus 99900800, Palestine
| | - Roman Iakoubov
- Department of Internal Medicine II, University Hospital Rechts der Isar, School of Medicine, Technical University, 81675 Munich, Germany
| | | | - Ricardo Rios
- Institute of Computing, Federal University of Bahia, Salvador 40110060, Brazil
| | - Tatiane Nogueira
- Institute of Computing, Federal University of Bahia, Salvador 40110060, Brazil
| | - Maria J. G. T. Vehreschild
- Department of Internal Medicine, Infectious Diseases, University Hospital Frankfurt, Goethe University Frankfurt, 60590 Frankfurt am Main, Germany
| | - Melanie Stecher
- Department I for Internal Medicine, University Hospital of Cologne, University of Cologne, 50937 Cologne, Germany
- German Center for Infection Research (DZIF), Partner-Site Bonn-Cologne, 50937 Cologne, Germany
| | - Hirotake Mori
- School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan
| | | | - Eisuke Adachi
- IMSUT Hospital of The Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Japan
| | - Carolin Jakob
- Department I for Internal Medicine, University Hospital of Cologne, University of Cologne, 50937 Cologne, Germany
- German Center for Infection Research (DZIF), Partner-Site Bonn-Cologne, 50937 Cologne, Germany
| | - Yoko Tabe
- School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan
| | | | | | - Toshio Naito
- School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan
| | - Kai Wille
- Johannes Wesling Klinikum Minden, Ruhr-Universitaet, 44801 Bochum, Germany
| | - Simon Valenti
- School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan
| | - Martin Hower
- Klinikum Dortmund gGmbH, Hospital of University Witten/Herdecke, 44137 Dortmund, Germany
| | - Nobutaka Hattori
- School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan
| | | | - Tetsutaro Nagaoka
- School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan
| | | | - Hiroshi Yotsuyanagi
- IMSUT Hospital of The Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Japan
| | | | - Hideoki Ogawa
- School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan
| | | | - Eiki Kominami
- School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan
| | - Christoph Roemmele
- Internal Medicine III—Gastroenterology and Infectious Diseases, University Hospital of Augsburg, 86156 Augsburg, Germany
| | - Satoshi Takahashi
- IMSUT Hospital of The Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Japan
| | - Jan Rupp
- Department of Infectious Diseases and Microbiology, University Hospital Schleswig-Holstein/Campus Luebeck, 23538 Luebeck, Germany
| | - Kazuhisa Takahashi
- School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan
| | - Frank Hanses
- Emergency Department and Department for Infectious Diseases and Infection Control, University Hospital Regensburg, 93053 Regensburg, Germany
| | - Koichi Hattori
- School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo 113-8421, Japan
- Correspondence:
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Jeon M, Park H, Kim HJ, Morley M, Cho H. k-SALSA: k-anonymous synthetic averaging of retinal images via local style alignment. COMPUTER VISION - ECCV ... : ... EUROPEAN CONFERENCE ON COMPUTER VISION : PROCEEDINGS. EUROPEAN CONFERENCE ON COMPUTER VISION 2022; 13681:661-678. [PMID: 37525827 PMCID: PMC10388376 DOI: 10.1007/978-3-031-19803-8_39] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/02/2023]
Abstract
The application of modern machine learning to retinal image analyses offers valuable insights into a broad range of human health conditions beyond ophthalmic diseases. Additionally, data sharing is key to fully realizing the potential of machine learning models by providing a rich and diverse collection of training data. However, the personallyidentifying nature of retinal images, encompassing the unique vascular structure of each individual, often prevents this data from being shared openly. While prior works have explored image de-identification strategies based on synthetic averaging of images in other domains (e.g. facial images), existing techniques face difficulty in preserving both privacy and clinical utility in retinal images, as we demonstrate in our work. We therefore introduce k-SALSA, a generative adversarial network (GAN)-based framework for synthesizing retinal fundus images that summarize a given private dataset while satisfying the privacy notion of k-anonymity. k-SALSA brings together state-of-the-art techniques for training and inverting GANs to achieve practical performance on retinal images. Furthermore, k-SALSA leverages a new technique, called local style alignment, to generate a synthetic average that maximizes the retention of fine-grain visual patterns in the source images, thus improving the clinical utility of the generated images. On two benchmark datasets of diabetic retinopathy (EyePACS and APTOS), we demonstrate our improvement upon existing methods with respect to image fidelity, classification performance, and mitigation of membership inference attacks. Our work represents a step toward broader sharing of retinal images for scientific collaboration. Code is available at https://github.com/hcholab/k-salsa.
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Affiliation(s)
- Minkyu Jeon
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Korea University, Seoul, Republic of Korea
| | | | | | - Michael Morley
- Harvard Medical School, Boston, MA, USA
- Ophthalmic Consultants of Boston, Boston, MA, USA
| | - Hyunghoon Cho
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
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15
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de Hesselle ML, Borgmann S, Rieg S, Vehreshild JJ, Spinner CD, Koll CEM, Hower M, Stecher M, Ebert D, Hanses F, Schumann J. Invasiveness of Ventilation Therapy Is Associated to Prevalence of Secondary Bacterial and Fungal Infections in Critically Ill COVID-19 Patients. J Clin Med 2022; 11:jcm11175239. [PMID: 36079168 PMCID: PMC9457079 DOI: 10.3390/jcm11175239] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 08/31/2022] [Accepted: 09/02/2022] [Indexed: 12/17/2022] Open
Abstract
Superinfections are a fundamental critical care problem, and their significance in severe COVID-19 cases needs to be determined. This study analyzed data from the Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS) cohort focusing on intensive care patients. A retrospective analysis of patient data from 840 cases of COVID-19 with critical courses demonstrated that co-infections were frequently present and were primarily of nosocomial origin. Furthermore, our analysis showed that invasive therapy procedures accompanied an increased risk for healthcare-associated infections. Non-ventilated ICU patients were rarely affected by secondary infections. The risk of infection, however, increased even when non-invasive ventilation was used. A further, significant increase in infection rates was seen with the use of invasive ventilation and even more so with extracorporeal membrane oxygenation (ECMO) therapy. The marked differences among ICU techniques used for the treatment of COVID-19-induced respiratory failure in terms of secondary infection risk profile should be taken into account for the optimal management of critically ill COVID-19 patients, as well as for adequate antimicrobial therapy.
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Affiliation(s)
- Marie Louise de Hesselle
- University Clinic and Outpatient Clinic for Anesthesiology and Operative Intensive Care, University Medicine Halle (Saale), 06112 Halle (Saale), Germany
| | - Stefan Borgmann
- Department of Infectious Diseases and Infection Control, Ingolstadt Hospital, 85049 Ingolstadt, Germany
| | - Siegbert Rieg
- Department of Medicine II, University of Freiburg, 79106 Freiburg, Germany
| | - Jörg Janne Vehreshild
- Department II of Internal Medicine, Hematology and Oncology, Goethe University Frankfurt, 60323 Frankfurt, Germany
- Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany
- German Center for Infection Research (DZIF), Partner Site Bonn-Cologne, 50937 Cologne, Germany
| | - Christoph D. Spinner
- Department of Internal Medicine II, University Hospital Rechts Der Isar, School of Medicine, Technical University of Munich, 81675 Munich, Germany
- German Center for Infection Research (DZIF), 38106 Brunswick, Germany
| | - Carolin E. M. Koll
- Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany
- German Center for Infection Research (DZIF), Partner Site Bonn-Cologne, 50937 Cologne, Germany
| | - Martin Hower
- Department of Pneumology, Infectious Diseases, Internal Medicine and Intensive Care, Klinikum Dortmund GmbH, 44137 Dortmund, Germany
| | - Melanie Stecher
- Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany
- German Center for Infection Research (DZIF), Partner Site Bonn-Cologne, 50937 Cologne, Germany
| | - Daniel Ebert
- University Clinic and Outpatient Clinic for Anesthesiology and Operative Intensive Care, University Medicine Halle (Saale), 06112 Halle (Saale), Germany
| | - Frank Hanses
- Emergency Department and Department for Infection Control and Infectious Diseases, University Hospital Regensburg, 93053 Regensburg, Germany
| | - Julia Schumann
- University Clinic and Outpatient Clinic for Anesthesiology and Operative Intensive Care, University Medicine Halle (Saale), 06112 Halle (Saale), Germany
- Correspondence:
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16
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Raichle C, Borgmann S, Bausewein C, Rieg S, Jakob CEM, Simon ST, Tometten L, Vehreschild JJ, Leisse C, Erber J, Stecher M, Pauli B, Rüthrich MM, Pilgram L, Hanses F, Isberner N, Hower M, Degenhardt C, Hertenstein B, Vehreschild MJGT, Römmele C, Jung N. Hospitalized patients dying with SARS-CoV-2 infection—An analysis of patient characteristics and management in ICU and general ward of the LEOSS registry. PLoS One 2022; 17:e0271822. [PMID: 35905129 PMCID: PMC9337665 DOI: 10.1371/journal.pone.0271822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 07/08/2022] [Indexed: 11/17/2022] Open
Abstract
Background
COVID-19 is a severe disease with a high need for intensive care treatment and a high mortality rate in hospitalized patients. The objective of this study was to describe and compare the clinical characteristics and the management of patients dying with SARS-CoV-2 infection in the acute medical and intensive care setting.
Methods
Descriptive analysis of dying patients enrolled in the Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS), a non-interventional cohort study, between March 18 and November 18, 2020. Symptoms, comorbidities and management of patients, including palliative care involvement, were compared between general ward and intensive care unit (ICU) by univariate analysis.
Results
580/4310 (13%) SARS-CoV-2 infected patients died. Among 580 patients 67% were treated on ICU and 33% on a general ward. The spectrum of comorbidities and symptoms was broad with more comorbidities (≥ four comorbidities: 52% versus 25%) and a higher age distribution (>65 years: 98% versus 70%) in patients on the general ward. 69% of patients were in an at least complicated phase at diagnosis of the SARS-CoV-2 infection with a higher proportion of patients in a critical phase or dying the day of diagnosis treated on ICU (36% versus 11%). While most patients admitted to ICU came from home (71%), patients treated on the general ward came likewise from home and nursing home (44% respectively) and were more frequently on palliative care before admission (29% versus 7%). A palliative care team was involved in dying patients in 15%. Personal contacts were limited but more often documented in patients treated on ICU (68% versus 47%).
Conclusion
Patients dying with SARS-CoV-2 infection suffer from high symptom burden and often deteriorate early with a demand for ICU treatment. Therefor a demand for palliative care expertise with early involvement seems to exist.
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Affiliation(s)
- Claudia Raichle
- Department of Geriatric and Palliative Medicine, Tropenklinik Paul-Lechler-Krankenhaus, Tübingen, Germany
- * E-mail: (NJ); (CR)
| | - Stefan Borgmann
- Department of Infectious Diseases and Infection Control, Ingolstadt Hospital, Ingolstadt, Germany
| | | | - Siegbert Rieg
- Division of Infectious Diseases, Department of Medicine II, Medical Centre–University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Carolin E. M. Jakob
- Department I of Internal Medicine, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
| | - Steffen T. Simon
- Department of Palliative Medicine, Faculty of Medicine, University of Cologne, Cologne, Germany
| | - Lukas Tometten
- Department I of Internal Medicine, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
| | - Jörg Janne Vehreschild
- Department I of Internal Medicine, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
- Center for Internal Medicine, Medical Department 2, Hematology/Oncology and Infectious Diseases, University Hospital of Frankfurt, Frankfurt, Germany
- German Centre for Infection Research, partner site Bonn-Cologne, Cologne, Germany
| | - Charlotte Leisse
- Department I of Internal Medicine, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
| | - Johanna Erber
- Department of Internal Medicine II, University Hospital rechts der Isar, Technical University of Munich, Munich, Germany
| | - Melanie Stecher
- Department I of Internal Medicine, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
- German Centre for Infection Research, partner site Bonn-Cologne, Cologne, Germany
| | - Berenike Pauli
- Department of Palliative Medicine, Faculty of Medicine, University of Cologne, Cologne, Germany
| | - Maria Madeleine Rüthrich
- Department of Internal Medicine II, Hematology and Medical Oncology, University Hospital Jena, Jena, Germany
| | - Lisa Pilgram
- Center for Internal Medicine, Medical Department 2, Hematology/Oncology and Infectious Diseases, University Hospital of Frankfurt, Frankfurt, Germany
| | - Frank Hanses
- Emergency Department, University Hospital Regensburg, Regensburg, Germany
- Department for Infectious Diseases and Infection Control, University Hospital Regensburg, Regensburg, Germany
| | - Nora Isberner
- Department of Internal Medicine II, Division of Infectious Diseases, University Hospital Würzburg, Würzburg, Germany
| | - Martin Hower
- Department of Internal Medicine, Klinikum Dortmund, Dortmund, Germany
| | | | | | - Maria J. G. T. Vehreschild
- Department of Internal Medicine 2, Infectious Diseases, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Christoph Römmele
- Department of Internal Medicine III–Gastroenterology and Infectious Diseases, University Hospital Augsburg, Augsburg, Germany
| | - Norma Jung
- Department I of Internal Medicine, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
- * E-mail: (NJ); (CR)
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17
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Stefan N, Sippel K, Heni M, Fritsche A, Wagner R, Jakob CEM, Preißl H, von Werder A, Khodamoradi Y, Borgmann S, Rüthrich MM, Hanses F, Haselberger M, Piepel C, Hower M, Vom Dahl J, Wille K, Römmele C, Vehreschild J, Stecher M, Solimena M, Roden M, Schürmann A, Gallwitz B, Hrabe de Angelis M, Ludwig DS, Schulze MB, Jensen BEO, Birkenfeld AL. Obesity and Impaired Metabolic Health Increase Risk of COVID-19-Related Mortality in Young and Middle-Aged Adults to the Level Observed in Older People: The LEOSS Registry. Front Med (Lausanne) 2022; 9:875430. [PMID: 35646955 PMCID: PMC9131026 DOI: 10.3389/fmed.2022.875430] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 04/08/2022] [Indexed: 12/15/2022] Open
Abstract
Advanced age, followed by male sex, by far poses the greatest risk for severe COVID-19. An unresolved question is the extent to which modifiable comorbidities increase the risk of COVID-19-related mortality among younger patients, in whom COVID-19-related hospitalization strongly increased in 2021. A total of 3,163 patients with SARS-COV-2 diagnosis in the Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS) cohort were studied. LEOSS is a European non-interventional multi-center cohort study established in March 2020 to investigate the epidemiology and clinical course of SARS-CoV-2 infection. Data from hospitalized patients and those who received ambulatory care, with a positive SARS-CoV-2 test, were included in the study. An additive effect of obesity, diabetes and hypertension on the risk of mortality was observed, which was particularly strong in young and middle-aged patients. Compared to young and middle-aged (18-55 years) patients without obesity, diabetes and hypertension (non-obese and metabolically healthy; n = 593), young and middle-aged adult patients with all three risk parameters (obese and metabolically unhealthy; n = 31) had a similar adjusted increased risk of mortality [OR 7.42 (95% CI 1.55-27.3)] as older (56-75 years) non-obese and metabolically healthy patients [n = 339; OR 8.21 (95% CI 4.10-18.3)]. Furthermore, increased CRP levels explained part of the elevated risk of COVID-19-related mortality with age, specifically in the absence of obesity and impaired metabolic health. In conclusion, the modifiable risk factors obesity, diabetes and hypertension increase the risk of COVID-19-related mortality in young and middle-aged patients to the level of risk observed in advanced age.
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Affiliation(s)
- Norbert Stefan
- Institute of Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich, Tübingen, Germany.,Department of Internal Medicine IV, University Hospital of Tübingen, Tübingen, Germany.,German Center for Diabetes Research (DZD), Munich, Germany
| | - Katrin Sippel
- Institute of Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich, Tübingen, Germany.,Department of Internal Medicine IV, University Hospital of Tübingen, Tübingen, Germany.,German Center for Diabetes Research (DZD), Munich, Germany
| | - Martin Heni
- Institute of Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich, Tübingen, Germany.,Department of Internal Medicine IV, University Hospital of Tübingen, Tübingen, Germany.,German Center for Diabetes Research (DZD), Munich, Germany
| | - Andreas Fritsche
- Institute of Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich, Tübingen, Germany.,Department of Internal Medicine IV, University Hospital of Tübingen, Tübingen, Germany.,German Center for Diabetes Research (DZD), Munich, Germany
| | - Robert Wagner
- Institute of Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich, Tübingen, Germany.,Department of Internal Medicine IV, University Hospital of Tübingen, Tübingen, Germany.,German Center for Diabetes Research (DZD), Munich, Germany
| | - Carolin E M Jakob
- Department of Internal Medicine I, Faculty of Medicine, University Hospital Cologne, Cologne, University of Cologne, Cologne, Germany.,German Center for Infection Research (DZIF), Partner-Site Bonn-Cologne, Cologne, Germany
| | - Hubert Preißl
- Institute of Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich, Tübingen, Germany.,German Center for Diabetes Research (DZD), Munich, Germany
| | - Alexander von Werder
- German Center for Infection Research (DZIF), Partner-Site Bonn-Cologne, Cologne, Germany.,Department of Internal Medicine II, School of Medicine, University Hospital Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Yascha Khodamoradi
- Department of Internal Medicine, Infectious Diseases, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Stefan Borgmann
- Department of Infectious Diseases and Infection Control, Ingolstadt Hospital, Ingolstadt, Germany
| | | | - Frank Hanses
- Emergency Department, University Hospital Regensburg, Regensburg, Germany
| | | | - Christiane Piepel
- Department of Internal Medicine I, Hospital Bremen-Center, Bremen, Germany
| | - Martin Hower
- Department for Pneumology, Infectiology, Internal Medicine and Intensive Care, gGmbH, Dortmund, Germany
| | - Jürgen Vom Dahl
- Division of Cardiology, Hospital Maria Hilf Mönchengladbach, Mönchengladbach, Germany
| | - Kai Wille
- University Clinic for Hematology, Oncology, Hemostaseology and Palliative Care, University of Bochum, Minden, Germany
| | - Christoph Römmele
- Internal Medicine III - Gastroenterology and Infectious Diseases, University Hospital of Augsburg, Augsburg, Germany
| | - Janne Vehreschild
- German Center for Diabetes Research (DZD), Munich, Germany.,Department of Internal Medicine I, Faculty of Medicine, University Hospital Cologne, Cologne, University of Cologne, Cologne, Germany.,Department of Internal Medicine, Hematology and Oncology, University Hospital Cologne, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Melanie Stecher
- Department of Internal Medicine I, Faculty of Medicine, University Hospital Cologne, Cologne, University of Cologne, Cologne, Germany.,German Center for Infection Research (DZIF), Partner-Site Bonn-Cologne, Cologne, Germany
| | - Michele Solimena
- German Center for Diabetes Research (DZD), Munich, Germany.,Helmholtz Center Munich, Faculty of Medicine, Paul Langerhans Institute Dresden, University Hospital, Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Michael Roden
- German Center for Diabetes Research (DZD), Munich, Germany.,Department of Endocrinology and Diabetology, Medical Faculty and University Hospital, Heinrich-Heine University, Düsseldorf, Germany.,Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich- Heine University, Düsseldorf, Germany
| | - Annette Schürmann
- German Center for Diabetes Research (DZD), Munich, Germany.,Department of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Baptist Gallwitz
- Department of Internal Medicine IV, University Hospital of Tübingen, Tübingen, Germany
| | - Martin Hrabe de Angelis
- German Center for Diabetes Research (DZD), Munich, Germany.,Institute of Experimental Genetics, Helmholtz Zentrum München, Oberschleißheim, Germany.,TUM School of Life Sciences (SoLS), Chair of Experimental Genetics, Technische Universität München, Freising, Germany
| | - David S Ludwig
- New Balance Foundation Obesity Prevention Center, Boston Children's Hospital, Boston, MA, United States.,Department of Pediatrics, Harvard Medical School, Boston, MA, United States.,Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Matthias B Schulze
- German Center for Diabetes Research (DZD), Munich, Germany.,Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Bjoern Erik Ole Jensen
- Department of Gastroenterology, Hepatology and Infectious Diseases, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Andreas L Birkenfeld
- Institute of Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich, Tübingen, Germany.,Department of Internal Medicine IV, University Hospital of Tübingen, Tübingen, Germany.,German Center for Diabetes Research (DZD), Munich, Germany
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18
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Brozat JF, Hanses F, Haelberger M, Stecher M, Dreher M, Tometten L, Ruethrich MM, Vehreschild JJ, Trautwein C, Borgmann S, Vehreschild MJGT, Jakob CEM, Stallmach A, Wille K, Hellwig K, Isberner N, Reuken PA, Geisler F, Nattermann J, Bruns T. COVID-19 mortality in cirrhosis is determined by cirrhosis-associated comorbidities and extrahepatic organ failure: Results from the multinational LEOSS registry. United European Gastroenterol J 2022; 10:409-424. [PMID: 35482663 PMCID: PMC9103364 DOI: 10.1002/ueg2.12232] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 04/11/2022] [Indexed: 02/06/2023] Open
Abstract
Background and Objective International registries have reported high mortality rates in patients with liver disease and COVID‐19. However, the extent to which comorbidities contribute to excess COVID‐19 mortality in cirrhosis is controversial. Methods We used the multinational Lean European Open Survey on SARS‐CoV‐2‐infected patients (LEOSS) to identify patients with cirrhosis documented between March 2020 and March 2021, when the wild‐type and alpha variant were predominant. We compared symptoms, disease progression and mortality after propensity score matching (PSM) for age, sex, obesity, smoking status, and concomitant diseases. Mortality was also compared with that of patients with spontaneous bacterial peritonitis (SBP) without SARS‐CoV‐2 infection, a common bacterial infection and well‐described precipitator of acute‐on‐chronic liver failure. Results Among 7096 patients with SARS‐CoV‐2 infection eligible for analysis, 70 (0.99%) had cirrhosis, and all were hospitalized. Risk factors for severe COVID‐19, such as diabetes, renal disease, and cardiovascular disease were more frequent in patients with cirrhosis. Case fatality rate in patients with cirrhosis was 31.4% with the highest odds of death in patients older than 65 years (43.6% mortality; odds ratio [OR] 4.02; p = 0.018), Child‐Pugh class C (57.1%; OR 4.00; p = 0.026), and failure of two or more organs (81.8%; OR 19.93; p = 0.001). After PSM for demographics and comorbidity, the COVID‐19 case fatality of patients with cirrhosis did not significantly differ from that of matched patients without cirrhosis (28.8% vs. 26.1%; p = 0.644) and was similar to the 28‐day mortality in a comparison group of patients with cirrhosis and SBP (33.3% vs. 31.5%; p = 1.000). Conclusions In immunologically naïve patients with cirrhosis, mortality from wild‐type SARS‐CoV‐2 and the alpha variant is high and is largely determined by cirrhosis‐associated comorbidities and extrahepatic organ failure.
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Affiliation(s)
- Jonathan F Brozat
- Department of Internal Medicine III, University Hospital RWTH Aachen, RWTH Aachen University, Aachen, Germany
| | - Frank Hanses
- Emergency Department, University Hospital Regensburg, Regensburg, Germany.,Department for Infectious Diseases and Infection Control, University Hospital, Regensburg, Germany
| | | | - Melanie Stecher
- Department I of Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,German Centre for Infection Research (DZIF), Partner Site Bonn-Cologne, Cologne, Germany
| | - Michael Dreher
- Department of Pneumology and Intensive Care Medicine, Internal Medicine V, University Hospital RWTH Aachen, RWTH Aachen University, Aachen, Germany
| | - Lukas Tometten
- Department I of Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Clinic for Intensive Care and Emergency Medicine, Hospital Ernst von Bergmann, Potsdam, Germany
| | - Maria M Ruethrich
- Department of Internal Medicine II, Hematology and Medical Oncology, University Hospital Jena, Jena, Germany
| | - Janne J Vehreschild
- Department I of Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,German Centre for Infection Research (DZIF), Partner Site Bonn-Cologne, Cologne, Germany.,Department II of Internal Medicine, Hematology/Oncology, Goethe University, Frankfurt, Frankfurt Am Main, Germany
| | - Christian Trautwein
- Department of Internal Medicine III, University Hospital RWTH Aachen, RWTH Aachen University, Aachen, Germany
| | - Stefan Borgmann
- Department of Infectious Diseases and Infection Control, Ingolstadt Hospital, Ingolstadt, Germany
| | - Maria J G T Vehreschild
- Department of Internal Medicine, Infectious Diseases, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Carolin E M Jakob
- Department I of Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,German Centre for Infection Research (DZIF), Partner Site Bonn-Cologne, Cologne, Germany
| | - Andreas Stallmach
- Department of Internal Medicine IV, Jena University Hospital, Jena, Germany
| | - Kai Wille
- Johannes Wesling Klinikum Minden, Oncology, Haemostaseology and Palliative Care, Johannes Wesling Klinikum, University of Bochum, Minden, Germany
| | - Kerstin Hellwig
- Department of Neurology, St. Josef-Hospital Bochum, Ruhr University Bochum, Bochum, Germany
| | - Nora Isberner
- Department of Internal Medicine II, Infectious Diseases, University Hospital Wuerzburg, Wuerzburg, Germany
| | - Philipp A Reuken
- Department of Internal Medicine IV, Jena University Hospital, Jena, Germany
| | - Fabian Geisler
- Department of Internal Medicine II, School of Medicine, Technical University of Munich, University Hospital Rechts der Isar, Munich, Germany
| | - Jacob Nattermann
- Department of Internal Medicine I, UKB University Hospital Bonn, Bonn, Germany
| | - Tony Bruns
- Department of Internal Medicine III, University Hospital RWTH Aachen, RWTH Aachen University, Aachen, Germany
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19
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Schons MJ, Caliebe A, Spinner CD, Classen AY, Pilgram L, Ruethrich MM, Rupp J, Nunes de Miranda SM, Römmele C, Vehreschild J, Jensen BE, Vehreschild M, Degenhardt C, Borgmann S, Hower M, Hanses F, Haselberger M, Friedrichs AK. All-cause mortality and disease progression in SARS-CoV-2-infected patients with or without antibiotic therapy: an analysis of the LEOSS cohort. Infection 2022; 50:423-436. [PMID: 34625912 PMCID: PMC8500268 DOI: 10.1007/s15010-021-01699-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 09/14/2021] [Indexed: 12/12/2022]
Abstract
PURPOSE Reported antibiotic use in coronavirus disease 2019 (COVID-19) is far higher than the actual rate of reported bacterial co- and superinfection. A better understanding of antibiotic therapy in COVID-19 is necessary. METHODS 6457 SARS-CoV-2-infected cases, documented from March 18, 2020, until February 16, 2021, in the LEOSS cohort were analyzed. As primary endpoint, the correlation between any antibiotic treatment and all-cause mortality/progression to the next more advanced phase of disease was calculated for adult patients in the complicated phase of disease and procalcitonin (PCT) ≤ 0.5 ng/ml. The analysis took the confounders gender, age, and comorbidities into account. RESULTS Three thousand, six hundred twenty-seven cases matched all inclusion criteria for analyses. For the primary endpoint, antibiotic treatment was not correlated with lower all-cause mortality or progression to the next more advanced (critical) phase (n = 996) (both p > 0.05). For the secondary endpoints, patients in the uncomplicated phase (n = 1195), regardless of PCT level, had no lower all-cause mortality and did not progress less to the next more advanced (complicated) phase when treated with antibiotics (p > 0.05). Patients in the complicated phase with PCT > 0.5 ng/ml and antibiotic treatment (n = 286) had a significantly increased all-cause mortality (p = 0.029) but no significantly different probability of progression to the critical phase (p > 0.05). CONCLUSION In this cohort, antibiotics in SARS-CoV-2-infected patients were not associated with positive effects on all-cause mortality or disease progression. Additional studies are needed. Advice of local antibiotic stewardship- (ABS-) teams and local educational campaigns should be sought to improve rational antibiotic use in COVID-19 patients.
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Affiliation(s)
- Maximilian J. Schons
- Department I of Internal Medicine, University Hospital of Cologne, Cologne, Germany
| | - Amke Caliebe
- Institute for Medical Informatics and Statistics, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
- Kiel University, Kiel, Germany
| | - Christoph D. Spinner
- School of Medicine, Department of Internal Medicine II, Technical University of Munich, University Hospital Rechts Der Isar, Munich, Germany
| | - Annika Y. Classen
- Department I of Internal Medicine, University Hospital of Cologne, Cologne, Germany
- German Centre for Infection Research (DZIF), Partner Site Bonn-Cologne, Cologne, Germany
| | - Lisa Pilgram
- Department II of Internal Medicine, Hematology/Oncology, Goethe University, Frankfurt, Frankfurt am Main, Germany
| | - Maria M. Ruethrich
- Institute for Infection Medicine and Hospital Hygiene, University Hospital Jena, Jena, Germany
| | - Jan Rupp
- University Hospital Schleswig-Holstein, Lübeck, Germany
| | | | - Christoph Römmele
- Internal Medicine III – Gastroenterology and Infectious Diseases, University Hospital of Augsburg, Augsburg, Germany
| | - Janne Vehreschild
- Department I of Internal Medicine, University Hospital of Cologne, Cologne, Germany
- German Centre for Infection Research (DZIF), Partner Site Bonn-Cologne, Cologne, Germany
- Department II of Internal Medicine, Hematology/Oncology, Goethe University, Frankfurt, Frankfurt am Main, Germany
| | - Bjoern-Erik Jensen
- Clinic for Gastroenterology, Hepatology and Infectiology, University Hospital Düsseldorf, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
| | - Maria Vehreschild
- Department II of Internal Medicine, Hematology/Oncology, Goethe University, Frankfurt, Frankfurt am Main, Germany
| | | | - Stefan Borgmann
- Department of Infectious Diseases and Infection Control, Ingolstadt Hospital, Ingolstadt, Germany
| | - Martin Hower
- Department of Pneumology, Infectious Diseases and Intensive Care, Klinikum Dortmund gGmbH, Dortmund, Germany
| | - Frank Hanses
- Interdisciplinary Emergency Department, University Hospital Regensburg, Regensburg, Germany
| | | | - Anette K. Friedrichs
- Clinic for Internal Medicine I, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
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20
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Linschoten M, Uijl A, Schut A, Jakob CEM, Romão LR, Bell RM, McFarlane E, Stecher M, Zondag AGM, van Iperen EPA, Hermans-van Ast W, Lea NC, Schaap J, Jewbali LS, Smits PC, Patel RS, Aujayeb A, van der Harst P, Siebelink HJ, van Smeden M, Williams S, Pilgram L, van Gilst WH, Tieleman RG, Williams B, Asselbergs FW, Al-Ali AK, Al-Muhanna FA, Al-Rubaish AM, Al-Windy NYY, Alkhalil M, Almubarak YA, Alnafie AN, Alshahrani M, Alshehri AM, Anning C, Anthonio RL, Badings EA, Ball C, van Beek EA, ten Berg JM, von Bergwelt-Baildon M, Bianco M, Blagova OV, Bleijendaal H, Bor WL, Borgmann S, van Boxem AJM, van den Brink FS, Bucciarelli-Ducci C, van Bussel BCT, Byrom-Goulthorp R, Captur G, Caputo M, Charlotte N, vom Dahl J, Dark P, De Sutter J, Degenhardt C, Delsing CE, Dolff S, Dorman HGR, Drost JT, Eberwein L, Emans ME, Er AG, Ferreira JB, Forner MJ, Friedrichs A, Gabriel L, Groenemeijer BE, Groenendijk AL, Grüner B, Guggemos W, Haerkens-Arends HE, Hanses F, Hedayat B, Heigener D, van der Heijden DJ, Hellou E, Hellwig K, Henkens MTHM, Hermanides RS, Hermans WRM, van Hessen MWJ, Heymans SRB, Hilt AD, van der Horst ICC, Hower M, van Ierssel SH, Isberner N, Jensen B, Kearney MT, van Kesteren HAM, Kielstein JT, Kietselaer BLJH, Kochanek M, Kolk MZH, Koning AMH, Kopylov PY, Kuijper AFM, Kwakkel-van Erp JM, Lanznaster J, van der Linden MMJM, van der Lingen ACJ, Linssen GCM, Lomas D, Maarse M, Macías Ruiz R, Magdelijns FJH, Magro M, Markart P, Martens FMAC, Mazzilli SG, McCann GP, van der Meer P, Meijs MFL, Merle U, Messiaen P, Milovanovic M, Monraats PS, Montagna L, Moriarty A, Moss AJ, Mosterd A, Nadalin S, Nattermann J, Neufang M, Nierop PR, Offerhaus JA, van Ofwegen-Hanekamp CEE, Parker E, Persoon AM, Piepel C, Pinto YM, Poorhosseini H, Prasad S, Raafs AG, Raichle C, Rauschning D, Redón J, Reidinga AC, Ribeiro MIA, Riedel C, Rieg S, Ripley DP, Römmele C, Rothfuss K, Rüddel J, Rüthrich MM, Salah R, Saneei E, Saxena M, Schellings DAAM, Scholte NTB, Schubert J, Seelig J, Shafiee A, Shore AC, Spinner C, Stieglitz S, Strauss R, Sturkenboom NH, Tessitore E, Thomson RJ, Timmermans P, Tio RA, Tjong FVY, Tometten L, Trauth J, den Uil CA, Van Craenenbroeck EM, van Veen HPAA, Vehreschild MJGT, Veldhuis LI, Veneman T, Verschure DO, Voigt I, de Vries JK, van de Wal RMA, Walter L, van de Watering DJ, Westendorp ICD, Westendorp PHM, Westhoff T, Weytjens C, Wierda E, Wille K, de With K, Worm M, Woudstra P, Wu KW, Zaal R, Zaman AG, van der Zee PM, Zijlstra LE, Alling TE, Ahmed R, van Aken K, Bayraktar-Verver ECE, Bermúdez Jiménes FJ, Biolé CA, den Boer-Penning P, Bontje M, Bos M, Bosch L, Broekman M, Broeyer FJF, de Bruijn EAW, Bruinsma S, Cardoso NM, Cosyns B, van Dalen DH, Dekimpe E, Domange J, van Doorn JL, van Doorn P, Dormal F, Drost IMJ, Dunnink A, van Eck JWM, Elshinawy K, Gevers RMM, Gognieva DG, van der Graaf M, Grangeon S, Guclu A, Habib A, Haenen NA, Hamilton K, Handgraaf S, Heidbuchel H, Hendriks-van Woerden M, Hessels-Linnemeijer BM, Hosseini K, Huisman J, Jacobs TC, Jansen SE, Janssen A, Jourdan K, ten Kate GL, van Kempen MJ, Kievit CM, Kleikers P, Knufman N, van der Kooi SE, Koole BAS, Koole MAC, Kui KK, Kuipers-Elferink L, Lemoine I, Lensink E, van Marrewijk V, van Meerbeeck JP, Meijer EJ, Melein AJ, Mesitskaya DF, van Nes CPM, Paris FMA, Perrelli MG, Pieterse-Rots A, Pisters R, Pölkerman BC, van Poppel A, Reinders S, Reitsma MJ, Ruiter AH, Selder JL, van der Sluis A, Sousa AIC, Tajdini M, Tercedor Sánchez L, Van De Heyning CM, Vial H, Vlieghe E, Vonkeman HE, Vreugdenhil P, de Vries TAC, Willems AM, Wils AM, Zoet-Nugteren SK. Clinical presentation, disease course, and outcome of COVID-19 in hospitalized patients with and without pre-existing cardiac disease: a cohort study across 18 countries. Eur Heart J 2022; 43:1104-1120. [PMID: 34734634 DOI: 10.1093/eurheartj/ehab656] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 06/22/2021] [Accepted: 09/01/2021] [Indexed: 12/25/2022] Open
Abstract
AIMS Patients with cardiac disease are considered high risk for poor outcomes following hospitalization with COVID-19. The primary aim of this study was to evaluate heterogeneity in associations between various heart disease subtypes and in-hospital mortality. METHODS AND RESULTS We used data from the CAPACITY-COVID registry and LEOSS study. Multivariable Poisson regression models were fitted to assess the association between different types of pre-existing heart disease and in-hospital mortality. A total of 16 511 patients with COVID-19 were included (21.1% aged 66-75 years; 40.2% female) and 31.5% had a history of heart disease. Patients with heart disease were older, predominantly male, and often had other comorbid conditions when compared with those without. Mortality was higher in patients with cardiac disease (29.7%; n = 1545 vs. 15.9%; n = 1797). However, following multivariable adjustment, this difference was not significant [adjusted risk ratio (aRR) 1.08, 95% confidence interval (CI) 1.02-1.15; P = 0.12 (corrected for multiple testing)]. Associations with in-hospital mortality by heart disease subtypes differed considerably, with the strongest association for heart failure (aRR 1.19, 95% CI 1.10-1.30; P < 0.018) particularly for severe (New York Heart Association class III/IV) heart failure (aRR 1.41, 95% CI 1.20-1.64; P < 0.018). None of the other heart disease subtypes, including ischaemic heart disease, remained significant after multivariable adjustment. Serious cardiac complications were diagnosed in <1% of patients. CONCLUSION Considerable heterogeneity exists in the strength of association between heart disease subtypes and in-hospital mortality. Of all patients with heart disease, those with heart failure are at greatest risk of death when hospitalized with COVID-19. Serious cardiac complications are rare during hospitalization.
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Linden T, Hanses F, Domingo-Fernández D, DeLong LN, Kodamullil AT, Schneider J, Vehreschild MJGT, Lanznaster J, Ruethrich MM, Borgmann S, Hower M, Wille K, Feldt T, Rieg S, Hertenstein B, Wyen C, Roemmele C, Vehreschild JJ, Jakob CEM, Stecher M, Kuzikov M, Zaliani A, Fröhlich H. Machine Learning Based Prediction of COVID-19 Mortality Suggests Repositioning of Anticancer Drug for Treating Severe Cases. ARTIFICIAL INTELLIGENCE IN THE LIFE SCIENCES 2021; 1:100020. [PMID: 34988543 PMCID: PMC8677630 DOI: 10.1016/j.ailsci.2021.100020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 11/22/2021] [Accepted: 11/22/2021] [Indexed: 02/08/2023]
Abstract
Despite available vaccinations COVID-19 case numbers around the world are still growing, and effective medications against severe cases are lacking. In this work, we developed a machine learning model which predicts mortality for COVID-19 patients using data from the multi-center 'Lean European Open Survey on SARS-CoV-2-infected patients' (LEOSS) observational study (>100 active sites in Europe, primarily in Germany), resulting into an AUC of almost 80%. We showed that molecular mechanisms related to dementia, one of the relevant predictors in our model, intersect with those associated to COVID-19. Most notably, among these molecules was tyrosine kinase 2 (TYK2), a protein that has been patented as drug target in Alzheimer's Disease but also genetically associated with severe COVID-19 outcomes. We experimentally verified that anti-cancer drugs Sorafenib and Regorafenib showed a clear anti-cytopathic effect in Caco2 and VERO-E6 cells and can thus be regarded as potential treatments against COVID-19. Altogether, our work demonstrates that interpretation of machine learning based risk models can point towards drug targets and new treatment options, which are strongly needed for COVID-19.
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Affiliation(s)
- Thomas Linden
- Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Schloss Birlinghoven, 53757 Sankt Augustin, Germany
- University of Bonn, Bonn-Aachen International Center for IT, Friedrich Hirzebruch-Allee 6, 53115 Bonn, Germany
| | - Frank Hanses
- Emergency Department, University Hospital Regensburg, 93053 Regensburg, Germany
- Department for Infectious Diseases and Infection Control, University Hospital Regensburg, Germany
| | - Daniel Domingo-Fernández
- Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Schloss Birlinghoven, 53757 Sankt Augustin, Germany
| | - Lauren Nicole DeLong
- Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Schloss Birlinghoven, 53757 Sankt Augustin, Germany
- University of Bonn, Bonn-Aachen International Center for IT, Friedrich Hirzebruch-Allee 6, 53115 Bonn, Germany
| | - Alpha Tom Kodamullil
- Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Schloss Birlinghoven, 53757 Sankt Augustin, Germany
| | - Jochen Schneider
- Technical University of Munich, School of Medicine, University Hospital rechts der Isar, Department of Internal Medicine II, 81675 Munich, Germany
| | - Maria J G T Vehreschild
- Department II of Internal Medicine, Infectious Diseases, University Hospital Frankfurt, Goethe University, 60590 Frankfurt, Germany
| | - Julia Lanznaster
- Department of Internal Medicine II, Hospital Passau, Innstraße 76, 94032 Passau, Germany
| | - Maria Madeleine Ruethrich
- Institute for Infection Medicine and Hospital Hygiene, University Hospital Jena, 07743 Jena, Germany
| | - Stefan Borgmann
- Department of Infectious Diseases and Infection Control, Hospital Ingolstadt, 85049 Ingolstadt, Germany
| | - Martin Hower
- Department of Pneumology, Infectious Diseases and Intensive Care, Klinikum Dortmund gGmbH, Hospital of University Witten / Herdecke, 44137 Dortmund, Germany
| | - Kai Wille
- University Clinic for Haematology, Oncology, Haemostaseology and Palliative Care, Johannes Wesling Medical Centre Minden, 32429 Minden, Germany
| | - Torsten Feldt
- Department of Gastroenterology, Hepatology and Infectious Diseases, University Hospital Düsseldorf, Medical Faculty of Heinrich Heine University Düsseldorf, Moorenstrasse 5, 40225 Düsseldorf, Germany
| | - Siegbert Rieg
- Department of Medicine II, University Hospital Freiburg, 79110 Freiburg, Germany
| | - Bernd Hertenstein
- Department of Medicine II, University Hospital Freiburg, 79110 Freiburg, Germany
| | - Christoph Wyen
- Christoph Wyen, Praxis am Ebertplatz Cologne, 50668 Cologne, Germany
| | - Christoph Roemmele
- Internal Medicine III - Gastroenterology and Infectious Diseases, University Hospital Augsburg, 86156 Augsburg, Germany
| | - Jörg Janne Vehreschild
- Department II of Internal Medicine, Infectious Diseases, University Hospital Frankfurt, Goethe University, 60590 Frankfurt, Germany
| | - Carolin E M Jakob
- Department I for Internal Medicine, University Hospital of Cologne, University of Cologne, 50931 Cologne, Germany
| | - Melanie Stecher
- Fraunhofer Institute for Translational Medicine and Pharmacologie (ITMP), VolksparkLabs, Schnackenburgallee 114, 22535 Hamburg, Germany
| | - Maria Kuzikov
- Department for Infectious Diseases and Infection Control, University Hospital Regensburg, Germany
| | - Andrea Zaliani
- Department for Infectious Diseases and Infection Control, University Hospital Regensburg, Germany
| | - Holger Fröhlich
- Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Schloss Birlinghoven, 53757 Sankt Augustin, Germany
- University of Bonn, Bonn-Aachen International Center for IT, Friedrich Hirzebruch-Allee 6, 53115 Bonn, Germany
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22
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Pilgram L, Schons M, Jakob CEM, Claßen AY, Franke B, Tscharntke L, Schulze N, Fuhrmann S, Sauer G, de Miranda SMN, Prasser F, Stecher M, Vehreschild JJ. [The COVID-19 Pandemic as an Opportunity and Challenge for Registries in Health Services Research: Lessons Learned from the Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS)]. DAS GESUNDHEITSWESEN 2021; 83:S45-S53. [PMID: 34731893 DOI: 10.1055/a-1655-8705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
OBJECTIVE The Coronavirus Disease-2019 (COVID-19) pandemic has brought opportunities and challenges, especially for health services research based on routine data. In this article we will demonstrate this by presenting lessons learned from establishing the currently largest registry in Germany providing a detailed clinical dataset on Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infected patients: the Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS). METHODS LEOSS is based on a collaborative and integrative research approach with anonymous recruitment and collection of routine data and the early provision of data in an open science context. The only requirement for inclusion was a SARS-CoV-2 infection confirmed by virological diagnosis. Crucial strategies to successfully realize the project included the dynamic reallocation of available staff and technical resources, an early and direct involvement of data protection experts and the ethics committee as well as the decision for an iterative and dynamic process of improvement and further development. RESULTS Thanks to the commitment of numerous institutions, a transsectoral and transnational network of currently 133 actively recruiting sites with 7,227 documented cases could be established (status: 18.03.2021). Tools for data exploration on the project website, as well as the partially automated provision of datasets according to use cases with varying requirements, enabled us to utilize the data collected within a short period of time. Data use and access processes were carried out for 97 proposals assigned to 27 different research areas. So far, nine articles have been published in peer-reviewed international journals. CONCLUSION As a collaborative effort of the whole network, LEOSS developed into a large collection of clinical data on COVID-19 in Germany. Even though in other international projects, much larger data sets could be analysed to investigate specific research questions through direct access to source systems, the uniformly maintained and technically verified documentation standard with many discipline-specific details resulted in a large valuable data set with unique characteristics. The lessons learned while establishing LEOSS during the current pandemic have already created important implications for the design of future registries and for pandemic preparedness and response.
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Affiliation(s)
- Lisa Pilgram
- Hämatologie, Onkologie, Hämostaseologie, Rheumatologie, Infektiologie, Universitätsklinikum Frankfurt Zentrum der Inneren Medizin, Frankfurt am Main, Deutschland
| | - Maximilian Schons
- Onkologie, Hämatologie, Klinische Infektiologie, Klinische Immunologie, Hämostaseologie, Internistische Intensivmedizin, Uniklinik Köln Klinik I für Innere Medizin, Köln, Deutschland
| | - Carolin E M Jakob
- Onkologie, Hämatologie, Klinische Infektiologie, Klinische Immunologie, Hämostaseologie, Internistische Intensivmedizin, Uniklinik Köln Klinik I für Innere Medizin, Köln, Deutschland.,Standort Köln-Bonn, Deutsches Zentrum für Infektionsforschung (DZIF), Köln, Deutschland
| | - Annika Y Claßen
- Onkologie, Hämatologie, Klinische Infektiologie, Klinische Immunologie, Hämostaseologie, Internistische Intensivmedizin, Uniklinik Köln Klinik I für Innere Medizin, Köln, Deutschland.,Standort Köln-Bonn, Deutsches Zentrum für Infektionsforschung (DZIF), Köln, Deutschland
| | - Bernd Franke
- Onkologie, Hämatologie, Klinische Infektiologie, Klinische Immunologie, Hämostaseologie, Internistische Intensivmedizin, Uniklinik Köln Klinik I für Innere Medizin, Köln, Deutschland.,Standort Köln-Bonn, Deutsches Zentrum für Infektionsforschung (DZIF), Köln, Deutschland
| | - Lene Tscharntke
- Onkologie, Hämatologie, Klinische Infektiologie, Klinische Immunologie, Hämostaseologie, Internistische Intensivmedizin, Uniklinik Köln Klinik I für Innere Medizin, Köln, Deutschland
| | - Nick Schulze
- Onkologie, Hämatologie, Klinische Infektiologie, Klinische Immunologie, Hämostaseologie, Internistische Intensivmedizin, Uniklinik Köln Klinik I für Innere Medizin, Köln, Deutschland.,Standort Köln-Bonn, Deutsches Zentrum für Infektionsforschung (DZIF), Köln, Deutschland
| | - Sandra Fuhrmann
- Onkologie, Hämatologie, Klinische Infektiologie, Klinische Immunologie, Hämostaseologie, Internistische Intensivmedizin, Uniklinik Köln Klinik I für Innere Medizin, Köln, Deutschland
| | - Gabriel Sauer
- Onkologie, Hämatologie, Klinische Infektiologie, Klinische Immunologie, Hämostaseologie, Internistische Intensivmedizin, Uniklinik Köln Klinik I für Innere Medizin, Köln, Deutschland
| | - Susana M Nunes de Miranda
- Onkologie, Hämatologie, Klinische Infektiologie, Klinische Immunologie, Hämostaseologie, Internistische Intensivmedizin, Uniklinik Köln Klinik I für Innere Medizin, Köln, Deutschland
| | - Fabian Prasser
- Charité Universitätsmedizin Berlin, Berlin Institute of Health, Berlin, Deutschland.,Corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charité Universitätsmedizin Berlin, Berlin, Deutschland
| | - Melanie Stecher
- Onkologie, Hämatologie, Klinische Infektiologie, Klinische Immunologie, Hämostaseologie, Internistische Intensivmedizin, Uniklinik Köln Klinik I für Innere Medizin, Köln, Deutschland.,Standort Köln-Bonn, Deutsches Zentrum für Infektionsforschung (DZIF), Köln, Deutschland
| | - Jörg J Vehreschild
- Hämatologie, Onkologie, Hämostaseologie, Rheumatologie, Infektiologie, Universitätsklinikum Frankfurt Zentrum der Inneren Medizin, Frankfurt am Main, Deutschland.,Onkologie, Hämatologie, Klinische Infektiologie, Klinische Immunologie, Hämostaseologie, Internistische Intensivmedizin, Uniklinik Köln Klinik I für Innere Medizin, Köln, Deutschland.,Standort Köln-Bonn, Deutsches Zentrum für Infektionsforschung (DZIF), Köln, Deutschland
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23
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Cremer S, Pilgram L, Berkowitsch A, Stecher M, Rieg S, Shumliakivska M, Bojkova D, Wagner JUG, Aslan GS, Spinner C, Luxán G, Hanses F, Dolff S, Piepel C, Ruppert C, Guenther A, Rüthrich MM, Vehreschild JJ, Wille K, Haselberger M, Heuzeroth H, Hansen A, Eschenhagen T, Cinatl J, Ciesek S, Dimmeler S, Borgmann S, Zeiher A. Angiotensin II receptor blocker intake associates with reduced markers of inflammatory activation and decreased mortality in patients with cardiovascular comorbidities and COVID-19 disease. PLoS One 2021; 16:e0258684. [PMID: 34673795 PMCID: PMC8530317 DOI: 10.1371/journal.pone.0258684] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 10/01/2021] [Indexed: 12/15/2022] Open
Abstract
AIMS Patients with cardiovascular comorbidities have a significantly increased risk for a critical course of COVID-19. As the SARS-CoV2 virus enters cells via the angiotensin-converting enzyme receptor II (ACE2), drugs which interact with the renin angiotensin aldosterone system (RAAS) were suspected to influence disease severity. METHODS AND RESULTS We analyzed 1946 consecutive patients with cardiovascular comorbidities or hypertension enrolled in one of the largest European COVID-19 registries, the Lean European Open Survey on SARS-CoV-2 (LEOSS) registry. Here, we show that angiotensin II receptor blocker intake is associated with decreased mortality in patients with COVID-19 [OR 0.75 (95% CI 0,59-0.96; p = 0.013)]. This effect was mainly driven by patients, who presented in an early phase of COVID-19 at baseline [OR 0,64 (95% CI 0,43-0,96; p = 0.029)]. Kaplan-Meier analysis revealed a significantly lower incidence of death in patients on an angiotensin receptor blocker (ARB) (n = 33/318;10,4%) compared to patients using an angiotensin-converting enzyme inhibitor (ACEi) (n = 60/348;17,2%) or patients who received neither an ACE-inhibitor nor an ARB at baseline in the uncomplicated phase (n = 90/466; 19,3%; p<0.034). Patients taking an ARB were significantly less frequently reaching the mortality predicting threshold for leukocytes (p<0.001), neutrophils (p = 0.002) and the inflammatory markers CRP (p = 0.021), procalcitonin (p = 0.001) and IL-6 (p = 0.049). ACE2 expression levels in human lung samples were not altered in patients taking RAAS modulators. CONCLUSION These data suggest a beneficial effect of ARBs on disease severity in patients with cardiovascular comorbidities and COVID-19, which is linked to dampened systemic inflammatory activity.
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Affiliation(s)
- Sebastian Cremer
- Department of Medicine, Cardiology, Goethe University Hospital, Frankfurt, Germany
- German Center for Cardiovascular Research DZHK, Partner Site Rhine-Main, Berlin, Germany
- Cardiopulmonary Institute, Goethe University Frankfurt, Frankfurt, Germany
| | - Lisa Pilgram
- Department of Internal Medicine, Hematology/Oncology, Goethe University Frankfurt, Frankfurt am Main, Germany
| | | | - Melanie Stecher
- Department I for Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Siegbert Rieg
- Internal Medicine II, Department of Infectious Diseases, Freiburg University Hospital, Freiburg, Germany
| | - Mariana Shumliakivska
- Institute for Cardiovascular Regeneration, Goethe University Frankfurt, Frankfurt, Germany
| | - Denisa Bojkova
- Institute of Medical Virology, University of Frankfurt, Frankfurt, Germany
| | | | - Galip Servet Aslan
- Institute for Cardiovascular Regeneration, Goethe University Frankfurt, Frankfurt, Germany
| | - Christoph Spinner
- Department of Internal Medicine II, Technical University of Munich, Hospital rechts der Isar, Munich, Germany
| | - Guillermo Luxán
- German Center for Cardiovascular Research DZHK, Partner Site Rhine-Main, Berlin, Germany
- Institute for Cardiovascular Regeneration, Goethe University Frankfurt, Frankfurt, Germany
| | - Frank Hanses
- University Hospital Regensburg, Regensburg, Germany
| | - Sebastian Dolff
- Department of Infectious Diseases, University Hospital Essen, Essen, Germany
| | - Christiane Piepel
- Department of Internal Medicine I, Hospital Bremen-Mitte, Bremen, Germany
| | - Clemens Ruppert
- Department of Internal Medicine II, Giessen University, Giessen, Germany
| | - Andreas Guenther
- Department of Internal Medicine II, Giessen University, Giessen, Germany
| | | | - Jörg Janne Vehreschild
- Department I for Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Kai Wille
- University Clinic for Hematology, Oncology, Hemostaseology and Palliative Care, University of Bochum, Minden, Germany
| | | | - Hanno Heuzeroth
- Department of Emergency and Intensive Care Medicine, Klinikum Ernst von Bergmann, Potsdam, Germany
| | - Arne Hansen
- Department of Experimental Pharmacology and Toxicology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Thomas Eschenhagen
- Department of Experimental Pharmacology and Toxicology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jindrich Cinatl
- Institute of Medical Virology, University of Frankfurt, Frankfurt, Germany
| | - Sandra Ciesek
- Institute of Medical Virology, University of Frankfurt, Frankfurt, Germany
| | - Stefanie Dimmeler
- German Center for Cardiovascular Research DZHK, Partner Site Rhine-Main, Berlin, Germany
- Cardiopulmonary Institute, Goethe University Frankfurt, Frankfurt, Germany
- Institute for Cardiovascular Regeneration, Goethe University Frankfurt, Frankfurt, Germany
| | - Stefan Borgmann
- Department of Infectious Diseases and Infection Control, Ingolstadt Hospital, Ingolstadt, Germany
| | - Andreas Zeiher
- Department of Medicine, Cardiology, Goethe University Hospital, Frankfurt, Germany
- German Center for Cardiovascular Research DZHK, Partner Site Rhine-Main, Berlin, Germany
- Cardiopulmonary Institute, Goethe University Frankfurt, Frankfurt, Germany
- * E-mail:
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Specific Risk Factors for Fatal Outcome in Critically Ill COVID-19 Patients: Results from a European Multicenter Study. J Clin Med 2021; 10:jcm10173855. [PMID: 34501301 PMCID: PMC8432209 DOI: 10.3390/jcm10173855] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2021] [Revised: 08/23/2021] [Accepted: 08/25/2021] [Indexed: 02/07/2023] Open
Abstract
(1) Background: The aim of our study was to identify specific risk factors for fatal outcome in critically ill COVID-19 patients. (2) Methods: Our data set consisted of 840 patients enclosed in the LEOSS registry. Using lasso regression for variable selection, a multifactorial logistic regression model was fitted to the response variable survival. Specific risk factors and their odds ratios were derived. A nomogram was developed as a graphical representation of the model. (3) Results: 14 variables were identified as independent factors contributing to the risk of death for critically ill COVID-19 patients: age (OR 1.08, CI 1.06–1.10), cardiovascular disease (OR 1.64, CI 1.06–2.55), pulmonary disease (OR 1.87, CI 1.16–3.03), baseline Statin treatment (0.54, CI 0.33–0.87), oxygen saturation (unit = 1%, OR 0.94, CI 0.92–0.96), leukocytes (unit 1000/μL, OR 1.04, CI 1.01–1.07), lymphocytes (unit 100/μL, OR 0.96, CI 0.94–0.99), platelets (unit 100,000/μL, OR 0.70, CI 0.62–0.80), procalcitonin (unit ng/mL, OR 1.11, CI 1.05–1.18), kidney failure (OR 1.68, CI 1.05–2.70), congestive heart failure (OR 2.62, CI 1.11–6.21), severe liver failure (OR 4.93, CI 1.94–12.52), and a quick SOFA score of 3 (OR 1.78, CI 1.14–2.78). The nomogram graphically displays the importance of these 14 factors for mortality. (4) Conclusions: There are risk factors that are specific to the subpopulation of critically ill COVID-19 patients.
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25
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Kleineberg NN, Knauss S, Gülke E, Pinnschmidt HO, Jakob CEM, Lingor P, Hellwig K, Berthele A, Höglinger G, Fink GR, Endres M, Gerloff C, Klein C, Stecher M, Classen AY, Rieg S, Borgmann S, Hanses F, Rüthrich MM, Hower M, Tometten L, Haselberger M, Piepel C, Merle U, Dolff S, Degenhardt C, Jensen BEO, Vehreschild MJGT, Erber J, Franke C, Warnke C. Neurological symptoms and complications in predominantly hospitalized COVID-19 patients: Results of the European multinational Lean European Open Survey on SARS-Infected Patients (LEOSS). Eur J Neurol 2021; 28:3925-3937. [PMID: 34411383 PMCID: PMC8444823 DOI: 10.1111/ene.15072] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 08/07/2021] [Indexed: 12/30/2022]
Abstract
Background and purpose During acute coronavirus disease 2019 (COVID‐19) infection, neurological signs, symptoms and complications occur. We aimed to assess their clinical relevance by evaluating real‐world data from a multinational registry. Methods We analyzed COVID‐19 patients from 127 centers, diagnosed between January 2020 and February 2021, and registered in the European multinational LEOSS (Lean European Open Survey on SARS‐Infected Patients) registry. The effects of prior neurological diseases and the effect of neurological symptoms on outcome were studied using multivariate logistic regression. Results A total of 6537 COVID‐19 patients (97.7% PCR‐confirmed) were analyzed, of whom 92.1% were hospitalized and 14.7% died. Commonly, excessive tiredness (28.0%), headache (18.5%), nausea/emesis (16.6%), muscular weakness (17.0%), impaired sense of smell (9.0%) and taste (12.8%), and delirium (6.7%) were reported. In patients with a complicated or critical disease course (53%) the most frequent neurological complications were ischemic stroke (1.0%) and intracerebral bleeding (ICB; 2.2%). ICB peaked in the critical disease phase (5%) and was associated with the administration of anticoagulation and extracorporeal membrane oxygenation (ECMO). Excessive tiredness (odds ratio [OR] 1.42, 95% confidence interval [CI] 1.20–1.68) and prior neurodegenerative diseases (OR 1.32, 95% CI 1.07–1.63) were associated with an increased risk of an unfavorable outcome. Prior cerebrovascular and neuroimmunological diseases were not associated with an unfavorable short‐term outcome of COVID‐19. Conclusion Our data on mostly hospitalized COVID‐19 patients show that excessive tiredness or prior neurodegenerative disease at first presentation increase the risk of an unfavorable short‐term outcome. ICB in critical COVID‐19 was associated with therapeutic interventions, such as anticoagulation and ECMO, and thus may be an indirect complication of a life‐threatening systemic viral infection.
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Affiliation(s)
- Nina N Kleineberg
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre Jülich, Jülich, Germany
| | - Samuel Knauss
- Department of Neurology with Experimental Neurology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany.,DZHK (German Centre for Cardiovascular Research), Partner Site, Berlin, Germany
| | - Eileen Gülke
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Hans O Pinnschmidt
- Institute of Medical Biometry, Epidemiology University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
| | - Carolin E M Jakob
- Department I for Internal Medicine, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany.,German Center for Infection Research (DZIF), Partner-Site Cologne-Bonn, Cologne, Germany
| | - Paul Lingor
- Department of Neurology, Technical University of Munich, School of Medicine, Klinikum Rechts der Isar, Munich, Germany
| | - Kerstin Hellwig
- Department of Neurology, Katholisches Klinikum Bochum, Klinikum der Ruhr Universität, Bochum, Germany
| | - Achim Berthele
- Department of Neurology, Technical University of Munich, School of Medicine, Klinikum Rechts der Isar, Munich, Germany
| | - Günter Höglinger
- Department of Neurology with Clinical Neurophysiology, Hannover Medical School, Hannover, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Gereon R Fink
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre Jülich, Jülich, Germany
| | - Matthias Endres
- Department of Neurology with Experimental Neurology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany.,Center for Stroke Research Berlin, Berlin, Germany.,ExcellenceCluster NeuroCure, Berlin, Germany.,German Center for Neurodegenerative Diseases (DZNE), Partner Site Berlin, Berlin, Germany.,German Centre for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
| | - Christian Gerloff
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Christine Klein
- Institute of Neurogenetics, University of Luebeck and University Hospital Schleswig-Holstein, Campus Luebeck, Luebeck, Germany
| | - Melanie Stecher
- Department I for Internal Medicine, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany.,German Center for Infection Research (DZIF), Partner-Site Cologne-Bonn, Cologne, Germany
| | - Annika Y Classen
- Department I for Internal Medicine, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany.,German Center for Infection Research (DZIF), Partner-Site Cologne-Bonn, Cologne, Germany
| | - Siegbert Rieg
- Division of Infectious Diseases, Department of Medicine II, Medical Centre, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Stefan Borgmann
- Department of Infectious Diseases and Infection Control, Ingolstadt Hospital, Ingolstadt, Germany
| | - Frank Hanses
- Emergency Department, University Hospital Regensburg, Regensburg, Germany.,Department of Infectious Diseases and Infection Control, University Hospital Regensburg, Regensburg, Germany
| | - Maria M Rüthrich
- Department of Internal Medicine II, Hematology and Medical Oncology, University Hospital Jena, Jena, Germany.,Leibniz Institute for Natural Product Research and Infection Biology, Hans-Knöll Institute, Jena, Germany
| | - Martin Hower
- Department of Internal Medicine, Klinikum Dortmund, Dortmund, Germany
| | - Lukas Tometten
- Department I for Internal Medicine, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
| | | | - Christiane Piepel
- Department of Internal Medicine I, Hospital Bremen Central, Bremen, Germany
| | - Uta Merle
- Department of Internal Medicine IV, University Hospital Heidelberg, Heidelberg, Germany
| | - Sebastian Dolff
- Department of Infectious Diseases, West German Centre of Infectious Diseases, University Hospital Essen, University Duisburg-Essen, Essen, Germany
| | | | - Björn-Erik O Jensen
- Department of Gastroenterology, Hepatology and Infectious Diseases, University Hospital Düsseldorf, Düsseldorf, Germany
| | - Maria J G T Vehreschild
- Department of Internal Medicine, Infectious Diseases, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Johanna Erber
- Department of Internal Medicine II, Technical University of Munich, School of Medicine, University Hospital Rechts der Isar, Munich, Germany
| | - Christiana Franke
- Department of Neurology with Experimental Neurology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
| | - Clemens Warnke
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
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26
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Werfel S, Jakob CEM, Borgmann S, Schneider J, Spinner C, Schons M, Hower M, Wille K, Haselberger M, Heuzeroth H, Rüthrich MM, Dolff S, Kessel J, Heemann U, Vehreschild JJ, Rieg S, Schmaderer C. Development and validation of a simplified risk score for the prediction of critical COVID-19 illness in newly diagnosed patients. J Med Virol 2021; 93:6703-6713. [PMID: 34331717 PMCID: PMC8426905 DOI: 10.1002/jmv.27252] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 05/13/2021] [Accepted: 07/29/2021] [Indexed: 11/10/2022]
Abstract
Scores to identify patients at high risk of progression of coronavirus disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), may become instrumental for clinical decision-making and patient management. We used patient data from the multicentre Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS) and applied variable selection to develop a simplified scoring system to identify patients at increased risk of critical illness or death. A total of 1946 patients who tested positive for SARS-CoV-2 were included in the initial analysis and assigned to derivation and validation cohorts (n = 1297 and n = 649, respectively). Stability selection from over 100 baseline predictors for the combined endpoint of progression to the critical phase or COVID-19-related death enabled the development of a simplified score consisting of five predictors: C-reactive protein (CRP), age, clinical disease phase (uncomplicated vs. complicated), serum urea, and D-dimer (abbreviated as CAPS-D score). This score yielded an area under the curve (AUC) of 0.81 (95% confidence interval [CI]: 0.77-0.85) in the validation cohort for predicting the combined endpoint within 7 days of diagnosis and 0.81 (95% CI: 0.77-0.85) during full follow-up. We used an additional prospective cohort of 682 patients, diagnosed largely after the "first wave" of the pandemic to validate the predictive accuracy of the score and observed similar results (AUC for the event within 7 days: 0.83 [95% CI: 0.78-0.87]; for full follow-up: 0.82 [95% CI: 0.78-0.86]). An easily applicable score to calculate the risk of COVID-19 progression to critical illness or death was thus established and validated.
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Affiliation(s)
- Stanislas Werfel
- Department of Nephrology, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich, Germany
| | - Carolin E M Jakob
- Department I for Internal Medicine, University Hospital of Cologne, University of Cologne, Cologne, Germany.,German Centre for Infection Research (DZIF), Partner Site Bonn-Cologne, Cologne, Germany
| | - Stefan Borgmann
- Department of Infectious Diseases and Infection Control, Ingolstadt Hospital, Ingolstadt, Germany
| | - Jochen Schneider
- Department of Internal Medicine II, School of Medicine, Technical University of Munich, University Hospital rechts der Isar, Munich, Germany.,German Centre for Infection Research (DZIF), Partner Site Munich, Munich, Germany
| | - Christoph Spinner
- Department of Internal Medicine II, School of Medicine, Technical University of Munich, University Hospital rechts der Isar, Munich, Germany.,German Centre for Infection Research (DZIF), Partner Site Munich, Munich, Germany
| | - Maximilian Schons
- Department I for Internal Medicine, University Hospital of Cologne, University of Cologne, Cologne, Germany
| | - Martin Hower
- Department of Pneumology, Infectious Diseases and Internal Medicine, Klinikum Dortmund gGmbH, Dortmund, Germany
| | - Kai Wille
- University Clinic for Haematology, Oncology, Haemostaseology and Palliative Care, Johannes Wesling Medical Centre Minden UKRUB, University of Bochum, Minden, Germany
| | | | - Hanno Heuzeroth
- Department of Emergency and Intensive Care Medicine, Klinikum Ernst von Bergmann, Potsdam, Germany
| | - Maria M Rüthrich
- Department of Internal Medicine II, Hematology and Medical Oncology, University Hospital Jena, Jena, Germany
| | - Sebastian Dolff
- Department of Infectious Diseases, University Hospital Essen, University Duisburg-Essen, Essen, Germany
| | - Johanna Kessel
- Department of Internal Medicine, Hematology and Oncology, Goethe University Frankfurt, Frankfurt, Germany
| | - Uwe Heemann
- Department of Nephrology, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich, Germany
| | - Jörg J Vehreschild
- Department I for Internal Medicine, University Hospital of Cologne, University of Cologne, Cologne, Germany.,German Centre for Infection Research (DZIF), Partner Site Bonn-Cologne, Cologne, Germany.,Department of Internal Medicine, Hematology and Oncology, Goethe University Frankfurt, Frankfurt, Germany
| | - Siegbert Rieg
- Department of Medicine II, University of Freiburg, Freiburg, Germany
| | - Christoph Schmaderer
- Department of Nephrology, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich, Germany
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27
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Prediction of COVID-19 deterioration in high-risk patients at diagnosis: an early warning score for advanced COVID-19 developed by machine learning. Infection 2021; 50:359-370. [PMID: 34279815 PMCID: PMC8287547 DOI: 10.1007/s15010-021-01656-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 06/26/2021] [Indexed: 01/08/2023]
Abstract
PURPOSE While more advanced COVID-19 necessitates medical interventions and hospitalization, patients with mild COVID-19 do not require this. Identifying patients at risk of progressing to advanced COVID-19 might guide treatment decisions, particularly for better prioritizing patients in need for hospitalization. METHODS We developed a machine learning-based predictor for deriving a clinical score identifying patients with asymptomatic/mild COVID-19 at risk of progressing to advanced COVID-19. Clinical data from SARS-CoV-2 positive patients from the multicenter Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS) were used for discovery (2020-03-16 to 2020-07-14) and validation (data from 2020-07-15 to 2021-02-16). RESULTS The LEOSS dataset contains 473 baseline patient parameters measured at the first patient contact. After training the predictor model on a training dataset comprising 1233 patients, 20 of the 473 parameters were selected for the predictor model. From the predictor model, we delineated a composite predictive score (SACOV-19, Score for the prediction of an Advanced stage of COVID-19) with eleven variables. In the validation cohort (n = 2264 patients), we observed good prediction performance with an area under the curve (AUC) of 0.73 ± 0.01. Besides temperature, age, body mass index and smoking habit, variables indicating pulmonary involvement (respiration rate, oxygen saturation, dyspnea), inflammation (CRP, LDH, lymphocyte counts), and acute kidney injury at diagnosis were identified. For better interpretability, the predictor was translated into a web interface. CONCLUSION We present a machine learning-based predictor model and a clinical score for identifying patients at risk of developing advanced COVID-19.
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28
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EPICOVIDEHA: A Ready to Use Platform for Epidemiological Studies in Hematological Patients With COVID-19. Hemasphere 2021; 5:e612. [PMID: 34235404 PMCID: PMC8232068 DOI: 10.1097/hs9.0000000000000612] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 05/28/2021] [Indexed: 01/08/2023] Open
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