1
|
Hurler L, Mescia F, Bergamaschi L, Kajdácsi E, Sinkovits G, Cervenak L, Prohászka Z, Lyons PA, Toonen EJ. sMR and PTX3 levels associate with COVID-19 outcome and survival but not with Long COVID. iScience 2024; 27:110162. [PMID: 39027374 PMCID: PMC11255846 DOI: 10.1016/j.isci.2024.110162] [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: 12/06/2023] [Revised: 02/28/2024] [Accepted: 05/29/2024] [Indexed: 07/20/2024] Open
Abstract
Biomarkers for monitoring COVID-19 disease course are lacking. Study aim was to identify biomarkers associated with disease severity, survival, long-term outcome, and Long COVID. As excessive macrophages activation is a hallmark of COVID-19 and complement activation is key in this, we selected the following proteins involved in these processes: PTX3, C1q, C1-INH, C1s/C1-INH, and sMR. EDTA-plasma concentrations were measured in 215 patients and 47 controls using ELISA. PTX3, sMR, C1-INH, and C1s/C1-INH levels were associated with disease severity. PTX3 and sMR were also associated with survival and long-term immune recovery. Lastly, sMR levels associate with ICU admittance. sMR (AUC 0.85) and PTX3 (AUC 0.78) are good markers for disease severity, especially when used in combination (AUC 0.88). No association between biomarker levels and Long COVID was observed. sMR has not previously been associated with COVID-19 disease severity, ICU admittance or survival and may serve as marker for disease course.
Collapse
Affiliation(s)
- Lisa Hurler
- Department of Internal Medicine and Haematology, Semmelweis University, Budapest, Hungary
| | - Federica Mescia
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge CB2 0AW, UK
- Department of Medicine, University of Cambridge, Addenbrooke’s Hospital, Cambridge CB2 0QQ, UK
| | - Laura Bergamaschi
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge CB2 0AW, UK
- Department of Medicine, University of Cambridge, Addenbrooke’s Hospital, Cambridge CB2 0QQ, UK
| | - Cambridge Institute of Therapeutic Immunology and Infectious Disease-National Institute of Health Research (CITIID-NIHR) COVID BioResource Collaboration
- Department of Internal Medicine and Haematology, Semmelweis University, Budapest, Hungary
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge CB2 0AW, UK
- Department of Medicine, University of Cambridge, Addenbrooke’s Hospital, Cambridge CB2 0QQ, UK
- Research Group for Immunology and Haematology, Semmelweis University - Eötvös Loránd Research Network (Office for Supported Research Groups), Budapest, Hungary
- Research and Development Department, Hycult Biotech, Uden, the Netherlands
| | - Erika Kajdácsi
- Department of Internal Medicine and Haematology, Semmelweis University, Budapest, Hungary
| | - György Sinkovits
- Department of Internal Medicine and Haematology, Semmelweis University, Budapest, Hungary
| | - László Cervenak
- Department of Internal Medicine and Haematology, Semmelweis University, Budapest, Hungary
| | - Zoltán Prohászka
- Department of Internal Medicine and Haematology, Semmelweis University, Budapest, Hungary
- Research Group for Immunology and Haematology, Semmelweis University - Eötvös Loránd Research Network (Office for Supported Research Groups), Budapest, Hungary
| | - Paul A. Lyons
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge CB2 0AW, UK
- Department of Medicine, University of Cambridge, Addenbrooke’s Hospital, Cambridge CB2 0QQ, UK
| | - Erik J.M. Toonen
- Research and Development Department, Hycult Biotech, Uden, the Netherlands
| |
Collapse
|
2
|
Zinchuk M, Kustov G, Beghi M, Bryzgalova Y, Sviatskaia E, Popova S, Voinova N, Terentieva M, Yakovlev A, Guekht A. Suicide risk in patients with a current depressive episode during the COVID-19 pandemic. Front Psychiatry 2024; 15:1343323. [PMID: 38726385 PMCID: PMC11079814 DOI: 10.3389/fpsyt.2024.1343323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 04/05/2024] [Indexed: 05/12/2024] Open
Abstract
Introduction The prevalence of major depressive disorder (MDD) increased during the COVID-19 pandemic. Data on suicidality in these patients during the pandemic period remain scarce. The aim of the study was to determine the prevalence and variables associated with serious suicide risk in Russian inpatients with MDD during the COVID-19 pandemic. Methods A cross-sectional cohort study with consecutive sampling was conducted from January 1, 2021 to December 31, 2021. All patients completed the Mini International Neuropsychiatric Interview (M.I.N.I.) (including the suicidality module), the Beck Depression Inventory, and the State-Trait Anxiety Inventory, and underwent a semi-structured interview to collect relevant demographic and clinical data. Effect sizes for all independent variables and covariates were calculated using partial eta-squared (ηp2). Results Of the 6757 patients with non-psychotic mental disorders assessed, 1605 (23.7%) had MDD confirmed by the M.I.N.I., of whom 17.8% were at serious risk for suicide according to the M.I.N.I. suicidality module. Factors independently associated with serious suicide risk in Russian inpatients with MDD during the pandemic were younger age (ηp2 = 0.021), greater severity of depression (0.038), higher state anxiety (0.003), and nonsuicidal self-injury (NSSI) (0.066). The same variables, except for state anxiety, were independently associated with suicide risk in the subgroup of MDD patients previously infected with SARS-CoV2. Conclusion In the COVID-19 pandemic, the proportion of patients with MDD at serious risk of suicide was similar to pre-pandemic data. No associations were found between suicidality in patients with MDD and COVID-related factors. Younger age, greater severity of depression, and especially NSSI were the most significant risk factors for suicide in patients with MDD during the COVID-19 pandemic.
Collapse
Affiliation(s)
- Mikhail Zinchuk
- Moscow Research and Clinical Center for Neuropsychiatry, Moscow, Russia
| | - Georgii Kustov
- Moscow Research and Clinical Center for Neuropsychiatry, Moscow, Russia
| | - Massimiliano Beghi
- Department of Mental Health, azienda unità sanitaria locale (AUSL) Romagna, Cesena, Italy
| | - Yulia Bryzgalova
- Moscow Research and Clinical Center for Neuropsychiatry, Moscow, Russia
| | | | - Sofya Popova
- Moscow Research and Clinical Center for Neuropsychiatry, Moscow, Russia
| | - Nadezhda Voinova
- Moscow Research and Clinical Center for Neuropsychiatry, Moscow, Russia
| | - Marina Terentieva
- Moscow Research and Clinical Center for Neuropsychiatry, Moscow, Russia
| | - Alexander Yakovlev
- Moscow Research and Clinical Center for Neuropsychiatry, Moscow, Russia
- Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, Moscow, Russia
| | - Alla Guekht
- Moscow Research and Clinical Center for Neuropsychiatry, Moscow, Russia
- Department of Neurology, Neurosurgery and Medical Genetics, Pirogov Russian National Research Medical University, Moscow, Russia
| |
Collapse
|
3
|
McGrath S, Zhao X, Ozturk O, Katzenschlager S, Steele R, Benedetti A. metamedian: An R package for meta-analyzing studies reporting medians. Res Synth Methods 2024; 15:332-346. [PMID: 38073145 DOI: 10.1002/jrsm.1686] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 11/15/2023] [Accepted: 11/16/2023] [Indexed: 01/05/2024]
Abstract
When performing an aggregate data meta-analysis of a continuous outcome, researchers often come across primary studies that report the sample median of the outcome. However, standard meta-analytic methods typically cannot be directly applied in this setting. In recent years, there has been substantial development in statistical methods to incorporate primary studies reporting sample medians in meta-analysis, yet there are currently no comprehensive software tools implementing these methods. In this paper, we present the metamedian R package, a freely available and open-source software tool for meta-analyzing primary studies that report sample medians. We summarize the main features of the software and illustrate its application through real data examples involving risk factors for a severe course of COVID-19.
Collapse
Affiliation(s)
- Sean McGrath
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - XiaoFei Zhao
- MOE Key Laboratory of Bioinformatics, Bioinformatics Division, BNRIST and Department of Automation, Tsinghua University, Beijing, China
| | - Omer Ozturk
- Department of Statistics, The Ohio State University, Columbus, Ohio, USA
| | | | - Russell Steele
- Department of Mathematics and Statistics, McGill University, Montreal, Quebec, Canada
| | - Andrea Benedetti
- Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada
- Respiratory Epidemiology and Clinical Research Unit (RECRU), McGill University Health Centre, Montreal, Quebec, Canada
- Department of Medicine, McGill University, Montreal, Quebec, Canada
| |
Collapse
|
4
|
Kugler S, Hahnefeld L, Kloka JA, Ginzel S, Nürenberg-Goloub E, Zinn S, Vehreschild MJ, Zacharowski K, Lindau S, Ullrich E, Burmeister J, Kohlhammer J, Schwäble J, Gurke R, Dorochow E, Bennett A, Dauth S, Campe J, Knape T, Laux V, Kannt A, Köhm M, Geisslinger G, Resch E, Behrens F. Short-term predictor for COVID-19 severity from a longitudinal multi-omics study for practical application in intensive care units. Talanta 2024; 268:125295. [PMID: 37866305 DOI: 10.1016/j.talanta.2023.125295] [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: 07/05/2023] [Revised: 09/29/2023] [Accepted: 10/06/2023] [Indexed: 10/24/2023]
Abstract
BACKGROUND The COVID-19 pandemic challenged the management of technical and human resources in intensive care units (ICU) across the world. Several long-term predictors for COVID-19 disease progression have been discovered. However, predictors to support short-term planning of resources and medication that can be translated to future pandemics are still missing. A workflow was established to identify a predictor for short-term COVID-19 disease progression in the acute phase of intensive care patients to support clinical decision-making. METHODS Thirty-two patients with SARS-CoV-2 infection were recruited on admission to the ICU and clinical data collected. During their hospitalization, plasma samples were acquired from each patient on multiple occasions, excepting one patient for which only one time point was possible, and the proteome (Inflammation, Immune Response and Organ Damage panels from Olink® Target 96), metabolome and lipidome (flow injection analysis and liquid chromatography-mass spectrometry) analyzed for each sample. Patient visits were grouped according to changes in disease severity based on their respiratory and organ function, and evaluated using a combination of statistical analysis and machine learning. The resulting short-term predictor from this multi-omics approach was compared to the human assessment of disease progression. Furthermore, the potential markers were compared to the baseline levels of 50 healthy subjects with no known SARS-CoV-2 or other viral infections. RESULTS A total of 124 clinical parameters, 271 proteins and 782 unique metabolites and lipids were assessed. The dimensionality of the dataset was reduced, selecting 47 from the 1177 parameters available following down-selection, to build the machine learning model. Subsequently, two proteins (C-C motif chemokine 7 (CCL7) and carbonic anhydrase 14 (CA14)) and one lipid (hexosylceramide 18:2; O2/20:0) were linked to disease progression in the studied SARS-CoV-2 infections. Thus, a predictor delivering the prognosis of an upcoming worsening of the patient's condition up to five days in advance with a reasonable accuracy (79 % three days prior to event, 84 % four to five days prior to event) was found. Interestingly, the predictor's performance was complementary to the clinicians' capabilities to foresee a worsening of a patient. CONCLUSION This study presents a workflow to identify omics-based biomarkers to support clinical decision-making and resource management in the ICU. This was successfully applied to develop a short-term predictor for aggravation of COVID-19 symptoms. The applied methods can be adapted for future small cohort studies.
Collapse
Affiliation(s)
- Sabine Kugler
- Fraunhofer Cluster of Excellence Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany; Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS, Schloss Birlinghoven 1, St. Augustin, Germany
| | - Lisa Hahnefeld
- Fraunhofer Cluster of Excellence Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany; Goethe University Frankfurt, University Hospital, Institute of Clinical Pharmacology, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany.
| | - Jan Andreas Kloka
- Goethe University Frankfurt, University Hospital, Clinic for Anesthesiology, Intensive Care Medicine and Pain Therapy, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Sebastian Ginzel
- Fraunhofer Cluster of Excellence Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany; Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS, Schloss Birlinghoven 1, St. Augustin, Germany
| | - Elina Nürenberg-Goloub
- Goethe University Frankfurt, University Hospital, Clinic for Anesthesiology, Intensive Care Medicine and Pain Therapy, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Sebastian Zinn
- Goethe University Frankfurt, University Hospital, Clinic for Anesthesiology, Intensive Care Medicine and Pain Therapy, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany; Fraunhofer Leistungszentrum TheraNova, Theodor-Stern-Kai 6, 60596, Frankfurt am Main, Germany
| | - Maria Jgt Vehreschild
- Goethe University Frankfurt, University Hospital, Department of Internal Medicine, Infectious Diseases, 60590, Frankfurt am Main, Germany
| | - Kai Zacharowski
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany; Goethe University Frankfurt, University Hospital, Clinic for Anesthesiology, Intensive Care Medicine and Pain Therapy, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Simone Lindau
- Goethe University Frankfurt, University Hospital, Clinic for Anesthesiology, Intensive Care Medicine and Pain Therapy, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Evelyn Ullrich
- University Cancer Center Frankfurt (UCT), University Hospital, Goethe University Frankfurt, Frankfurt, Germany; Frankfurt Cancer Institute (FCI), Frankfurt am Main, Germany; Goethe University Frankfurt, Department of Pediatrics, Experimental Immunology and Cell Therapy, Frankfurt, Germany
| | - Jan Burmeister
- Fraunhofer Institute for Computer Graphics Research IGD, Darmstadt, Germany
| | - Jörn Kohlhammer
- Fraunhofer Institute for Computer Graphics Research IGD, Darmstadt, Germany
| | - Joachim Schwäble
- Goethe University Frankfurt, University Hospital, Institute of Transfusion Medicine and Immunohematology, German Red Cross Blood Transfusion Service Baden-Württemberg, Frankfurt, Germany
| | - Robert Gurke
- Fraunhofer Cluster of Excellence Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany; Goethe University Frankfurt, University Hospital, Institute of Clinical Pharmacology, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany
| | - Erika Dorochow
- Goethe University Frankfurt, University Hospital, Institute of Clinical Pharmacology, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Alexandre Bennett
- Fraunhofer Cluster of Excellence Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany
| | - Stephanie Dauth
- Fraunhofer Cluster of Excellence Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany
| | - Julia Campe
- Goethe University Frankfurt, Department of Pediatrics, Experimental Immunology and Cell Therapy, Frankfurt, Germany; Goethe University Frankfurt, Biological Sciences, Frankfurt am Main, Germany
| | - Tilo Knape
- Fraunhofer Cluster of Excellence Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany
| | - Volker Laux
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany
| | - Aimo Kannt
- Fraunhofer Cluster of Excellence Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany; Fraunhofer Leistungszentrum TheraNova, Theodor-Stern-Kai 6, 60596, Frankfurt am Main, Germany
| | - Michaela Köhm
- Fraunhofer Cluster of Excellence Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany; Goethe University Frankfurt, University Hospital, Rheumatology, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany
| | - Gerd Geisslinger
- Fraunhofer Cluster of Excellence Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany; Goethe University Frankfurt, University Hospital, Institute of Clinical Pharmacology, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany
| | - Eduard Resch
- Fraunhofer Cluster of Excellence Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany
| | - Frank Behrens
- Fraunhofer Cluster of Excellence Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany; Goethe University Frankfurt, University Hospital, Rheumatology, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany
| |
Collapse
|
5
|
Leitner M, Pötz G, Berger M, Fellner M, Spat S, Koini M. Characteristics and burden of acute COVID-19 and long-COVID: Demographic, physical, mental health, and economic perspectives. PLoS One 2024; 19:e0297207. [PMID: 38252638 PMCID: PMC10802963 DOI: 10.1371/journal.pone.0297207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2023] [Accepted: 12/30/2023] [Indexed: 01/24/2024] Open
Abstract
BACKGROUND COVID-19 infection and its associated consequence, known as long-COVID, lead to a significant burden on the global healthcare system and limitations in people's personal and work lives. This study aims to provide further insight into the impact of acute and ongoing COVID-19 symptoms and investigates the role of patients' gender and vaccination status. METHODS 416 individuals (73.9% female) between the ages of 16 and 80 years (M = 44.18, SD = 12.90) with self-reported symptoms of long-COVID participated in an online survey conducted between March and May 2022. RESULTS 6.0%, 74.3%, and 19.7% of all respondents reported having had an asymptomatic, mild, or severe acute illness, respectively. Out of all participants, 7.8% required hospitalization. The most prevalent symptoms during the acute infection (Mdn = 23.50 symptoms, IQR = 13-39) included fatigue, exhaustion, cough, brain fog, and memory problems. The median long-COVID disease duration was 12.10 months (IQR = 2.8-17.4). Among 64 inquired long-COVID symptoms (Mdn = 17.00 symptoms, IQR = 9-27), participants reported fatigue, exhaustion, memory problems, brain fog, and dyspnea as the most common ongoing symptoms, which were generally experienced as fluctuating and deteriorating after physical or cognitive activity. Common consequences of long-COVID included financial losses (40.5%), changes in the participants' profession (41.0%), stress resistance (87.5%), sexual life (38.1%), and mood (72.1%), as well as breathing difficulties (41.3%), or an increased drug intake (e.g., medicine, alcohol; 44.6%). In addition, vaccinated individuals exhibited a shorter acute illness duration and an earlier onset of long-COVID symptoms. In general, women reported more long-COVID symptoms than men. CONCLUSION Long-COVID represents a heterogeneous disease and impacts multiple life aspects of those affected. Tailored rehabilitation programs targeting the plurality of physical and mental symptoms are needed.
Collapse
Affiliation(s)
- Manuel Leitner
- Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, Austria
| | | | - Martin Berger
- Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, Austria
| | | | | | - Marisa Koini
- Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, Austria
| |
Collapse
|
6
|
Wan G, Wu X, Zhang X, Sun H, Yu X. Development of a novel machine learning model based on laboratory and imaging indices to predict acute cardiac injury in cancer patients with COVID-19 infection: a retrospective observational study. J Cancer Res Clin Oncol 2023; 149:17039-17050. [PMID: 37747525 DOI: 10.1007/s00432-023-05417-3] [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: 07/27/2023] [Accepted: 09/07/2023] [Indexed: 09/26/2023]
Abstract
PURPOSE Due to the increased risk of acute cardiac injury (ACI) and poor prognosis in cancer patients with COVID-19 infection, our aim was to develop a novel and interpretable model for predicting ACI occurrence in cancer patients with COVID-19 infection. METHODS This retrospective observational study screened 740 cancer patients with COVID-19 infection from December 2022 to April 2023. The least absolute shrinkage and selection operator (LASSO) regression was used for the preliminary screening of the indices. To enhance the model accuracy, we introduced an alpha index to further screen and rank the indices based on their significance. Random forest (RF) was used to construct the prediction model. The Shapley Additive Explanation (SHAP) and Local Interpretable Model-Agnostic Explanation (LIME) methods were utilized to explain the model. RESULTS According to the inclusion criteria, 201 cancer patients with COVID-19, including 36 variables indices, were included in the analysis. The top eight indices (albumin, lactate dehydrogenase, cystatin C, neutrophil count, creatine kinase isoenzyme, red blood cell distribution width, D-dimer and chest computed tomography) for predicting the occurrence of ACI in cancer patients with COVID-19 infection were included in the RF model. The model achieved an area under curve (AUC) of 0.940, an accuracy of 0.866, a sensitivity of 0.750 and a specificity of 0.900. The calibration curve and decision curve analysis showed good calibration and clinical practicability. SHAP results demonstrated that albumin was the most important index for predicting the occurrence of ACI. LIME results showed that the model could predict the probability of ACI in each cancer patient infected with COVID-19 individually. CONCLUSION We developed a novel machine-learning model that demonstrates high explainability and accuracy in predicting the occurrence of ACI in cancer patients with COVID-19 infection, using laboratory and imaging indices.
Collapse
Affiliation(s)
- Guangcai Wan
- Department of Clinical Laboratory, Jilin Cancer Hospital, Changchun, 130012, China
| | - Xuefeng Wu
- Department of Clinical Laboratory, Jilin Cancer Hospital, Changchun, 130012, China
| | - Xiaowei Zhang
- Department of Clinical Laboratory, Jilin Cancer Hospital, Changchun, 130012, China
| | - Hongshuai Sun
- Department of Clinical Laboratory, Jilin Cancer Hospital, Changchun, 130012, China
| | - Xiuyan Yu
- Department of Clinical Laboratory, Jilin Cancer Hospital, Changchun, 130012, China.
| |
Collapse
|
7
|
Neves FF, Pott-Junior H, Yamashita KMC, de Sousa Santos S, Cominetti MR, de Melo Freire CC, Cunha AFD, Jordão Júnior AA. Do the oxidative stress biomarkers predict COVID-19 outcome? An in-hospital cohort study. Free Radic Biol Med 2023; 207:194-199. [PMID: 37454917 DOI: 10.1016/j.freeradbiomed.2023.06.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 06/07/2023] [Accepted: 06/24/2023] [Indexed: 07/18/2023]
Abstract
In SARSCoV-2 infections, excessive activation of the immune system dramatically elevates reactive oxygen species levels, harms cell structures, and directly increases disease severity and mortality. We aimed to evaluate whether plasma oxidative stress biomarker levels could predict mortality in adults admitted with Coronavirus Disease 2019 (COVID-19), considering potential confounders. We conducted a cohort study of 115 adults (62.1 ± 17.6 years, 65 males) admitted to a Brazilian public hospital for severely symptomatic COVID-19. Serum levels of α-tocopherol, glutathione, superoxide dismutase, 8-hydroxy-2'-deoxyguanosine, malondialdehyde, and advanced oxidation protein products were quantified at COVID-19 diagnosis using real-time polymerase chain reaction. Serum levels of α-tocopherol, glutathione, superoxide dismutase, and advanced oxidation protein products differed significantly between survivors and non-survivors. Serum glutathione levels below 327.2 μmol/mL were associated with a significant risk of death in COVID-19 patients, even after accounting for other factors (adjusted hazard ratio = 3.12 [95% CI: 1.83-5.33]).
Collapse
Affiliation(s)
- Fabio Fernandes Neves
- Department of Medicine, Federal University of São Carlos - UFSCar, 13565-905, São, Carlos, Brazil.
| | - Henrique Pott-Junior
- Department of Medicine, Federal University of São Carlos - UFSCar, 13565-905, São, Carlos, Brazil
| | | | - Sigrid de Sousa Santos
- Department of Medicine, Federal University of São Carlos - UFSCar, 13565-905, São, Carlos, Brazil
| | - Marcia Regina Cominetti
- Department of Gerontology, Federal University of São Carlos - UFSCar, 13565-905, São, Carlos, Brazil
| | - Caio Cesar de Melo Freire
- Department of Genetics and Evolution, Federal University of São Carlos - UFSCar, 13565-905, São Carlos, Brazil
| | - Anderson Ferreira da Cunha
- Department of Genetics and Evolution, Federal University of São Carlos - UFSCar, 13565-905, São Carlos, Brazil
| | - Alceu Afonso Jordão Júnior
- Department of Health Sciences, Ribeirão Preto Medical School, University of São Paulo - USP, 14049-900, Ribeirão Preto, Brazil
| |
Collapse
|
8
|
Aloisio E, Colombo G, Dolci A, Panteghini M. C-reactive protein and clinical outcome in COVID-19 patients: the importance of harmonized measurements. Clin Chem Lab Med 2023; 61:1546-1551. [PMID: 37036741 DOI: 10.1515/cclm-2023-0276] [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: 01/31/2023] [Accepted: 03/30/2023] [Indexed: 04/11/2023]
Abstract
C-reactive protein (CRP) is a cytokine-mediated acute phase reactant with a recognized role in inflammatory conditions and infectious disease. In coronavirus disease 2019 (COVID-19), elevated CRP concentrations in serum were frequently detected and significantly associated with poor outcome in terms of disease severity, need for intensive care, and in-hospital death. For these reasons, the marker was proposed as a powerful test for prognostic classification of COVID-19 patients. In most of available publications, there was however confounding information about how interpretative criteria for CRP in COVID-19 should be derived, including quality of employed assays and optimal cut-off definition. Assuring result harmonization and controlling measurement uncertainty in terms of performance specifications are fundamental to allow worldwide application of clinical information according to specific CRP thresholds and to avoid risk of patient misclassification.
Collapse
|
9
|
Park JM, Woo W, Lee SC, Park S, Yon DK, Lee SW, Smith L, Koyanagi A, Shin JI, Kim YW. Prevalence and Mortality Risk of Neurological Disorders during the COVID-19 Pandemic: An Umbrella Review of the Current Evidence. Neuroepidemiology 2023; 57:129-147. [PMID: 37044073 DOI: 10.1159/000530536] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 03/22/2023] [Indexed: 04/14/2023] Open
Abstract
INTRODUCTION Coronavirus disease 2019 (COVID-19), a global pandemic, has infected approximately 10% of the world's population. This comprehensive review aimed to determine the prevalence of various neurological disorders in COVID-19 without overlapping meta-analysis errors. METHODS We searched for meta-analyses on neurological disorders following COVID-19 published up to March 14, 2023. We obtained 1,184 studies, of which 44 meta-analyses involving 9,228,588 COVID-19 patients were finally included. After confirming the forest plot of each study and removing overlapping individual studies, a re-meta-analysis was performed using the random-effects model. RESULTS The summarized combined prevalence of each neurological disorder is as follows: stroke 3.39% (95% confidence interval, 1.50-5.27), dementia 6.41% (1.36-11.46), multiple sclerosis 4.00% (2.50-5.00), epilepsy 5.36% (-0.60-11.32), Parkinson's disease 0.67% (-1.11-2.45), encephalitis 0.66% (-0.44-1.77), and Guillain-Barré syndrome 3.83% (-0.13-7.80). In addition, the mortality risk of patients with comorbidities of COVID-19 is as follows: stroke OR 1.63 (1.23-2.03), epilepsy OR 1.71 (1.00-2.42), dementia OR 1.90 (1.31-2.48), Parkinson's disease OR 3.94 (-2.12-10.01). CONCLUSION Our results show that the prevalence and mortality risk may increase in some neurological diseases during the COVID-19 pandemic. Future studies should elucidate the precise mechanisms for the link between COVID-19 and neurological diseases, determine which patient characteristics predispose them to neurological diseases, and consider potential global patient management.
Collapse
Affiliation(s)
- Jong Mi Park
- Department and Research Institute of Rehabilitation Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Wongi Woo
- Department of Thoracic and Cardiovascular Surgery, Gangnam Severance Hospital, Seoul, Republic of Korea
| | - Sang Chul Lee
- Department and Research Institute of Rehabilitation Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Seoyeon Park
- Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Dong Keon Yon
- Center for Digital Health, Medical Science Research Institute, Kyung Hee University College of Medicine, Seoul, Republic of Korea
| | - Seung Won Lee
- Department of Data Science, Sejong University College of Software Convergence, Seoul, Republic of Korea
- Sungkyunkwan University School of Medicine, Suwon, Republic of Korea
| | - Lee Smith
- Centre for Health, Performance, and Wellbeing, Anglia Ruskin University, Cambridge, UK
| | - Ai Koyanagi
- Parc Sanitari Sant Joan de Deu/CIBERSAM, ISCIII, Universitat de Barcelona, Fundacio Sant Joan de Deu, Sant Boi de Llobregat, Barcelona, Spain
- ICREA, Pg. Lluis Companys 23, Barcelona, Spain
| | - Jae Il Shin
- Department of Pediatrics, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Yong Wook Kim
- Department and Research Institute of Rehabilitation Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| |
Collapse
|
10
|
Nilsen A, Lichtwarck B, Eriksen S, Mork Rokstad AM. Clinical expressions, characteristics and treatments of confirmed COVID-19 in nursing home residents: a systematic review. BMC Geriatr 2023; 23:101. [PMID: 36803435 PMCID: PMC9936944 DOI: 10.1186/s12877-023-03826-0] [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: 10/10/2022] [Accepted: 02/15/2023] [Indexed: 02/19/2023] Open
Abstract
BACKGROUND The coronavirus 2019 (COVID-19) pandemic has led to a high rate of infections, frequent outbreaks, and high mortality rates in nursing homes (NH) worldwide. To protect and improve the treatment and care of the vulnerable NH population, it is pivotal to systematise and synthesise data from cases of COVID-19 among NH residents. In our systematic review, we therefore aimed to describe the clinical expressions, characteristics, and treatments of NH residents confirmed to have COVID-19. METHODS We conducted two comprehensive literature searches in several electronic databases: (1) PubMed, (2) CINAHL, (3) AgeLine, (4) Embase, and (5) PsycINFO in April and July 2021. Of the 438 articles screened, 19 were included in our sample, and we used the Newcastle-Ottawa Assessment Scale to assess the quality of the reported studies. A weighted mean (Mweighted), was calculated to account for the large variation in sample sizes of the studies, and due to heterogeneity among the studies, we report our findings in a narrative synthesis. RESULTS According to the mean weights (Mweighted), common symptoms and signs in NH residents confirmed to have COVID-19 were fever (53.7%), cough (56.5%), hypoxia (32.3%), and delirium or confusion (31.2%). Common comorbidities were hypertension (78.6%), dementia or cognitive impairment (55.3%), and cardiovascular diseases (52.0%). Six studies presented data concerning medical and pharmacological treatments, such as inhalers, oxygen supplementation, anticoagulation, and parenteral/enteral fluids or nutrition. The treatments were used to improve outcomes, as part of palliative care, or as end-of-life treatment. Transfers to hospital for NH residents with confirmed COVID-19 were reported in six of the included studies, and the rate of hospital transfers ranged from 6.9% to 50% in this population. In the 17 studies reporting mortality, 40.2% of the NH residents died during the studies' observation periods. CONCLUSIONS Our systematic review allowed us to summarise important clinical findings about COVID-19 among NH residents and to identify the population's risk factors for serious illness and death caused by the disease. However, the treatment and care of NH residents with severe COVID-19 warrant further investigation.
Collapse
Affiliation(s)
- Anita Nilsen
- Faculty of Health Sciences and Social Care, Molde University College, Molde, Norway.
| | - Bjørn Lichtwarck
- grid.412929.50000 0004 0627 386XThe Research Centre for Age-Related Functional Decline and Disease, Innlandet Hospital Trust, Ottestad, Norway
| | - Siren Eriksen
- grid.417292.b0000 0004 0627 3659Norwegian National Centre for Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway ,grid.458172.d0000 0004 0389 8311Lovisenberg Diaconal University College, Oslo, Norway
| | - Anne Marie Mork Rokstad
- grid.411834.b0000 0004 0434 9525Faculty of Health Sciences and Social Care, Molde University College, Molde, Norway ,grid.417292.b0000 0004 0627 3659Norwegian National Centre for Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway
| |
Collapse
|
11
|
Tóth K, Fresilli S, Paoli N, Maiucci G, Salvioni M, Kotani Y, Katzenschlager S, Weigand MA, Landoni G. D-dimer levels in non-COVID-19 ARDS and COVID-19 ARDS patients: A systematic review with meta-analysis. PLoS One 2023; 18:e0277000. [PMID: 36745595 PMCID: PMC9901787 DOI: 10.1371/journal.pone.0277000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 01/20/2023] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Hypercoagulability and thrombo-inflammation are the main reasons for death in COVID-19 patients. It is unclear whether there is a difference between D-dimer levels in patients without or with COVID-19 acute respiratory distress syndrome (ARDS). METHODS We searched PubMed, EMBASE, and ClinicalTrails.gov databases looking for studies reporting D-dimer levels in patients without or with COVID-19 ARDS. Secondary endpoints included length of hospital stay, and mortality data at the longest follow-up available. RESULTS We included 12 retrospective and 3 prospective studies with overall 2,828 patients, of whom 1,404 (49.6%) had non-COVID-19 ARDS and 1,424 had COVID-19 ARDS. D-dimer levels were not significantly higher in non-COVID-19 ARDS than in COVID-19 ARDS patients (mean 7.65 mg/L vs. mean 6.20 mg/L MD 0.88 [CI: -0.61 to 2.38] p = 0.25; I² = 85%) while the length of hospital stay was shorter (non-COVID-19 mean 37.4 days vs. COVID-19 mean 48.5 days, MD -10.92 [CI: -16.71 to -5.14] p < 0.001; I² = 44%). No difference in mortality was observed: non-COVID-19 ARDS 418/1167 (35.8%) vs. COVID-19 ARDS 467/1201 (38.8%). CONCLUSIONS We found no difference in the mean D-dimer levels between non-COVID-19 ARDS and COVID-19 ARDS patients.
Collapse
Affiliation(s)
- Krisztina Tóth
- Doctoral School of Theoretical and Translational Medicine, Semmelweis University, Budapest, Hungary
| | - Stefano Fresilli
- Department of Anesthesia and Intensive Care, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Nicola Paoli
- Department of Anesthesia and Intensive Care, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Giacomo Maiucci
- Department of Anesthesia and Intensive Care, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Mariateresa Salvioni
- Department of Anesthesia and Intensive Care, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Yuki Kotani
- Department of Anesthesia and Intensive Care, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Intensive Care Medicine, Kameda Medical Center, Kamogawa, Japan
| | - Stephan Katzenschlager
- Department of Anesthesiology, Heidelberg University Hospital, Heidelberg, Germany
- University Center for ARDS and Weaning, Heidelberg University Hospital, Heidelberg, Germany
| | - Markus A. Weigand
- Department of Anesthesiology, Heidelberg University Hospital, Heidelberg, Germany
- University Center for ARDS and Weaning, Heidelberg University Hospital, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC-H), Member of the German Center for Lung Research (DZL), Heidelberg, Germany
| | - Giovanni Landoni
- Department of Anesthesia and Intensive Care, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- * E-mail:
| |
Collapse
|
12
|
McGrath S, Katzenschlager S, Zimmer AJ, Seitel A, Steele R, Benedetti A. Standard error estimation in meta-analysis of studies reporting medians. Stat Methods Med Res 2023; 32:373-388. [PMID: 36412105 DOI: 10.1177/09622802221139233] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
We consider the setting of an aggregate data meta-analysis of a continuous outcome of interest. When the distribution of the outcome is skewed, it is often the case that some primary studies report the sample mean and standard deviation of the outcome and other studies report the sample median along with the first and third quartiles and/or minimum and maximum values. To perform meta-analysis in this context, a number of approaches have recently been developed to impute the sample mean and standard deviation from studies reporting medians. Then, standard meta-analytic approaches with inverse-variance weighting are applied based on the (imputed) study-specific sample means and standard deviations. In this article, we illustrate how this common practice can severely underestimate the within-study standard errors, which results in poor coverage for the pooled mean in common effect meta-analyses and overestimation of between-study heterogeneity in random effects meta-analyses. We propose a straightforward bootstrap approach to estimate the standard errors of the imputed sample means. Our simulation study illustrates how the proposed approach can improve the estimation of the within-study standard errors and consequently improve coverage for the pooled mean in common effect meta-analyses and estimation of between-study heterogeneity in random effects meta-analyses. Moreover, we apply the proposed approach in a meta-analysis to identify risk factors of a severe course of COVID-19.
Collapse
Affiliation(s)
- Sean McGrath
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | - Alexandra J Zimmer
- Department of Epidemiology, Biostatistics, and Occupational Health, 5620McGill University, Montreal, Quebec, Canada.,McGill International TB Centre, Montreal, Quebec, Canada
| | - Alexander Seitel
- Division of Intelligent Medical Systems, 28333German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Russell Steele
- Department of Mathematics and Statistics, 5620McGill University, Montreal, Quebec, Canada
| | - Andrea Benedetti
- Department of Epidemiology, Biostatistics, and Occupational Health, 5620McGill University, Montreal, Quebec, Canada.,Respiratory Epidemiology and Clinical Research Unit (RECRU), 54473McGill University Health Centre, Montreal, Quebec, Canada.,Department of Medicine, 5620McGill University, Montreal, Quebec, Canada
| |
Collapse
|
13
|
Zhang HP, Sun YL, Wang YF, Yazici D, Azkur D, Ogulur I, Azkur AK, Yang ZW, Chen XX, Zhang AZ, Hu JQ, Liu GH, Akdis M, Akdis CA, Gao YD. Recent developments in the immunopathology of COVID-19. Allergy 2023; 78:369-388. [PMID: 36420736 PMCID: PMC10108124 DOI: 10.1111/all.15593] [Citation(s) in RCA: 27] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Revised: 11/01/2022] [Accepted: 11/22/2022] [Indexed: 11/25/2022]
Abstract
There has been an important change in the clinical characteristics and immune profile of Coronavirus disease 2019 (COVID-19) patients during the pandemic thanks to the extensive vaccination programs. Here, we highlight recent studies on COVID-19, from the clinical and immunological characteristics to the protective and risk factors for severity and mortality of COVID-19. The efficacy of the COVID-19 vaccines and potential allergic reactions after administration are also discussed. The occurrence of new variants of concerns such as Omicron BA.2, BA.4, and BA.5 and the global administration of COVID-19 vaccines have changed the clinical scenario of COVID-19. Multisystem inflammatory syndrome in children (MIS-C) may cause severe and heterogeneous disease but with a lower mortality rate. Perturbations in immunity of T cells, B cells, and mast cells, as well as autoantibodies and metabolic reprogramming may contribute to the long-term symptoms of COVID-19. There is conflicting evidence about whether atopic diseases, such as allergic asthma and rhinitis, are associated with a lower susceptibility and better outcomes of COVID-19. At the beginning of pandemic, the European Academy of Allergy and Clinical Immunology (EAACI) developed guidelines that provided timely information for the management of allergic diseases and preventive measures to reduce transmission in the allergic clinics. The global distribution of COVID-19 vaccines and emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with reduced pathogenic potential dramatically decreased the morbidity, severity, and mortality of COVID-19. Nevertheless, breakthrough infection remains a challenge for disease control. Hypersensitivity reactions (HSR) to COVID-19 vaccines are low compared to other vaccines, and these were addressed in EAACI statements that provided indications for the management of allergic reactions, including anaphylaxis to COVID-19 vaccines. We have gained a depth knowledge and experience in the over 2 years since the start of the pandemic, and yet a full eradication of SARS-CoV-2 is not on the horizon. Novel strategies are warranted to prevent severe disease in high-risk groups, the development of MIS-C and long COVID-19.
Collapse
Affiliation(s)
- Huan-Ping Zhang
- Department of Allergology, Shanxi Bethune Hospital, Shanxi Academy of Medical Science, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China
| | - Yuan-Li Sun
- Department of Allergology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Yan-Fen Wang
- Department of Pediatrics, Shanxi Bethune Hospital, Shanxi Academy of Medical Science, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China
| | - Duygu Yazici
- Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Davos, Switzerland
| | - Dilek Azkur
- Division of Pediatric Allergy and Immunology, Department of Pediatrics, Faculty of Medicine, University of Kirikkale, Kirikkale, Turkey
| | - Ismail Ogulur
- Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Davos, Switzerland
| | - Ahmet Kursat Azkur
- Department of Virology, Faculty of Veterinary Medicine, University of Kirikkale, Kirikkale, Turkey
| | - Zhao-Wei Yang
- Department of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Xiao-Xue Chen
- Department of Allergology, Shanxi Bethune Hospital, Shanxi Academy of Medical Science, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China
| | - Ai-Zhi Zhang
- Intensive Care Unit, The Second Hospital of Shanxi Medical University, Taiyuan, China
| | - Jia-Qian Hu
- Department of Allergology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Guang-Hui Liu
- Department of Allergology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Mübeccel Akdis
- Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Davos, Switzerland
| | - Cezmi A Akdis
- Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Davos, Switzerland
| | - Ya-Dong Gao
- Department of Allergology, Zhongnan Hospital of Wuhan University, Wuhan, China
| |
Collapse
|
14
|
Gatto NM, Freund D, Ogata P, Diaz L, Ibarrola A, Desai M, Aspelund T, Gluckstein D. Correlates of Coronavirus Disease 2019 Inpatient Mortality at a Southern California Community Hospital With a Predominantly Hispanic/Latino Adult Population. Open Forum Infect Dis 2023; 10:ofad011. [PMID: 36726553 PMCID: PMC9887269 DOI: 10.1093/ofid/ofad011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 12/06/2023] [Indexed: 01/11/2023] Open
Abstract
Background Studies of inpatient coronavirus disease 2019 (COVID-19) mortality risk factors have mainly used data from academic medical centers or large multihospital databases and have not examined populations with large proportions of Hispanic/Latino patients. In a retrospective cohort study of 4881 consecutive adult COVID-19 hospitalizations at a single community hospital in Los Angeles County with a majority Hispanic/Latino population, we evaluated factors associated with mortality. Methods Data on demographic characteristics, comorbidities, laboratory and clinical results, and COVID-19 therapeutics were abstracted from the electronic medical record. Cox proportional hazards regression modeled statistically significant, independently associated predictors of hospital mortality. Results Age ≥65 years (hazard ratio [HR] = 2.66; 95% confidence interval [CI] = 1.90-3.72), male sex (HR = 1.31; 95% CI = 1.07-1.60), renal disease (HR = 1.52; 95% CI = 1.18-1.95), cardiovascular disease (HR = 1.45; 95% CI = 1.18-1.78), neurological disease (HR = 1.84; 95% CI = 1.41-2.39), D-dimer ≥500 ng/mL (HR = 2.07; 95% CI = 1.43-3.0), and pulse oxygen level <88% (HR = 1.39; 95% CI = 1.13-1.71) were independently associated with increased mortality. Patient household with (1) multiple COVID-19 cases and (2) Asian, Black, or Hispanic compared with White non-Hispanic race/ethnicity were associated with reduced mortality. In hypoxic COVID-19 inpatients, remdesivir, tocilizumab, and convalescent plasma were associated with reduced mortality, and corticosteroid use was associated with increased mortality. Conclusions We corroborate several previously identified mortality risk factors and find evidence that the combination of factors associated with mortality differ between populations.
Collapse
Affiliation(s)
- Nicole M Gatto
- Correspondence: Nicole M. Gatto, MPH, PhD, Adjunct Research Assistant Professor Department of Population and Public Health Sciences Keck School of Medicine University of Southern California 1845 N Soto St, Los Angeles, CA 90032, USA ()
| | - Debbie Freund
- School of Community and Global Health, Claremont Graduate University, Claremont, California, USA,Department of Economic Sciences, Claremont Graduate University, Claremont, California, USA,Department of Health Policy and Management, Fielding School of Public Health, University of California Los Angeles, Los Angeles, California, USA
| | - Pamela Ogata
- School of Community and Global Health, Claremont Graduate University, Claremont, California, USA
| | - Lisa Diaz
- Pomona Valley Hospital and Medical Center, Pomona, California, USA
| | - Ace Ibarrola
- Pomona Valley Hospital and Medical Center, Pomona, California, USA
| | - Mamta Desai
- Pomona Valley Hospital and Medical Center, Pomona, California, USA
| | - Thor Aspelund
- Center for Public Health Sciences, University of Iceland, Reykjavik, Iceland
| | | |
Collapse
|
15
|
Kunzler AM, Lindner S, Röthke N, Schäfer SK, Metzendorf MI, Sachkova A, Müller-Eberstein R, Klinger C, Burns J, Coenen M, Lieb K. Mental Health Impact of Early Stages of the COVID-19 Pandemic on Individuals with Pre-Existing Mental Disorders: A Systematic Review of Longitudinal Research. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:948. [PMID: 36673705 PMCID: PMC9858748 DOI: 10.3390/ijerph20020948] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 12/30/2022] [Accepted: 01/01/2023] [Indexed: 06/17/2023]
Abstract
In view of disease-related threats, containment measures, and disrupted healthcare, individuals with pre-existing mental illness might be vulnerable to adverse effects of the COVID-19 pandemic. Previous reviews indicated increased mental distress, with limited information on peri-pandemic changes. In this systematic review, we aimed to identify longitudinal research investigating pre- to peri-pandemic and/or peri-pandemic changes of mental health in patients, focusing on the early phase and considering specific diagnoses. PsycINFO, Web of Science, the WHO Global literature on coronavirus disease database, and the Cochrane COVID-19 Study Register weresearched through 31 May 2021. Studies were synthesized using vote counting based on effect direction. We included 40 studies mostly from Western, high-income countries. Findings were heterogeneous, with improving and deteriorating mental health observed compared to pre-pandemic data, partly depending on underlying diagnoses. For peri-pandemic changes, evidence was limited, with some suggestion of recovery of mental distress. Study quality was heterogeneous; only few studies investigated potential moderators (e.g., chronicity of mental illness). Mental health effects on people with pre-existing conditions are heterogeneous within and across diagnoses for pre- to peri-pandemic and peri-pandemic comparisons. To improve mental health services amid future global crises, forthcoming research should understand medium- and long-term effects, controlling for containment measures.
Collapse
Affiliation(s)
- Angela M. Kunzler
- Leibniz Institute for Resilience Research (LIR), 55122 Mainz, Germany
- Institute for Evidence in Medicine, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79110 Freiburg, Germany
| | - Saskia Lindner
- Department of Psychiatry and Psychotherapy, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Nikolaus Röthke
- Department of Psychiatry and Psychotherapy, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Sarah K. Schäfer
- Leibniz Institute for Resilience Research (LIR), 55122 Mainz, Germany
| | - Maria-Inti Metzendorf
- Institute of General Practice (ifam), Medical Faculty, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Alexandra Sachkova
- Department of Anesthesiology, University Medical Center of the Georg August University Göttingen, 37075 Göttingen, Germany
| | - Roxana Müller-Eberstein
- Chair of Public Health and Health Services Research, Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), LMU Munich, 81377 Munich, Germany
- Pettenkofer School of Public Health, 81377 Munich, Germany
| | - Carmen Klinger
- Chair of Public Health and Health Services Research, Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), LMU Munich, 81377 Munich, Germany
- Pettenkofer School of Public Health, 81377 Munich, Germany
| | - Jacob Burns
- Chair of Public Health and Health Services Research, Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), LMU Munich, 81377 Munich, Germany
- Pettenkofer School of Public Health, 81377 Munich, Germany
| | - Michaela Coenen
- Chair of Public Health and Health Services Research, Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), LMU Munich, 81377 Munich, Germany
- Pettenkofer School of Public Health, 81377 Munich, Germany
| | - Klaus Lieb
- Leibniz Institute for Resilience Research (LIR), 55122 Mainz, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| |
Collapse
|
16
|
Denkinger CM, Janssen M, Schäkel U, Gall J, Leo A, Stelmach P, Weber SF, Krisam J, Baumann L, Stermann J, Merle U, Weigand MA, Nusshag C, Bullinger L, Schrezenmeier JF, Bornhäuser M, Alakel N, Witzke O, Wolf T, Vehreschild MJGT, Schmiedel S, Addo MM, Herth F, Kreuter M, Tepasse PR, Hertenstein B, Hänel M, Morgner A, Kiehl M, Hopfer O, Wattad MA, Schimanski CC, Celik C, Pohle T, Ruhe M, Kern WV, Schmitt A, Lorenz HM, Souto-Carneiro M, Gaeddert M, Halama N, Meuer S, Kräusslich HG, Müller B, Schnitzler P, Parthé S, Bartenschlager R, Gronkowski M, Klemmer J, Schmitt M, Dreger P, Kriegsmann K, Schlenk RF, Müller-Tidow C. Anti-SARS-CoV-2 antibody-containing plasma improves outcome in patients with hematologic or solid cancer and severe COVID-19: a randomized clinical trial. NATURE CANCER 2023; 4:96-107. [PMID: 36581734 PMCID: PMC9886549 DOI: 10.1038/s43018-022-00503-w] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 11/29/2022] [Indexed: 04/26/2023]
Abstract
Patients with cancer are at high risk of severe coronavirus disease 2019 (COVID-19), with high morbidity and mortality. Furthermore, impaired humoral response renders severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines less effective and treatment options are scarce. Randomized trials using convalescent plasma are missing for high-risk patients. Here, we performed a randomized, open-label, multicenter trial ( https://www.clinicaltrialsregister.eu/ctr-search/trial/2020-001632-10/DE ) in hospitalized patients with severe COVID-19 (n = 134) within four risk groups ((1) cancer (n = 56); (2) immunosuppression (n = 16); (3) laboratory-based risk factors (n = 36); and (4) advanced age (n = 26)) randomized to standard of care (control arm) or standard of care plus convalescent/vaccinated anti-SARS-CoV-2 plasma (plasma arm). No serious adverse events were observed related to the plasma treatment. Clinical improvement as the primary outcome was assessed using a seven-point ordinal scale. Secondary outcomes were time to discharge and overall survival. For the four groups combined, those receiving plasma did not improve clinically compared with those in the control arm (hazard ratio (HR) = 1.29; P = 0.205). However, patients with cancer experienced a shortened median time to improvement (HR = 2.50; P = 0.003) and superior survival with plasma treatment versus the control arm (HR = 0.28; P = 0.042). Neutralizing antibody activity increased in the plasma cohort but not in the control cohort of patients with cancer (P = 0.001). Taken together, convalescent/vaccinated plasma may improve COVID-19 outcomes in patients with cancer who are unable to intrinsically generate an adequate immune response.
Collapse
Affiliation(s)
- Claudia M Denkinger
- Division of Infectious Disease and Tropical Medicine, Department of Infectious Diseases, Heidelberg University Hospital, Heidelberg, Germany.
- Partner site Heidelberg University Hospital, German Center for Infection Research, Heidelberg, Germany.
| | - Maike Janssen
- Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany
| | - Ulrike Schäkel
- Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany
| | - Julia Gall
- NCT Trial Center, National Center for Tumor Diseases, Heidelberg University Hospital and German Cancer Research Center, Heidelberg, Germany
| | - Albrecht Leo
- Institute for Clinical Transfusion Medicine and Cell Therapy Heidelberg, Heidelberg, Germany
| | - Patrick Stelmach
- Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany
| | - Stefan F Weber
- Division of Infectious Disease and Tropical Medicine, Department of Infectious Diseases, Heidelberg University Hospital, Heidelberg, Germany
| | - Johannes Krisam
- Institute of Medical Biometry, University of Heidelberg, Heidelberg, Germany
| | - Lukas Baumann
- Institute of Medical Biometry, University of Heidelberg, Heidelberg, Germany
| | - Jacek Stermann
- Institute of Medical Biometry, University of Heidelberg, Heidelberg, Germany
| | - Uta Merle
- Department of Internal Medicine IV, Heidelberg University Hospital, Heidelberg, Germany
| | - Markus A Weigand
- Department of Anesthesiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Christian Nusshag
- Department of Nephrology, University of Heidelberg, Heidelberg, Germany
| | - Lars Bullinger
- Department of Hematology, Oncology and Tumor Immunology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Jens-Florian Schrezenmeier
- Department of Hematology, Oncology and Tumor Immunology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Martin Bornhäuser
- Department of Internal Medicine I, University Hospital Dresden and Faculty of Medicine Carl Gustav Carus of TU Dresden, Dresden, Germany
| | - Nael Alakel
- Department of Internal Medicine I, University Hospital Dresden and Faculty of Medicine Carl Gustav Carus of TU Dresden, Dresden, Germany
| | - Oliver Witzke
- Department of Infectious Diseases, West German Centre for Infectious Diseases, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Timo Wolf
- Department of Internal Medicine, Infectious Diseases, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt, Germany
| | - Maria J G T Vehreschild
- Department of Internal Medicine, Infectious Diseases, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt, Germany
| | - Stefan Schmiedel
- Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Marylyn M Addo
- Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Partner site Hamburg-Lübeck-Borstel-Riems, German Center for Infection Research, Hamburg, Germany
- University Medical Center Hamburg-Eppendorf, Institute for Infection Research and Vaccine Development, Hamburg, Germany
| | - Felix Herth
- Pneumology and Critical Care Medicine, Thoraxklinik, University of Heidelberg and Translational Lung Research Center, Heidelberg, Germany
| | - Michael Kreuter
- Center for Interstitial and Rare Lung Diseases, Pneumology and Critical Care Medicine, Thoraxklinik, University of Heidelberg and German Center for Lung Research, Heidelberg, Germany
| | - Phil-Robin Tepasse
- Department of Medicine B, Gastroenterology and Hepatology, University Hospital Münster, Münster, Germany
| | | | - Mathias Hänel
- Department of Internal Medicine III, Klinikum Chemnitz, Chemnitz, Germany
| | - Anke Morgner
- Department of Internal Medicine III, Klinikum Chemnitz, Chemnitz, Germany
| | - Michael Kiehl
- Department of Internal Medicine I, Frankfurt (Oder) General Hospital, Frankfurt (Oder), Germany
| | - Olaf Hopfer
- Department of Internal Medicine I, Frankfurt (Oder) General Hospital, Frankfurt (Oder), Germany
| | - Mohammad-Amen Wattad
- Department of Hematology, Oncology, Palliative Care and Stem Cell Transplantation, Klinikum Hochsauerland, Meschede, Germany
| | - Carl C Schimanski
- Department of Internal Medicine II, Klinikum Darmstadt, Darmstadt, Germany
| | - Cihan Celik
- Department of Internal Medicine II, Klinikum Darmstadt, Darmstadt, Germany
| | - Thorsten Pohle
- Department of Internal Medicine I, Klinikum Herford, Herford, Germany
| | - Matthias Ruhe
- Department of Internal Medicine I, Klinikum Herford, Herford, Germany
| | - Winfried V Kern
- Department of Medicine II, Division of Infectious Diseases and Travel Medicine, University Medical Centre Freiburg, Freiburg, Germany
| | - Anita Schmitt
- Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany
| | - Hanns-Martin Lorenz
- Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany
| | | | - Mary Gaeddert
- Division of Infectious Disease and Tropical Medicine, Department of Infectious Diseases, Heidelberg University Hospital, Heidelberg, Germany
| | - Niels Halama
- Department of Medical Oncology, National Center for Tumor Diseases, Heidelberg University Hospital, Heidelberg, Germany
- Department of Translational Immunotherapy (D240), German Cancer Research Center, Heidelberg, Germany
- Helmholtz Institute for Translational Oncology, Mainz, Germany
| | - Stefan Meuer
- Institute for Clinical Transfusion Medicine and Cell Therapy Heidelberg, Heidelberg, Germany
| | - Hans-Georg Kräusslich
- Department of Infectious Diseases, Virology, Heidelberg University Hospital, Heidelberg, Germany
| | - Barbara Müller
- Department of Infectious Diseases, Virology, Heidelberg University Hospital, Heidelberg, Germany
| | - Paul Schnitzler
- Department of Infectious Diseases, Virology, Heidelberg University Hospital, Heidelberg, Germany
| | - Sylvia Parthé
- Department of Infectious Diseases, Virology, Heidelberg University Hospital, Heidelberg, Germany
| | - Ralf Bartenschlager
- Department of Infectious Diseases, Molecular Virology, Heidelberg University Hospital, Heidelberg, Germany
| | - Martina Gronkowski
- Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany
| | - Jennifer Klemmer
- Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany
| | - Michael Schmitt
- Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany
| | - Peter Dreger
- Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany
| | - Katharina Kriegsmann
- Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany
| | - Richard F Schlenk
- Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany
- NCT Trial Center, National Center for Tumor Diseases, Heidelberg University Hospital and German Cancer Research Center, Heidelberg, Germany
- Department of Medical Oncology, National Center for Tumor Diseases, Heidelberg University Hospital, Heidelberg, Germany
| | - Carsten Müller-Tidow
- Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany.
- National Center for Tumor Diseases, Heidelberg, Germany.
| |
Collapse
|
17
|
Styrzynski F, Zhakparov D, Schmid M, Roqueiro D, Lukasik Z, Solek J, Nowicki J, Dobrogowski M, Makowska J, Sokolowska M, Baerenfaller K. Machine Learning Successfully Detects Patients with COVID-19 Prior to PCR Results and Predicts Their Survival Based on Standard Laboratory Parameters in an Observational Study. Infect Dis Ther 2023; 12:111-129. [PMID: 36333475 PMCID: PMC9638383 DOI: 10.1007/s40121-022-00707-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 09/27/2022] [Indexed: 11/06/2022] Open
Abstract
INTRODUCTION In the current COVID-19 pandemic, clinicians require a manageable set of decisive parameters that can be used to (i) rapidly identify SARS-CoV-2 positive patients, (ii) identify patients with a high risk of a fatal outcome on hospital admission, and (iii) recognize longitudinal warning signs of a possible fatal outcome. METHODS This comparative study was performed in 515 patients in the Maria Skłodowska-Curie Specialty Voivodeship Hospital in Zgierz, Poland. The study groups comprised 314 patients with COVID-like symptoms who tested negative and 201 patients who tested positive for SARS-CoV-2 infection; of the latter, 72 patients with COVID-19 died and 129 were released from hospital. Data on which we trained several machine learning (ML) models included clinical findings on admission and during hospitalization, symptoms, epidemiological risk, and reported comorbidities and medications. RESULTS We identified a set of eight on-admission parameters: white blood cells, antibody-synthesizing lymphocytes, ratios of basophils/lymphocytes, platelets/neutrophils, and monocytes/lymphocytes, procalcitonin, creatinine, and C-reactive protein. The medical decision tree built using these parameters differentiated between SARS-CoV-2 positive and negative patients with up to 90-100% accuracy. Patients with COVID-19 who on hospital admission were older, had higher procalcitonin, C-reactive protein, and troponin I levels together with lower hemoglobin and platelets/neutrophils ratio were found to be at highest risk of death from COVID-19. Furthermore, we identified longitudinal patterns in C-reactive protein, white blood cells, and D dimer that predicted the disease outcome. CONCLUSIONS Our study provides sets of easily obtainable parameters that allow one to assess the status of a patient with SARS-CoV-2 infection, and the risk of a fatal disease outcome on hospital admission and during the course of the disease.
Collapse
Affiliation(s)
- Filip Styrzynski
- Department of Rheumatology with Subdepartment of Internal Medicine, Medical University of Lodz, 90-419 Lodz, Poland
| | - Damir Zhakparov
- Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Herman-Burchard-Strasse 9, 7265 Davos, Switzerland ,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Marco Schmid
- University of Applied Sciences of the Grisons, 7000 Chur, Switzerland
| | - Damian Roqueiro
- Swiss Institute of Bioinformatics, Lausanne, Switzerland ,Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland
| | - Zuzanna Lukasik
- Department of Rheumatology with Subdepartment of Internal Medicine, Medical University of Lodz, 90-419 Lodz, Poland ,Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Herman-Burchard-Strasse 9, 7265 Davos, Switzerland
| | - Julia Solek
- Department of Pathology, Chair of Oncology, Medical University of Lodz, 90-419 Lodz, Poland ,Department of Biostatistics and Translational Medicine, Medical University of Lodz, 90-419 Lodz, Poland
| | - Jakub Nowicki
- Department of Paediatrics, Newborn Pathology and Bone Metabolic Diseases, Medical University of Lodz, 90-419 Lodz, Poland
| | - Milosz Dobrogowski
- Maria Sklodowska-Curie Specialty Voivodeship Hospital, 95-100 Zgierz, Poland
| | - Joanna Makowska
- Department of Rheumatology with Subdepartment of Internal Medicine, Medical University of Lodz, 90-419 Lodz, Poland
| | - Milena Sokolowska
- Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Herman-Burchard-Strasse 9, 7265 Davos, Switzerland ,Christine Kühne – Center for Allergy Research and Education (CK-CARE), 7265 Davos, Switzerland
| | - Katja Baerenfaller
- Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Herman-Burchard-Strasse 9, 7265 Davos, Switzerland ,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| |
Collapse
|
18
|
Kyriakoulis KG, Kyriakoulis IG, Trontzas IP, Syrigos N, Kyprianou IA, Fyta E, Kollias A. Cardiac Injury in COVID-19: A Systematic Review of Relevant Meta-Analyses. Rev Cardiovasc Med 2022; 23:404. [PMID: 39076653 PMCID: PMC11270392 DOI: 10.31083/j.rcm2312404] [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: 05/18/2022] [Revised: 09/05/2022] [Accepted: 10/20/2022] [Indexed: 07/31/2024] Open
Abstract
Background Cardiac injury (CI) is not a rare condition among hospitalized patients with coronavirus disease 2019 (COVID-19). Its prognostic value has been extensively reported through the literature, mainly in the context of observational studies. An impressive number of relevant meta-analyses has been conducted. These meta-analyses present similar and consistent results; yet interesting methodological issues emerge. Methods A systematic literature search was conducted aiming to identify all relevant meta-analyses on (i) the incidence, and (ii) the prognostic value of CI among hospitalized patients with COVID-19. Results Among 118 articles initially retrieved, 73 fulfilled the inclusion criteria and were included in the systematic review. Various criteria were used for CI definition mainly based on elevated cardiac biomarkers levels. The most frequently used biomarker was troponin. 30 meta-analyses reported the pooled incidence of CI in hospitalized patients with COVID-19 that varies from 5% to 37%. 32 meta-analyses reported on the association of CI with COVID-19 infection severity, with only 6 of them failing to show a statistically significant association. Finally, 46 meta-analyses investigated the association of CI with mortality and showed that patients with COVID-19 with CI had increased risk for worse prognosis. Four meta-analyses reported pooled adjusted hazard ratios for death in patients with COVID-19 and CI vs those without CI ranging from 1.5 to 3. Conclusions The impact of CI on the prognosis of hospitalized patients with COVID-19 has gained great interest during the pandemic. Methodological issues such as the inclusion of not peer-reviewed studies, the inclusion of potentially overlapping populations or the inclusion of studies with unadjusted analyses for confounders should be taken into consideration. Despite these limitations, the adverse prognosis of patients with COVID-19 and CI has been consistently demonstrated.
Collapse
Affiliation(s)
- Konstantinos G Kyriakoulis
- National and Kapodistrian University of Athens, School of Medicine, Third Department of Medicine, Sotiria Hospital, 11527 Athens, Greece
| | - Ioannis G Kyriakoulis
- National and Kapodistrian University of Athens, School of Medicine, Third Department of Medicine, Sotiria Hospital, 11527 Athens, Greece
| | - Ioannis P Trontzas
- National and Kapodistrian University of Athens, School of Medicine, Third Department of Medicine, Sotiria Hospital, 11527 Athens, Greece
| | - Nikolaos Syrigos
- National and Kapodistrian University of Athens, School of Medicine, Third Department of Medicine, Sotiria Hospital, 11527 Athens, Greece
| | - Ioanna A Kyprianou
- National and Kapodistrian University of Athens, School of Medicine, Third Department of Medicine, Sotiria Hospital, 11527 Athens, Greece
| | - Eleni Fyta
- National and Kapodistrian University of Athens, School of Medicine, Third Department of Medicine, Sotiria Hospital, 11527 Athens, Greece
| | - Anastasios Kollias
- National and Kapodistrian University of Athens, School of Medicine, Third Department of Medicine, Sotiria Hospital, 11527 Athens, Greece
| |
Collapse
|
19
|
Depression, aging, and immunity: implications for COVID-19 vaccine immunogenicity. Immun Ageing 2022; 19:32. [PMID: 35836263 PMCID: PMC9281075 DOI: 10.1186/s12979-022-00288-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 07/06/2022] [Indexed: 11/26/2022]
Abstract
The aging process can have detrimental effects on the immune system rendering the elderly more susceptible to infectious disease and less responsive to vaccination. Major depressive disorder (MDD) has been hypothesized to show characteristics of accelerated biological aging. This raises the possibility that depressed individuals will show some overlap with elderly populations with respect to their immune response to infection and vaccination. Here we provide an umbrella review of this literature in the context of the SARS CoV-2 pandemic. On balance, the available data do indeed suggest that depression is a risk factor for both adverse outcomes following COVID-19 infection and for reduced COVID-19 vaccine immunogenicity. We conclude that MDD (and other major psychiatric disorders) should be recognized as vulnerable populations that receive priority for vaccination along with other at-risk groups.
Collapse
|
20
|
Mertens E, Serrien B, Vandromme M, Peñalvo JL. Predicting COVID-19 progression in hospitalized patients in Belgium from a multi-state model. Front Med (Lausanne) 2022; 9:1027674. [PMID: 36507535 PMCID: PMC9727386 DOI: 10.3389/fmed.2022.1027674] [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: 08/25/2022] [Accepted: 11/03/2022] [Indexed: 11/24/2022] Open
Abstract
Objectives To adopt a multi-state risk prediction model for critical disease/mortality outcomes among hospitalised COVID-19 patients using nationwide COVID-19 hospital surveillance data in Belgium. Materials and methods Information on 44,659 COVID-19 patients hospitalised between March 2020 and June 2021 with complete data on disease outcomes and candidate predictors was used to adopt a multi-state, multivariate Cox model to predict patients' probability of recovery, critical [transfer to intensive care units (ICU)] or fatal outcomes during hospital stay. Results Median length of hospital stay was 9 days (interquartile range: 5-14). After admission, approximately 82% of the COVID-19 patients were discharged alive, 15% of patients were admitted to ICU, and 15% died in the hospital. The main predictors of an increased probability for recovery were younger age, and to a lesser extent, a lower number of prevalent comorbidities. A patient's transition to ICU or in-hospital death had in common the following predictors: high levels of c-reactive protein (CRP) and lactate dehydrogenase (LDH), reporting lower respiratory complaints and male sex. Additionally predictors for a transfer to ICU included middle-age, obesity and reporting loss of appetite and staying at a university hospital, while advanced age and a higher number of prevalent comorbidities for in-hospital death. After ICU, younger age and low levels of CRP and LDH were the main predictors for recovery, while in-hospital death was predicted by advanced age and concurrent comorbidities. Conclusion As one of the very few, a multi-state model was adopted to identify key factors predicting COVID-19 progression to critical disease, and recovery or death.
Collapse
Affiliation(s)
- Elly Mertens
- Unit of Non-Communicable Diseases, Department of Public Health, Institute of Tropical Medicine Antwerp, Antwerp, Belgium,*Correspondence: Elly Mertens,
| | - Ben Serrien
- Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium
| | - Mathil Vandromme
- Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium
| | - José L. Peñalvo
- Unit of Non-Communicable Diseases, Department of Public Health, Institute of Tropical Medicine Antwerp, Antwerp, Belgium
| |
Collapse
|
21
|
Mandal SK, Neupane J, Kumar AMV, Davtyan H, Thekkur P, Jayaram A, Chalise BS, Rawal M, Paudel M, Baral B, Shah RK, Maharjan K, Shrestha S, Bhandari L, K.C. N, Gautam N, Sunny AK, Thakur N, Subeedee KC, Mandal SK, Bastola A. Audit of Clinical Care Received by COVID-19 Patients Treated at a Tertiary Care Hospital of Nepal in 2021. Trop Med Infect Dis 2022; 7:tropicalmed7110381. [PMID: 36422932 PMCID: PMC9698854 DOI: 10.3390/tropicalmed7110381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 11/10/2022] [Accepted: 11/13/2022] [Indexed: 11/18/2022] Open
Abstract
Like the world over, Nepal was also hard hit by the second wave of COVID-19. We audited the clinical care provided to COVID-19 patients admitted from April to June 2021 in a tertiary care hospital of Nepal. This was a cohort study using routinely collected hospital data. There were 620 patients, and most (458, 74%) had severe illness. The majority (600, 97%) of the patients were eligible for admission as per national guidelines. Laboratory tests helping to predict the outcome of COVID-19, such as D-dimer and C-reactive protein, were missing in about 25% of patients. Nearly all (>95%) patients with severe disease received corticosteroids, anticoagulants and oxygen. The use of remdesivir was low (22%). About 70% of the patients received antibiotics. Hospital exit outcomes of most (>95%) patients with mild and moderate illness were favorable (alive and discharged). Among patients with severe illness, about 25% died and 4% were critically ill, needing further referral. This is the first study from Nepal to audit and document COVID-19 clinical care provision in a tertiary care hospital, thus filling the evidence gap in this area from resource-limited settings. Adherence to admission guidelines was excellent. Laboratory testing, access to essential drugs and data management needs to be improved.
Collapse
Affiliation(s)
- Shrawan Kumar Mandal
- Sukraraj Tropical and Infectious Disease Hospital, Ministry of Health and Population, Government of Nepal, Kathmandu 44600, Nepal
- Correspondence: ; Tel.: +977-9841597341
| | - Jenish Neupane
- Sukraraj Tropical and Infectious Disease Hospital, Ministry of Health and Population, Government of Nepal, Kathmandu 44600, Nepal
| | - Ajay M. V. Kumar
- International Union Against Tuberculosis and Lung Disease, 2 Rue Jean Lantier, 75001 Paris, France
- International Union Against Tuberculosis and Lung Disease, South-East Asia Office, C-6 Qutub Institutional Area, New Delhi 110016, The National Capital Territory of Delhi, India
- Yenepoya Medical College, Yenepoya (Deemed to be University), University Road, Deralakatte, Mangaluru 575018, Karnataka, India
| | - Hayk Davtyan
- Tuberculosis Research and Prevention Center, NGO, Yerevan 0014, Armenia
| | - Pruthu Thekkur
- International Union Against Tuberculosis and Lung Disease, 2 Rue Jean Lantier, 75001 Paris, France
- International Union Against Tuberculosis and Lung Disease, South-East Asia Office, C-6 Qutub Institutional Area, New Delhi 110016, The National Capital Territory of Delhi, India
| | - Anup Jayaram
- Manipal Institute of Virology, Manipal, Academy of Higher Education, Manipal, Udupi 576104, Karnataka, India
| | - Bimal Sharma Chalise
- Sukraraj Tropical and Infectious Disease Hospital, Ministry of Health and Population, Government of Nepal, Kathmandu 44600, Nepal
| | - Manisha Rawal
- Sukraraj Tropical and Infectious Disease Hospital, Ministry of Health and Population, Government of Nepal, Kathmandu 44600, Nepal
| | - Manu Paudel
- Sukraraj Tropical and Infectious Disease Hospital, Ministry of Health and Population, Government of Nepal, Kathmandu 44600, Nepal
| | - Bishwodip Baral
- Sukraraj Tropical and Infectious Disease Hospital, Ministry of Health and Population, Government of Nepal, Kathmandu 44600, Nepal
| | - Rajesh Kumar Shah
- Sukraraj Tropical and Infectious Disease Hospital, Ministry of Health and Population, Government of Nepal, Kathmandu 44600, Nepal
| | - Kijan Maharjan
- Sukraraj Tropical and Infectious Disease Hospital, Ministry of Health and Population, Government of Nepal, Kathmandu 44600, Nepal
| | - Sanjay Shrestha
- Sukraraj Tropical and Infectious Disease Hospital, Ministry of Health and Population, Government of Nepal, Kathmandu 44600, Nepal
| | - Lilanath Bhandari
- Sukraraj Tropical and Infectious Disease Hospital, Ministry of Health and Population, Government of Nepal, Kathmandu 44600, Nepal
| | - Nisha K.C.
- Sukraraj Tropical and Infectious Disease Hospital, Ministry of Health and Population, Government of Nepal, Kathmandu 44600, Nepal
| | - Nabaraj Gautam
- Sukraraj Tropical and Infectious Disease Hospital, Ministry of Health and Population, Government of Nepal, Kathmandu 44600, Nepal
| | | | - Nishant Thakur
- Epidemiology and Disease Control Division, Kathmandu 44600, Nepal
| | | | | | - Anup Bastola
- Sukraraj Tropical and Infectious Disease Hospital, Ministry of Health and Population, Government of Nepal, Kathmandu 44600, Nepal
| |
Collapse
|
22
|
Sarri G, Bennett D, Debray T, Deruaz‐Luyet A, Soriano Gabarró M, Largent JA, Li X, Liu W, Lund JL, Moga DC, Gokhale M, Rentsch CT, Wen X, Yanover C, Ye Y, Yun H, Zullo AR, Lin KJ. ISPE-Endorsed Guidance in Using Electronic Health Records for Comparative Effectiveness Research in COVID-19: Opportunities and Trade-Offs. Clin Pharmacol Ther 2022; 112:990-999. [PMID: 35170021 PMCID: PMC9087010 DOI: 10.1002/cpt.2560] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2021] [Accepted: 02/02/2022] [Indexed: 11/08/2022]
Abstract
As the scientific research community along with healthcare professionals and decision makers around the world fight tirelessly against the coronavirus disease 2019 (COVID-19) pandemic, the need for comparative effectiveness research (CER) on preventive and therapeutic interventions for COVID-19 is immense. Randomized controlled trials markedly under-represent the frail and complex patients seen in routine care, and they do not typically have data on long-term treatment effects. The increasing availability of electronic health records (EHRs) for clinical research offers the opportunity to generate timely real-world evidence reflective of routine care for optimal management of COVID-19. However, there are many potential threats to the validity of CER based on EHR data that are not originally generated for research purposes. To ensure unbiased and robust results, we need high-quality healthcare databases, rigorous study designs, and proper implementation of appropriate statistical methods. We aimed to describe opportunities and challenges in EHR-based CER for COVID-19-related questions and to introduce best practices in pharmacoepidemiology to minimize potential biases. We structured our discussion into the following topics: (1) study population identification based on exposure status; (2) ascertainment of outcomes; (3) common biases and potential solutions; and (iv) data operational challenges specific to COVID-19 CER using EHRs. We provide structured guidance for the proper conduct and appraisal of drug and vaccine effectiveness and safety research using EHR data for the pandemic. This paper is endorsed by the International Society for Pharmacoepidemiology (ISPE).
Collapse
Affiliation(s)
| | - Dimitri Bennett
- Takeda Global Evidence and OutcomesTakeda Pharmaceuticals USA, IncCambridgeMassachusettsUSA
- Center for Clinical Epidemiology and BiostatisticsPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Thomas Debray
- Julius Center for Health Sciences and Primary CareUniversity Medical Centre UtrechtUtrechtThe Netherlands
- Smart Data Analysis and StatisticsUtrechtThe Netherlands
| | - Anouk Deruaz‐Luyet
- Global Epidemiology and Real‐World Evidence CoECorporate Medical AffairsBoehringer Ingelheim International GmbHIngelheim‐am‐RheinGermany
| | - Montse Soriano Gabarró
- Bayer Partnerships and Integrated Evidence Generation OfficeIntegrated Evidence Generation & Business InnovationMedical Affairs & PharmacovigilanceBayer AGBerlinGermany
| | | | - Xiaojuan Li
- Department of Population MedicineHarvard Medical School and Harvard Pilgrim Health Care InstituteBostonMassachusettsUSA
| | - Wei Liu
- Division of EpidemiologyOffice of Surveillance and EpidemiologyCenter for Drug Evaluation and Research, Food and Drug AdministrationSilver SpringMarylandUSA
| | - Jennifer L. Lund
- Department of EpidemiologyGillings School of Global Public HealthUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Daniela C. Moga
- Department of Pharmacy Practice and ScienceCollege of PharmacyUniversity of KentuckyLexingtonKentuckyUSA
| | - Mugdha Gokhale
- Department of EpidemiologyGillings School of Global Public HealthUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
- Department of EpidemiologyMerckWest PointPennsylvaniaUSA
| | - Christopher T. Rentsch
- Faculty of Epidemiology and Population HealthDepartment of Non‐communicable Disease EpidemiologyLondon School of Hygiene & Tropical MedicineLondonUK
- Department of Internal MedicineYale School of MedicineNew HavenConnecticutUSA
| | - Xuerong Wen
- Health OutcomesPharmacy PracticeCollege of PharmacyUniversity of Rhode IslandKinstonRhode IslandUSA
| | | | - Yizhou Ye
- Global Epidemiology, Pharmacovigilance and Patient SafetyAbbVie IncNorth ChicagoIllinoisUSA
| | - Huifeng Yun
- Department of EpidemiologyUniversity of Alabama at BirminghamBirminghamAlabamaUSA
| | - Andrew R. Zullo
- Department of Health Services, Policy, and PracticeBrown University School of Public HealthProvidenceRhode IslandUSA
- Department of EpidemiologyBrown University School of Public HealthProvidenceRhode IslandUSA
- Center of Innovation in Long‐Term Services and SupportsProvidence Veterans Affairs Medical CenterProvidenceRhode IslandUSA
- Department of PharmacyLifespan‐Rhode Island HospitalProvidenceRhode IslandUSA
| | - Kueiyu Joshua Lin
- Brigham and Women’s Hospital and Harvard Medical SchoolBostonMassachusettsUSA
| |
Collapse
|
23
|
Monari C, Pisaturo M, Maggi P, Macera M, Di Caprio G, Pisapia R, Gentile V, Fordellone M, Chiodini P, Coppola N. Early predictors of clinical deterioration in a cohort of outpatients with COVID-19 in southern Italy: A multicenter observational study. J Med Virol 2022; 94:5336-5344. [PMID: 35854433 PMCID: PMC9545617 DOI: 10.1002/jmv.28007] [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: 04/30/2022] [Revised: 06/09/2022] [Accepted: 07/17/2022] [Indexed: 12/15/2022]
Abstract
Data regarding early predictors of clinical deterioration in patients with infection of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is still scarce. The aim of the study is to identify early symptoms or signs that may be associated with severe coronavirus disease 2019 (COVID-19). We conducted a multicentre prospective cohort study on a cohort of patients with COVID-19 in home isolation from March 2020 to April 2021. We assessed longitudinal clinical data (fever, dyspnea, need for hospitalization) through video calls at three specific time points: the beginning of symptoms or the day of the first positivity of the nasopharyngeal swab for SARS-CoV-2-RNA (t0 ), and 3 (t3 ) and 7 (t7 ) days after the onset of symptoms. We included 329 patients with COVID-19: 182 (55.3%) males, mean age 53.4 ± 17.4 years, median Charlson comorbidity index (CCI) of 1 (0-3). Of the 329 patients enrolled, 171 (51.98%) had a mild, 81 (24.6%) a moderate, and 77 (23.4%) a severe illness; 151 (45.9%) were hospitalized. Compared to patients with mild COVID-19, moderate and severe patients were older (p < 0.001) and had more comorbidities, especially hypertension (p < 0.001) and cardiovascular diseases (p = 0.01). At t3 and t7 , we found a significant higher rate of persisting fever (≥37°C) among patients with moderate (91.4% and 58.0% at t3 and t7 , respectively; p < 0.001) and severe outcome (75.3% and 63.6%, respectively; p < 0.001) compared to mild COVID-19 outcome (27.5% and 11.7%, respectively; p < 0.001). Factors independently associated with a more severe outcome were persisting fever at t3 and t7 , increasing age, and CCI above 2 points. Persisting fever at t3 and t7 seems to be related to a more severe COVID-19. This data may be useful to assess hospitalization criteria and optimize the use of resources in the outpatient setting.
Collapse
Affiliation(s)
- Caterina Monari
- Department of Mental Health and Public Medicine, Infectious Diseases UnitUniversity of Campania Luigi VanvitelliNaplesItaly
| | - Mariantonietta Pisaturo
- Department of Mental Health and Public Medicine, Infectious Diseases UnitUniversity of Campania Luigi VanvitelliNaplesItaly
| | - Paolo Maggi
- Infectious Disease UnitAORN CasertaCasertaItaly
| | | | | | | | - Valeria Gentile
- Department of Mental Health and Public Medicine, Infectious Diseases UnitUniversity of Campania Luigi VanvitelliNaplesItaly
| | - Mario Fordellone
- Medical Statistics UnitUniversity of Campania Luigi VanvitelliNaplesItaly
| | - Paolo Chiodini
- Medical Statistics UnitUniversity of Campania Luigi VanvitelliNaplesItaly
| | - Nicola Coppola
- Department of Mental Health and Public Medicine, Infectious Diseases UnitUniversity of Campania Luigi VanvitelliNaplesItaly
| | | |
Collapse
|
24
|
Malundo AFG, Abad CLR, Salamat MSS, Sandejas JCM, Poblete JB, Planta JEG, Morales SJL, Gabunada RRW, Evasan ALM, Cañal JPA, Santos JA, Manto JT, Mercado MEP, Rojo RD, Ornos EDB, Alejandria MM. Predictors of mortality among inpatients with COVID-19 infection in a tertiary referral center in the Philippines. IJID REGIONS 2022; 4:134-142. [PMID: 35854825 PMCID: PMC9281405 DOI: 10.1016/j.ijregi.2022.07.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 07/08/2022] [Accepted: 07/11/2022] [Indexed: 01/08/2023]
Abstract
Mortality data were comparable to those of early reports relating to the wild-type SARS-CoV-2. Clinical and laboratory monitoring is critical during the 2nd to 3rd week of illness. Common and inexpensive laboratory tests may aid in the monitoring of patients. Clinical pathways can be adapted to local data, especially in resource-poor settings.
Objectives The aim of this study was to determine the predictors of mortality and describe laboratory trends among adults with confirmed COVID-19. Methods The medical records of adult patients admitted to a referral hospital with COVID-19 were retrospectively reviewed. Demographic and clinical characteristics, and laboratory parameters, were compared between survivors and non-survivors. Predictors of mortality were determined by multivariate analysis. Mean laboratory values were plotted across illness duration. Results Of 1215 patients, 203 (16.7%) had mild, 488 (40.2%) moderate, 183 (15.1%) severe, and 341 (28.1%) critical COVID-19 on admission. In-hospital mortality was 18.2% (0% mild, 6.1% moderate, 15.8% severe, 47.5% critical). Predictors of mortality were age ≥ 60 years, COPD, qSOFA score ≥ 2, WBC > 10 × 109/L, absolute lymphocyte count < 1000, neutrophil ≥ 70%, PaO2/FiO2 ratio ≤ 200, eGFR < 90 mL/min/1.73 m2, LDH > 600 U/L, and CRP > 12 mg/L. Non-survivors exhibited an increase in LDH and decreases in PaO2/FiO2 ratio and eGFR during the 2nd–3rd week of illness. Conclusion The overall mortality rate was high. Predictors of mortality were similar to those of other reports globally. Marked inflammation and worsening pulmonary and renal function were evident among non-survivors by the 2nd–3rd week of illness.
Collapse
|
25
|
De Freitas VM, Chiloff DM, Bosso GG, Teixeira JOP, Hernandes ICDG, Padilha MDP, Moura GC, De Andrade LGM, Mancuso F, Finamor FE, Serodio AMDB, Arakaki JSO, Sartori MGF, Ferreira PRA, Rangel ÉB. A Machine Learning Model for Predicting Hospitalization in Patients with Respiratory Symptoms during the COVID-19 Pandemic. J Clin Med 2022; 11:jcm11154574. [PMID: 35956189 PMCID: PMC9369854 DOI: 10.3390/jcm11154574] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 07/30/2022] [Accepted: 08/01/2022] [Indexed: 12/28/2022] Open
Abstract
A machine learning approach is a useful tool for risk-stratifying patients with respiratory symptoms during the COVID-19 pandemic, as it is still evolving. We aimed to verify the predictive capacity of a gradient boosting decision trees (XGboost) algorithm to select the most important predictors including clinical and demographic parameters in patients who sought medical support due to respiratory signs and symptoms (RAPID RISK COVID-19). A total of 7336 patients were enrolled in the study, including 6596 patients that did not require hospitalization and 740 that required hospitalization. We identified that patients with respiratory signs and symptoms, in particular, lower oxyhemoglobin saturation by pulse oximetry (SpO2) and higher respiratory rate, fever, higher heart rate, and lower levels of blood pressure, associated with age, male sex, and the underlying conditions of diabetes mellitus and hypertension, required hospitalization more often. The predictive model yielded a ROC curve with an area under the curve (AUC) of 0.9181 (95% CI, 0.9001 to 0.9361). In conclusion, our model had a high discriminatory value which enabled the identification of a clinical and demographic profile predictive, preventive, and personalized of COVID-19 severity symptoms.
Collapse
Affiliation(s)
- Victor Muniz De Freitas
- Paulista School of Medicine, Hospital São Paulo, Federal University of São Paulo, São Paulo 04038-901, Brazil
| | - Daniela Mendes Chiloff
- Paulista School of Medicine, Hospital São Paulo, Federal University of São Paulo, São Paulo 04038-901, Brazil
| | - Giulia Gabriella Bosso
- Paulista School of Medicine, Hospital São Paulo, Federal University of São Paulo, São Paulo 04038-901, Brazil
| | | | | | - Maira do Patrocínio Padilha
- Paulista School of Medicine, Hospital São Paulo, Federal University of São Paulo, São Paulo 04038-901, Brazil
| | - Giovanna Corrêa Moura
- Paulista School of Medicine, Hospital São Paulo, Federal University of São Paulo, São Paulo 04038-901, Brazil
| | | | - Frederico Mancuso
- Discipline of Emergency Medicine, Department of Medicine, Paulista School of Medicine, Hospital São Paulo, Federal University of São Paulo, São Paulo 04038-901, Brazil
| | - Francisco Estivallet Finamor
- Discipline of Emergency Medicine, Department of Medicine, Paulista School of Medicine, Hospital São Paulo, Federal University of São Paulo, São Paulo 04038-901, Brazil
| | - Aluísio Marçal de Barros Serodio
- Sector of Bioethics, Department of Surgery, Paulista School of Medicine, Hospital São Paulo, Federal University of São Paulo, São Paulo 04038-901, Brazil
| | - Jaquelina Sonoe Ota Arakaki
- Pneumology Division, Department of Medicine, Paulista School of Medicine, Hospital São Paulo, Federal University of São Paulo, São Paulo 04038-901, Brazil
| | - Marair Gracio Ferreira Sartori
- Department of Obstetrics, Paulista School of Medicine, Hospital São Paulo, Federal University of São Paulo, São Paulo 04038-901, Brazil
| | - Paulo Roberto Abrão Ferreira
- Infectious Disease Division, Department of Medicine, Paulista School of Medicine, Hospital São Paulo, Federal University of São Paulo, São Paulo 04038-901, Brazil
| | - Érika Bevilaqua Rangel
- Nephrology Division, Department of Medicine, Paulista School of Medicine, Hospital São Paulo, Federal University of São Paulo, São Paulo 04038-901, Brazil
- Correspondence:
| |
Collapse
|
26
|
Ganesh R, Vanichkachorn GS, Munipalli B, Hanson SN, Abu Dabrh AM, Croghan IT, Dawson NL, Hurt RT. Postacute Sequelae of SARS-CoV-2 Infection-Lessons Learned From a Coordinated Health System Response. MAYO CLINIC PROCEEDINGS: INNOVATIONS, QUALITY & OUTCOMES 2022; 6:311-319. [PMID: 35669936 PMCID: PMC9156955 DOI: 10.1016/j.mayocpiqo.2022.05.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Objective To outline a consensus-designed process for triaging and managing patients with post-coronavirus disease (COVID-19) syndrome at Mayo Clinic. Patients and Methods We convened a central multidisciplinary team including members from the departments of general internal medicine, occupational medicine, physical medicine and rehabilitation, psychology, allergy and immunology, infectious disease, pulmonology, neurology, cardiology, and pediatrics and otorhinolaryngology with membership from all Mayo Clinic sites in Arizona, Florida, Iowa, Minnesota, and Wisconsin. Results Consensus recommendations were made for the best practice guidelines on triaging and managing patients. Several innovations were agreed upon, including a postacute sequelae of COVID-19-specific appointment request form for data collection, a bioregistry, a biorepository, and a postacute sequelae of COVID-19-specific treatment program. Conclusion Given that each clinical site had individual clinical practices, these recommendations were implemented using different models, which may provide broad applicability to other clinical settings.
Collapse
Key Words
- ARF, appointment request form
- CARP, Coronavirus Disease 2019 Activity Rehabilitation Program
- CFS, chronic fatigue syndrome
- COVID-19, coronavirus disease 2019
- FMS, fibromyalgia
- GIM, general internal medicine
- MC, Mayo Clinic
- MCA, Mayo Clinic Arizona
- MCF, Mayo Clinic Florida
- MCHS, Mayo Clinic Health System
- MCR, Mayo Clinic Rochester
- NIH, National Institutes of Health
- PASC, postacute sequelae of coronavirus disease 2019
- PCOCC, post-COVID-19 care clinic
- POTS, postural orthostatic tachycardia syndrome
- PoCOS, post-COVID-19 syndrome
- Prev Med, Preventative Medicine
- SARS-CoV-2, severe acute respiratory syndrome coronavirus 2
Collapse
Affiliation(s)
- Ravindra Ganesh
- Division of General Internal Medicine, Mayo Clinic, Rochester, MN
| | | | - Bala Munipalli
- Division of General Internal Medicine, Mayo Clinic, Jacksonville, FL
| | | | | | - Ivana T Croghan
- Division of General Internal Medicine, Mayo Clinic, Rochester, MN
| | - Nancy L Dawson
- Division of General Internal Medicine, Mayo Clinic, Jacksonville, FL
| | - Ryan T Hurt
- Division of General Internal Medicine, Mayo Clinic, Rochester, MN
| |
Collapse
|
27
|
Kirsch F, Lindemann AK, Geppert J, Borzekowski D, Lohmann M, Böl GF. Personal Protective Measures during the COVID-19 Pandemic in Germany. Int J Infect Dis 2022; 121:177-183. [PMID: 35597554 PMCID: PMC9113954 DOI: 10.1016/j.ijid.2022.05.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 05/12/2022] [Accepted: 05/13/2022] [Indexed: 01/25/2023] Open
Abstract
OBJECTIVES The coronavirus SARS-CoV-2 is highly contagious and can only be contained if the majority of the population takes measures to protect themselves against infection. The present study aimed to investigate personal protective measures, their development over the course of the pandemic in Germany, and potential differences in behavior in terms of sex, age, and education. METHODS Data from 20 waves of the serial cross-sectional study "BfR-Corona-Monitor" were analyzed. The total sample consisted of N = 20,317 respondents (about 1000 per wave). Data were collected through telephone surveys between June 2020 and March 2021. RESULTS To protect themselves from infection, participants primarily relied on wearing covers for mouth and nose, keeping their distance from other individuals, and washing their hands thoroughly. Analyses over time showed a strong positive correlation between the number of measures taken and the national incidence rate. Sociodemographic differences also emerged, with women and those who are higher educated as well as younger respondents taking a higher number of protective measures. CONCLUSIONS Our results indicated that in times of greater infection risks, individuals adapted accordingly and took more protective measures. However, on the basis of sociodemographic differences, campaigns should especially focus on older individuals, the male sex, and those with lower education to enhance their protective behavior.
Collapse
Affiliation(s)
- Fabian Kirsch
- Corresponding authors. Postal address: Max-Dohrn-Str. 8–10, 10589 Berlin, Germany
| | | | | | | | | | | |
Collapse
|
28
|
SARS-CoV-2 Infection and Vaccination Coverage among Fragile Populations in a Local Health Area of Northern Italy. LIFE (BASEL, SWITZERLAND) 2022; 12:life12071009. [PMID: 35888096 PMCID: PMC9316873 DOI: 10.3390/life12071009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Revised: 06/08/2022] [Accepted: 07/05/2022] [Indexed: 11/17/2022]
Abstract
Italy was dramatically hit by the COVID-19 pandemic, and the province of Brescia was one of the epicenters of the outbreak. Furthermore, Brescia has one of the highest incidences of people living with HIV (PLWH) and a substantial presence of migrants. We conducted a retrospective cohort study involving all citizens connected to the Brescia Health Protection Agency, assessing the SARS-CoV-2 burden, COVID-19 prevalence, and vaccination coverage. A total of 1,004,210 persons were included, 3817 PLWH and 134,492 foreigners. SARS-CoV-2 infection, hospitalizations and death were more frequent among Italians than foreigners. SARS-CoV-2 infections and deaths were more frequent in HIV-uninfected people than in PLWH. PLWH and foreigners were less likely to have a SARS-CoV-2 diagnosis compared to HIV-negative patients. Migrants were more likely to be hospitalized but had a lower risk of death compared to HIV-negative patients. Regarding vaccination, 89.1% of the population received at least one dose of vaccine, while 70.4% of the Italian citizens and 36.3% of the foreigner subjects received three doses of vaccine. Foreigners showed a lower risk of being diagnosed with SARS-CoV-2 but a higher risk of complications. HIV infection was not associated with a higher risk of SARS-CoV-2 severe manifestations compared to the general population. COVID-19 vaccine hesitancy was not different between PLWH and HIV uninfected people, but foreigners were more hesitant.
Collapse
|
29
|
Doherty MT, Aris E, Servotte N, Beck E. Capturing the value of vaccination: impact of vaccine-preventable disease on hospitalization. Aging Clin Exp Res 2022; 34:1551-1561. [PMID: 35633477 PMCID: PMC9142834 DOI: 10.1007/s40520-022-02110-2] [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: 01/26/2022] [Accepted: 03/06/2022] [Indexed: 11/24/2022]
Abstract
Evidence from epidemiological studies suggests that vaccine-preventable disease (VPD) such as influenza or herpes zoster contribute significantly to the increased risk of older adults for cardiovascular, cerebrovascular, neurological, and renal complications in the period after illnesses. However, since the period of elevated risk can persist well beyond the duration of the acute illness, the connection is not always recognized. To obtain insights into the relationship between diagnoses for vaccine-preventable disease and for other conditions, we analyzed principal and secondary diagnoses for 3,127,768 inpatient admissions of adults 50 years and older in the United States, using medical insurance claims drawn from the IBM® MarketScan® Research Databases (Marketscan). The Marketscan data indicated that overall, 3.1% of these hospitalizations had a principal diagnosis of VPD with variation by month of admission, and age. However, hospitalizations with a principal non-VPD diagnosis but secondary VPD diagnoses were 2.8 times more frequent, with particularly high rates in those whose principal diagnoses were non-VPD respiratory or circulatory disease. Hospitalized patients with a secondary VPD diagnosis tended to have poorer discharge outcomes, and longer length of stay in comparison to hospitalized patients without a secondary VPD diagnosis. In total, these data are consistent with suggestions that VPDs play a significant and potentially under-estimated role in hospitalization and outcomes, which may be potentially preventable by improved vaccination coverage.
Collapse
Affiliation(s)
- Mark T Doherty
- GSK, Building W23, 20 Avenue Fleming, 1300, Wavre, Belgium.
| | - Emmanuel Aris
- GSK, Building W23, 20 Avenue Fleming, 1300, Wavre, Belgium
| | | | - Ekkehard Beck
- GSK, Building W23, 20 Avenue Fleming, 1300, Wavre, Belgium
| |
Collapse
|
30
|
Rapin A, Noujaim PJ, Taiar R, Carazo-Mendez S, Deslee G, Jolly D, Boyer FC. Characteristics of COVID-19 Inpatients in Rehabilitation Units during the First Pandemic Wave: A Cohort Study from a Large Hospital in Champagne Region. BIOLOGY 2022; 11:biology11060937. [PMID: 35741459 PMCID: PMC9219626 DOI: 10.3390/biology11060937] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 06/06/2022] [Accepted: 06/14/2022] [Indexed: 06/01/2023]
Abstract
Background: Data describing patients hospitalized in medical rehabilitation wards after the acute phase of COVID-19 could help to better understand the rehabilitation needs in the current pandemic situation. Methods: Cohort including all patients with COVID-19 hospitalized in a single, large university hospital in Northeast France from 25 February to 30 April 2020. Results: 479 patients were admitted with COVID-19 during the study period, of whom 128 died (26.7%). Among the 351 survivors, 111 were referred to rehabilitation units, including 63 (17.9%) referred to physical and rehabilitation medicine (PRM) units. The median age of patients referred to rehabilitation units was 72 years. Patients who had been in intensive care, or who had had a long hospital stay, required referral to PRM units. Two biomarkers were associated with referral to rehabilitation units, namely, elevated troponin (p = 0.03) and impaired renal function (p = 0.03). Age was associated with referral to PRM units (p = 0.001). Conclusions: Almost one-third of COVID-19 patients required post-acute care, but only one-fifth had access to PRM units. The optimal strategy for post-acute management of COVID-19 patients remains to be determined. The need for rehabilitation wards during a pandemic is a primary concern in enabling the long-term functioning of infected patients.
Collapse
Affiliation(s)
- Amandine Rapin
- Faculté de Médecine, Université de Reims Champagne Ardennes, UR 3797 VieFra, 51097 Reims, France; (A.R.); (D.J.); (F.C.B.)
- Service de Médecine Physique et de Réadaptation, Hôpital Sébastopol, CHU de Reims, 51092 Reims, France;
| | - Peter-Joe Noujaim
- Unité D’aide Méthodologique, Pôle Recherche et Santé Publique, Hôpital Robert Debré, CHU de Reims, 51092 Reims, France;
| | - Redha Taiar
- Matériaux et Ingénierie Mécanique MATIM, Université de Reims Champagne Ardennes, CEDEX 2, 51687 Reims, France
| | - Sandy Carazo-Mendez
- Service de Médecine Physique et de Réadaptation, Hôpital Sébastopol, CHU de Reims, 51092 Reims, France;
| | - Gaetan Deslee
- Service des Maladies Respiratoires, Hôpital Maison Blanche, CHU de Reims, 51092 Reims, France;
- Inserm UMR-S1250, P3Cell, University of Reims Champagne-Ardenne, SFR CAP-SANTE, 51092 Reims, France
| | - Damien Jolly
- Faculté de Médecine, Université de Reims Champagne Ardennes, UR 3797 VieFra, 51097 Reims, France; (A.R.); (D.J.); (F.C.B.)
- Unité D’aide Méthodologique, Pôle Recherche et Santé Publique, Hôpital Robert Debré, CHU de Reims, 51092 Reims, France;
| | - François Constant Boyer
- Faculté de Médecine, Université de Reims Champagne Ardennes, UR 3797 VieFra, 51097 Reims, France; (A.R.); (D.J.); (F.C.B.)
- Service de Médecine Physique et de Réadaptation, Hôpital Sébastopol, CHU de Reims, 51092 Reims, France;
| |
Collapse
|
31
|
Takase T, Tsugawa N, Sugiyama T, Ikesue H, Eto M, Hashida T, Tomii K, Muroi N. Association between 25-hydroxyvitamin D levels and COVID-19 severity. Clin Nutr ESPEN 2022; 49:256-263. [PMID: 35623823 PMCID: PMC8994250 DOI: 10.1016/j.clnesp.2022.04.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 03/12/2022] [Accepted: 04/01/2022] [Indexed: 11/05/2022]
Abstract
Background and aims Despite reports on the impact of vitamin D status on coronavirus disease 2019 (COVID-19) severity, the association between low vitamin D status and severe COVID-19 remains unclear. Moreover, researchers have not determined the aforementioned association in Japanese patients. This study aimed to investigate the association between 25-hydroxyvitamin D [25(OH)D] levels and COVID-19 severity in Japanese patients. Methods This retrospective observational study included 117 consecutive patients with COVID-19 admitted to the Kobe City Medical Center General Hospital between October 01, 2020, and January 31, 2021. We measured the serum 25(OH)D levels using blood specimens collected within 5 days of hospital admission using liquid chromatography-tandem mass spectrometry. Results There were 21 (17.9%), 73 (62.4%), 19 (16.2%) and 4 (3.4%) patients with severe deficiency (<10 ng/mL), deficiency (10–<20 ng/mL), insufficiency (20–<30 ng/mL), and sufficiency (≥30 ng/mL) of vitamin D, respectively. In univariate logistic regression analyses, lower serum 25(OH)D levels [odds ratio (OR) 1.18 per 1 ng/mL decrease, 95% confidence interval (CI) 1.04–1.33, p = 0.007] were significantly associated with invasive mechanical ventilation (IMV) or death. In a multivariate logistic regression analysis, low serum 25(OH)D levels [OR 1.22 per 1 ng/mL decrease, 95% CI 1.06–1.40, p = 0.005] were significantly associated with IMV or death. The cut-off value of serum 25(OH)D levels was 10.4 ng/mL, calculated by the receiver operating characteristic curve to detect the requirement for IMV or death. Conclusions To the best of our knowledge, this is the first study to assess the association between vitamin D status and COVID-19 severity in Japanese patients. Low serum 25(OH)D level was detected as an independent risk factor for severe COVID-19 among Japanese patients.
Collapse
|
32
|
Davis JW, Wang B, Tomczak E, Chi-Fu C, Harmouch W, Reynoso D, Keiser P, Cabada MM. Prediction of the need for intensive oxygen supplementation during hospitalisation among subjects with COVID-19 admitted to an academic health system in Texas: a retrospective cohort study and multivariable regression model. BMJ Open 2022; 12:e058238. [PMID: 35361651 PMCID: PMC8971360 DOI: 10.1136/bmjopen-2021-058238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
OBJECTIVE SARS-CoV-2 has caused a pandemic claiming more than 4 million lives worldwide. Overwhelming COVID-19 respiratory failure placed tremendous demands on healthcare systems increasing the death toll. Cost-effective prognostic tools to characterise the likelihood of patients with COVID-19 to progress to severe hypoxemic respiratory failure are still needed. DESIGN We conducted a retrospective cohort study to develop a model using demographic and clinical data collected in the first 12 hours of admission to explore associations with severe hypoxemic respiratory failure in unvaccinated and hospitalised patients with COVID-19. SETTING University-based healthcare system including six hospitals located in the Galveston, Brazoria and Harris counties of Texas. PARTICIPANTS Adult patients diagnosed with COVID-19 and admitted to one of six hospitals between 19 March and 30 June 2020. PRIMARY OUTCOME The primary outcome was defined as reaching a WHO ordinal scale between 6 and 9 at any time during admission, which corresponded to severe hypoxemic respiratory failure requiring high-flow oxygen supplementation or mechanical ventilation. RESULTS We included 329 participants in the model cohort and 62 (18.8%) met the primary outcome. Our multivariable regression model found that lactate dehydrogenase (OR 2.36), Quick Sequential Organ Failure Assessment score (OR 2.26) and neutrophil to lymphocyte ratio (OR 1.15) were significant predictors of severe disease. The final model showed an area under the curve of 0.84. The sensitivity analysis and point of influence analysis did not reveal inconsistencies. CONCLUSIONS Our study suggests that a combination of accessible demographic and clinical information collected on admission may predict the progression to severe COVID-19 among adult patients with mild and moderate disease. This model requires external validation prior to its use.
Collapse
Affiliation(s)
- John W Davis
- School of Public and Population Health Sciences, The University of Texas Medical Branch at Galveston, Galveston, Texas, USA
- School of Medicine, The University of Texas Medical Branch at Galveston, Galveston, Texas, USA
| | - Beilin Wang
- Internal Medicine, The University of Texas Medical Branch at Galveston, Galveston, Texas, USA
| | - Ewa Tomczak
- Internal Medicine, The University of Texas Medical Branch at Galveston, Galveston, Texas, USA
| | - Chia Chi-Fu
- School of Medicine, The University of Texas Medical Branch at Galveston, Galveston, Texas, USA
| | - Wissam Harmouch
- School of Medicine, The University of Texas Medical Branch at Galveston, Galveston, Texas, USA
| | - David Reynoso
- Internal Medicine, The University of Texas Medical Branch at Galveston, Galveston, Texas, USA
| | - Philip Keiser
- Internal Medicine, The University of Texas Medical Branch at Galveston, Galveston, Texas, USA
| | - Miguel Mauricio Cabada
- Internal Medicine, The University of Texas Medical Branch at Galveston, Galveston, Texas, USA
- Medicine, Instituto de Medicina Tropical 'Alexander von Humboldt', Wanchaq, Cusco, Peru
| |
Collapse
|
33
|
Heber S, Pereyra D, Schrottmaier WC, Kammerer K, Santol J, Rumpf B, Pawelka E, Hanna M, Scholz A, Liu M, Hell A, Heiplik K, Lickefett B, Havervall S, Traugott MT, Neuböck MJ, Schörgenhofer C, Seitz T, Firbas C, Karolyi M, Weiss G, Jilma B, Thålin C, Bellmann-Weiler R, Salzer HJF, Szepannek G, Fischer MJM, Zoufaly A, Gleiss A, Assinger A. A Model Predicting Mortality of Hospitalized Covid-19 Patients Four Days After Admission: Development, Internal and Temporal-External Validation. Front Cell Infect Microbiol 2022; 11:795026. [PMID: 35141170 PMCID: PMC8819729 DOI: 10.3389/fcimb.2021.795026] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 12/13/2021] [Indexed: 12/24/2022] Open
Abstract
Objective To develop and validate a prognostic model for in-hospital mortality after four days based on age, fever at admission and five haematological parameters routinely measured in hospitalized Covid-19 patients during the first four days after admission. Methods Haematological parameters measured during the first 4 days after admission were subjected to a linear mixed model to obtain patient-specific intercepts and slopes for each parameter. A prediction model was built using logistic regression with variable selection and shrinkage factor estimation supported by bootstrapping. Model development was based on 481 survivors and 97 non-survivors, hospitalized before the occurrence of mutations. Internal validation was done by 10-fold cross-validation. The model was temporally-externally validated in 299 survivors and 42 non-survivors hospitalized when the Alpha variant (B.1.1.7) was prevalent. Results The final model included age, fever on admission as well as the slope or intercept of lactate dehydrogenase, platelet count, C-reactive protein, and creatinine. Tenfold cross validation resulted in a mean area under the receiver operating characteristic curve (AUROC) of 0.92, a mean calibration slope of 1.0023 and a Brier score of 0.076. At temporal-external validation, application of the previously developed model showed an AUROC of 0.88, a calibration slope of 0.95 and a Brier score of 0.073. Regarding the relative importance of the variables, the (apparent) variation in mortality explained by the six variables deduced from the haematological parameters measured during the first four days is higher (explained variation 0.295) than that of age (0.210). Conclusions The presented model requires only variables routinely acquired in hospitals, which allows immediate and wide-spread use as a decision support for earlier discharge of low-risk patients to reduce the burden on the health care system. Clinical Trial Registration Austrian Coronavirus Adaptive Clinical Trial (ACOVACT); ClinicalTrials.gov, identifier NCT04351724.
Collapse
Affiliation(s)
- Stefan Heber
- Institute of Physiology, Centre of Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
| | - David Pereyra
- Department of Vascular Biology and Thrombosis Research, Centre of Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
- Department of General Surgery, Division of Visceral Surgery, Medical University of Vienna, General Hospital Vienna, Vienna, Austria
| | - Waltraud C. Schrottmaier
- Department of Vascular Biology and Thrombosis Research, Centre of Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Kerstin Kammerer
- Department of Vascular Biology and Thrombosis Research, Centre of Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Jonas Santol
- Department of Vascular Biology and Thrombosis Research, Centre of Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
- Department of General Surgery, Division of Visceral Surgery, Medical University of Vienna, General Hospital Vienna, Vienna, Austria
| | - Benedikt Rumpf
- Department of Medicine IV, Kaiser Franz Josef Hospital, Vienna, Austria
| | - Erich Pawelka
- Department of Medicine IV, Kaiser Franz Josef Hospital, Vienna, Austria
| | - Markus Hanna
- Department of Vascular Biology and Thrombosis Research, Centre of Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Alexander Scholz
- Department of Vascular Biology and Thrombosis Research, Centre of Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Markus Liu
- Department of Vascular Biology and Thrombosis Research, Centre of Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Agnes Hell
- Department of Vascular Biology and Thrombosis Research, Centre of Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Klara Heiplik
- Department of Vascular Biology and Thrombosis Research, Centre of Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Benno Lickefett
- Department of Vascular Biology and Thrombosis Research, Centre of Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Sebastian Havervall
- Division of Internal Medicine, Department of Clinical Sciences, Karolinska Institutet, Danderyd Hospital, Stockholm, Sweden
| | | | - Matthias J. Neuböck
- Department of Pulmonology, Kepler University Hospital and Johannes Kepler University, Linz, Austria
| | - Christian Schörgenhofer
- Department of Clinical Pharmacology, Medical University of Vienna, General Hospital Vienna, Vienna, Austria
| | - Tamara Seitz
- Department of Medicine IV, Kaiser Franz Josef Hospital, Vienna, Austria
| | - Christa Firbas
- Department of Clinical Pharmacology, Medical University of Vienna, General Hospital Vienna, Vienna, Austria
| | - Mario Karolyi
- Department of Medicine IV, Kaiser Franz Josef Hospital, Vienna, Austria
| | - Günter Weiss
- Department of Internal Medicine II, Medical University of Innsbruck, Innsbruck, Austria
| | - Bernd Jilma
- Department of Clinical Pharmacology, Medical University of Vienna, General Hospital Vienna, Vienna, Austria
| | - Charlotte Thålin
- Division of Internal Medicine, Department of Clinical Sciences, Karolinska Institutet, Danderyd Hospital, Stockholm, Sweden
| | - Rosa Bellmann-Weiler
- Department of Internal Medicine II, Medical University of Innsbruck, Innsbruck, Austria
| | - Helmut J. F. Salzer
- Department of Pulmonology, Kepler University Hospital and Johannes Kepler University, Linz, Austria
| | - Gero Szepannek
- Institute of Applied Computer Science, Stralsund University of Applied Sciences, Stralsund, Germany
| | - Michael J. M. Fischer
- Institute of Physiology, Centre of Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Alexander Zoufaly
- Department of Medicine IV, Kaiser Franz Josef Hospital, Vienna, Austria
| | - Andreas Gleiss
- Section for Clinical Biometrics, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria
| | - Alice Assinger
- Department of Vascular Biology and Thrombosis Research, Centre of Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
| |
Collapse
|
34
|
Abstract
PURPOSE Low dose radiation therapy (LDRT) using doses in the range of 30-150 cGy has been proposed as a means of mitigating the pneumonia associated with COVID-19. However, preliminary results from ongoing clinical trials have been mixed. The aim of this work is to develop a mathematical model of the viral infection and associated systemic inflammation in a patient based on the time evolution of the viral load. The model further proposes an immunomodulatory response to LDRT based on available data. Inflammation kinetics are then explored and compared to clinical results. METHODS The time evolution of a viral infection, inflammatory signaling factors, and inflammatory response are modeled by a set of coupled differential equations. Adjustable parameters are taken from the literature where available and otherwise iteratively adjusted to fit relevant data. Simple functions modeling both the suppression of pro-inflammatory signal factors and the enhancement of anti-inflammatory factors in response to low doses of radiation are developed. The inflammation response is benchmarked against C-reactive protein (CRP) levels measured for cohorts of patients with severe COVID-19. RESULTS The model fit the time-evolution of viral load data, cytokine data, and inflammation (CRP) data. When LDRT was applied early, the model predicted a reduction in peak inflammation consistent with the difference between the non-surviving and surviving cohorts. This reduction of peak inflammation diminished as the application of LDRT was delayed. CONCLUSION The model tracks the available data on viral load, cytokine levels, and inflammatory biomarkers well. An LDRT effect is large enough in principle to provide a life-saving immunomodulatory effect, though patients treated with LDRT already near the peak of their inflammation trajectory are unlikely to see drastic reductions in that peak. This result potentially explains some discrepancies in the preliminary clinical trial data.
Collapse
Affiliation(s)
- Charles Kirkby
- Department of Medical Physics, Jack Ady Cancer Centre, Lethbridge, Alberta, Canada.,Department of Oncology, University of Calgary, Calgary, Alberta, Canada.,Department of Physics and Astronomy, University of Calgary, Calgary, Alberta, Canada
| |
Collapse
|
35
|
Mahmoudabadi HZ, Hadadi A, Fattahi MR, Kafan S, Ashouri M, Allahbeigi R, Hajebi R. Rectus Sheath Hematoma in COVID-19 Patients as a Mortal Complication: A Retrospective Report. Int J Clin Pract 2022; 2022:7436827. [PMID: 35685571 PMCID: PMC9159132 DOI: 10.1155/2022/7436827] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 12/21/2021] [Accepted: 01/28/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Rectus sheath hematoma is a rare self-limited presentation that has become a concern in hospitalized COVID-19 patients receiving anticoagulant therapies. METHOD A retrospective multicentric study was conducted in referral hospitals affiliated with the Tehran University of Medical Science, Tehran, Iran, between June and August 2021. Patients with a confirmed diagnosis of COVID-19 that were complicated with rectus sheath hematoma during hospitalization were included. Median (lower quartile to upper quartile) was used to report the distribution of the results. RESULT This study was conducted on nine patients with confirmed COVID-19 pneumonia, including eight females and one male. The severity of viral pneumonia was above average in eight patients. The median age and median body mass index were 65 (55.5 to 78) years and 29.38 (23.97 to 31.71) kg/m2. The duration of anticoagulant therapy was 10 (6 to 14) days, and the median length of hospital stay was 20 (10 to 23.5) days. Rectus sheath hematoma occurred after a median reduction of 4 (2.7 to 6.6) units in blood hemoglobin. Although 66.7% received ICU care and all of them were under full observation in well-equipped hospitals, the mortality rate was 55.6%. CONCLUSION In summary, increased levels of inflammatory markers such as lactic acid dehydrogenase along with an abrupt decrease in blood hemoglobin in COVID-19 patients should be considered as predisposing factors for rectus sheath hematoma, especially in patients with moderate to severe COVID-19 pneumonia under anticoagulant therapy. This complication had been considered a self-limited condition; however, it seems to be fatal in patients with COVID-19 pneumonia. Further studies in larger sample sizes should be conducted to find out suitable management for this complication.
Collapse
Affiliation(s)
| | - Azar Hadadi
- Department of Infectious Diseases, Sina Hospital, Tehran University of Medical Sciences, Tehran, Iran
- Virology Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Reza Fattahi
- Department of Surgery, Sina Hospital, Tehran University of Medical Sciences, Tehran, Iran
- Virology Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Samira Kafan
- Department of Pulmonary Disease, Sina Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Ashouri
- Department of Surgery, Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Rashad Allahbeigi
- Department of Surgery, Sina Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Reza Hajebi
- Department of Surgery, Sina Hospital, Tehran University of Medical Sciences, Tehran, Iran
| |
Collapse
|
36
|
Kasapoglu B, Yozgat A, Tanoglu A, Can G, Sakin YS, Kekilli M. Gamma-glutamyl-transferase may predict COVID-19 outcomes in hospitalised patients. Int J Clin Pract 2021; 75:e14933. [PMID: 34605109 PMCID: PMC8646326 DOI: 10.1111/ijcp.14933] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Accepted: 10/01/2021] [Indexed: 01/08/2023] Open
Abstract
AIM In this study, we aimed to define the predictive role of liver function tests at admission to the hospital in outcomes of hospitalised patients with COVID-19. MATERIAL AND METHOD In this multicentric retrospective study, a total of 269 adult patients (≥18 years of age) with confirmed COVID-19 who were hospitalised for the treatment were enrolled. Demographic features, complete medical history and laboratory findings of the study participants at admission were obtained from the medical records. Patients were grouped regarding their intensive care unit (ICU) requirements during their hospitalisation periods. RESULTS Among all 269 participants, 106 were hospitalised in the ICU and 66 died. The patients hospitalised in ICU were older than patients hospitalised in wards (P = .001) and expired patients were older than alive patients (P = .001). Age, elevated serum D-dimer, creatinine and gamma-glutamyl transferase (GGT) levels at admission were independent factors predicting ICU hospitalisation and mortality in COVID-19 patients. CONCLUSION In conclusion, in hospitalised patients with COVID-19, laboratory data on admission, including serum, creatinine, GGT and d-dimer levels have an important predictive role for the ICU requirement and mortality. Since these tests are readily available in all hospitals and inexpensive, some predictive formulas may be calculated with these parameters at admission, to define the patients requiring intensive care.
Collapse
Affiliation(s)
- Benan Kasapoglu
- Department of GastroenterologyFaculty of MedicineLokman Hekim UniversityAnkaraTurkey
| | - Ahmet Yozgat
- Department of GastroenterologyFaculty of MedicineUfuk UniversityAnkaraTurkey
| | - Alpaslan Tanoglu
- Department of GastroenterologySancaktepe Şehit Prof. Dr. İlhan Varank Training and Research HospitalUniversity of Health SciencesIstanbulTurkey
| | - Guray Can
- Department of GastroenterologyFaculty of MedicineAbant İzzet Baysal UniversityBoluTurkey
| | - Yusuf Serdar Sakin
- Department of GastroenterologyGulhane Training and Research HospitalUniversity of Health SciencesAnkaraTurkey
| | - Murat Kekilli
- Department of GastroenterologyFaculty of MedicineGazi UniversityAnkaraTurkey
| |
Collapse
|
37
|
Koutroulos MV, Bakola SA, Kalpakidis S, Avramidou D, Panagaris S, Melissopoulou E, Souleiman H, Partsalidis A, Metaxa E, Feresiadis I, Kampaki E, Papadopoulos V. The MaD-CLINYC score: An easy tool for the prediction of the outcome of hospitalized COVID-19 patients. Hippokratia 2021; 25:119-125. [PMID: 36683905 PMCID: PMC9851139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
BACKGROUND Most outcome-predictive models for COVID-19 patients use hospital admission data, offering a spontaneous mortality risk estimation. We aimed to elaborate on a tool that could be applied repeatedly, thus being more suitable for these patients' rapidly changing clinical course. METHODS In this prospective study, we evaluated 560 samples derived from 156 patients hospitalized for COVID-19 in a single center. Age >61 years, male sex, comorbidities >2, need for intensive care unit admission, lactate dehydrogenase (LDH) >408 U/L, Neutrophil/Lymphocyte Ratio (NLR) >17, C-reactive protein (CRP) >10 mg/dl, and D-dimers >3,200 ng/ml were incorporated in an eight-scale score (MaD-CLINYC) after optimal scaling, ridge regression, and bootstrapping, which was documented to correlate with outcome independently of one or more samples analyzed, day from admission at sampling, and need for delivery. Validation process was performed over 574 samples derived from three centers. RESULTS The developing and the validation cohort Area under Curve (AUC) was 0.90 (95 % Confidence Interval: 0.82-0.98) and 0.91 (0.88-0.94), respectively (p =0.822). A MaD-CLINYC score ≥4 had 75 % sensitivity and 81 % specificity to predict fatal outcome. CONCLUSIONS MaD-CLINYC score is a powerful, feasible, easy-to-use, dynamic tool to assess the risk of the outcome, thus assisting clinicians in close monitoring and timely decisions in COVID-19 hospitalized patients. HIPPOKRATIA 2021, 25 (3):119-125.
Collapse
Affiliation(s)
- M V Koutroulos
- Department of Internal Medicine, Xanthi General Hospital, Xanthi, Greece
| | - S A Bakola
- Department of Internal Medicine, Xanthi General Hospital, Xanthi, Greece
| | - S Kalpakidis
- Department of Internal Medicine, Xanthi General Hospital, Xanthi, Greece
| | - D Avramidou
- Department of Internal Medicine, Xanthi General Hospital, Xanthi, Greece
| | - S Panagaris
- Department of Internal Medicine, Xanthi General Hospital, Xanthi, Greece
| | - E Melissopoulou
- Department of Internal Medicine, Xanthi General Hospital, Xanthi, Greece
| | - H Souleiman
- Department of Internal Medicine, Xanthi General Hospital, Xanthi, Greece
| | - A Partsalidis
- Department of Internal Medicine, Xanthi General Hospital, Xanthi, Greece
| | - E Metaxa
- Department of Internal Medicine, Xanthi General Hospital, Xanthi, Greece
| | - I Feresiadis
- Department of Internal Medicine, Xanthi General Hospital, Xanthi, Greece
| | - E Kampaki
- Department of Internal Medicine, Xanthi General Hospital, Xanthi, Greece
| | - V Papadopoulos
- Department of Internal Medicine, Xanthi General Hospital, Xanthi, Greece
| |
Collapse
|