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MeSH Disease

COVID-19 (489)

Fever (101)

Pneumonia (94)

Death (80)

Hypertension (72)


HGNC Genes

SARS-CoV-2 proteins

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ProteinS (2)

ORF1ab (1)

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    ABC2 HGNC-SPH risk score for in-hospital mortality in COVID-19 MESHD patients: development, external validation and comparison with other available scores

    Authors: Milena Soriano Marcolino; Magda Carvalho Pires; Lucas Emanuel Ferreira Ramos; Rafael Tavares Silva; Luana Martins Oliveira; Rafael Lima Rodrigues de Carvalho; Rodolfo Lucas Silva Mourato; Adrian Sanchez Montalva; Berta Raventos; Fernando Anschau; Jose Miguel Chatkin; Matheus Carvalho Alves Nogueira; Milton Henriques Guimaraes Junior; Giovanna Grunewald Vietta; Helena Duani; Daniela Ponce; Patricia Klarmann Ziegelmann; Luis Cesar de Castro; Karen Brasil Ruschel; Christiane Correa Rodrigues Cimini; Saionara Cristina Francisco; Maiara Anschau Floriani; Guilherme Fagundes Nascimento; Barbara Lopes Farace; Luanna da Silva Monteiro; Maira Viana Rego Souza e Silva; Thais Lorenna Souza Sales; Karina Paula Medeiros Prado Martins; Israel Junior Borges do Nascimento; Tatiani Oliveira Fereguetti; Daniel Taiar Marinho Oliveira Ferrara; Fernando Antonio Botoni; Ana Paula Beck da Silva Etges; Eric Boersma; Carisi Anne Polanczyk; Alexandre Vargas Schwarbold; Amanda Oliveira Maurilio; Ana Luiza Bahia Alves Scotton; Andre Pinheiro Weber; Andre Soares de Moura Costa; Andressa Barreto Glaeser; Angelica Aparecida Coelho Madureira; Angelinda Rezende Bhering; Bruno Mateus Castro; Carla Thais Candida Alves da Silva; Carolina Marques Ramos; Caroline Danubia Gomes; Cintia Alcantara de Carvalho; Daniel Vitorio Silveira; Diego Henrique de Vasconcelos; Edilson Cezar; Elayne Crestani Pereira; Emanuele Marianne Souza Kroger; Felipe Barbosa Vallt; Fernanda Barbosa Lucas; Fernando Graca Aranha; Frederico Bartolazzi; Gabriela Petry Crestani; Gisele Alsina Nader Bastos; Glicia Cristina de Castro Madeira; Helena Carolina Noal; Heloisa Reniers Vianna; Henrique Cerqueira Guimaraes; Isabela Moraes Gomes; Israel Molina Romero; Joanna dArc Lyra Batista; Joice Coutinho de Alvarenga; Julia Di Sabatino Santos Guimaraes; Julia Drumond Parreiras de Morais; Juliana Machado Rugolo; Karen Cristina Jung Rech Pontes; Kauane Aline Maciel dos Santos; Leonardo Seixas de Oliveira; Lilian Santos Pinheiro; Liliane Souto Pacheco; Lucas de Deus Sousa; Luciana Siuves Ferreira Couto; Luciane Kopittke; Luis Cesar Souto de Moura; Luisa Elem Almeida Santos; Maderson Alvares de Souza Cabral; Maira Dias Souza; Marcela Goncalves Trindade Tofani; Marcelo Carneiro; Marcus Vinicius de Melo Andrade; Maria Angelica Pires Ferreira; Maria Aparecida Camargos Bicalho; Maria Clara Pontello Barbosa Lima; Mariana Frizzo de Godoy; Marilia Mastrocolla de Almeida Cardoso; Meire Pereira de Figueiredo; Natalia da Cunha Severino Sampaio; Natalia Lima Rangel; Natalia Trifiletti Crespo; Neimy Ramos de Oliveira; Pedro Ledic Assaf; Petronio Jose de Lima Martelli; Rafaela dos Santos Charao de Almeida; Raphael Castro Martins; Raquel Lutkmeier; Reginaldo Aparecido Valacio; Renan Goulart Finger; Ricardo Bertoglio Cardoso; Roberta Pozza; Roberta Xavier Campos; Rochele Mosmann Menezes; Roger Mendes de Abreu; Rufino de Freitas Silva; Silvana Mangeon Mereilles Guimaraes; Silvia Ferreira Araujo; Susany Anastacia Pereira; Talita Fischer Oliveira; Tatiana Kurtz; Thainara Conceicao de Oliveira; Thaiza Simonia Marinho Albino de Araujo; Thulio Henrique Oliveira Diniz; Veridiana Baldon dos Santos Santos; Virginia Mara Reis Gomes; Vitor Augusto Lima do Vale; Yuri Carlotto Ramires

    doi:10.1101/2021.02.01.21250306 Date: 2021-02-03 Source: medRxiv

    Objective: To develop and validate a rapid scoring system at hospital admission for predicting in-hospital mortality in patients hospitalized with coronavirus disease MESHD 19 ( COVID-19 MESHD), and to compare this score with other existing ones. Design: Cohort study Setting: The Brazilian COVID-19 MESHD Registry has been conducted in 36 Brazilian hospitals in 17 cities. Logistic regression analysis was performed to develop a prediction model for in-hospital mortality, based on the 3978 patients that were admitted between March-July, 2020. The model was then validated in the 1054 patients admitted during August-September, as well as in an external cohort of 474 Spanish patients. Participants: Consecutive symptomatic patients ([≥]18 years old) with laboratory confirmed COVID-19 MESHD admitted to participating hospitals. Patients who were transferred between hospitals and in whom admission data from the first hospital or the last hospital were not available were excluded, as well those who were admitted for other reasons and developed COVID-19 MESHD symptoms during their stay. Main outcome measures: In-hospital mortality Results: Median (25th-75th percentile) age of the model-derivation cohort was 60 (48-72) years, 53.8% were men, in-hospital mortality was 20.3%. The validation cohorts had similar age distribution and in-hospital mortality. From 20 potential predictors, seven significant variables were included in the in-hospital mortality risk score: age, blood urea nitrogen, number of comorbidities, C-reactive protein HGNC, SpO2/FiO2 ratio, platelet count and heart rate. The model had high discriminatory value (AUROC 0.844, 95% CI 0.829 to 0.859), which was confirmed in the Brazilian (0.859) and Spanish (0.899) validation cohorts. Our ABC2 HGNC-SPH score showed good calibration in both Brazilian cohorts, but, in the Spanish cohort, mortality was somewhat underestimated in patients with very high (>25%) risk. The ABC2 HGNC-SPH score is implemented in a freely available online risk calculator (https://abc2sph.com/). Conclusions: We designed and validated an easy-to-use rapid scoring system based on characteristics of COVID-19 MESHD patients commonly available at hospital presentation, for early stratification for in-hospital mortality risk of patients with COVID-19 MESHD.

    SEVERE COVID-19 MESHD IS MARKED BY DYSREGULATED SERUM LEVELS OF CARBOXYPEPTIDASE A3 HGNC AND SEROTONIN MESHD

    Authors: Rodolfo Soria-Castro; Yatsiri G. Meneses-Preza; Gloria M. Rodriguez-Lopez; Sandra Romero-Ramirez; Victor A. Sosa-Hernandez; Rodrigo Cervantes-Diaz; Alfredo Perez-Fragoso; Jose J Torres-Ruiz; Diana Gomez-Martin; Marcia Campillo-Navarro; Violeta D. Alvarez-Jimenez; Sonia M. Perez-Tapia; Alma D. Chavez-Blanco; Sergio Estrada-Parra; Jose L. Maravillas-Montero; Rommel Chacon-Salinas

    doi:10.1101/2021.02.02.21251020 Date: 2021-02-03 Source: medRxiv

    The immune response plays a critical role in the pathophysiology of SARS-CoV-2 infection MESHD ranging from protection to tissue damage. This is observed in the development of acute respiratory distress syndrome MESHD when elevated levels of inflammatory cytokines are detected. Several cells of the immune response are implied in this dysregulated immune response including innate immune cells and T and B cell lymphocytes. Mast cells are abundant resident cells of the respiratory tract, able to rapidly release different inflammatory mediators following stimulation. Recently, mast cells have been associated with tissue damage during viral infections, but little is known about their role in SARS-CoV-2 infection MESHD. In this study we examined the profile of mast cell activation markers in the serum of COVID-19 MESHD patients. We noticed that SARS-CoV-2 infected MESHD patients showed increased carboxypeptidase A3 HGNC ( CPA3 HGNC), and decreased serotonin levels in their serum. CPA3 HGNC levels correlated with C-reactive protein HGNC, the number of circulating neutrophils and quick SOFA. CPA3 HGNC in serum was a good biomarker for identifying severe COVID-19 MESHD patients, while serotonin was a good predictor of SARS-CoV-2 infection MESHD. In summary, our results show that serum CPA3 HGNC and serotonin levels are relevant biomarkers during SARS-CoV-2 infection MESHD, suggesting that mast cells are relevant players in the inflammatory response in COVID-19 MESHD, might represent targets for therapeutic intervention.

    Prognosis and hematological findings in patients with COVID-19 MESHD in an Amazonian population of Peru

    Authors: Sebastian Iglesias-Osores; Arturo Rafael-Heredia; Eric Ricardo Rojas-Tello; Washington A. Ortiz-Uribe; Walter Leveau-Bartra; Orison Armando Leveau-Bartra; Miguel Alcantara-Mimbela; Lizbeth M. Cordova-Rojas; Elmer Lopez-Lopez; Virgilio E. Failoc-Rojas

    doi:10.1101/2021.01.31.21250859 Date: 2021-02-01 Source: medRxiv

    Objective: This study examined the laboratory results of COVID-19 MESHD patients from a hospital in the Peruvian Amazon and their clinical prognosis. Methods: An analytical cross-sectional study was carried out whose purpose was to identify the laboratory tests of patients with COVID-19 MESHD and mortality in a hospital in Ucayali, Peru during the period from March 13 to May 9, 2020, selecting a total of 127 with Covid-19 MESHD. Mean and the standard deviation was described for age, leukocytes, neutrophils, platelets, RDW-SD; median and interquartile range for the variables lymphocyte, RN / L, fibrinogen HGNC, CRP HGNC, D-dimer, DHL, hematocrit, monocytes, eosinophils. Results: No differences were observed in this population regarding death MESHD and sex (OR: 1.31; 95% CI 0.92 to 1.87), however, it was observed that, for each one-year increase, the probability of death increased by 4% (PR: 1.04, 95% CI 1.03 to 1.05). The IRR HGNC (Incidence Risk Ratio) analysis for the numerical variables showed results strongly associated with hematological values such as Leukocytes (scaled by 2500 units) ( IRR HGNC: 1.08, 95% CI 1.03 to 1.13), neutrophils (scaled by 2500 units) ( IRR HGNC: 1.08; 95% CI 1.03 to 1.13), on the contrary, it is observed that the increase of 1000 units in lymphocytes, the probability of dying decreased by 48% ( IRR HGNC: 0.52; 95% CI 0.38 to 071). Conclusion: Parameters such as leukocytes and neutrophils were statistically much higher in patients who died.

    Predicting Prognosis in COVID-19 MESHD Patients using Machine Learning and Readily Available Clinical Data

    Authors: Thomas W Campbell; Melissa P Wilson; Heinrich Roder; Samantha MaWhinney; Robert W Georgantas III; Laura K Maguire; Joanna Roder; Kristine M Erlandson

    doi:10.1101/2021.01.29.21250762 Date: 2021-02-01 Source: medRxiv

    RationalePrognostic tools for aiding in the treatment of hospitalized COVID-19 MESHD patients could help improve outcome by identifying patients at higher or lower risk of severe disease. ObjectivesThe study objective was to develop models to stratify patients by risk of severe outcomes during COVID-19 MESHD hospitalization using readily available information at hospital admission. MethodsHierarchical ensemble classification models were trained on a set of 229 patients hospitalized with COVID-19 MESHD to predict severe outcomes, including ICU admission, development of ARDS, or intubation, using easily attainable attributes including basic patient characteristics, vital signs at admission, and basic lab results collected at time of presentation. Each test stratifies patients into groups of increasing risk. An additional cohort of 330 patients was used for blinded, independent validation. Shapley value analysis evaluated which attributes contributed most to the models predictions of risk. Measurements and Main ResultsTest performance was assessed using precision (positive predictive value) and recall (sensitivity) of the final risk groups. All test cut-offs were fixed prior to blinded validation. In both development and validation, the tests achieved precision in the lowest risk groups near or above 0.9. The proportion of patients with severe outcomes significantly increased across increasing risk groups. While the importance of attributes varied by test and patient, CRP HGNC, LDH, and D-dimer were often found to be important in the assignment of risk label. ConclusionsRisk of severe outcomes for patients hospitalized with COVID-19 MESHD infection can be assessed using machine learning-based models based on attributes routinely collected at hospital admission.

    Therapeutic efficacy of macrolides in management of patients with mild COVID-19 MESHD

    Authors: Alaa Rashad; Asmaa Nafady; Mohammed H. Hassan; Haggagy Mansour; Usama Taya; Shamardan Ezzeldin S. Bazeed; Zaki F. Aref; Mennatallah Ali Abdelrahman Sayed; Hanaa Nafady-Hego; Aida A. Abdelmaksoud

    doi:10.21203/rs.3.rs-181996/v1 Date: 2021-01-29 Source: ResearchSquare

    Evidence on the efficacy of adding macrolides (azithromycin or clarithromycin) to the treatment regimen for COVID-19 MESHD is limited. We testify whether adding azithromycin or clarithromycin to a standard of care regimen was superior to standard of supportive care alone in patients with mild COVID-19 MESHD.The study included three groups of patients with COVID-19 MESHD. The azithromycin group included, 107 patients who received azithromycin 500 mg/24 h for 7 days, the clarithromycin group included 99 patients who received clarithromycin 500 /12 h for 7 days, and the control group included 99 patients who received standard care only. All three groups received only symptomatic treatment for control of fever MESHD and cough MESHD .Clinical and laboratory evaluations of the study participants including assessment of the symptoms duration, real-time reverse transcription-polymerase chain reaction (rRT-PCR), C-reactive protein HGNC ( CRP HGNC), serum ferritin, D-dimer, complete blood count (CBC), non-contrast chest computed tomography (CT), were performed.The overall results revealed significant early improvement of symptoms ( fever MESHD, dyspnea MESHD and cough MESHD) in patients treated with either azithromycin or clarithromycin compared to control group, also there was significant early conversion of SARS-CoV-2 PCR to negative in patients treated with either azithromycin or clarithromycin compared to control group (p˂0.05 for all).There was no significant difference in time to improvement of fever MESHD, cough MESHD, dyspnea MESHD, anosmia MESHD, GIT symptoms and time to PCR negative conversion between patients treated with azithromycin compared to patients treated with clarithromycin (p˃0.05 for all). Follow up chest CT done after 2 weeks of start of treatment showed significant improvement in patients treated with either azithromycin or clarithromycin compared to control group (p˂0.05 for all).Adding Clarithromycin or Azithromycin to the therapeutic protocols for COVID-19 MESHD could be beneficial for early control of fever MESHD and early PCR negative conversion in Mild COVID-19 MESHD

    Benefits of Treatment With Favipiravir in Hospitalized Patients for COVID-19 MESHD: a Retrospective Observational Case-control Study

    Authors: Anıl Uçan; Pamir Çerçi; Serdar Efe; Hakan Akgün; Ahmet Özmen; Aysel Yağmuroğlu; Muzaffer Bilgin; Deniz Avcı

    doi:10.21203/rs.3.rs-175340/v1 Date: 2021-01-28 Source: ResearchSquare

    Background: Although more than a year past since COVID-19 MESHD was defined, there is no specific treatment yet. Since COVID-19 MESHD management differs over time, it is hard to determine which therapy is more efficacious. In this study, we aimed to evaluate the efficacy of the regimen with Favipiravir (FPV) and determine if the timing of FPV addition offers any improvement. Methods: A retrospective observational case-controlled cohort study was performed between March and Sep-tember 2020, including adults with COVID-19 MESHD in a single-center in Turkey. We categorized patients into age-sex matched three groups, group 1 (n=48) and group 2 (n=48) included patients treated with the combination of FPV plus Hydroxychloroquine (HQ) early and late, respectively. Group 3 (n=48) consisted of patients on HQ monot-herapy. In Group 2, if the respiratory or clinic condition had not improved sufficiently, FPV was added on or after day 3. Results: We found that starting FPV early had an impact on PCR negativity and the progression of the disease. 'No progression' was defined as the absence of a new finding in the control radiological examination and the absence of accompanying clinical deterioration. Also, the decrease in C-reactive protein HGNC ( CRP HGNC) was greater in Group 1 than Group 3 (p <0.001). However, we found that early initiation of FPV treatment did not have a posi-tive effect on the estimated survival time.  Conclusions: According to this retrospective study results, we believe that for better clinical outcomes, FPV treatment should be started promptly to enhance antiviral effects and improve clinical outcomes.

    Development and validation of a prognostic COVID-19 MESHD severity assessment (COSA) score and machine learning models for patient triage at a tertiary hospital

    Authors: Verena Schöning; Evangelia Liakoni; Christine Baumgartner; Aristomenis K. Exadaktylos; Wolf E. Hautz; Andrew Atkinson; Felix Hammann

    doi:10.21203/rs.3.rs-165301/v1 Date: 2021-01-28 Source: ResearchSquare

    Background: Clinical risk scores and machine learning models based on routine laboratory values could assist in automated early identification of severe acute respiratory syndrome coronavirus 2 MESHD (SARS-CoV-2) patients at risk for severe clinical outcomes. They can guide patient triage, inform allocation of health care resources, and contribute to the improvement of clinical outcomes. Methods: In- and out-patients tested positive for SARS-CoV-2 at the Insel Hospital Group Bern, Switzerland, between February 1st and August 31st (‘first wave’, n=198) and September 1st through November 16th 2020 (‘second wave’, n=459) were used as training and prospective validation cohort, respectively. A clinical risk stratification score and machine learning (ML) models were developed using demographic data, medical history, and laboratory values taken up to three days before, or one day after, positive testing to predict severe outcomes of hospitalization (a composite endpoint of admission to intensive care, or death MESHD from any cause). Test accuracy was assessed using the area under the receiver operating characteristic curve (AUROC).Results: Sex, C-reactive protein HGNC, sodium, hemoglobin, glomerular filtration rate, glucose, and leucocytes around the time of first positive testing (‑3 to +1 days) were the most predictive parameters. AUROC of the risk stratification score on training data (AUROC = 0.94, positive predictive value (PPV) = 0.97, negative predictive value (NPV) = 0.80) were comparable to the prospective validation cohort (AUROC = 0.85, PPV = 0.91, NPV = 0.81). The most successful ML algorithm with respect to AUROC was support vector machines (median = 0.96, interquartile range = 0.85-0.99, PPV = 0.90, NPV = 0.58).Conclusion: With a small set of easily obtainable parameters, both the clinical risk stratification score and the ML models were predictive for severe outcomes at our tertiary hospital center, and performed well in prospective validation.

    Clinical Characteristics and Risk Factors of Mortality Among Severe COVID-19 MESHD Patients

    Authors: Reham Mohamed Elmorshedy; Maha Mohamed El-kholy; Alaa Eldin AbdelMoniem; Shimaa Abbas Hassan; Samiaa Hamdy Sadek

    doi:10.21203/rs.3.rs-166002/v1 Date: 2021-01-28 Source: ResearchSquare

    Background:The novel corona virus is attacking several millions of people worldwide, resulting in death of almost a million and a half-humans. The rational of the current study was to detect clinical characteristics of severe COVID- 19 patients, and assessment of risk factors for death MESHD.Methodology:This retrospective cohort study included all laboratory confirmed COVID-19 MESHD patients with severe disease admitted to critical care unit in June and July 2020. All recorded data were collected,which included clinincal, radiological, and laboratory data, in addition to the outcome and duration of ICU stay.Statistical analysis was performed for obtaining descriptive information, comparison between living and dead patients,in addition to regression analysis to identify risk factors for mortality.Results:One hundred and three patients were included in the current study; cough MESHD and fever MESHD were the most common clinical presentations, and bilateral ground glass opacity was the most common radiological presentation. Patients had elevated values of  neutrophils, neutrophil lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), serum ferritin, CRP HGNC, and D-dimer, also had longer ICU stay ,with reduced values of  lymphocytes, and PaO2/FIO2 ratio. Most of these variables were more exaggerated in dead patients compared to living ones. Older age, lower values of PaO2/FIO2 ratio, and higher values of neutrophils, NLR, and D-dimer were predictors for death MESHD.Conclusion: Cough, fever MESHD and bilateral ground glass opacity were the most common clinical and radiological presentation of severe COVID 19. Older age, lower value of PaO2/FIO2 ratio, and higher values of D- dimer, neutrophil and NLR were risk factors associated with increased risk of mortality.

    COVID-19 MESHD anosmia MESHD and gustatory symptoms as a prognosis factor: a subanalysis of the HOPE COVID-19 MESHD (Health Outcome Predictive Evaluation for COVID-19 MESHD) Registry

    Authors: Jesús Porta-Etessam; Iván Núñez-Gil; Nuria González García; Cristina Fernández; María Viana-LLamas; Charbel Maroun Eid; Rodolfo Romero; Marta Molina; Aitor Uribarri; Victor Becerra; Marcos García Aguado; Jia Huang; Elisa Rondano; Enrico Cerrato; Emilio Alfonso; Alex Castro; francisco Marín; Sergio Raposeiras; Martino Pepe; Gisela Feites; Paloma Mate; Bernardo Cortese; Luís Buzón; Jorge Javita; Vicente Estrada

    doi:10.21203/rs.3.rs-158894/v1 Date: 2021-01-27 Source: ResearchSquare

    Olfactory and gustatory dysfunctions MESHD ( OGD MESHD) are a frequent symptom of Coronavirus disease 2019 MESHD ( COVID-19 MESHD). It has been proposed that the neuroinvasive potential of the novel SARS-CoV-2 could be due to olfactory bulb invasion, conversely studies suggest it could be a good prognostic factor. The aim of the current study was to investigate the prognosis value of OGD in COVID-19 MESHD.These symptoms were recorded on admission from a cohort study of 5868 patients with confirmed or highly suspected COVID-19 MESHD infection included in the multicenter international HOPE Registry (NCT04334291).There was statistical relation in multivariate analysis for OGD in gender, more frequent in female 12.41% vs 8.67% in male, related to age, more frequent under 65 years, presence of hypertension MESHD, dyslipidemia MESHD, diabetes MESHD, smoke, renal insufficiency MESHD, lung, heart, cancer MESHD and neurological disease MESHD. We did not find statistical differences in pregnant (p=0.505), patient suffering cognitive (p=0.484), liver (p=0.1) or immune disease (p=0.32). There was inverse relation (protective) between OGD MESHD and prone positioning (0.005) and death MESHD (<0.0001), but no with ICU (0.165) or mechanical ventilation (0.292). On univariable logistic regression OGD was found to be inversely related to death in COVID-19 MESHD patients. The Odds Ratio was 0.26 (0.15-0.44) (p<0.001) and Z was -5.05.The presence of anosmia MESHD is fundamental in the diagnosis of SARS.CoV-2 infection MESHD, but also could be important when classifying patients and in therapeutic decisions. Even more knowing that it is an early symptom of the disease. Knowing that other situations as being Afro-American or Latino-American, Hypertension MESHD, renal insufficiency MESHD, or increase of C-reactive protein HGNC ( CRP HGNC) imply a worse prognosis we can make a clinical score to estimate the vital prognosis of the patient.The exact pathogenesis of SARS-CoV-2 that causes olfactory and gustative disorders remains unknown but seems related to the prognosis. This point is fundamental, insomuch as could be a plausible way to find a treatment. 

    Association between clinical characteristics and laboratory findings with outcome of hospitalized COVID-19 MESHD patients, a report from northeast of Iran

    Authors: Sahar Sobhani; Reihaneh Aryan; Elham Kalantari; Salman Soltani; Nafise Malek; Parisa Pirzadeh; Amir Yarahmadi; Atena Aghaee

    doi:10.1101/2021.01.23.21250359 Date: 2021-01-25 Source: medRxiv

    Coronavirus disease 2019 MESHD ( COVID-19 MESHD) was first discovered in December 2019 in China and has rapidly spread worldwide. Clinical characteristics, laboratory findings, and their association with the outcome of patients with COVID-19 MESHD can be decisive in management and early diagnosis. Data were obtained retrospectively from medical records of 397 hospitalized COVID-19 MESHD patients between February and May 2020 in Imam Reza hospital, northeast of Iran. Clinical and laboratory features were evaluated among survivors and non-survivors. The correlation between variables and duration of hospitalization and admission to the Intensive Care Unit (ICU) was determined. Male sex, age, hospitalization duration, and admission to ICU were significantly related to mortality rate. Headache MESHD was a more common feature in patients who survived (p = 0.017). It was also related to a shorter stay in the hospital (p = 0.032) as opposed to patients who experienced chest pain MESHD (p = 0.033). Decreased levels of consciousness and dyspnea MESHD were statistically more frequent in non-survivors (p = 0.003 and p = 0.011, respectively). Baseline white blood cell count (WBC), erythrocyte sedimentation rate (ESR), and C-reactive protein HGNC ( CRP HGNC) were significantly higher in non-survivors (p < 0.001). Patients with higher WBC and CRP HGNC levels were more likely to be admitted to ICU (p = 0.009 and p = 0.001, respectively). Evaluating clinical and laboratory features can help clinicians find ways for risk stratifying patients and even make predictive tools. Chest pain MESHD, decreased level of consciousness, dyspnea MESHD, and increased CRP HGNC and WBC levels seem to be the most potent predictors of severe prognosis.

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HGNC Genes
SARS-CoV-2 Proteins


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