Gout, known as “the disease of the kings”, is the most frequent type of arthritis. It results from sustained hyperuricemia that leads to monosodium urate crystal deposition in joint structures and soft tissue. Environmental factors such as diet affect the incidence of gout; there is a known relationship between the occurrence of an acute attack of gout and the consumption of alcohol and meat; and a low purine diet is a widely recognized nonpharmacological method of supplementing the treatment and preventing recurrence of arthritis. This review aims to summarize the current knowledge about the role of vitamin C in prevention and treatment of gout. A PubMed/Medline database search on the role of vitamin C in purine metabolism was done. Reports from in vitro and animal studies seem to be promising and to allow explanation of the physiological relationship between vitamin C and uric acid. Most epidemiological studies indicate a significant correlation between high vitamin C intake and lower serum uric acid levels. Despite promising observations, there are few observational and interventional studies, and their results do not clearly define the benefits of a high daily intake of vitamin C in preventing the development and recurrence of gout.

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.

Background and Objectives: Severe COVID-19 still constitutes an important health problem. Taking into account the crucial role of HLA in immune reactions, evaluation of the impact of HLA on COVID-19 risk and clinical course seemed necessary, as the already available data are inconsistent. The aim of the present study was to compare the HLA profiles of patients with symptomatic SARS-CoV-2 infection and a healthy control group, as well as to compare HLA allele frequencies in patients with severe and non-severe courses of COVID-19. Materials and Methods: HLA classes were genotyped using a next-generation sequencing method in 2322 persons, including 2217 healthy hematopoietic stem cell potential donors and 105 patients with symptomatic COVID-19. Results: Symptomatic course of SARS-CoV-2 infection appeared to be associated with the presence of HLA-A*30:01, B*44:02, B*52:01, C*05:01, C*17:01, and DRB1*11:02, while HLA-C*07:04 and DQB1*03:03 seem to play a protective role. Moreover, we demonstrated that the severe symptomatic course of COVID-19 can be associated with the presence of HLA-B*08:01, C*04:01, DRB1*03:01, and DQB1*03:01, while HLA-DRB1*08:01 appeared to be protective against severe COVID-19 disease. Conclusions: Identification of alleles that are potentially associated with symptomatic SARS-CoV-2 infection as well as the severe course of COVID-19 broadens the knowledge on the genetic background of COVID-19 course and can constitute an important step in the development of personalized medicine.

Background: In the current pandemic, oversaturation of hospitals with patients with SARS-CoV-2 infection-like symptoms and an excess of hospitalized COVID-19 patients led to a global healthcare crisis. The aim of our study was to find a manageable set of decisive parameters that can be used to i) rapidly identify SARS-CoV-2 positive patients, ii) identify high-risk patients, and iii) recognize longitudinal warning signs of a possible fatal outcome. Methods: We trained several machine learning (ML) models using data on reported comorbidities, medications, symptoms, and laboratory parameters on hospital admission, and over the disease course in 201 SARS-CoV-2 positive and 314 SARS-CoV-2 negative subjects with a COVID-19-like clinical presentation. Findings: 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. Next, we determined that COVID-19 patients who on hospital admission were older, had higher procalcitonin, C-reactive protein, and troponin I together with lower hemoglobin and platelets/neutrophils ratio, were at highest risk of death from COVID-19. Finally, we identified patterns of changes in C-reactive protein, white blood cells, and D-Dimer that predicted the disease outcome. Interpretation: Our study provides sets of easily obtainable parameters that allow to assess a SARS-CoV-2 patient’s status prior to RT-PCR results and the dynamics of the disease, based on which the hospital logistics and treatment can be planned. Funding Information: This work has been supported by the Medical University of Lodz, Poland, by the Swiss Institute of Allergy and Asthma Research (SIAF), and by the Center for Data Analysis, Visualization and Simulation (DAViS) that is funded by the Swiss canton of Grisons. Declaration of Interests: MiSo reports research grants from Swiss National Science Foundation, GSK, Novartis and speakers fee from AstraZeneca and a board secretary position of the Basic and Clinical Immunology Section of the European Academy of Allergy and Clinical Immunology (EAACI). JM, FS, DZ, MaS, and KB report no competing interests. Ethics Approval Statement: The project has been accepted by the Ethical Committee of Medical University of Lodz, Poland (Nr. 228 RNN/126/20/KE).