Determinants of COVID-19 Disease Severity-Lessons from Primary and Secondary Immune Disorders including Cancer.

At the beginning of the COVID-19 pandemic, patients with primary and secondary immune disorders-including patients suffering from cancer-were generally regarded as a high-risk population in terms of COVID-19 disease severity and mortality. By now, scientific evidence indicates that there is substantial heterogeneity regarding the vulnerability towards COVID-19 in patients with immune disorders. In this review, we aimed to summarize the current knowledge about the effect of coexistent immune disorders on COVID-19 disease severity and vaccination response. In this context, we also regarded cancer as a secondary immune disorder. While patients with hematological malignancies displayed lower seroconversion rates after vaccination in some studies, a majority of cancer patients' risk factors for severe COVID-19 disease were either inherent (such as metastatic or progressive disease) or comparable to the general population (age, male gender and comorbidities such as kidney or liver disease). A deeper understanding is needed to better define patient subgroups at a higher risk for severe COVID-19 disease courses. At the same time, immune disorders as functional disease models offer further insights into the role of specific immune cells and cytokines when orchestrating the immune response towards SARS-CoV-2 infection. Longitudinal serological studies are urgently needed to determine the extent and the duration of SARS-CoV-2 immunity in the general population, as well as immune-compromised and oncological patients.

Dynamic associations between the respiratory tract and gut antibiotic resistome of patients with COVID-19 and its prediction power for disease severity.

The antibiotic resistome is the collection of all antibiotic resistance genes (ARGs) present in an individual. Whether an individual's susceptibility to infection and the eventual severity of coronavirus disease 2019 (COVID-19) is influenced by their respiratory tract antibiotic resistome is unknown. Additionally, whether a relationship exists between the respiratory tract and gut ARGs composition has not been fully explored. We recruited 66 patients with COVID-19 at three disease stages (admission, progression, and recovery) and conducted a metagenome sequencing analysis of 143 sputum and 97 fecal samples obtained from them. Respiratory tract, gut metagenomes, and peripheral blood mononuclear cell (PBMC) transcriptomes are analyzed to compare the gut and respiratory tract ARGs of intensive care unit (ICU) and non-ICU (nICU) patients and determine relationships between ARGs and immune response. Among the respiratory tract ARGs, we found that Aminoglycoside, Multidrug, and Vancomycin are increased in ICU patients compared with nICU patients. In the gut, we found that Multidrug, Vancomycin, and Fosmidomycin were increased in ICU patients. We discovered that the relative abundances of Multidrug were significantly correlated with clinical indices, and there was a significantly positive correlation between ARGs and microbiota in the respiratory tract and gut. We found that immune-related pathways in PBMC were enhanced, and they were correlated with Multidrug, Vancomycin, and Tetracycline ARGs. Based on the ARG types, we built a respiratory tract-gut ARG combined random-forest classifier to distinguish ICU COVID-19 patients from nICU patients with an AUC of 0.969. Cumulatively, our findings provide some of the first insights into the dynamic alterations of respiratory tract and gut antibiotic resistome in the progression of COVID-19 and disease severity. They also provide a better understanding of how this disease affects different cohorts of patients. As such, these findings should contribute to better diagnosis and treatment scenarios.

COVID-19 Severity Shifts the Cytokine Milieu Toward a Proinflammatory State in Egyptian Patients: A Cross-Sectional Study.

Despite extensive research to decipher the immunological basis of coronavirus disease (COVID-19), limited evidence on immunological correlates of COVID-19 severity from MENA region and Egypt was reported. In a single-center cross-sectional study, we have analyzed 25 cytokines that are related to immunopathologic lung injury, cytokine storm, and coagulopathy in plasma samples from 78 hospitalized Egyptian COVID-19 patients in Tanta University Quarantine Hospital and 21 healthy control volunteers between April 2020 and September 2020. The enrolled patients were divided into 4 categories based on disease severity, namely mild, moderate, severe, and critically ill. Interestingly, interleukin (IL)-1-α, IL-2Rα, IL-6, IL-8, IL-18, tumor necrosis factor-alpha (TNF-α), FGF1, CCL2, and CXC10 levels were significantly altered in severe and/or critically ill patients. Moreover, principal component analysis (PCA) demonstrated that severe and critically ill COVID-19 patients cluster based on specific cytokine signatures that distinguish them from mild and moderate COVID-19 patients. Specifically, levels of IL-2Rα, IL-6, IL-10, IL-18, TNF-α, FGF1, and CXCL10 largely contribute to the observed differences between early and late stages of COVID-19 disease. Our PCA showed that the described immunological markers positively correlate with high D-dimer and C-reactive protein levels and inversely correlate with lymphocyte counts in severe and critically ill patients. These data suggest a disordered immune regulation, particularly in severe and critically ill Egyptian COVID-19 patients, manifested as overactivated innate immune and dysregulated T-helper1 responses. Additionally, our study emphasizes the importance of cytokine profiling to identify potentially predictive immunological signatures of COVID-19 disease severity.

Risk factors for disease severity among children with Covid-19: a clinical prediction model.

BACKGROUND: Children account for a significant proportion of COVID-19 hospitalizations, but data on the predictors of disease severity in children are limited. We aimed to identify risk factors associated with moderate/severe COVID-19 and develop a nomogram for predicting children with moderate/severe COVID-19. METHODS: We identified children ≤ 12 years old hospitalized for COVID-19 across five hospitals in Negeri Sembilan, Malaysia, from 1 January 2021 to 31 December 2021 from the state's pediatric COVID-19 case registration system. The primary outcome was the development of moderate/severe COVID-19 during hospitalization. Multivariate logistic regression was performed to identify independent risk factors for moderate/severe COVID-19. A nomogram was constructed to predict moderate/severe disease. The model performance was evaluated using the area under the curve (AUC), sensitivity, specificity, and accuracy. RESULTS: A total of 1,717 patients were included. After excluding the asymptomatic cases, 1,234 patients (1,023 mild cases and 211 moderate/severe cases) were used to develop the prediction model. Nine independent risk factors were identified, including the presence of at least one comorbidity, shortness of breath, vomiting, diarrhea, rash, seizures, temperature on arrival, chest recessions, and abnormal breath sounds. The nomogram's sensitivity, specificity, accuracy, and AUC for predicting moderate/severe COVID-19 were 58·1%, 80·5%, 76·8%, and 0·86 (95% CI, 0·79 - 0·92) respectively. CONCLUSION: Our nomogram, which incorporated readily available clinical parameters, would be useful to facilitate individualized clinical decisions.

Coinfection with porcine epidemic diarrhea virus and Clostridium perfringens type A enhances disease severity in weaned pigs.

Clostridium perfringens is a constituent of the normal gut microbiome in pigs; however, it can potentially cause pre- and post-weaning diarrhea. Nevertheless, the importance of this bacterium as a primary pathogen of diarrhea in piglets needs to be better understood, and the epidemiology of C. perfringens in Korean pig populations is unknown. To study the prevalence and typing of C. perfringens, 203 fecal samples were collected from diarrheal piglets on 61 swine farms during 2021-2022 and examined for the presence of C. perfringens and enteric viruses, including porcine epidemic diarrhea virus (PEDV). We determined that the most frequently identified type of C. perfringens was C. perfringens type A (CPA; 64/203, 31.5%). Among the CPA infections, single infections with CPA (30/64, 46.9%) and coinfections with CPA and PEDV (29/64, 45.3%) were the most common in diarrheal samples. Furthermore, we conducted animal experiments to investigate the clinical outcome of single infections and coinfections with highly pathogenic (HP)-PEDV and CPA in weaned piglets. The pigs infected with HP-PEDV or CPA alone showed mild or no diarrhea, and none of them died. However, animals that were co-inoculated with HP-PEDV and CPA showed more-severe diarrheal signs than those of the singly infected pigs. Additionally, CPA promoted PEDV replication in coinfected piglets, with high viral titers in the feces. A histopathological examination revealed more-severe villous atrophy in the small intestine of coinfected pigs than in singly infected pigs. This indicates a synergistic effect of PEDV and CPA coinfection on clinical disease in weaned piglets.

Associated effects of clinical characteristics, risk factors, and comorbidity on disease severity and mortality among patients with COVID-19 in Sulaimani City/ Kurdistan Region of Iraq.

The effects of clinical symptoms, laboratory indicators, and comorbidity status of SARS-CoV-2-infected patients on the severity of disease and the risk of death were investigated. Questionnaires and electronic medical records of 371 hospitalized COVID-19 patients were used for data collection (demographics, clinical manifestation, comorbidities, laboratory data). Association among categorical variables was determined using Kolmogorov-Smirnov test (P-value ≤0.05). Median age of study population (249 males, 122 females) was 65 years. Roc curves analysis found that age ≥64 years and age ≥67 years are significant cut-offs identifying patients with more severe disease and mortality at 30 days. CRP values at cut-off ≥80.7 and ≥95.8 significantly identify patients with more severe disease and mortality. Patients with more severe disease and risk of death were significantly identified with platelet value at the cut-off ≤160,000, hemoglobin value at the cut-off ≤11.7, D-Dimer values ≥1383 and ≥1270, and with values of neutrophil granulocytes (≥8.2 and ≤2) and lymphocytes (≤2 and ≤2.4). Detailed clinical investigation suggests granulocytes together with lymphopenia may be a potential indicator for diagnosis. Older age, several comorbidities (cancer, cardiovascular diseases, hypertension) and more laboratory abnormalities (CRP, D-Dimer, platelets, hemoglobin) were associated with development of more severity and mortality among COVID-19 patients.

The Impact of Serum Levels of Reactive Oxygen and Nitrogen Species on the Disease Severity of COVID-19.

Elucidation of the redox pathways in severe coronavirus disease 2019 (COVID-19) might aid in the treatment and management of the disease. However, the roles of individual reactive oxygen species (ROS) and individual reactive nitrogen species (RNS) in COVID-19 severity have not been studied to date. The main objective of this research was to assess the levels of individual ROS and RNS in the sera of COVID-19 patients. The roles of individual ROS and RNS in COVID-19 severity and their usefulness as potential disease severity biomarkers were also clarified for the first time. The current case-control study enrolled 110 COVID-19-positive patients and 50 healthy controls of both genders. The serum levels of three individual RNS (nitric oxide (NO•), nitrogen dioxide (ONO-), and peroxynitrite (ONOO-)) and four ROS (superoxide anion (O2•-), hydroxyl radical (•OH), singlet oxygen (1O2), and hydrogen peroxide (H2O2)) were measured. All subjects underwent thorough clinical and routine laboratory evaluations. The main biochemical markers for disease severity were measured and correlated with the ROS and RNS levels, and they included tumor necrosis factor-alpha (TNF-alpha), interleukin-6 (IL-6), the neutrophil-to-lymphocyte ratio (NLR), and angiotensin-converting enzyme 2 (ACE2). The results indicated that the serum levels of individual ROS and RNS were significantly higher in COVID-19 patients than in healthy subjects. The correlations between the serum levels of ROS and RNS and the biochemical markers ranged from moderate to very strongly positive. Moreover, significantly elevated serum levels of ROS and RNS were observed in intensive care unit (ICU) patients compared with non-ICU patients. Thus, ROS and RNS concentrations in serum can be used as biomarkers to track the prognosis of COVID-19. This investigation demonstrated that oxidative and nitrative stress play a role in the etiology of COVID-19 and contribute to disease severity; thus, ROS and RNS are probable innovative targets in COVID-19 therapeutics.

Angiotensin converting enzyme 2 gene expression and markers of oxidative stress are correlated with disease severity in patients with COVID-19.

BACKGROUND: Oxidative stress is thought to play a significant role in the pathogenesis and severity of COVID-19. Additionally, angiotensin converting enzyme 2 (ACE2) expression may predict the severity and clinical course of COVID-19. Accordingly, the aim of the present study was to evaluate the association of oxidative stress and ACE2 expression with the clinical severity in patients with COVID-19. METHODS AND RESULTS: The present study comprised 40 patients with COVID-19 and 40 matched healthy controls, recruited between September 2021 and March 2022. ACE 2 expression levels were measured using Hera plus SYBR Green qPCR kits with GAPDH used as an internal control. Serum melatonin (MLT) levels, serum malondialdehyde (MDA) levels, and total antioxidant capacity (TAC) were estimated using ELISA. The correlations between the levels of the studied markers and clinical indicators of disease severity were evaluated. Significantly, lower expression of ACE2 was observed in COVID-19 patients compared to controls. Patients with COVID-19 had lower serum levels of TAC and MLT but higher serum levels of MDA compared to normal controls. Serum MDA levels were correlated with diastolic blood pressure (DBP), Glasgow coma scale (GCS) scores, and serum potassium levels. Serum MLT levels were positively correlated with DBP, mean arterial pressure (MAP), respiratory rate, and serum potassium levels. TAC was correlated with GCS, mean platelet volume, and serum creatinine levels. Serum MLT levels were significantly lower in patients treated with remdesivir and inotropes. Receiver operating characteristic curve analysis demonstrates that all markers had utility in discriminating COVID-19 patients from healthy controls. CONCLUSIONS: Increased oxidative stress and increased ACE2 expression were correlated with disease severity and poor outcomes in hospitalized patients with COVID-19 in the present study. Melatonin supplementation may provide a utility as an adjuvant therapy in decreasing disease severity and death in COVID-19 patients.

Circulating eosinophils associated with responsiveness to COVID-19 vaccine and the disease severity in patients with SARS-CoV-2 omicron variant infection.

OBJECTIVE: This study aimed to investigate the longitudinal circulating eosinophil (EOS) data impacted by the COVID-19 vaccine, the predictive role of circulating EOS in the disease severity, and its association with T cell immunity in patients with SARS-CoV-2 Omicron BA.2 variant infection in Shanghai, China. METHODS: We collected a cohort of 1,157 patients infected with SARS-CoV-2 Omicron/BA.2 variant in Shanghai, China. These patients were diagnosed or admitted between Feb 20, 2022, and May 10, 2022, and were classified as asymptomatic (n = 705), mild (n = 286) and severe (n = 166) groups. We compiled and analyzed data of patients' clinical demographic characteristics, laboratory findings, and clinical outcomes. RESULTS: COVID-19 vaccine reduced the incidence of severe cases. Severe patients were shown to have declined peripheral blood EOS. Both the 2 doses and 3 doses of inactivated COVID-19 vaccines promoted the circulating EOS levels. In particular, the 3rd booster shot of inactivated COVID-19 vaccine was shown to have a sustained promoting effect on circulating EOS. Univariate analysis showed that there was a significant difference in age, underlying comorbidities, EOS, lymphocytes, CRP, CD4, and CD8 T cell counts between the mild and the severe patients. Multivariate logistic regression analysis and ROC curve analysis indicate that circulating EOS (AUC = 0.828, p = 0.025), the combination of EOS and CD4 T cell (AUC = 0.920, p = 0.017) can predict the risk of disease severity in patients with SARS-CoV-2 Omicron BA.2 variant infection. CONCLUSIONS: COVID-19 vaccine promotes circulating EOS and reduces the risk of severe illness, and particularly the 3rd booster dose of COVID-19 vaccine sustainedly promotes EOS. Circulating EOS, along with T cell immunity, may have a predictive value for the disease severity in SARS-CoV-2 Omicron infected patients.

Improving COVID-19 Disease Severity Surveillance Measures: Statewide Implementation Experience.

Measurement of the burden of COVID-19 on U.S. hospitals has been an important element of the public health response to the pandemic. However, because of variation in testing density and policies, the metric is not standardized across facilities. Two types of burdens exist, one related to the infection control measures that patients who test positive for SARS-CoV-2 require and one from the care of severely ill patients receiving treatment of COVID-19. With rising population immunity from vaccination and infection, as well as the availability of therapeutics, severity of illness has declined. Prior research showed that dexamethasone administration was highly correlated with other disease severity metrics and sensitive to the changing epidemiology associated with the emergence of immune-evasive variants.On 10 January 2022, the Massachusetts Department of Public Health began requiring hospitals to expand surveillance to include reports of both the total number of "COVID-19 hospitalizations" daily and the number of inpatients who received dexamethasone at any point during their hospital stay. All 68 acute care hospitals in Massachusetts submitted COVID-19 hospitalization and dexamethasone data daily to the Massachusetts Department of Public Health over a 1-year period. A total of 44 196 COVID-19 hospitalizations were recorded during 10 January 2022 to 9 January 2023, of which 34% were associated with dexamethasone administration. The proportion of patients hospitalized with COVID-19 who had received dexamethasone was 49.6% during the first month of surveillance and decreased to a monthly average of approximately 33% by April 2022, where it has remained since (range, 28.7% to 33%).Adding a single data element to mandated reporting to estimate the frequency of severe COVID-19 in hospitalized patients was feasible and provided actionable information for health authorities and policy makers. Updates to surveillance methods are necessary to match data collection with public health response needs.

Altered somatic hypermutation patterns in COVID-19 patients classifies disease severity.

Introduction: The success of the human body in fighting SARS-CoV2 infection relies on lymphocytes and their antigen receptors. Identifying and characterizing clinically relevant receptors is of utmost importance. Methods: We report here the application of a machine learning approach, utilizing B cell receptor repertoire sequencing data from severely and mildly infected individuals with SARS-CoV2 compared with uninfected controls. Results: In contrast to previous studies, our approach successfully stratifies non-infected from infected individuals, as well as disease level of severity. The features that drive this classification are based on somatic hypermutation patterns, and point to alterations in the somatic hypermutation process in COVID-19 patients. Discussion: These features may be used to build and adapt therapeutic strategies to COVID-19, in particular to quantitatively assess potential diagnostic and therapeutic antibodies. These results constitute a proof of concept for future epidemiological challenges.

Elevated interleukin (IL)-6 as a predictor of disease severity among Covid-19 patients: a prospective cohort study.

BACKGROUND: accompanied to the spreading of coronavirus disease 2019 (Covid-19) in the world, identifying factors related to the severity of the disease is one of the interests of physician and medical researchers. We hypothesized that interleukin 6 serum level is associated with severe outcome. METHODS: In this longitudinal prospective cohort study we enrolled 208 confirmed COVID-19 patients who were admitted to the Tohid Hospital (Sanandaj, Iran). Patients were classified into two groups based on IL-6 value in the first day of admission, elevated (n = 107) or not elevated/normal (n = 101), and followed until the occurrence of final outcome (death or discharge from the hospital). Data were analyzed using univariate methods, Chi-squared and independent two sample T test. The relationship between the independent variables and our interesting outcomes were investigated by multiple linear and penalized logistic regression modeling. RESULTS: A total of 208 patients, 51% female and mean age 53.6 ± 16.3 years, including 107 elevated and 101 non-elevated IL-6 patients, were followed. No significant difference was observed between the two groups in demographic and clinical characteristics. Although not significant, logistic regression results showed that the chance of death occurrence among patients with elevated IL-6 are 3.91 times higher. According to the multiple linear regression modeling, elevated IL-6 significantly increased the duration of hospital stay (P = 0.02). Frequency of ICU admission (P = 0.04) and mean of ICU stay (P = 0.8) are also higher in elevated IL-6 group. CONCLUSION: This study revealed that elevated IL-6 is significantly related to prolongation of hospital stay in Covid-19 patients. Although not significant, the occurrence of death among patients who had increased IL-6 in the time of admission was higher than patients with normal or lower serum levels of IL-6.

SARS-CoV-2 intra-host diversity, antibody response, and disease severity after reinfection by the variant of concern Gamma in Brazil.

The rapid spread of the SARS-CoV-2 Variant of Concern (VOC) Gamma in Amazonas during early 2021 fueled a second large COVID-19 epidemic wave and raised concern about the potential role of reinfections. Very few cases of reinfection associated with the VOC Gamma have been reported to date, and their potential impact on clinical, immunological, and virological parameters remains largely unexplored. Here we describe 25 cases of SARS-CoV-2 reinfection in Brazil. SARS-CoV-2 genomic analysis confirmed that individuals were primo-infected with distinct viral lineages between March and December 2020 (B.1.1, B.1.1.28, B.1.1.33, B.1.195, and P.2) and reinfected with the VOC Gamma between 3 to 12 months after primo-infection. We found a similar mean cycle threshold (Ct) value and limited intra-host viral diversity in both primo-infection and reinfection samples. Sera of 14 patients tested 10-75 days after reinfection displayed detectable neutralizing antibodies (NAb) titers against SARS-CoV-2 variants that circulated before (B.1.*), during (Gamma), and after (Delta and Omicron) the second epidemic wave in Brazil. All individuals had milder or no symptoms after reinfection, and none required hospitalization. These findings demonstrate that individuals reinfected with the VOC Gamma may display relatively high RNA viral loads at the upper respiratory tract after reinfection, thus contributing to onward viral transmissions. Despite this, our study points to a low overall risk of severe Gamma reinfections, supporting that the abrupt increase in hospital admissions and deaths observed in Amazonas and other Brazilian states during the Gamma wave was mostly driven by primary infections. Our findings also indicate that most individuals analyzed developed a high anti-SARS-CoV-2 NAb response after reinfection that may provide some protection against reinfection or disease by different SARS-CoV-2 variants.

COVID-19 in inherited metabolic disorders: Clinical features and risk factors for disease severity.

BACKGROUND: Old age, obesity, and certain chronic conditions are among the risk factors for severe COVID-19. More information is needed on whether inherited metabolic disorders (IMD) confer risk of more severe COVID-19. We aimed to establish COVID-19 severity and associated risk factors in patients with IMD currently followed at a single metabolic center. METHODS: Among all IMD patients followed at a single metabolic referral center who had at least one clinic visit since 2018, those with accessible medical records were reviewed for SARS-CoV-2 tests. COVID-19 severity was classified according to the WHO recommendations, and IMD as per the international classification of IMD. RESULTS: Among the 1841 patients with IMD, 248 (13.5%) had tested positive for COVID-19, 223 of whom gave consent for inclusion in the study (131 children and 92 adults). Phenylalanine hydroxylase (48.4%) and biotinidase (12.1%) deficiencies were the most common diagnoses, followed by mucopolysaccharidoses (7.2%). 38.1% had comorbidities, such as neurologic disabilities (22%) or obesity (9.4%). The majority of COVID-19 episodes were asymptomatic (16.1%) or mild (77.6%), but 6 patients (2.7%) each had moderate and severe COVID-19, and two (0.9%) had critical COVID-19, both of whom died. 3 patients had an acute metabolic decompensation during the infection. Two children developed multisystem inflammatory syndrome (MIS-C). Long COVID symptoms were present in 25.2%. Presence of comorbidities was significantly associated with more severe COVID-19 in adults with IMD (p < 0.01), but not in children (p = 0.45). Compared to other categories of IMD, complex molecule degradation disorders were significantly associated with more severe COVID-19 in children (p < 0.01); such a significant IMD category distinction was not found in adults. DISCUSSION: This is the largest study on COVID-19 in IMD patients relying on real-word data and objective definitions, and not on merely expert opinions or physician surveys. COVID-19 severity and long COVID incidence in IMD are probably similar to the general population, and the risk of acute metabolic decompensation is not likely to be greater than that in other acute infections. Disease category (complex molecule degradation) in children, and comorbidities in adults may be associated with COVID-19 severity in IMD. Additionally, the first documented accounts of COVID-19 in 27 different IMD are recorded. The high occurrence of MIS-C may be coincidental, but warrants further study.

γ' fibrinogen levels as a biomarker of COVID-19 respiratory disease severity.

Coronavirus disease 2019 (COVID-19) is characterized by a pro-inflammatory state associated with organ failure, thrombosis, and death. We investigated a novel inflammatory biomarker, γ' fibrinogen (GPF), in 103 hospitalized patients with COVID-19 and 19 healthy controls. We found significant associations between GPF levels and the severity of COVID-19 as judged by blood oxygen saturation (SpO2). The mean level of GPF in the patients with COVID-19 was significantly higher than in controls (69.8 (95 % CI 64.8-74.8) mg/dL compared with 36.9 (95 % CI 31.4-42.4) mg/dL, p < 0.0001), whereas C-reactive protein (CRP), lactate dehydrogenase (LDH), and total fibrinogen levels were not significantly different between groups. Mean GPF levels were significantly highest in patients with severe COVID-19 (SpO2 ≤ 93 %, GPF 75.2 (95 % CI 68.7-81.8) mg/dL), compared to mild/moderate COVID-19 (SpO2 > 93 %, GPF 62.5 (95 % CI 55.0-70.0) mg/dL, p = 0.01, AUC of 0.68, 95 % CI 0.57-0.78; Youden's index cutpoint 62.9 mg/dL, sensitivity 0.64, specificity 0.63). In contrast, CRP, interleukin-6, ferritin, LDH, D-dimers, and total fibrinogen had weaker associations with COVID-19 disease severity (all ROC curves with lower AUCs). Thus, GPF may be a useful inflammatory marker of COVID-19 respiratory disease severity.

Baseline electrolyte disorders predict disease severity and mortality in patients with COVID-19.

Distinguishing critical laboratory biomarkers for disease severity at the time of hospital presentation is important for early identification of patients who are most likely to have poor outcomes and effective use of health resources. This study aimed to evaluate whether electrolyte imbalances on hospital admission predict severe disease and mortality in patients with coronavirus disease 2019 (COVID-19). We retrospectively collected data on the blood electrolyte concentrations of 286 COVID-19 patients at admission. The correlations between electrolyte imbalances, inflammation, and thrombosis markers in COVID-19 patients were also evaluated. We assessed the predictive performance of baseline blood electrolyte concentrations for severe disease and death using receiver operating characteristic curve analysis and multivariate logistic regression methods. Abnormalities in serum sodium, calcium, and potassium levels at admission were found at 20.6%, 14%, and 4.2%, respectively in this study. In the receiver operating characteristic curve analyses, hypocalcemia and hyponatremia effectively predicted disease progression to hospitalization (area under the curve 0.82, P < .001 and 0.81, P < .001, respectively) and 30-day mortality (area under the curve 0.85, P < .001 and 0.91, P < .001, respectively). In the multivariate logistic regression analysis, baseline hypocalcemia was identified as an independent risk factor associated with the risk of hospitalization (ß = 2.019, P = .01; odds ratio: 7.53). Baseline hypocalcemia and hyponatremia effectively predicted disease progression toward hospitalization and 30-day mortality in patients with COVID-19. Clinicians should closely follow up or reevaluate COVID-19 patients with baseline electrolyte disorders.