Low serum albumin: A neglected predictor in patients with cardiovascular disease.

Albumin, the most abundant circulating protein in blood, is an essential protein which binds and transports various drugs and substances, maintains the oncotic pressure of blood and influences the physiological function of the circulatory system. Albumin also has anti-inflammatory, antioxidant, and antithrombotic properties. Evidence supports albumin's role as a strong predictor of cardiovascular (CV) risk in several patient groups. Its protective role extends to those with coronary artery disease, heart failure, hypertension, atrial fibrillation, peripheral artery disease or ischemic stroke, as well as those undergoing revascularization procedures or with aortic stenosis undergoing transcatheter aortic valve replacement, and patients with congenital heart disease and/or endocarditis. Hypoalbuminemia is a strong prognosticator of increased all-cause and CV mortality according to several cohort studies and meta-analyses in hospitalized and non-hospitalized patients with or without comorbidities. Normalization of albumin levels before discharge lowers mortality risk, compared with hypoalbuminemia before discharge. Modified forms of albumin, such as ischemia modified albumin, also has prognostic value in patients with coronary or peripheral artery disease. When albumin is combined with other risk factors, such as uric acid or C-reactive protein, the prognostic value is enhanced. Although albumin supplementation may be a plausible approach, its efficacy has not been established and in patients with hypoalbuminemia, priority is focused on diagnosing and managing the underlying condition. The CV effects of hypoalbuminemia and relevant issues are considered in this review. Large cohort studies and meta-analyses are tabulated and the physiologic effects of albumin and the deleterious effects of low albumin are pictorially illustrated.

Prognostic indicators associated with progresses of severe dengue.

BACKGROUND: Dengue usually progress abnormally, especially in the critical phase. The main causes of death were shock, severe bleeding and organ failure. The aim of our study was to evaluate prognostic indicators of severe dengue according to the phases of the disease progression. METHODS: A cross-sectional study was conducted from July to December 2017 at the National Hospital for Tropical Diseases and the Hospital for Tropical Diseases of Ho Chi Minh City. 326 patients, aged 6 years and over, including 99/326 patients with severe dengue and 227/326 patients with non-severe dengue, hospitalized in the first 3 days of illness, confirmed Dengue virus by the RT-PCR assay have been registered for the study. Clinical manifestations were monitored daily. The hematocrit, white blood cells, platelet, serum albumin, ALT, AST, bilirubin, prothrombin time (PT%, PTs), fibrinogen, aPTT, INR and creatinine were evaluated at two times: febrile phase and critical phase. RESULTS: Independent factors associated with severe dengue were identified on multivariate logistic regression models. During the first 3 days of the disease, the prognostic indicators were platelet count ≤ 100 G/L (OR = 2.2; 95%CI: 1.2-3.9), or serum albumin < 35 g/L (OR = 3.3; 95%CI: 1.8-6.1). From day 4-6, the indicator were AST > 400 U/L (OR = 3.0; 95%CI: 1.1-7.9), ALT > 400 U/L (OR = 6.6; 95%CI: 1.7-24.6), albumin < 35 g/L (OR = 3.0; 95%CI: 1.5-5.9), and bilirubin total >17 µmol/L (OR = 4.6; 95%CI: 2.0-10.4). CONCLUSION: To predict the risk of patients with severe dengue, prognostic laboratory indicators should be indicated consistent with the progression of the disease. During the first 3 days of illness, prognostic indicators should be platelet count, or serum albumin. From the 4th - 6th day of illness, prognostic indicators should be AST, ALT, albumin, or bilirubin total.

Eosinophil: A Nonnegligible Predictor in COVID-19 Re-Positive Patients.

Although vaccine resources are being distributed worldwide, insufficient vaccine production remains a major obstacle to herd immunity. In such an environment, the cases of re-positive occurred frequently, and there is a big controversy regarding the cause of re-positive episodes and the infectivity of re-positive cases. In this case-control study, we tracked 39 patients diagnosed with COVID-19 from the Jiaodong Peninsula area of China, of which 7 patients tested re-positive. We compared the sex distribution, age, comorbidities, and clinical laboratory results between normal patients and re-positive patients, and analysed the correlation between the significantly different indicators and the re-positive. Re-positive patients displayed a lower level of serum creatinine (63.38 ± 4.94 U/L vs. 86.82 ± 16.98 U/L; P =0.014) and lower albumin (34.70 ± 5.46 g/L vs. 41.24 ± 5.44 g/L, P =0.039) at the time of initial diagnosis. In addition, two positive phases and the middle negative phase in re-positive patients with significantly different eosinophil counts (0.005 ± 0.005 × 109/L; 0.103 ± 0.033 × 109/L; 0.007 ± 0.115 × 109/L; Normal range: 0.02-0.52 × 109/L). The level of eosinophils in peripheral blood can be used as a marker to predict re-positive in patients who once had COVID-19.

COVID-19 diagnosis by routine blood tests using machine learning.

Physicians taking care of patients with COVID-19 have described different changes in routine blood parameters. However, these changes hinder them from performing COVID-19 diagnoses. We constructed a machine learning model for COVID-19 diagnosis that was based and cross-validated on the routine blood tests of 5333 patients with various bacterial and viral infections, and 160 COVID-19-positive patients. We selected the operational ROC point at a sensitivity of 81.9% and a specificity of 97.9%. The cross-validated AUC was 0.97. The five most useful routine blood parameters for COVID-19 diagnosis according to the feature importance scoring of the XGBoost algorithm were: MCHC, eosinophil count, albumin, INR, and prothrombin activity percentage. t-SNE visualization showed that the blood parameters of the patients with a severe COVID-19 course are more like the parameters of a bacterial than a viral infection. The reported diagnostic accuracy is at least comparable and probably complementary to RT-PCR and chest CT studies. Patients with fever, cough, myalgia, and other symptoms can now have initial routine blood tests assessed by our diagnostic tool. All patients with a positive COVID-19 prediction would then undergo standard RT-PCR studies to confirm the diagnosis. We believe that our results represent a significant contribution to improvements in COVID-19 diagnosis.

The relationship between nutritional status and the prognosis of COVID-19: A retrospective analysis of 63 patients.

ABSTRACT: It is important for patients to maintain a good nutritional status as a health promotion strategy to improve the immune function and thus the prognosis of coronavirus disease 2019 (COVID-19).The objective of this retrospective study is to analyze the relationships of nutritional status with inflammation levels, protein reserves, baseline immune status, severity, length of hospital stay, and prognosis of COVID-19 patients.A total of 63 COVID-19 patients hospitalized in the People's Hospital and the Traditional Chinese Medicine Hospital of the Xinzhou District, Wuhan, China, from January 29, 2020 to March 17, 2020. Sixty-three patients were divided into 3 groups according to the guidelines, moderate (n = 22), severe (n = 14), and critical (n = 25), respectively. The differences in the total nutrition risk screening (NRS) score, inflammation level, protein reserve, baseline immune status, length of hospital stay, and prognosis were compared among patients with moderate, severe, and critical COVID-19.Patients with higher NRS scores tend to have more severe COVID-19, higher C-reactive protein and serum procalcitonin levels, higher white blood cell counts, lower lymphocyte counts, and higher mortality rates (P < .05).Nutritional status may be an indirect factor of the severity and prognosis of COVID-19.

Hypoalbuminemia in patients following their recovery from severe coronavirus disease 2019.

Coronavirus disease 2019 (COVID-19) is caused by a contagious virus that has spread to more than 200 countries, territories, and regions. Thousands of studies to date have examined all aspects of this disease, yet little is known about the postrecovery status of patients, especially in the long term. Here, we examined erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and serum albumin biomarkers in patients with a history of severe and mild-to-moderate COVID-19 following their recovery. In patients with severe COVID-19 serum albumin had a strong negative correlation with both ESR and CRP levels (R2 = - 0.861 and R2 = - 0.711), respectively. Also, there was a positive correlation between ESR and CRP level (R2 = 0.85) in the same group. However, there was no correlation between these biomarkers among mild-to-moderate COVID-19 patients. In addition, no correlation was recorded between the severe and mild-to-moderate COVID-19 groups. This finding highlights the sustained elevation of ESR and CRP level and reduced serum albumin level that may persist postrecovery in patients with a history of severe COVID-19.

Higher albumin levels on admission predict better prognosis in patients with confirmed COVID-19.

BACKGROUND: Research surrounding COVID-19 (coronavirus disease 2019) is rapidly increasing, including the study of biomarkers for predicting outcomes. There is little data examining the correlation between serum albumin levels and COVID-19 disease severity. The purpose of this study is to evaluate whether admission albumin levels reliably predict outcomes in COVID-19 patients. METHODS: We retrospectively reviewed 181 patients from two hospitals who had COVID-19 pneumonia confirmed by polymerase chain reaction (PCR) testing and radiologic imaging, who were hospitalized between March and July 2020. We recorded demographics, COVID-19 testing techniques, and day of admission labs. The outcomes recorded included the following: venous thromboembolism (VTE), acute respiratory distress syndrome (ARDS), intensive care unit (ICU) admission, discharge with new or higher home oxygen supplementation, readmission within 90 days, in-hospital mortality, and total adverse events. A multivariate modified Poisson regression analysis was then performed to determine significant predictors for increased adverse events in patients with COVID-19 pneumonia. RESULTS: A total of 109 patients (60.2%) had hypoalbuminemia (albumin level < 3.3 g/dL). Patients with higher albumin levels on admission had a 72% decreased risk of developing venous thromboembolism (adjusted relative risk [RR]:0.28, 95% confidence interval [CI]:0.14-0.53, p<0.001) for every 1 g/dL increase of albumin. Moreover, higher albumin levels on admission were associated with a lower risk of developing ARDS (adjusted RR:0.73, 95% CI:0.55-0.98, p = 0.033), admission to the ICU (adjusted RR:0.64, 95% CI:0.45-0.93, p = 0.019), and were less likely to be readmitted within 90 days (adjusted RR:0.37, 95% CI:0.17-0.81, p = 0.012). Furthermore, higher albumin levels were associated with fewer total adverse events (adjusted RR:0.65, 95% CI:0.52-0.80, p<0.001). CONCLUSIONS: Admission serum albumin levels appear to be a predictive biomarker for outcomes in COVID-19 patients. We found that higher albumin levels on admission were associated with significantly fewer adverse outcomes, including less VTE events, ARDS development, ICU admissions, and readmissions within 90 days. Screening patients may lead to early identification of patients at risk for developing in-hospital complications and improve optimization and preventative efforts in this cohort.

LDH, CRP and ALB predict nucleic acid turn negative within 14 days in symptomatic patients with COVID-19.

AIMS: To search for biochemical indicators that can identify symptomatic patients with COVID-19 whose nucleic acid could turn negative within 14 days, and assess the prognostic value of these biochemical indicators in patients with COVID-19. PATIENTS AND METHODS: We collected the clinical data of patients with COVID-19 admitted to our hospital, by using logistic regression analysis and AUC curves, explored the relationship between biochemical indicators and nucleic acid positive duration, the severity of COVID-19, and hospital stay respectively. RESULTS: A total of two hundred and thirty-three patients with COVID-19 were enrolled in the study. We found patients whose nucleic acid turned negative within 14 days had lower LDH, CRP and higher ALB (P < 0.05). ROC curve results indicated that lower LDH, TP, CRP and higher ALB predicted the nucleic acid of patients turned negative within 14 days with statistical significance(P < 0.05), AST, LDH, CRP and PCT predicted the severe COVID-19 with statistical significance, and CRP predicted hospital stay >31days with statistical significance (P < 0.05). After verification, the probability of nucleic acid turning negative within 14 days in patients with low LDH (<256 U/L), CRP (<44.5 mg/L) and high ALB (>35.8 g/L) was about 4 times higher than that in patients with high LDH, CRP and low ALB (P < 0.05). CONCLUSIONS: LDH, CRP and ALB are useful prognostic marker for predicting nucleic acid turn negative within 14 days in symptomatic patients with COVID-19.

Persistence of SARS-CoV-2-specific antibodies in COVID-19 patients.

To better understand humoral immunity following SARS-CoV-2 infection, 114 hospitalised COVID-19 patients with antibody monitored over 8 weeks from symptom onset were retrospectively investigated. A total of 445 serum samples were assessed via chemiluminescence immunoassay. Positive rate of virus-specific IgM reached up to over 80% from the second week to the eighth week after symptom onset, then declined quickly to below 30% in the twelfth week. Concentrations of IgG remained high for at least 3 months before subsequently declining. As compared with the non-severe group, serum IgM level from week 3 to week 8 was significantly higher among the patients with severe clinical symptoms (P = 0.012) but not IgG (P = 0.053). Serum IgM level from week 3 to week 8 was correlated with positive virus RNA test (r = 0.201, P = 0.044), albumin level (r = -0.295, P = 0.003), lactic dehydrogenase (LDH) level (r = 0.292, P = 0.003), alkaline phosphatase (ALP) level (r = 0.254, P = 0.010), C-reactive protein (CRP) level (r = 0.281, P = 0.004) during the same course, while serum IgG level was correlated with age (r = 0.207, P = 0.038). This presented results provide insight into duration of SARS-CoV-2 antibodies and interaction between the virus and host systems.

Predictors of clinical deterioration in non-severe patients with COVID-19: a retrospective cohort study.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains pandemic with considerable morbidity and mortality around the world. The aim of this study was to identify the predictors for clinical deterioration in patients with COVID-19 who did not show clinical deterioration upon hospital admission. METHODS: Two hundred fifty-seven patients with confirmed COVID-19 pneumonia admitted to Guangzhou Eighth People's Hospital between 23 January and 21 March 2020 were retrospectively enrolled. Demographic data, symptoms, laboratory values, comorbidities and treatments were all collected. The study endpoint was clinical deterioration within 20 days from hospital admission. Univariate and multivariable logistic regression methods were used to explore the risk factors associated with clinical deterioration. RESULTS: A total of 49 (19%) patients showed clinical deterioration after admission. Compared with patients that did not experience clinical deterioration, clinically deteriorated patients had more dyspnea, cough and myalgia (65.3% versus 29.3%) symptoms and more had comorbidities (89.8% versus 36.1%). Clinical and laboratory characteristics at admission that were associated with clinical deterioration included senior age, diabetes, hypertension, myalgia, higher temperature, systolic blood pressure, C-reactive protein (CRP), procalcitonin, activated partial thromboplastin time, aspartate aminotransferase, alanine transaminase, direct bilirubin, plasma creatinine, lymphocytopenia, thrombocytopenia, decreased albumin and bicarbonate concentration. Medical history of angiotensin-converting enzyme inhibitors/angiotensin receptor blockers, calcium channel blockers and metformin were also risk factors. CONCLUSION: The four best predictors for clinical deterioration were CRP, procalcitonin, age and albumin. A "best" multivariable prediction model, resulting from using a variable selection procedure, included senior age, presentation with myalgia, and higher level of CRP and serum creatinine (bias-corrected c-statistic = 0.909). Sensitivity and specificity corresponding to a cut point of CRP ≥18.45 mg/L for predicting clinical deterioration were 85% and 74%, respectively.

Predictive value of the prognostic nutritional index for the severity of coronavirus disease 2019.

OBJECTIVES: Malnutrition plays a critical role in the onset and progress of the coronavirus disease 2019 (COVID-19). The aim of the present study was to explore the association of the prognostic nutritional index (PNI) score with the severity of COVID-19 and its predictive value of the severe form of COVID-19. METHODS: Clinical data were collected from 122 patients infected with COVID-19 and hospitalized at the Sixth People's Hospital of Wenzhou, China, a specialized infectious hospital affiliated with the Wenzhou Central Hospital. PNI score was calculated as serum albumin (g/L) + 5 × total lymphocyte count (/nL). RESULTS: The study population consisted of 105 patients (86.1%) with a common form and 17 patients (13.9%) with a severe form of COVID-19. PNI score significantly decreased from patients with common to severe forms of COVID-19 (P = .029) regardless of sex, age range, and body mass index (BMI). After adjustment for sex, age, indexes of liver and renal function, C-reactive protein, and current smoking status, PNI scores remained independently and inversely associated with the severity of COVID-19 (odd ratio: 0.797; P = .030). A receiver operating characteristic analysis showed that PNI scores had a similar accuracy to predict severe forms of COVID-19 compared with its combination with sex, age, and BMI (P = .402). PNI < 49 was defined as the cutoff value to predict the severe form of COVID-19. CONCLUSIONS: Poorer nutritional status predisposed patients infected with COVID-19 to its severe form. Independently associated with the severity of COVID-19, PNI score could serve as a simple, fast, and effective predictor among patients with different sex, age, and BMI.

Predicting severe or critical symptoms in hospitalized patients with COVID-19 from Yichang, China.

OBJECTIVES: We aimed to identify potential risk factors for severe or critical coronavirus disease 2019 (COVID-19) and establish a prediction model based on significant factors. METHODS: A total of 370 patients with COVID-19 were consecutively enrolled at The Third People's Hospital of Yichang from January to March 2020. COVID-19 was diagnosed according to the COVID-19 diagnosis and treatment plan released by the National Health and Health Committee of China. Effect-size estimates are summarized as odds ratio (OR) and 95% confidence interval (CI). RESULTS: 326 patients were diagnosed with mild or ordinary COVID-19, and 44 with severe or critical COVID-19. After propensity score matching and statistical adjustment, eight factors were significantly associated with severe or critical COVID-19 (p <0.05) relative to mild or ordinary COVID-19. Due to strong pairwise correlations, only five factors, including diagnostic delay (OR, 95% CI, p: 1.08, 1.02 to 1.17, 0.048), albumin (0.82, 0.75 to 0.91, <0.001), lactate dehydrogenase (1.56, 1.14 to 2.13, 0.011), white blood cell (1.27, 1.08 to 1.50, 0.004), and neutrophil (1.40, 1.16 to 1.70, <0.001), were retained for model construction and performance assessment. The nomogram model based on the five factors had good prediction capability and accuracy (C-index: 90.6%). CONCLUSIONS: Our findings provide evidence for the significant contribution of five independent factors to the risk of severe or critical COVID-19, and their prediction was reinforced in a nomogram model.

Retrospective Study of Clinical Features of COVID-19 in Inpatients and Their Association with Disease Severity.

BACKGROUND The aim of this study was to analyze the clinical features and laboratory indices of patients with coronavirus disease (COVID-19) and explore their association with the severity of the disease. MATERIAL AND METHODS A total of 61 patients with COVID-19 were divided into groups with common symptoms and with severe diseases, and clinical data were collected to analyze and compare the differences between them. RESULTS In patients with severe COVID-19, compared with the common group, lymphocyte count and albumin levels were lower, and aspartate aminotransferase (AST), blood urea, blood creatinine, lactate dehydrogenase (LDH), and C-reactive protein (CRP) levels, and prothrombin time (PT) were elevated (all P<0.05). The neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), mean platelet volume-to-lymphocyte ratio (MPVLR), and C-reactive protein-to-albumin ratio (CAR) were significantly elevated in the severe group compared with the group with common symptoms; however, the lymphocyte-to-monocyte ratio (LMR) was significantly reduced (P<0.05). Univariate logistic regression showed that lower lymphocyte count, prolonged PT, elevated CRP and LDH levels, and elevated NLR, PLR, MPVLR, and CAR were risk factors for COVID-19 severity (P<0.05). Multivariate logistic regression showed that elevated CRP levels (odds ratio [OR], 0.028; 95% confidence interval [CI]: 0.002-0.526; P=0.017), prolonged PT (OR, 0.014; 95% CI: 0.001-0.341; P=0.09), and an MPVLR >8.9 (OR, 0.026; 95% CI: 0.002-0.349; P=0.006) were independent risk factors for COVID-19 severity. CONCLUSIONS Elevated CRP and prolonged PT, and an MPVLR >8.9 were independent risk factors for COVID-19 severity.

Decrease in hemoglobin level predicts increased risk for severe respiratory failure in COVID-19 patients with pneumonia.

BACKGROUND: In December 2019, the coronavirus disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), emerged in Wuhan, China, and has since spread throughout the world. This study aimed to investigate the association between the change in laboratory markers during the three days after pneumonia diagnosis and severe respiratory failure in COVID-19 patients. METHODS: Data of 23 COVID-19 patients with pneumonia, admitted to the Kumamoto City Hospital between February and April 2020 were retrospectively analyzed. RESULTS: Among the 23 patients, eight patients received mechanical ventilation (MV) (MV group), and the remaining 15 comprised the non-MV group. The levels of hemoglobin (Hb) and albumin (Alb) decreased in the MV group during the three days after pneumonia diagnosis more than in the non-MV group (median Hb: 1.40 vs. -0.10 g/dL, P = 0.015; median Alb: 0.85 vs. -0.30 g/dL, P = 0.020). Univariate logistic regression analysis showed that the decrease in Hb was associated with receiving MV care (odds ratio: 0.313, 95% confidence interval: 0.100-0.976, P = 0.045). Receiver operating characteristic curve analyses showed that the optimal cut-off value for the decrease in Hb level was -1.25 g/dL, with sensitivity and specificity values of 0.867 and 0.750, respectively. CONCLUSIONS: The decrease in Hb level during the short period after pneumonia diagnosis might be a predictor of worsening pneumonia in COVID-19 patients.

Measurement of oxidized albumin: An opportunity for diagnoses or treatment of COVID-19.

Human serum albumin (HSA) as the most abundant protein in human blood plasma, can be a good indicator for evaluating severity of some diseases in the clinic. HSA can be find in two forms: reduced albumin (human mercaptalbumin (HMA)) and oxidized albumin (human non-mercaptalbumin (HNA)). The rate of oxidized albumin to total albumin can be enhanced in multiple diseases. Increase in HNA level have been demonstrated in liver, diabetes plus fatigue and coronary artery diseases. In liver patients, this enhancement can reach to 50-200 percent which can then lead to bacterial/viral infections and eventually death in severe conditions. Due to the induction of cytokine storm, we can say that the level of HNA in serum of coronavirus disease 2019 (COVID-19) patients may be a positive predictor of mortality, especially in patients with underlying diseases such as cardiovascular disease (CVD), diabetes, aging and other inflammatory diseases. We suggest that checking oxidized albumin in COVID-19 patients may provide new therapeutic and diagnostic opportunities to better combat COVID-19.

Combination of serum lactate dehydrogenase and sex is predictive of severe disease in patients with COVID-19.

Elevated serum lactate dehydrogenase (LDH) was commonly reported in COVID-19 patients. However, the relationship between LDH and the incidence of severe cases has not been characterized in those patients.We retrospectively analyzed the characteristics of patients from a designated isolation medical center for COVID-19 patients diagnosed from February 6 to March 1. Variables accessed within 48 hours on admission were compared between patients with and without the severe disease. Logistic model analyses were performed to examine the prognostic value of LDH for predicting severe disease.52 (28.6%) patients later developed severe disease. Comparing to non-severe cases, severe cases had a higher level of serum LDH (321.85 ±â€Š186.24 vs 647.35 ±â€Š424.26, P < .001), neutrophils (5.42 ±â€Š3.26 vs 9.19 ±â€Š6.33, P < .001), and C-reactive protein (38.63 ±â€Š43.14 vs 83.20 ±â€Š51.01, P < .001). The patients with severe disease tended to be male (44.6% vs 80.8%, P < .001), lower level of serum albumin (31.41 ±â€Š6.20 vs 27.18 ±â€Š5.74, P < .001), and SpO2 (96.30 ±â€Š2.75 vs 92.37 ±â€Š8.29, P < .001). In the multivariate analysis model, LDH and sex remained independent risk factors for severe disease. The serum LDH predicted severe cases with an area under the curve (AUC) of 0.7999. A combination of serum LDH and sex predicted severe cases with an AUC of 0.849. A combination of serum LDH accessed on admission and sex had a better predictive performance than the serum LDH (P = .0238).Serum LDH on admission combined with sex is independently associated with severe disease in COVID-19.

Factors significantly associated with COVID-19 severity in symptomatic patients: A retrospective single-center study.

INTRODUCTION: The severity of coronavirus disease (COVID-19) in Japanese patients is unreported. We retrospectively examined significant factors associated with disease severity in symptomatic COVID-19 patients (COVID-Pts) admitted to our institution between February 20 and April 30, 2020. METHODS: All patients were diagnosed based on the genetic detection of severe acute respiratory syndrome coronavirus 2. Information on the initial symptoms, laboratory data, and computed tomography (CT) images at hospitalization were collected from the patients' records. COVID-Pts were categorized as those with critical or severe illness (Pts-CSI) or those with moderate or mild illness (Pt-MMI). All statistical analyses were performed using R software. RESULTS: Data from 61 patients (16 Pt-CSI, 45 Pt-MMI), including 58 Japanese and three East Asians, were analyzed. Pt-CSI were significantly older and had hypertension or diabetes than Pt-MMI (P < 0.001, 0.014 and < 0.001, respectively). Serum albumin levels were significantly lower in Pt-CSI than in Pt-MMI (P < 0.001), whereas the neutrophil-to-lymphocyte ratio and C-reactive protein level were significantly higher in Pt-CSI than in Pt-MMI (P < 0.001 and P < 0.001, respectively). In the CT images of 60 patients, bilateral lung lesions were more frequently observed in Pt-CSI than in Pt-MMI (P = 0.013). Among the 16 Pt-CSI, 15 received antiviral therapy, 12 received tocilizumab, five underwent methylprednisolone treatment, six received mechanical ventilation, and one died. CONCLUSIONS: The illness severity of Japanese COVID-Pts was associated with older age, hypertension and/or diabetes, low serum albumin, high neutrophil-to-lymphocyte ratio, and C-reactive protein.

Novel serological biomarkers for inflammation in predicting disease severity in patients with COVID-19.

BACKGROUND: Patients with severe coronavirus disease 2019 (COVID-19) develop acute respiratory distress and multi-system organ failure and are associated with poor prognosis and high mortality. Thus, there is an urgent need to identify early diagnostic and prognostic biomarkers to determine the risk of developing serious illness. METHODS: We retrospectively analyzed 114 patients with COVID-19 at the Jinyintan Hospital, Wuhan based on their clinical and laboratory data. Patients were categorized into severe and mild to moderate disease groups. We analyzed the potential of serological inflammation indicators in predicting the severity of COVID-19 in patients using univariate and multivariate logistic regression, receiver operating characteristic curves, and nomogram analysis. The Spearman method was used to understand the correlation between the serological biomarkers and duration of hospital stay. RESULTS: Patients with severe disease had reduced neutrophils and lymphocytes; severe coagulation dysfunction; altered content of biochemical factors (such as urea, lactate dehydrogenase); elevated high sensitivity C-reactive protein levels, neutrophil-lymphocyte, platelet-lymphocyte, and derived neutrophil-lymphocyte ratios, high sensitivity C-reactive protein-prealbumin ratio (HsCPAR), systemic immune-inflammation index, and high sensitivity C-reactive protein-albumin ratio (HsCAR); and low lymphocyte-monocyte ratio, prognostic nutritional index (PNI), and albumin-to-fibrinogen ratio. PNI, HsCAR, and HsCPAR correlated with the risk of severe disease. The nomogram combining the three parameters showed good discrimination with a C-index of 0.873 and reliable calibration. Moreover, HsCAR and HsCPAR correlated with duration of hospital stay. CONCLUSION: Taken together, PNI, HsCAR, and HsCPAR may serve as accurate biomarkers for the prediction of disease severity in patients with COVID-19 upon admission/hospitalization.

Elevated Liver Biochemistries in Hospitalized Chinese Patients With Severe COVID-19: Systematic Review and Meta-analysis.

BACKGROUND AND AIMS: Several recent studies have reported an abnormal liver chemistry profile among patients with coronavirus disease 2019 (COVID-19), although its clinical significance remains unknown. APPROACH AND RESULTS: This systematic review and meta-analysis identified six studies of 586 patients delineating liver chemistries among patients with severe/critical illness versus mild cases of COVID-19 infection. Patients with severe/critical illness with COVID-19 infection have increased prevalence of coronary artery disease, cerebrovascular disease, and chronic obstructive pulmonary disease as compared with mild cases. A significant association between severe/critical COVID-19 infections with elevations in aspartate aminotransferase (pooled mean difference [MD], 11.70 U/L; 95% confidence interval [CI], 2.97, 20.43; P = 0.009), elevated total bilirubin (pooled MD, 0.14 mg/dL; 95% CI, 0.06, 0.22; P = 0.0005), and decreased albumin (pooled MD, -0.68 g/L; 95% CI, -0.81, -0.55; P < 0.00001) was noted. There was also a trend toward elevated alanine aminotransferase levels among these severe cases (pooled MD, 8.84 U/L; 95% CI, -2.28, 19.97; P = 0.12); however, this did not reach statistical significance. More severe/critically ill cases were associated with leukocytosis, neutrophilia, lymphopenia, elevated creatinine kinase, elevated lactate dehydrogenase (LDH), and elevated prothrombin time (PT). CONCLUSIONS: Comorbidities, including coronary artery disease, cerebrovascular disease and chronic obstructive pulmonary disease, are more prevalent in hospitalized Chinese patients with severe/critical illness from COVID-19, and these patients are more likely to manifest with abnormal liver chemistries. Further prospective studies are crucial to understand the pathophysiologic mechanisms underlying the hepatic manifestations of the novel COVID-19 infection and its clinical significance.