Crucial laboratory parameters in COVID-19 diagnosis and prognosis: An updated meta-analysis

Clinical features that predict the mortality risk in older patients with Omicron pneumonia: the MLWAP score

In December 2022, the Chinese suffered widespread Omicron of SARS-CoV-2 with variable symptom severity and outcome. We wanted to develop a scoring model to predict the mortality risk of older Omicron pneumonia patients by analyzing admission data. We enrolled 227 Omicron pneumonia patients aged 60 years and older, admitted to our hospital from December 15, 2022, to January 16, 2023, and divided them randomly into a 70% training set and a 30% test set. The former were used to identify predictors and develop a model, the latter to verify the model, using the area under the receiver operating characteristic curve (AUC), the Hosmer-Lemeshow goodness-of-fit test, a calibration curve to test its performance and comparing it to the existing scores. The MLWAP score was calculated based on a multivariate logistic regression model to predict mortality with a weighted score that included immunosuppression, lactate ≥ 2.4, white blood cell count ≥ 6.70 × 109/L, age ≥ 77 years, and PaO2/FiO2 ≤ 211. The AUC for the model in the training and test sets was 0.852 (95% CI, 0.792-0.912) and 0.875 (95% CI, 0.789-0.961), respectively. The calibration curves showed a good fit. We grouped the risk scores into low (score 0-7 points), medium (8-10 points), and high (11-13 points). This model had a sensitivity of 0.849, specificity of 0.714, and better predictive ability than the CURB-65 and PSI scores (AUROC = 0.859 vs. 0.788 vs. 0.801, respectively). The MLWAP-mortality score may help clinicians to stratify hospitalized older Omicron pneumonia patients into relevant risk categories, rationally allocate medical resources, and reduce the mortality.

Elucidating systemic immune responses to acute and convalescent SARS-CoV-2 infection in children and elderly individuals

BACKGROUND

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), a causative pathogen of the COVID-19 pandemic, affects all age groups. However, various studies have shown that COVID-19 presentation and severity vary considerably with age. We, therefore, wanted to examine the differences between the immune responses of children with COVID-19 and elderly COVID-19 individuals.

METHODS

We analyzed cytokines, chemokines, growth factors, and acute phase proteins in acute and convalescent COVID-19 children and the elderly with acute and convalescent COVID-19.

RESULTS

We show that most of the pro-inflammatory cytokines (interferon [IFN]γ, interleukin [IL]-2, tumor necrosis factor-α [TNFα], IL-1α, IFNα, IFNβ, IL-6, IL-12, IL-3, IL-7, IL-1Ra, IL-13, and IL-10), chemokines (CCL4, CCL11, CCL19, CXCL1, CXCL2, CXCL8, and CXL10), growth factors (vascular endothelial growth factor and CD40L) and acute phase proteins (C-reactive protein, serum amyloid P, and haptoglobin) were decreased in children with acute COVID 19 as compared with elderly individuals. In contrast, children with acute COVID-19 exhibited elevated levels of cytokines- IL-1β, IL-33, IL-4, IL-5, and IL-25, growth factors-fibroblast growth factor-2, platelet- derived growth factors-BB, and transforming growth factorα as compared with elderly individuals. Similar, differences were manifest in children and elderly with convalescent COVID-19.

CONCLUSION

Thus, COVID-19 children are characterized by distinct cytokine/chemokine/growth factor/acute phase protein markers that are markedly different from elderly COVID-19 individuals.

Relationship between clinical-epidemiological parameters and outcomes of patients with COVID-19 admitted to the intensive care unit: a report from a Brazilian hospital

Background

People in low-income countries, especially those with low socio-economic conditions, are likelier to test positive for SARS-CoV-2. The unequal conditions of public health systems also increase the infection rate and make early identification and treatment of at-risk patients difficult. Here, we aimed to characterize the epidemiological profile of COVID-19 patients in intensive care and identify laboratory and clinical markers associated with death.

Materials and methods

We conducted an observational, descriptive, and cross-sectional study in a reference hospital for COVID-19 treatment in the Southern Region of Bahia State, in Brazil, to evaluate the epidemiological, clinical, and laboratory characteristics of COVID-19 patients admitted to the intensive care unit (ICU). Additionally, we used the area under the curve (AUC) to classify survivors and non-survivors and a multivariate logistic regression analysis to assess factors associated with death. Data was collected from the hospital databases between April 2020 and July 2021.

Results

The use of bladder catheters (OR 79.30; p < 0.0001) and central venous catheters (OR, 45.12; p < 0.0001) were the main factors associated with death in ICU COVID-19 patients. Additionally, the number of non-survivors increased with age (p < 0.0001) and prolonged ICU stay (p < 0.0001). Besides, SAPS3 presents a higher sensibility (77.9%) and specificity (63.1%) to discriminate between survivors and non-survivor with an AUC of 0.79 (p < 0.0001).

Conclusion

We suggest that multi-laboratory parameters can predict patient prognosis and guide healthcare teams toward more assertive clinical management, better resource allocation, and improved survival of COVID-19 patients admitted to the ICU.

Neurological manifestations in SARS-CoV-2 infection: A single-center cross-sectional study in Malaysia

Background

Neurological involvement associated with SARS-CoV-2 infection has been reported from different regions of the world. However, data from South East Asia are scarce. We described the neurological manifestations and their associated factors among the hospitalized COVID-19 patients from an academic tertiary hospital in Malaysia.

Methods

A cross-sectional observational study of hospitalized COVID-19 patients was conducted. The neurological manifestations were divided into the self-reported central nervous system (CNS) symptoms, stroke associated symptoms, symptoms of encephalitis or encephalopathy and specific neurological complications. Multiple logistic regression was performed using demographic and clinical variables to determine the factors associated with outcome.

Results

Of 156 hospitalized COVID-19 patients with mean age of 55.88 ± 6.11 (SD) years, 23.7% developed neurological complications, which included stroke, encephalitis and encephalopathy. Patients with neurological complications were more likely to have diabetes mellitus (p = 0.033), symptoms of stroke [limb weakness (p < 0.001), slurred speech (p < 0.001)]; and encephalitis or encephalopathy [confusion (p < 0.001), forgetfulness (p = 0.006) and seizure (p = 0.019)]. Unvaccinated patients had a 4.25-fold increased risk of having neurological complications (adjusted OR = 4.25; 95% CI: 1.02, 17.71, p = 0.047). Anosmia and dysgeusia were less associated with neurological complications (adjusted OR = 0.22; 95% CI: 0.05, 0.96, p = 0.044). The odds of neurological complications were increased by 18% in patients with leukocytosis (adjusted OR = 1.18, 95% CI: 1.003, p = 0.0460).

Conclusions

Stroke, encephalitis and encephalopathy were the common neurological complications from our study. Diabetes mellitus, presence of symptoms of stroke, symptoms of encephalitis or encephalopathy, leukocytosis, and being unvaccinated against COVID-19 were the associated risk factors of developing neurological complications.

Biochemical Parameters as Prognostic Markers in Severely Ill COVID-19 Patients

Background

Prognostication plays a pivotal role in critical care medicine. Its importance is indisputable in the management of coronavirus disease 2019 (COVID-19), as the presentation of this disease may vary from docile, self-limiting symptoms to lethal conditions. Amid the COVID-19 pandemic, much emphasis was initially placed on molecular and serological testing. However, it was realized later that routine laboratory tests also provide key information in terms of the severity of the disease and thus could be used to predict the outcome of these patients.

Methodology

The aim of our study was to evaluate the biochemical parameters as prognostic markers in severely ill COVID-19 patients. We carried out a retrospective, case-control study. The study population was comprised of all severely ill COVID-19 patients admitted between October 2020 and January 2021 at our level 3 COVID hospital. Cases were defined as the patients who expired despite treatment and all resuscitative measures as per the standard operating procedures (SOPs) of our COVID intensive care unit (ICU) while controls were defined as the patients that were transferred out of the COVID ICU for further recovery. The detailed history, findings of physical examination, vitals recorded by point of care testing (POCT) devices at our ICU, clinical diagnosis, and the results of the biochemical analysis were recorded in a specially designed pro forma. The biochemical parameters recorded at the time of admission were compared between the groups of controls and cases in order to evaluate their role as predictors of mortality using appropriate statistical methods. P-values less than 0.05 were considered statistically significant. For all the parameters that showed a statistically significant difference, receiver operating characteristics (ROC) analysis was done to assess the utility of biochemical parameters as predictors of mortality or survival. Areas under the curve (AUCs) of 0.6 to 0.7, 0.7 to 0.8, 0.8 to 0.9, and >0.9 were considered acceptable, fair, good, and excellent for discrimination, respectively.

Results

Of the 178 severely ill COVID-19 patients enrolled in the study, 86 were controls and 92 were cases (52% mortality). Serum urea (p<0.0001), creatinine (p=0.0019), aspartate transaminase (AST) (p=0.0104), lactate dehydrogenase (LDH) (p=0.0001), procalcitonin (PCT) (p=0.0344), and interleukin 6 (IL-6) (p=0.0311) levels were significantly higher (p<0.05), while total protein (p=0.0086), albumin (p<0.0001), and indirect bilirubin (p=0.0147) levels were significantly lower (p<0.05) in cases as compared to controls. The difference was statistically insignificant (p>0.05) for serum sodium, potassium, total and direct bilirubin, globulin, alanine transaminase (ALT), alkaline phosphatase (ALP), D-dimer, and ferritin. On ROC analysis, urea was fair (AUC=0.721), creatinine (AUC=0.698) and IL-6 (AUC=0.698) were acceptable predictors of mortality, while albumin (AUC=0.698) was an acceptable predictor of survival in severely ill COVID-19 patients during their intensive care stay.

Conclusion

Understanding the pathophysiological changes associated with the severity of COVID-19 in terms of an alteration of biochemical parameters is a pressing priority. Our study highlights the importance of routine laboratory tests in predicting outcomes in severely ill COVID-19 patients.

Comparison of the clinical parameters of patients with COVID-19 and influenza using blood test data: a retrospective cross-sectional survey

Objective

The characteristic features, including blood test data, of the novel coronavirus disease 2019 (COVID-19) versus influenza have not been defined. We therefore compared the clinical parameters, including blood test data, of COVID-19 and influenza.

Methods

This retrospective cross-sectional survey was conducted at Juntendo University Nerima Hospital. We recruited patients diagnosed with COVID-19 between 1 January 2020 and 31 December 2020 who underwent blood tests. For comparison, we recruited an equivalent number of patients who were diagnosed with influenza and who underwent blood tests.

Results

During the study period, 228 patients (male:female, 123 [54.0%]:105 [46.0%]; age, 54.68 ± 18.98 years) were diagnosed with COVID-19. We also recruited 228 patients with influenza (male:female, 129 [56.6%]:99 [43.4%]; age, 69.6 ± 21.25 years). An age of 15 to 70 years (vs. 71 years), breathing difficulty, and malaise were significantly more common in patients with COVID-19 than in those with influenza. However, nausea, body temperature >38.1°C, and white blood cell count >9000/μL were more common in patients with influenza.

Conclusions

Our results are useful for differentiating COVID-19 from influenza, and these findings will be extremely helpful for future practice as we learn to coexist with COVID-19.

Are blood groups related to the distribution and severity of COVID-19? A cross-sectional study in a tertiary care hospital in South India

Background: Blood groups are inherited traits that affect the susceptibility/severity of a disease. A clear relationship between coronavirus disease 2019 (COVID-19) and ABO blood groups is yet to be established in the Indian population. This study aimed to demonstrate an association of the distribution and severity of COVID-19 with ABO blood groups. Methods: A cross-sectional study was conducted after obtaining ethics approval (IEC 207/20) among hospitalized patients using in-patient records and analyzed on SPSS-25. Chi-square tests were used for the analysis of categorical data and independent sample t-test/Mann–Whitney U tests were used for continuous data. Results: The B blood group had the highest prevalence among COVID-19-positive patients. The AB blood group was significantly associated with acute respiratory distress syndrome (ARDS) (p = 0.03), sepsis (p = 0.02), and septic shock (p = 0.02). The O blood group was associated with significantly lower rates of lymphopenia and leucocytosis. However, no significant clinical association was seen in the O blood group. Conclusion: This study has demonstrated that blood groups have a similar distribution among patients hospitalized with COVID-19 in the South Indian population. Additionally, it preludes to a possible association between the AB blood group and ARDS, sepsis, and septic shock. Further studies having a larger representation of AB blood groups, especially in patients hospitalized for critical COVID-19, with adjustment for possible covariates, are warranted to provide a reliable estimate of the risk in the South Indian population.

Psychiatric sequelae in COVID-19 survivors: A narrative review

In December 2019, a novel coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) was initially reported in Wuhan, China. Previous epidemics including SARS and middle east respiratory syndrome raises concern that COVID-19 infection may pose a significant threat to the mental health of affected individuals. Studies and reviews have shown the acute psychiatric manifestations in COVID-19 patients, although long term psychiatric sequelae are predicted, there are only few review studies about the long term psychiatry outcome in COVID-19 survivors. Clinically significant post-traumatic stress disorder, anxiety, and/or depression among COVID-19 survivors during 14-90 d were observed following the diagnosis. Risk of anxiety or depression were higher in patients with more severe illness at 6 mo follow-up, early convalescence, and at 1 mo follow-up. Diagnosis of COVID-19 Led to more first diagnoses and relapses of psychiatric illness during the first 14-90 d after COVID-19 diagnosis. The possible underlying mechanisms of psychiatric sequelae in COVID-19 infection are neurotropism, immune response to SARS-CoV-2, hypothalamo-pituitary-adrenal axis hyperactivity, disrupted neuronal circuits in several brain regions, increased stress levels, neuroinflammation, and neuronal death. This study will review the psychiatric sequelae in previous coronavirus pandemics, current studies, risk factors, and thorough explanation on pathophysiology of the psychiatric sequalae in COVID-19 survivors.

Annexin A1 as a potential prognostic biomarker for COVID-19 disease: Case-control study

BACKGROUND

Annexin A1 (AnxA1) is an important endogenous glucocoticoid protein that contributes to the suppression of inflammation by limiting the production of neutrophil and pro-inflammatory cytokines. This study aims to determine the clinical predictivity value of blood AnxA1 levels in patients with mild and severe-critical pneumonia induced by COVID-19.

METHODS

This study employed a prospective, case-control study design and was conducted at Ankara Training and Research hospital between 10 February 2021 and 15 March 2021. A total of 74 patients (42 of whom had moderate and 32 of whom had severe/critical cases of COVID-19 disease according to World Health Organization guidelines) and 50 nonsymptomatic healthy volunteers participated in the study. Blood samples were taken from patients at the time of hospital admission, after which serum was isolated. Following the isolation of serum, AnxA1 levels were evaluated using the enzyme-linked immunosorbent assay method.

RESULTS

The serum AnxA1 levels were measured as 25.5 (18.6-38.6) ng/ml in the control group, 21.2 (14.7-32) ng/ml in the moderate disease group, and 14.8 (9.7-26.8) ng/ml in the severe/critical disease group. Serum AnxA1 levels were significantly lower in the severe/critical disease group compared with the control and moderate disease groups (P = .01 and P = .0001, respectively). Using receiver operating characteristic analysis, a larger area under the curve (AUC) for the serum AnxA1 levels of the control group (AUC = 0.715, 95% CI = 0.626-0.803; P = .0001) was calculated compared with the COVID-19 patient group for the diagnosis of COVID-19 disease. The AnxA1 level was found to be 80% sensitive and 54.1% specific at a cut-off level of 18.5 ng/ml for the diagnosis of COVID-19 disease. Moreover, the AnxA1 level was found to be 69.8% sensitive and 58.1% specific at a cut-off level of 17.2 ng/ml in predicting the need for intensive care unit (ICU) treatment.

CONCLUSION

AnxA1 levels may be a beneficial biomarker in the diagnosis of COVID-19 pneumonia and in predicting the need for ICU treatment in patients with COVID-19 pneumonia at the time of admission to the emergency department.

High-value laboratory testing for hospitalized COVID-19 patients: a review

We present here an evidence-based review of the utility, timing, and indications for laboratory test use in the domains of inflammation, cardiology, hematology, nephrology and co-infection for clinicians managing the care of hospitalized COVID-19 patients. Levels of IL-6, CRP, absolute lymphocyte count, neutrophils and neutrophil-to-lymphocyte ratio obtained upon admission may help predict the severity of COVID-19. Elevated LDH, ferritin, AST, and d-dimer are associated with severe illness and mortality. Elevated cardiac troponin at hospital admission can alert clinicians to patients at risk for cardiac complications. Elevated proBNP may help distinguish a cardiac complication from noncardiac etiologies. Evaluation for co-infection is typically unnecessary in nonsevere cases but is essential in severe COVID-19, intensive care unit patients, and immunocompromised patients.

Optic Nerve Head Vessel Density Assessment in Recovered COVID-19 Patients: A Prospective Study Using Optical Coherence Tomography Angiography

PRECIS

Vascular diseases have been linked to alterations in optic nerve head perfusion.

PURPOSE

The main objective was to investigate the changes in peripapillary vessel density (VD) in post coronavirus disease (COVID-19) patients.

METHODS

In this prospective pilot exploratory study, patients with COVID-19 that were attended in the Emergency Department of Hospital Clinico San Carlos (Madrid) were included. All patients underwent optic nerve head optical coherence tomography angiography using the Cirrus HD-OCT 500 with AngioPlex OCTA (Zeiss, Dublin, CA) 4 and 12 weeks after diagnosis by positive reverse transcriptase-polymerase chain reaction test from nasopharyngeal swab at the Emergency Department. Sociodemographic data, medical history, disease severity, and laboratory work-up were collected.

RESULTS

One hundred and eighty eyes of 90 patients with severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection were included. None of the patients reported visual changes. Severe patients were older, more frequently hispanic, dyslipidemic, and presented lower lymphocytes counts, as well as increased ferritin, D-dimer, fibrinogen, and international normalized ratio levels. No changes in optic nerve head vascularization were observed when both visits were compared. No correlation was found between VD and clinical parameters, disease severity and laboratory work-up.

CONCLUSIONS

Changes to peripapillary VD were not observed in patients with COVID-19 in the early months following diagnosis.

Using Unsupervised Machine Learning to Identify Age- and Sex-Independent Severity Subgroups Among Patients with COVID-19: Observational Longitudinal Study

Background

Early detection and intervention are the key factors for improving outcomes in patients with COVID-19.

Objective

The objective of this observational longitudinal study was to identify nonoverlapping severity subgroups (ie, clusters) among patients with COVID-19, based exclusively on clinical data and standard laboratory tests obtained during patient assessment in the emergency department.

Methods

We applied unsupervised machine learning to a data set of 853 patients with COVID-19 from the HM group of hospitals (HM Hospitales) in Madrid, Spain. Age and sex were not considered while building the clusters, as these variables could introduce biases in machine learning algorithms and raise ethical implications or enable discrimination in triage protocols.

Results

From 850 clinical and laboratory variables, four tests—the serum levels of aspartate transaminase (AST), lactate dehydrogenase (LDH), C-reactive protein (CRP), and the number of neutrophils—were enough to segregate the entire patient pool into three separate clusters. Further, the percentage of monocytes and lymphocytes and the levels of alanine transaminase (ALT) distinguished cluster 3 patients from the other two clusters. The highest proportion of deceased patients; the highest levels of AST, ALT, LDH, and CRP; the highest number of neutrophils; and the lowest percentages of monocytes and lymphocytes characterized cluster 1. Cluster 2 included a lower proportion of deceased patients and intermediate levels of the previous laboratory tests. The lowest proportion of deceased patients; the lowest levels of AST, ALT, LDH, and CRP; the lowest number of neutrophils; and the highest percentages of monocytes and lymphocytes characterized cluster 3.

Conclusions

A few standard laboratory tests, deemed available in all emergency departments, have shown good discriminative power for the characterization of severity subgroups among patients with COVID-19.

Human immunodeficiency virus and mortality from coronavirus disease 2019: A systematic review and meta-analysis

Background

Persons living with human immunodeficiency virus (PLWH) constitute a vulnerable population in view of their impaired immune status. At this time, the full interaction between HIV and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been incompletely described.

Objective

The purpose of this study was to explore the impact of HIV and SARS-CoV-2 co-infection on mortality.

Method

We systematically searched PubMed and the Europe PMC databases up to 19 January 2021, using specific keywords related to our aims. All published articles on coronavirus disease 2019 (COVID-19) and HIV were retrieved. The quality of the studies was evaluated using the Newcastle–Ottawa Scale for observational studies. Statistical analysis was performed with Review Manager version 5.4 and Comprehensive Meta-Analysis version 3 software.

Results

A total of 28 studies including 18 255 040 COVID-19 patients were assessed in this meta-analysis. Overall, HIV was associated with a higher mortality from COVID-19 on random-effects modelling {odds ratio [OR] = 1.19 [95% confidence interval (CI) = 1.01–1.39], p = 0.03; I² = 72%}. Meta-regression confirmed that this association was not influenced by age (p = 0.208), CD4 cell count (p = 0.353) or the presence of antiretroviral therapy (ART) (p = 0.647). Further subgroup analysis indicated that the association was only statistically significant in studies from Africa (OR = 1.13, p = 0.004) and the United States (OR = 1.30, p = 0.006).

Conclusion

Whilst all persons ought to receive a SARS-CoV-2 vaccine, PLWH should be prioritised to minimise the risk of death because of COVID-19. The presence of HIV should be regarded as an important risk factor for future risk stratification of COVID-19.

Potential Predictors of Poor Prognosis among Severe COVID-19 Patients: A Single-Center Study

Background

Timely detection of the progression of the highly contagious coronavirus disease (COVID-19) is of utmost importance for management and intervention for patients in intensive care (ICU).

Aim

This study aims to better understand this new infection and report the changes in the various laboratory tests identified in critically ill patients and associated with poor prognosis among COVID-19 patients admitted to the ICU.

Methods

This was a retrospective study that included 160 confirmed SARS-CoV-2-positive patients.

Results

Elevated serum ferritin, D-dimer, aspartate aminotransferase (AST), alanine aminotransferase (ALT), and nonconjugated bilirubin levels were present in 139 (96%), 131 (96%), 107 (68%), 52 (34%), and 89 (70%) patients, respectively. Renal parameters were abnormal in a significant number of cases with elevated creatinine and blood urea nitrogen in 93 (62%) and 102 (68%) cases, respectively. Hematological profiles revealed lower red blood cell count, hemoglobin, eosinophils, basophils, monocytes, and lymphocytes in 90 (57%), 103 (65%), 89 (62%), 105 (73%), 35 (24%), and 119 (83%) cases, respectively. The neutrophil count was found to increase in 71.3% of the cases. There was significantly higher mortality (83%) among patients older than 60 years (p=0.001) and in female patients (75%) (p=0.012). Patients with lung diseases had a poor outcome compared to patients with other comorbidities (p=0.002). There was a significant association between elevated D-dimer levels and increased mortality (p=0.003). Elevated levels of AST, creatinine, blood urea nitrogen, and bilirubin were significantly associated with unfavorable outcomes.

Conclusion

Different parameters can be used to predict disease prognosis, especially the risk of poor prognosis. Accurate diagnosis and monitoring of disease progression from the early stages will help in reducing mortality and unfavorable outcomes.

Biomarkers in COVID-19: An Up-To-Date Review

The ongoing pandemic of coronavirus disease 2019 (COVID-19) poses several challenges to clinicians. Timely diagnosis and hospitalization, risk stratification, effective utilization of intensive care services, selection of appropriate therapies, monitoring and timely discharge are essential to save the maximum number of lives. Clinical assessment is indispensable, but laboratory markers, or biomarkers, can provide additional, objective information which can significantly impact these components of patient care. COVID-19 is not a localized respiratory infection but a multisystem disease caused by a diffuse systemic process involving a complex interplay of the immunological, inflammatory and coagulative cascades. The understanding of what the virus does to the body and how the body reacts to it has uncovered a gamut of potential biomarkers. This review discusses the different classes of biomarkers - immunological, inflammatory, coagulation, hematological, cardiac, biochemical and miscellaneous - in terms of their pathophysiological basis followed by the current evidence. Differences between children and adults are highlighted. The role of biomarkers in the diagnosis and management of Multisystem Inflammatory Syndrome in Children (MIS-C) is reviewed. The correlation of biomarkers with clinical and radiological features and the viral load, temporal evolution and the effect of treatment remain to be studied in detail. Which biomarker needs to be evaluated when and in whom, and how best this information can contribute to patient care are questions which currently lack convincing answers. With the evidence currently available broad guidelines on the rational use of available biomarkers are presented. Integrating clinical and laboratory data, monitoring trends rather than a single value, correlating with the natural course of the disease and tailoring guidelines to the individual patient and healthcare setting are essential.

Application of a prediction model with laboratory indexes in the risk stratification of patients with COVID-19

In the present study, a prediction model with combined laboratory indexes in risk stratification of patients with COVID-19 was established and tested. The data of 170 patients with COVID-19 who were divided into an asymptomatic-moderate group (141 cases) and severe or above group (29 cases) were retrospectively analyzed. The clinical characteristics and laboratory indexes of the two groups were compared. Multivariate logistic regression analysis was performed to construct the prediction model based on laboratory indexes. A receiver operating characteristic (ROC) curve analysis was used to compare the diagnostic efficacy of different indexes. Decision curve analysis (DCA) was performed to quantify and compare the clinical validity of the prediction models. There were significant differences in blood cell count, high-sensitivity C-reactive protein (hsCRP) and procalcitonin (PCT) levels between the severe or above group and the asymptomatic-moderate group (all P<0.05). Among all individual indexes, hsCRP had the highest diagnostic efficacy (area under the curve=0.870), with a sensitivity and specificity of 0.828 and 0.802, respectively. The red blood cell count, hsCRP and PCT were used to construct the prediction model. The AUC of the prediction model was higher than that of hsCRP (0.912 vs. 0.870) but the difference was not significant (P=0.307). DCA suggested that the net benefit of the prediction model was higher than that of hsCRP in most cases and significantly higher than that of PCT, lymphocytes and monocytes. The prediction model with combined laboratory indexes was able to more effectively predict the clinical classification of patients with COVID-19 and may be used as a tool for risk stratification of patients.

Biomarkers and short-term prognosis in COVID-19

PURPOSE

The aim of our study was to analyse the short-term prognostic value of different biomarkers in patients with COVID-19.

METHODS

We included patients admitted to emergency department with COVID-19 and available concentrations of cardiac troponin I (cTnI), D-dimer, C-reactive protein (CRP) and lactate dehydrogenase (LDH). Patients were classified for each biomarker into two groups (low vs. high concentrations) according to their best cut-off point, and 30-day all-cause death was evaluated.

RESULTS

After multivariate adjustment, cTnI ≥21 ng/L, D-dimer ≥1112 ng/mL, CRP ≥10 mg/dL and LDH ≥334 U/L at admission were associated with an increased risk of 30-day all-cause death (hazard ratio (HR) 4.30; 95% CI 1.74-10.58; p = 0.002; HR 3.35; 95% CI 1.58-7.13; p = 0.002; HR 2.25; 95% CI 1.13-4.50; p = 0.021; HR 2.00; 95% CI 1.04-3.84; p = 0.039, respectively). The area under the curve for cTnI was 0.825 (95% CI 0.759-0.892) and, in comparison, was significantly better than CRP (0.685; 95% CI 0.600-0.770; p = 0.009) and LDH (0.643; 95% CI 0.534-0.753; p = 0.006) but non-significantly better than D-dimer (0.756; 95% CI 0.674-0.837; p = 0.115).

CONCLUSIONS

In patients with COVID-19, increased concentrations of cTnI, D-dimer, CRP and LDH are associated with short-term mortality. Of these, cTnI provides better mortality risk prediction. However, differences with D-dimer were non-significant.

Risk factors for severe and critically ill COVID-19 patients: A review

The pandemic of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused an unprecedented global social and economic impact, and high numbers of deaths. Many risk factors have been identified in the progression of COVID-19 into a severe and critical stage, including old age, male gender, underlying comorbidities such as hypertension, diabetes, obesity, chronic lung diseases, heart, liver and kidney diseases, tumors, clinically apparent immunodeficiencies, local immunodeficiencies, such as early type I interferon secretion capacity, and pregnancy. Possible complications include acute kidney injury, coagulation disorders, thoromboembolism. The development of lymphopenia and eosinopenia are laboratory indicators of COVID-19. Laboratory parameters to monitor disease progression include lactate dehydrogenase, procalcitonin, high-sensitivity C-reactive protein, proinflammatory cytokines such as interleukin (IL)-6, IL-1β, Krebs von den Lungen-6 (KL-6), and ferritin. The development of a cytokine storm and extensive chest computed tomography imaging patterns are indicators of a severe disease. In addition, socioeconomic status, diet, lifestyle, geographical differences, ethnicity, exposed viral load, day of initiation of treatment, and quality of health care have been reported to influence individual outcomes. In this review, we highlight the scientific evidence on the risk factors of severity of COVID-19.

Data on attitudes, religious perspectives, and practices towards COVID-19 among Indonesian residents: a quick online cross-sectional survey

Although previously large-scale social restrictions were implemented by the Indonesian government, the total number of coronavirus cases is overcome China in the global ranking per July 18th, 2020, implying a higher infection rate among Indonesian residents. The surge of new coronavirus cases started since the loosening of large-scale social restrictions, thereby implicating that public gathering (including religious gathering) evidently increases transmission [1]. It has been reported that Indonesia's coronavirus disease-19 (COVID-19) mortality rate is the second-highest among Southeast Asian Nations, which may be associated with several health determinants, including biochemical factors and health comorbidity [2], [3], [4], [5], [6], [7]. Because people's adherence to control measures is affected by their attitudes, religious perspectives, and practices (ARP) towards COVID-19. Hence, the information regarding Indonesian's ARP towards COVID-19 post-large-scale social restrictions is required. The data were collected via an online questionnaire, including demographic information (7 items), attitude and practice (5 items), and religious perspective and practice (5 items), from July 11 - 18, 2020, collecting a total of 1,345 respondents. Although our data collection did not provide other precautionary measures (e.g., adequate ventilation). It is notable that most of the religious venues are having a close ventilation system. Hence, this may contribute to the propagation of SARS-CoV-2 transmission [8]. Altogether, these data will help in determining non-health-related factors to prevent the spread of COVID-19.