Value of clinical laboratory test for early prediction of mortality in patients with COVID-19: the BGM score

Significant association between asthma and a lower risk of mortality among COVID-19 patients in Spain: A meta-analysis

Background

Various prevalences of asthma in coronavirus disease 2019 (COVID-19) have been reported in different regions, and the association between asthma and COVID-19 subsequent mortality has been in debate. Thus, this study aimed to investigate whether there was a significant association between asthma and COVID-19 mortality in Spain through a meta-analysis.

Methods

The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines were strictly complied with conducting this study. The pooled odds ratio (OR) with a corresponding 95% confidence interval (CI) was calculated by a random-effects model. The I 2 statistics for heterogeneity, sensitivity analysis for robustness, Begg's test, and Egger's test for publication bias, along with subgroup analyses for confounding bias, were also performed to support the foundation of this study.

Results

The meta-analysis revealed that asthma was significantly associated with a lower risk of mortality among COVID-19 patients in Spain with a random-effects model (pooled OR = 0.78, 95% CI = 0.69-0.88, I 2 = 35%). Further subgroup analyses by male proportion and sample size also indicated that a statistically significant negative correlation did exist between asthma and COVID-19 mortality. Robustness and no publication on-bias were evidenced by sensitivity analysis, Egger's test, and Begg's test, respectively.

Conclusion

In conclusion, patients with asthma were found to have a lower risk of mortality from COVID-19 in Spain, especially among elderly patients. In addition, asthmatic patients infected with COVID-19 may be at risk of death compared to non-asthmatic patients, which is not a cause for undue concern, thereby reducing the burden of medication.

SCD14-ST and New Generation Inflammatory Biomarkers in the Prediction of COVID-19 Outcome

Since no definitive cure for COVID-19 is available so far, one of the challenges against the disease is understanding the clinical features and the laboratory inflammatory markers that can differentiate among different severity grades of the disease. The aim of the present study is a comprehensive and longitudinal evaluation of SCD14-ST and other new inflammatory markers, as well as cytokine storm molecules and current inflammatory parameters, in order to define a panel of biomarkers that could be useful for a better prognostic prediction of COVID-19 mortality. SCD14-ST, as well as the inflammatory markers IL-6, IL-10, SuPAR and sRAGE, were measured in plasma-EDTA of ICU COVID-19 positive patients. In this longitudinal study, SCD14-ST resulted significantly higher in patients who eventually died compared to those who were discharged from the ICU. The results suggest that the new infection biomarker SCD14-ST, in addition to new generation inflammatory biomarkers, such as SuPAR, sRAGE and the cytokines IL-6 and IL-10, can be a useful prognostic tool associated with canonical inflammatory parameters, such as CRP, to predict SARS-CoV-2 outcome in ICU patients.

Early changes in laboratory tests predict liver function damage in patients with moderate coronavirus disease 2019: a retrospective multicenter study

BACKGROUND

Most patients with coronavirus disease 2019 demonstrate liver function damage. In this study, the laboratory test data of patients with moderate coronavirus disease 2019 were used to establish and evaluate an early prediction model to assess the risk of liver function damage.

METHODS

Clinical data and the first laboratory examination results of 101 patients with moderate coronavirus disease 2019 were collected from four hospitals' electronic medical record systems in Jilin Province, China. Data were randomly divided into training and validation sets. A logistic regression analysis was used to determine the independent factors related to liver function damage in patients in the training set to establish a prediction model. Model discrimination, calibration, and clinical usefulness were evaluated in the training and validation sets.

RESULTS

The logistic regression analysis showed that plateletcrit, retinol-binding protein, and carbon dioxide combining power could predict liver function damage (P < 0.05 for all). The receiver operating characteristic curve showed high model discrimination (training set area under the curve: 0.899, validation set area under the curve: 0.800; P < 0.05). The calibration curve showed a good fit (training set: P = 0.59, validation set: P = 0.19; P > 0.05). A decision curve analysis confirmed the clinical usefulness of this model.

CONCLUSIONS

In this study, the combined model assesses liver function damage in patients with moderate coronavirus disease 2019 performed well. Thus, it may be helpful as a reference for clinical differentiation of liver function damage. Trial registration retrospectively registered.

Association of Interleukin-17F Polymorphism and Mortality Predictors with the Risk of COVID-19

BACKGROUND

Th-17 cells, a proinflammatory subset of CD4 T lymphocytes, have been suggested as a possible cause of coronavirus disease-19 (COVID-19)-related immunological injuries. The aim of this study was to investigate the relationship between IL-17F (rs763780) polymorphism and the susceptibility to and outcomes of COVID-19 infection and to determine the clinical and laboratory predictors of COVID-19 death.

METHODS

This case-control study included 132 COVID-19 patients and 135 healthy age- and sex-matched controls. The participants were tested for IL-17F rs763780 polymorphism via TaqMan-based genotyping and for the expression of IL-17 by enzyme-linked immunosorbent assay. This study also investigated the predictors for COVID-19 mortality.

RESULTS

A non-statistically significant association was observed between IL-17F alleles and genotypes with COVID-19 (P=0.309, P=0.138, respectively). Moreover, no significant difference in the IL-17F genotypes was observed between non-survivors and survivors (P=0.482). In the multivariate analysis, the participants with the following characteristics had 17.7-, 11.2-, 8-, and 17.9-fold higher odds of exhibiting in-hospital mortality, respectively: (1) hypertension, (2) age of >57 years, (3) WBC count of >12.6 × 10³/mm³, and (4) D-dimer of >0.9 ng/ml. The ROC curve analysis showed that IL-17 at a cutoff point of >46 pg/ml was a perfect discriminator of COVID-19 patients from control subjects (AUC = 1.0).

CONCLUSION

The findings indicate that the IL-17F H161R variant does not influence the risk of COVID-19. However, the IL-17 level is a perfect discriminator of COVID-19 infection. Hypertension, age of >57 years, white blood cell count of >12.6 × 10³/mm³, and D-dimer of >0.9 ng/ml are the independent predictors for death among COVID-19 patients.