Evidence-based characterization of the diagnostic and prognostic value of the hematological and immunological markers related to the epidemic of Coronavirus Disease 2019 (COVID-19) is critical to understand the clinical course of the infection and to assess in development and validation of biomarkers. Based on systematic search in Web of Science, PubMed, Scopus, and Science Direct up to April 22, 2020, a total of 52 eligible articles with 6,320 laboratory-confirmed COVID-19 cohorts were included. Pairwise comparison between severe versus mild disease, Intensive Care Unit (ICU) versus general ward admission and expired versus survivors were performed for 36 laboratory parameters. The pooled standardized mean difference (SMD) and 95% confidence intervals (CI) were calculated using the DerSimonian Laird method/random effects model and converted to the Odds ratio (OR). The decision tree algorithm was employed to identify the key risk factor(s) attributed to severe COVID-19 disease. Cohorts with elevated levels of white blood cells (WBCs) (OR = 1.75), neutrophil count (OR = 2.62), D-dimer (OR = 3.97), prolonged prothrombin time (PT) (OR = 1.82), fibrinogen (OR = 3.14), erythrocyte sedimentation rate (OR = 1.60), procalcitonin (OR = 4.76), IL-6 (OR = 2.10), and IL-10 (OR = 4.93) had higher odds of progression to severe phenotype. Decision tree model (sensitivity = 100%, specificity = 81%) showed the high performance of neutrophil count at a cut-off value of more than 3.74x10⁹/L for identifying patients at high risk of severe COVID‐19. Likewise, ICU admission was associated with higher levels of WBCs (OR = 5.21), neutrophils (OR = 6.25), D-dimer (OR = 4.19), and prolonged PT (OR = 2.18). Patients with high IL-6 (OR = 13.87), CRP (OR = 7.09), D-dimer (OR = 6.36), and neutrophils (OR = 6.25) had the highest likelihood of mortality. Several hematological and immunological markers, in particular neutrophilic count, could be helpful to be included within the routine panel for COVID-19 infection evaluation to ensure risk stratification and effective management.

Background: As an immune modulator, vitamin D has been implicated in the coronavirus disease‐2019 (COVID‐19) outcome. We aim to systematically explore the association of vitamin D serum levels with COVID‐19 severity and prognosis.Methods: The standardized mean difference (SMD) or odds ratio and 95% confidence interval (CI) were applied to estimate pooled results from six studies. The prognostic performance of vitamin D serum levels for predicting adverse outcomes with detection of the best cutoff threshold was determined by receiver operating characteristic curve analysis. Decision tree analysis by combining vitamin D levels and clinical features was applied to predict severity in COVID‐19 patients.Results: Mean vitamin D serum level of 376 patients, was 21.9 nmol/L (95% CI = 15.36–28.45). Significant heterogeneity was found (I² = 99.1%, p < .001). Patients with poor prognosis (N = 150) had significantly lower serum levels of vitamin D compared with those with good prognosis (N = 161), representing an adjusted standardized mean difference of −0.58 (95% Cl = −0.83 to −0.34, p < .001).Conclusion: Serum vitamin D levels could be implicated in the COVID‐19 prognosis. Diagnosis of vitamin D deficiency could be a helpful adjunct in assessing patients' potential of developing severe COVID‐19. Appropriate preventative and/or therapeutic intervention may improve COVID‐19 outcomes.

GLP-1 receptor agonists, traditionally used for treating type 2 diabetes mellitus and obesity, have demonstrated anti-inflammatory properties. However, their potential neuroprotective effects in neurodegenerative disorders remain unclear. To evaluate the impact of GLP-1 receptor agonists on the risk of developing various neurodegenerative conditions in obese patients. This comprehensive retrospective cohort study analyzed data from 5,307,845 obese adult patients across 73 healthcare organizations in 17 countries. Propensity score matching was performed, resulting in 102,935 patients in each cohort. We compared the risk of developing neurodegenerative disorders between obese patients receiving GLP-1 receptor agonist therapy and those who were not. Obese patients treated with GLP-1 receptor agonists showed significantly lower risks of developing Alzheimer's disease (RR = 0.627, 95 %CI = 0.481-0.817), Lewy body dementia (RR = 0.590, 95 %CI = 0.462-0.753), and vascular dementia (RR = 0.438, 95 %CI = 0.327-0.588). The risk reduction for Parkinson's disease was not statistically significant overall (RR = 0.784, 95 %CI = 0.580-1.058) but was significant for semaglutide users (RR = 0.574, 95 %CI = 0.369-0.893). Semaglutide consistently showed the most pronounced protective effects across all disorders. Additionally, a significant reduction in all-cause mortality was observed (HR = 0.525, 95 %CI = 0.493-0.558). This study provides evidence that the effects of GLP-1 receptor agonists may extend beyond their known metabolic and cardioprotective benefits to include neuroprotection, associated with a decreased risk of developing various neurodegenerative disorders. These findings suggest the potential for expanding the therapeutic applications of GLP-1 receptor agonists to improve neurocognitive outcomes. Further research is warranted to elucidate the mechanisms underlying these neuroprotective effects and to explore their clinical applications in neurodegenerative disease prevention and treatment.

Background: Coronavirus disease‐2019 (COVID‐19) has a deleterious effect on several systems, including the cardiovascular system. We aim to systematically explore the association of COVID‐19 severity and mortality rate with the history of cardiovascular diseases and/or other comorbidities and cardiac injury laboratory markers.Methods: The standardized mean difference (SMD) or odds ratio (OR) and 95% confidence intervals (CIs) were applied to estimate pooled results from the 56 studies. The prognostic performance of cardiac markers for predicting adverse outcomes and to select the best cutoff threshold was estimated by receiver operating characteristic curve analysis. Decision tree analysis by combining cardiac markers with demographic and clinical features was applied to predict mortality and severity in patients with COVID‐19.Results: A meta‐analysis of 17 794 patients showed patients with high cardiac troponin I (OR = 5.22, 95% CI = 3.73‐7.31, P < .001) and aspartate aminotransferase (AST) levels (OR = 3.64, 95% CI = 2.84‐4.66, P < .001) were more likely to develop adverse outcomes. High troponin I more than 13.75 ng/L combined with either advanced age more than 60 years or elevated AST level more than 27.72 U/L was the best model to predict poor outcomes.Conclusions: COVID‐19 severity and mortality are complicated by myocardial injury. Assessment of cardiac injury biomarkers may improve the identification of those patients at the highest risk and potentially lead to improved therapeutic approaches.

Cancer chemoresistance is a problematic dilemma that significantly restrains numerous cancer management protocols. It can promote cancer recurrence, spreading of cancer, and finally, mortality. Accordingly, enhancing the responsiveness of cancer cells towards chemotherapies could be a vital approach to overcoming cancer chemoresistance. Tumour cells express a high level of sphingosine kinase-1 (SphK1), which acts as a protooncogenic factor and is responsible for the synthesis of sphingosine-1 phosphate (S1P). S1P is released through a Human ATP-binding cassette (ABC) transporter to interact with other phosphosphingolipids components in the interstitial fluid in the tumor microenvironment (TME), provoking communication, progression, invasion, and tumor metastasis. Also, S1P is associated with several impacts, including anti-apoptotic behavior, metastasis, mesenchymal transition (EMT), angiogenesis, and chemotherapy resistance. Recent reports addressed high levels of S1P in several carcinomas, including ovarian, prostate, colorectal, breast, and HCC. Therefore, targeting the S1P/SphK signaling pathway is an emerging therapeutic approach to efficiently attenuate chemoresistance. In this review, we comprehensively discussed S1P functions, metabolism, transport, and signaling. Also, through a bioinformatic framework, we pointed out the alterations of SphK1 gene expression within different cancers with their impact on patient survival, and we demonstrated the protein–protein network of SphK1, elaborating its sparse roles. Furthermore, we made emphasis on different machineries of cancer resistance and the tight link with S1P. We evaluated all publicly available SphK1 inhibitors and their inhibition activity using molecular docking and how SphK1 inhibitors reduce the production of S1P and might reduce chemoresistance, an approach that might be vital in the course of cancer treatment and prognosis. Graphical Abstract