18 research outputs found
Risk factors prediction, clinical outcomes, and mortality in COVID-19 patients
Preventing communicable diseases requires understanding the spread, epidemiology, clinical features, progression, and prognosis of the disease. Early identification of risk factors and clinical outcomes might help in identifying critically ill patients, providing appropriate treatment, and preventing mortality. We conducted a prospective study in patients with flu-like symptoms referred to the imaging department of a tertiary hospital in Iran between March 3, 2020, and April 8, 2020. Patients with COVID-19 were followed up after two months to check their health condition. The categorical data between groups were analyzed by Fisher's exact test and continuous data by Wilcoxon rank-sum test. Three hundred and nineteen patients (mean age 45.48 ± 18.50 years, 177 women) were enrolled. Fever, dyspnea, weakness, shivering, C-reactive protein, fatigue, dry cough, anorexia, anosmia, ageusia, dizziness, sweating, and age were the most important symptoms of COVID-19 infection. Traveling in the past 3 months, asthma, taking corticosteroids, liver disease, rheumatological disease, cough with sputum, eczema, conjunctivitis, tobacco use, and chest pain did not show any relationship with COVID-19. To the best of our knowledge, a number of factors associated with mortality due to COVID-19 have been investigated for the first time in this study. Our results might be helpful in early prediction and risk reduction of mortality in patients infected with COVID-19. © 2020 Wiley Periodicals LL
Patient-Specific Predictive Modeling Using Random Forests: An Observational Study for the Critically Ill
Meta-analysis illustrates roles of cholesterol synthesis, dysregulated apoptosis, and other processes in nash pathogenesis.
Background: Non-alcoholic steatosis (NASH) is a form of non-alcoholic fatty liver disease (NAFLD) characterized by inflammation. NASH can progress to hepatic fibrosis, cirrhosis, and hepatocellular carcinoma. While the pathogenesis of NASH remains unclear, excess lipid storage, insulin resistance, and increased formation of reactive oxidation species are thought to be involved. Methods: The NCBI Gene Expression Omnibus (GEO) is an open database of more than 2 million samples of functional genomics experiments. The Search Tag Analyze Resource for GEO (STARGEO) platform allows for meta-analysis of genomic signatures of disease and tissue. We employed the STARGEO platform to search the GEO and performed meta-analysis on 187 NASH liver samples, using 154 healthy liver samples as a control. We then analyzed the signature in Ingenuity Pathway Analysis (IPA) to help define the genomic signature of NASH and identify disease pathways. Results: We identified several cholesterol biosynthesis pathways as top canonical pathways, including cholesterol synthesis via 24, 25-dihydrolanosterol, desmosterol, and the superpathway. IGF1 signaling was also a top canonical pathway and is a proven indicator of NASH severity. TNF, PDGF BB (negatively correlated with fibrosis), and beta-estradiol were top regulators. We found upregulation of genes involved in fat synthesis, transport, and accumulation including crystallin (CRYAA) and gamma-butyrobetaine hydroxylase 1 (BBOX1). Notably, we saw upregulation of the novel myokine fibronectin type 3 (FNDC5), which correlated with NAFLD severity and extracellular matrix deposition. Our genetic analysis also highlighted dysregulated apoptosis through the downregulation of pro-apoptotic regulators such as the matricellular protein CYR61, FOS protein (modulates JUN signaling), and RASD1 from the RAS family. The downregulation of our top regulator PDFG BB also suggests dysregulated apoptosis and increased risk for fibrosis. Lastly, we found decreased insulin sensitivity through downregulation of nicotinamide phosphoribosyltransferase (NAMPT). Conclusion: Our analysis suggests that NASH pathogenesis is complex and includes several pathophysiological processes including excess cholesterol biosynthesis and fat accumulation, extracellular matrix deposition, insulin resistance, and dysregulated apoptosis. We identified several molecules that drive these processes and demonstrated their regulation by PDGF BB (figure 1). These molecules can serve as biomarkers and PDGF BB is a promising therapeutic target
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Data Analytics of Electronic Health Records to Enhance Care of Coronary Artery Disease in Younger Women with Avoiding Possible Delay in Treatment.
Early detection plays a key role to enhance the outcome for Coronary Artery Disease. We utilized a big data analytics platform on ∼32,000 patients to trace patients from the first encounter to CAD treatment. There are significant gender-based differences in patients younger than 60 from the time of the first encounter to Coronary Artery Bypass Grafting with a p-value=0.03. This recognition makes significant changes in outcome by avoiding delay in treatment
Gender-based time discrepancy in diagnosis of coronary artery disease based on data analytics of electronic medical records.
BackgroundWomen continue to have worse Coronary Artery Disease (CAD) outcomes than men. The causes of this discrepancy have yet to be fully elucidated. The main objective of this study is to detect gender discrepancies in the diagnosis and treatment of CAD.MethodsWe used data analytics to risk stratify ~32,000 patients with CAD of the total 960,129 patients treated at the UCSF Medical Center over an 8 year period. We implemented a multidimensional data analytics framework to trace patients from admission through treatment to create a path of events. Events are any medications or noninvasive and invasive procedures. The time between events for a similar set of paths was calculated. Then, the average waiting time for each step of the treatment was calculated. Finally, we applied statistical analysis to determine differences in time between diagnosis and treatment steps for men and women.ResultsThere is a significant time difference from the first time of admission to diagnostic Cardiac Catheterization between genders (p-value = 0.000119), while the time difference from diagnostic Cardiac Catheterization to CABG is not statistically significant.ConclusionWomen had a significantly longer interval between their first physician encounter indicative of CAD and their first diagnostic cardiac catheterization compared to men. Avoiding this delay in diagnosis may provide more timely treatment and a better outcome for patients at risk. Finally, we conclude by discussing the impact of the study on improving patient care with early detection and managing individual patients at risk of rapid progression of CAD