Using machine learning of clinical data to diagnose COVID-19: a systematic review and meta-analysis.

BACKGROUND: The recent Coronavirus Disease 2019 (COVID-19) pandemic has placed severe stress on healthcare systems worldwide, which is amplified by the critical shortage of COVID-19 tests. METHODS: In this study, we propose to generate a more accurate diagnosis model of COVID-19 based on patient symptoms and routine test results by applying machine learning to reanalyzing COVID-19 data from 151 published studies. We aim to investigate correlations between clinical variables, cluster COVID-19 patients into subtypes, and generate a computational classification model for discriminating between COVID-19 patients and influenza patients based on clinical variables alone. RESULTS: We discovered several novel associations between clinical variables, including correlations between being male and having higher levels of serum lymphocytes and neutrophils. We found that COVID-19 patients could be clustered into subtypes based on serum levels of immune cells, gender, and reported symptoms. Finally, we trained an XGBoost model to achieve a sensitivity of 92.5% and a specificity of 97.9% in discriminating COVID-19 patients from influenza patients. CONCLUSIONS: We demonstrated that computational methods trained on large clinical datasets could yield ever more accurate COVID-19 diagnostic models to mitigate the impact of lack of testing. We also presented previously unknown COVID-19 clinical variable correlations and clinical subgroups.

Tobacco, but Not Nicotine and Flavor-Less Electronic Cigarettes, Induces ACE2 and Immune Dysregulation.

The COVID-19 pandemic caused by the SARS-CoV-2 virus, overlaps with the ongoing epidemics of cigarette smoking and electronic cigarette (e-cig) vaping. However, there is scarce data relating COVID-19 risks and outcome with cigarette or e-cig use. In this study, we mined three independent RNA expression datasets from smokers and vapers to understand the potential relationship between vaping/smoking and the dysregulation of key genes and pathways related to COVID-19. We found that smoking, but not vaping, upregulates ACE2, the cellular receptor that SARS-CoV-2 requires for infection. Both smoking and use of nicotine and flavor-containing e-cigs led to upregulation of pro-inflammatory cytokines and inflammasome-related genes. Specifically, chemokines including CCL20 and CXCL8 are upregulated in smokers, and CCL5 and CCR1 are upregulated in flavor/nicotine-containing e-cig users. We also found genes implicated in inflammasomes, such as CXCL1, CXCL2, NOD2, and ASC, to be upregulated in smokers and these e-cig users. Vaping flavor and nicotine-less e-cigs, however, did not lead to significant cytokine dysregulation and inflammasome activation. Release of inflammasome products, such as IL-1B, and cytokine storms are hallmarks of COVID-19 infection, especially in severe cases. Therefore, our findings demonstrated that smoking or vaping may critically exacerbate COVID-19-related inflammation or increase susceptibility to COVID-19.

Identification and Characterization of the Intra-Articular Microbiome in the Osteoarthritic Knee.

Osteoarthritis (OA) is the most common joint disorder in the United States, and the gut microbiome has recently emerged as a potential etiologic factor in OA development. Recent studies have shown that a microbiome is present at joint synovia. Therefore, we aimed to characterize the intra-articular microbiome within osteoarthritic synovia and to illustrate its role in OA disease progression. RNA-sequencing data from OA patient synovial tissue was aligned to a library of microbial reference genomes to identify microbial reads indicative of microbial abundance. Microbial abundance data of OA and normal samples was compared to identify differentially abundant microbes. We computationally explored the correlation of differentially abundant microbes to immunological gene signatures, immune signaling pathways, and immune cell infiltration. We found that microbes correlated to OA are related to dysregulation of two main functional pathways: increased inflammation-induced extracellular matrix remodeling and decreased cell signaling pathways crucial for joint and immune function. We also confirmed that the differentially abundant and biologically relevant microbes we had identified were not contaminants. Collectively, our findings contribute to the understanding of the human microbiome, well-known OA risk factors, and the role microbes play in OA pathogenesis. In conclusion, we present previously undiscovered microbes implicated in the OA disease progression that may be useful for future treatment purposes.

Low-Threshold Buprenorphine via Community Partnerships and Telemedicine-Case Reports of Expanding Access to Addiction Treatment During COVID-19.

BACKGROUND: To reduce coronavirus disease 2019 (COVID-19) spread, federal agencies eased telemedicine restrictions including audio-only appointments. These changes permitted clinicians to prescribe buprenorphine to patients with opioid use disorder (OUD) without in-person or audio/video assessment. Our clinic utilized existing community collaborations to implement protocols and extend outreach. We describe 3 patients with OUD who engaged with treatment through outreach with trusted community partners and low-threshold telemedicine. CASE PRESENTATIONS: Patient 1-a 40-year-old man with severe OUD who injected heroin and was living outside. A weekend harm reduction organization volunteer the patient previously knew used her mobile phone to facilitate an audio-only intake appointment during clinic hours. He completed outpatient buprenorphine initiation. Patient 2-a 48-year-old man with severe opioid and methamphetamine use disorders who injected both and was living in his recreational vehicle. He engaged regularly with syringe services program (SSP), but utilized no other healthcare services. Initially, an SSP worker connected him to our clinic for audio-only appointment using their landline to initiate buprenorphine; a harm reduction volunteer coordinated follow-up. Patient 3-a 66-year-old man with moderate OUD used non-prescribed pill opioids without prior buprenorphine experience. He lived over 5 hours away in a rural town. He underwent virtual appointment and completed home buprenorphine initiation. CONCLUSION: These 3 cases illustrate examples of how policy changes allowing for telemedicine buprenorphine prescribing can expand availability of addiction services for patients with OUD who were previously disengaged for reasons including geography, lack of housing, transportation difficulties, and mistrust of traditional healthcare systems.

Low-barrier buprenorphine during the COVID-19 pandemic: A rapid transition to on-demand telemedicine with wide-ranging effects.

Low barrier addiction clinics increase access to medications to treat substance use disorders, while emphasizing harm reduction. The Harm Reduction and BRidges to Care (HRBR) Clinic is an on demand, low barrier addiction clinic that opened in October 2019. In the first three months of operation (November through January 2020), HRBR saw steadily increasing numbers of patients. Oregon saw its first case of novel coronavirus in February, and declared a state of emergency and enacted a formal "Stay at Home" order in March. That same month, the DEA announced that patients could be initiated on buprenorphine through telemedicine visits without an in-person exam. Within a week of being granted the ability to see patients virtually, HRBR had transitioned to over 90% virtual visits, while still allowing patients without technology to access in-person care. Within four weeks, the clinic expanded hours significantly, established workflows with community harm reduction partners, and was caring for patients in rural areas of the state. In response to the COVID-19 crisis, the HRBR clinic was able to quickly transition from in-person to almost completely virtual visits within a week. This rapid pivot to telemedicine significantly increased access to care for individuals seeking low-threshold treatment in multiple contexts. Overarching institutional support, grant funding and a small flexible team were critical. HRBR's increased access and capacity were only possible with the Drug Enforcement Agency loosening restrictions around the use of telehealth for new patients. Keeping these altered regulations in place will be key to improving health and health care equity for people who use drugs, even after the pandemic subsides. Further research is needed in to whether addiction telemedicine impacts medication diversion rates, continued substance use, or provider practices.

Cardiovascular, cerebrovascular, and renal co-morbidities in COVID-19 patients: A systematic-review and meta-analysis.

BACKGROUND: COVID-19 has infected over 35 million people worldwide and led to over 1 million deaths. Several risk factors that increase COVID-19 severity have emerged, including age and a history of cardiovascular disease, hypertension, or kidney disease. However, a number of outstanding questions persist, including whether the above comorbidities correlate with increased mortality from COVID-19 or whether age is a significant confounding variable that accounts for the observed relationship between COVID-19 severity and other comorbidities. METHODS AND FINDINGS: We conducted a systematic review and meta-analysis of studies documenting COVID-19 patients with hypertension, cardiovascular disease, cerebrovascular disease, or chronic kidney disease. We classified COVID-19 cases into severe/non-severe or deceased/surviving and calculated the odds ratio (OR) for each of the four comorbidities in these cohorts. 36 studies, comprising 22,573 patients, are included in our meta-analysis. We found that hypertension is the most prevalent comorbidity in deceased COVID-19 patients (55.4%; CI: 49.4-61.3%), followed by cardiovascular disease (30.7%; CI: 22.6-38.8%), cerebrovascular disease (13.4%; CI: 9.12-19.2%), then chronic kidney disease (9.05%; CI: 5.57-15.0%). The risk of death is also significantly higher for patients with these comorbidities, with the greatest risk factor being chronic kidney disease (OR: 8.86; CI: 5.27-14.89), followed by cardiovascular disease (OR: 6.87; CI: 5.56-8.50), hypertension (OR: 4.87; CI: 4.19-5.66), and cerebrovascular disease (OR: 4.28; CI: 2.86-6.41). These risks are significantly higher than previously reported, while correlations between comorbidities and COVID-19 severity are similar to previously reported figures. Using meta-regression analysis with age as a moderating variable, we observed that age contributes to the observed risks but does not explain them fully. CONCLUSIONS: In this meta-analysis, we observed that cardiovascular, cerebrovascular, and kidney-related comorbidities in COVID-19 significantly contributes to greater risk of mortality and increased disease severity. We also demonstrated that age may not be a confounder to these associations.

COVID-19 Severity Potentially Modulated by Cardiovascular-Disease-Associated Immune Dysregulation.

Patients with underlying cardiovascular conditions are particularly vulnerable to severe COVID-19. In this project, we aimed to characterize similarities in dysregulated immune pathways between COVID-19 patients and patients with cardiomyopathy, venous thromboembolism (VTE), or coronary artery disease (CAD). We hypothesized that these similarly dysregulated pathways may be critical to how cardiovascular diseases (CVDs) exacerbate COVID-19. To evaluate immune dysregulation in different diseases, we used four separate datasets, including RNA-sequencing data from human left ventricular cardiac muscle samples of patients with dilated or ischemic cardiomyopathy and healthy controls; RNA-sequencing data of whole blood samples from patients with single or recurrent event VTE and healthy controls; RNA-sequencing data of human peripheral blood mononuclear cells (PBMCs) from patients with and without obstructive CAD; and RNA-sequencing data of platelets from COVID-19 subjects and healthy controls. We found similar immune dysregulation profiles between patients with CVDs and COVID-19 patients. Interestingly, cardiomyopathy patients display the most similar immune landscape to COVID-19 patients. Additionally, COVID-19 patients experience greater upregulation of cytokine- and inflammasome-related genes than patients with CVDs. In all, patients with CVDs have a significant overlap of cytokine- and inflammasome-related gene expression profiles with that of COVID-19 patients, possibly explaining their greater vulnerability to severe COVID-19.

Tobacco Smoke and Electronic Cigarette Vapor Alter Enhancer RNA Expression That Can Regulate the Pathogenesis of Lung Squamous Cell Carcinoma.

Tobacco is the primary etiologic agent in worsened lung squamous cell carcinoma (LUSC) outcomes. Meanwhile, it has been shown that etiologic agents alter enhancer RNAs (eRNAs) expression. Therefore, we aimed to identify the effects of tobacco and electronic cigarette (e-cigarette) use on eRNA expression in relation to LUSC outcomes. We extracted eRNA counts from RNA-sequencing data of tumor/adjacent normal tissue and before/after e-cigarette tissue from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO), respectively. Tobacco-mediated LUSC eRNAs were correlated to patient survival, clinical variables, and immune-associated elements. eRNA expression was also correlated to mutation rates through the Repeated Evaluation of Variables Conditional Entropy and Redundance (REVEALER) algorithm and methylated sites through methylationArrayAnalysis. Differential expression analysis was then completed for the e-cigarette data to compare with key tobacco-mediated eRNAs. We identified 684 downregulated eRNAs and 819 upregulated eRNAs associated with tobacco-mediated LUSC, specifically, with the cancer pathological stage. We also observed a decrease in immune cell abundance in tobacco-mediated LUSC. Yet, we found an increased association of eRNA expression with immune cell abundance in tobacco-mediated LUSC. We identified 16 key eRNAs with significant correlations to 8 clinical variables, implicating these eRNAs in LUSC malignancy. Furthermore, we observed that these 16 eRNAs were highly associated with chromosomal alterations and reduced CpG site methylation. Finally, we observed large eRNA expression upregulation with e-cigarette use, which corresponded to the upregulation of the 16 key eRNAs. Our findings provide a novel mechanism by which tobacco and e-cigarette smoke influences eRNA interactions to promote LUSC pathogenesis and provide insight regarding disease progression at a molecular level.

Influence of Intratumor Microbiome on Clinical Outcome and Immune Processes in Prostate Cancer.

Although 1 in 9 American men will receive a diagnosis of prostate cancer (PC), most men with this diagnosis will not die from it, as most PCs are indolent. However, there is a subset of patients in which the once-indolent PC becomes metastatic and eventually, fatal. In this study, we analyzed microbial compositions of intratumor bacteria in PC to determine the influence of the microbiome on metastatic growth. Using large-scale RNA-sequencing data and corresponding clinical data, we correlated the abundance of microbes to immune pathways and PC risk factors, identifying specific microbes that either significantly deter or contribute to cancer aggressiveness. Interestingly, most of the microbes we found appeared to play anti-tumor roles in PC. Since these anti-tumor microbes were overrepresented in tumor samples, we believe that microbes thrive in the tumor microenvironment, outcompete cancer cells, and directly mitigate tumor growth by recruiting immune cells. These include Listeria monocytogenes, Methylobacterium radiotolerans JCM 2831, Xanthomonas albilineans GPE PC73, and Bradyrhizobium japonicum, which are negatively correlated with Gleason score, Tumor-Node-Metastasis (TNM) stage, prostate-specific antigen (PSA) level, and Androgen Receptor (AR) expression, respectively. We also identified microbes that contribute to tumor growth and are positively correlated with genomic alterations, dysregulated immune-associated (IA) genes, and prostate cancer stem cells (PCSC) genes.

Efficient recovery of fluoroquinolone-susceptible and fluoroquinolone-resistant Escherichia coli strains from frozen samples.

We assessed the rate of recovery of fluoroquinolone-resistant and fluoroquinolone-susceptible Escherichia coli isolates from culture of frozen perirectal swab samples compared with the results for culture of the same specimen before freezing. Recovery rates for these 2 classes of E. coli were 91% and 83%, respectively. The majority of distinct strains recovered from the initial sample were also recovered from the frozen sample. The strains that were not recovered were typically present only in low numbers in the initial sample. These findings emphasize the utility of frozen surveillance samples.