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1.
18th International Conference on Intelligent Computing, ICIC 2022 ; 13395 LNAI:589-603, 2022.
Article in English | Scopus | ID: covidwho-2027437

ABSTRACT

The Covid-19 pandemic has highlighted the importance of forecasting in managing public health. The two of the most commonly used approaches for time series forecasting methods are autoregressive (AR) and deep learning models (DL). While there exist a number of studies comparing the performance of AR and DL models in specific domains, there is no work that analyzes the two approaches in the general context of theoretically simulated time series. To fill the gap in the literature, we conduct an empirical study using different configurations of generalized autoregressive conditionally heteroskedastic (GARCH) time series. The results show that DL models can achieve a significant degree of accuracy in fitting and forecasting AR-GARCH time series. In particular, DL models outperform the AR-based models over a range of parameter values. However, the results are not consistent and depend on a number of factors including the DL architecture, AR-GARCH configuration, and parameter values. The study demonstrates that DL models can be an effective alternative to AR-based models in time series forecasting. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

2.
Journal of Hepatology ; 77:S14, 2022.
Article in English | EMBASE | ID: covidwho-1967492

ABSTRACT

Background and aims: Approval of a drug therapy for NASH requires a very good safety/tolerability profile and acceptable therapeutic index. MAESTRO-NAFLD-1 (NCT04197479) is a randomized doubleblind (DB) Phase 3 clinical trial of placebo (PBO) versus resmetirom (RES), a once-a-day oral selective thyroid hormone receptor β agonist, in >1100 patients with NAFLD with safety as the primary end point. Method: Enrollment was Dec 2019 to Oct 2020 at 79 US sites. Requirements included 3 metabolic risk factors, fibroscan (FS) ≥5.5 kPa/CAP≥280 dBm, MRI-PDFF≥8%. Randomization was 1:1:1:1 to 3 DB arms, PBO, 80 or 100 mg RES (n = 972) or an 100 mg open label (OL) arm (n = 171). The primary objective was to evaluate the safety and tolerability of 80 or 100 mg RES versus PBO measured by the incidence of adverse events (AEs). Results: At baseline the DB safety population (n = 969) was age 55.9 (11.8);female, 54.4%, white 88.6%;hispanic 34.7%;BMI 35.3 (6.0) type 2 diabetes 49%, hypertension 76.1%, dyslipidemia 87.9%;FS 7.4 (4.7) kPa. Discontinuations (22.5%) did not differ by treatment, most patient decision (pandemic related). DB compliancewas impacted by COVID drug kit delays. AE withdrawals were 80 mg, 2.4%;100 mg, 2.8%;PBO, 1.3%. The primary objective was met. TEAEs were 80 mg, 88.4%;100 mg, 86.1%;PBO, 81.8%. TEAEs ≥grade 3 severity were 80 mg, 7.6%;100 mg, 9.0%;PBO, 9.1%. AEs in excess of PBOwere grade 1–2 AEs of diarrhea (80 mg, 23.5%;100 mg, 31.2%;PBO, 13.8%) and nausea (80 mg, 11.9%;100 mg, 18.2%;PBO, 7.9%), in the first few weeks. ALT increases ≥3XULN were 80 mg, 0.61%;100 mg, 0.31%;PBO,1.6%. Therewere no changes in bodyweight or HR. BP decreased by 2–3 mmHg in the RES arms. Key 2o end points were met (Table). Comparative mean reduction in FS VCTE was not significant;a responder analysis of FS and MRE showed significant reductions with RES treatment. Conclusion: RES achieved the primary safety end point in this 52- week Phase 3 NAFLD clinical trial that identified patients by metabolic risk and non-invasive imaging. Key 2o end points were met including LDL-C, ApoB, triglycerides, MRI-PDFF, FS (CAP).(Table Presented) 1MRE combined RES groups.

3.
Open Public Health Journal ; 14(1):352-359, 2021.
Article in English | EMBASE | ID: covidwho-1581527

ABSTRACT

Background: Coronavirus disease 2019 (COVID-19) vaccine development is the best approach to fight the disease. However, rising vaccine hesitancy can make widespread vaccine application difficult. Objectives: To explore health care workers' attitudes towards the COVID-19 vaccine and find the reasons lying behind vaccine hesitancy among participants. Methods: Our study was a cross-sectional survey. An anonymous online questionnaire was sent to a sample of health care workers living and working in the Middle East region. Data collected included demographic data, educational attainment, household crowding, risk factors for severe COVID-19 infection, influenza vaccination history, and questions about COVID-19 vaccine acceptance. Results: We received 864 validated responses. The study included 365 physicians, 391 nurses, and 108 allied professions. Females represented 61% of participants and 98.5% of participants were below 65 years old. Around 60% of participants were hesitant to get the COVID-19 vaccine. The commonest reasons for hesitancy were lack of information and fear of side effects. Vaccine acceptance was higher among males (p< 0.001), physicians (p= 0.017), participants with medical risk factors (p= 0.017), and participants vaccinated against influenza (p< 0.001). After control for other factors, male (OR, 1.94;CI 1.42-2.66), married participant (OR, 1.89;CI 1.22-2.92), living in a less crowded accommodation (OR, 1.33;CI 1.11-1.59), and who got influenza vaccine (OR, 1.64;CI 1.13-2.37) tended to accept the COVID-19 vaccine more likely. Conclusion: Rates of vaccine hesitancy among health care workers were high. The current pandemic offers an opportunity to establish better vaccine confidence towards the COVID-19 vaccine and vaccines in general.

4.
Microbiology Research ; 12(1), 2021.
Article in English | EMBASE | ID: covidwho-1348671

ABSTRACT

The devastating SARS-CoV2 pandemic is worsening with relapsing surges, emerging mu-tants, and increasing mortalities. Despite enormous efforts, it is not clear how SARS-CoV2 adapts and evolves in a clonal background. Laboratory research is hindered by high biosafety demands. How-ever, the rapid sequence availability opened doors for bioinformatics. Using different bioinformatics programs, we investigated 6305 sequences for clonality, expressions strategies, and evolutionary dynamics. Results showed high nucleotide identity of 99.9% among SARS-CoV2 indicating clonal evolution and genome. High sequence identity and phylogenetic tree concordance were obtained with isolates from different regions. In any given tree topology, ~50% of isolates in a country formed country-specific sub-clusters. However, abundances of subtle overexpression strategies were found including transversions, signature-sequences and slippery-structures. Five different short tracks dominated with identical location patterns in all genomes where Slippery-4 AAGAA was the most abundant. Interestingly, transversion and transition substitutions mostly affected the same amino acid residues implying compensatory changes. To ensure these strategies were independent of sequence clonality, we simultaneously examined sequence homology indicators;tandem-repeats, restriction-site, and 3′ UTR, 5′ UTR-caps and stem-loop locations in addition to stringent alignment parameters for 100% identity which all confirmed stability. Nevertheless, two rare events;a rearrange-ment in two SARS-CoV2 isolates against betacoronavirus ancestor and a polymorphism in S gene, were detected. Thus, we report on abundance of transversions, slippery sequences, and ON/OFF molecular structures, implying adaptive expressions had occurred, despite clonal evolution and genome stability. Furthermore, functional validation of the point mutations would provide insights into mechanisms of SARS-CoV2 virulence and adaptation.

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