Background Treatment of patients with COVID-19 has included supportive care to mainly relief symptoms of the disease. Although World Health Organization (WHO) has not recommended any effective treatments for COVID-19, there are some reports about use of antiviral drugs. The aim of this study is to determine the effect of Arbidol (ARB) on COVID-19 disease. Methods Using an open-label randomized controlled trial, we examined the efficacy of ARB in patients with COVID-19 in a teaching hospital. One hundred eligible patients with diagnosis of COVID-19 were recruited in the study and assigned randomly to two groups of either hydroxychloroquine followed by KALETRA (Lopinavir/ritonavir) or hydroxychloroquine followed by ARB. The primary outcome was hospitalization duration and clinical improvement 7 days after admission. The criteria of improvement were relief of cough, dyspnea, and fever. Time to relief from fever was also assessed across the two groups. Without any dropouts, 100 patients were entered into the study for the final analysis at significance level of 0.05. Results The mean age of patients was 56.6 (17.8) years and 56.2 (14.8) years in ARB and KALETRA groups, respectively. Majority of patients were male across two groups (66 and 54%). The duration of hospitalization in ARB group was significantly less than KALETRA arm (7.2 versus 9.6 days; P = 0.02). Time to relief fever was almost similar across two groups (2.7 versus 3.1 days in ARB and KALETRA arms, respectively). Peripheral oxygen saturation rate was significantly different after 7 days of admission across two groups (94% versus 92% in ARB and KALETRA groups respectively) (P = 0.02). Based on multiple linear regression analysis, IHD, Na level, and oxygen saturation at the time of admission and type of therapy were the independent adjusted variables that determined the duration of hospitalization in patients with COVID-19. Conclusion Our findings showed that Arbidol, compared to KALETRA, significantly contributes to clinical and laboratory improvements, including peripheral oxygen saturation, requiring ICU admissions, duration of hospitalization, chest CT involvements, WBC, and ESR. We suggest further studies on ARB against COVID-19 using larger sample size and multicenter design. Trial registration IRCT20180725040596N2 on 18 April 2020.
Coronavirus disease 2019 (Covid-19) is highly contagious with limited treatment options. Early and accurate diagnosis of Covid-19 is crucial in reducing the spread of the disease and its accompanied mortality. Currently, detection by reverse transcriptase-polymerase chain reaction (RT-PCR) is the gold standard of outpatient and inpatient detection of Covid-19. RT-PCR is a rapid method; however, its accuracy in detection is only ~70–75%. Another approved strategy is computed tomography (CT) imaging. CT imaging has a much higher sensitivity of ~80–98%, but similar accuracy of 70%. To enhance the accuracy of CT imaging detection, we developed an open-source framework, CovidCTNet, composed of a set of deep learning algorithms that accurately differentiates Covid-19 from community-acquired pneumonia (CAP) and other lung diseases. CovidCTNet increases the accuracy of CT imaging detection to 95% compared to radiologists (70%). CovidCTNet is designed to work with heterogeneous and small sample sizes independent of the CT imaging hardware. To facilitate the detection of Covid-19 globally and assist radiologists and physicians in the screening process, we are releasing all algorithms and model parameter details as open-source. Open-source sharing of CovidCTNet enables developers to rapidly improve and optimize services while preserving user privacy and data ownership.
A cell-surface heparan proteoglycan called Syndecan-1 (SDC-1) has multiple roles in healthy and pathogenic conditions, including respiratory viral infection. In this study, we explore the dynamic alternation in the levels of SDC-1 in cases with COVID-19. A total of 120 cases definitely diagnosed with COVID-19 were admitted to the Firoozgar Hospital, Tehran, Iran, from December 1, 2020, to January 29, 2021, and included in our study. Also, 58 healthy subjects (HS) were chosen as the control group. Patients were classified into two groups: 1) ICU patients and (63 cases) 2) non-ICU patients (57 cases). The dynamic changes of serum SCD-1, CRP, IL-6, IL-10, IL-18, and Vit D levels a well as the disease activity were investigated in three-time points (T1-T3). Our results indicated that the COVID-19 patients had significantly increased SCD-1, CRP, IL-6, IL-10, and IL-18 levels than in HS, while the Vit D levels in COVID-19 patients were significantly lower than HS. Further analysis demonstrated that the SCD-1, CRP, IL-6, IL-10, and IL-18 levels in ICU patients were significantly higher than in non-ICU patients. Tracking dynamic changes in the above markers indicated that on the day of admission, the SCD-1, CRP, IL-6, IL-10, and IL-18 levels were gradually increased on day 5 (T2) and then gradually decreased on day 10 (T3). ROC curve analysis suggests that markers mentioned above, SDC-1, IL-6, and IL-18 are valuable indicators in evaluating the activity of COVID-19. All in all, it seems that the serum SDC-1 levels alone or combined with other markers might be a good candidate for disease activity monitoring.
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