COVID-19 (coronavirus disease 2019) vaccines induce immunity through different mechanisms. The aim of this study is to compare the titers of specific antibodies in subjects vaccinated with either the Pfizer-BioNTech COVID-19 vaccine or the Sinopharm vaccine. This prospective observational cohort included Jordanian adults vaccinated with two doses, 21 days apart, of either of the two aforementioned vaccines. Titers were collected 6 weeks after the administration of the second dose. Overall, 288 participants were included, of which 141 were administered the Pfizer-BioNTech vaccine, while 147 were administered the Sinopharm vaccine. Remarkably, 140 (99.3%) of the Pfizer-BioNTech vaccine recipients had positive IgG titers, while 126 (85.7%) of Sinopharm recipients had positive IgG (p < 0.001). The mean titer for IgG among Pfizer-BioNTech recipients was 515.5 ± 1143.5 BAU/mL, compared to 170.0 ± 230.0 BAU/mL among Sinopharm subjects (p < 0.001). Multivariable regression analysis showed that the Pfizer-BioNTech vaccine positively correlated with positive IgG titers (OR: 25.25; 95% CI: 3.25–196.15; p = 0.002), compared with a negative effect of cardiovascular diseases (OR: 0.33; 95% CI: 0.11–0.99; p = 0.48) on IgG titers. In conclusion, fully vaccinated recipients of the Pfizer-BioNTech vaccine had superior quantitative efficiency compared to Sinopharm recipients. A booster dose is supported for Sinopharm recipients, or those with chronic immunosuppressive diseases.

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Background The development of specific immunoglobulins to COVID-19 after natural infection or vaccination has been proposed. The efficacy and dynamics of this response are not clear yet. Aim This study aims to analyze the immunoglobulins response among COVID-19 patients, COVID-19 vaccine recipients and random individuals. Methods A total of 665 participants including 233 COVID-19 patients, 288 COVID-19 vaccine recipients, and 144 random individuals were investigated for anti-COVID-19 immunoglobulins (IgA, IgG, IgM). Results Among COVID-19 patients, 22.7% had detectable IgA antibodies with a mean of 27.3±57.1 ng/ml, 29.6% had IgM antibodies with a mean of 188.4±666.0 BAU/ml, while 59.2% had IgG antibodies with a mean of 101.7±139.7 BAU/ml. Pfizer-BioNTech vaccine recipients had positive IgG in 99.3% with a mean of 515.5±1143.5 BAU/ml while 85.7% of Sinopharm vaccine recipients had positive IgG with a mean of 170.0±230.0 BAU/ml. Regarding random individuals, 54.9% had positive IgG with a mean of 164.3±214 BAU/ml. The peak IgM response in COVID-19 patients was detected early at 15–22 days, followed by IgG peak at 16–30 days, and IgA peak at 0–60 days. IgM antibodies disappeared at 61–90 days, while IgG and IgA antibodies decreased slowly after the peak and remained detectable up to 300 days. The frequency of IgG positivity among patients was significantly affected by increased age, admission department (inpatient or outpatient), symptoms, need for oxygen therapy, and increased duration between positive COVID-19 RT PCR test and serum sampling (p˂0.05). Positive correlations were noted between different types of immunoglobulins (IgG, IgM, and IgA) among patients. Conclusions Natural infection and COIVD-19 vaccines provide IgG-mediated immunity. The class, positivity, mean, efficacy, and duration of immunoglobulins response are affected by the mechanism of immunity and host related variables. Random community individuals had detectable COVID-19 IgG at ~55%, far from reaching herd immunity levels.

Introduction: Coronavirus 2019 disease (COVID-19) has variable clinical, sinonasal, and smell/taste outcomes.Methods: Observational study was conducted at a tertiary hospital in Amman, Jordan. Demographic data, clinical presentation and smoking status were collected.Sinonasal symptoms, using Sino-Nasal Outcome Test (SNOT-22) Questionnaire, were evaluated. Smell/taste dysfunction was followed for three months.Results: Ninety-Seven patients had satisfactory responses. Eighty-six patients were symptomatic (41 at presentation, and 45 during admission). Among those patients, 59.3% had cough, 52.3% sore throat and 48.8% fever. The most common initial symptom was sore throat. Shortness of breath and smell/taste dysfunction were significantly higher in females. Surprisingly, shortness of breath was more common in non-smokers. Smell/taste dysfunction affected 25.6% of patients, but was the first symptom in only one patient. Fourteen of 22 symptoms in SNOT-22 had significant increase. The overall average of symptoms scores increased from 0.472 to 1.034, with smell/taste dysfunction to have the most increment. The latter symptom recovered completely in 81% and dysgeusia developed in 9.5% at three months, and it recovered completely in all patients at six months. Conclusion:Although COVID-19 may produce severe lower airways disease, it has modest effect on nose and paranasal sinuses. Moreover, smell/taste dysfunction is a prominent symptom, but it usually recovers dramatically.

Background The number of COVID-19 infected patients has been soaring in the Middle East countries. The disease poses a significant threat, decisions about prioritizing care should be made in accordance with the proven risk factors for complications. Objective The present study provides the first bespoke prediction model in the Middle East to identify COVID-19 patients, who are at higher risk for complications. Method A case-control study design was adopted to compare the characteristics of successfully recovered patients with those who had complications. Complications were defined as admission to the intensive care unit, mechanical ventilation, sepsis or septic shock, pneumonia or respiratory failure, and death. The prediction model was created through multivariable logistic regression. C statistic was used to assess overall discriminatory ability. Results All COVID-19 infected hospitalized patients (n = 133) in Amman – Jordan were included in the study. Successfully recovered were 125 patients. The median age (IRQ) was 26 (10-40). Almost 30% were >40 years. Patients with complications were eight patients, age 63 (51.5-71.5). The prediction model identified the following variables as risk factors: diabetes (OR = 59.7; 95% CI: 3.5–1011.5, P = 0.005), fever (OR = 24.8; 95% CI: 1.4–447.3, P = 0.029), SHORTNESS OF BREATH (OR = 15.9; 95% CI: 1.3–189.7, P = 0.029), body mass index (OR = 0.74; 95% CI: 0.61–0.88, P = 0.001), abnormal Neutrophils (OR = 16.8; 95% CI: 1.0–292.0, P = 0.053). Prediction model was statistically significant, χ2(5) = 86.1, p < 0.0005. Conclusions Unlike reports from China, the most influential variables that led to disease progression in Jordanian patients were diabetes, fever, shortness of breath, body mass index, and abnormal neutrophils. Similar to reports from the USA, smoking was not a leading factor for complications. Comorbidities and patient health status, rather than age, were the primary risk factors for complications. Treatment with Hydroxychloroquine showed no protective effect.