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Abstract Introduction Asthma is a heterogenous disease with various phenotypes that is characterized by airway limitation due to bronchospasm and airway inflammation associated with excessive mucus secretion. Eosinophilic asthma subtype is described as a late onset asthma that presents with more severe respiratory symptoms, and with sputum eosinophilia ≥ 3%. In the current study, we aimed to identify the difference in the clinical and demographic characteristics between eosinophilic and non-eosinophilic asthma subtypes and to determine predictors of eosinophilic asthma. Materials and methods One hundred bronchial asthma patients with age ≥ 18 years were divided into two groups according to sputum eosinophilia. All patients were subjected to medical history, Asthma Control Test (ACT), spirometry, serum IgE level, skin prick testing (SPT), and nasal endoscopy to detect nasal polyposis and allergic signs. Results No statistical difference was found between eosinophilic and non-eosinophilic asthma patients regarding age, gender, and body mass index. Patients with sputum eosinophilia had more severe obstruction by spirometry, and positive SPT to food allergens, pollens, and latex with statistical significance (p values 0.001, 0.016, and 0.017 respectively). Additionally, patients with sputum eosinophilia had lower ACT score, higher serum IgE level and higher serum eosinophil count. Total IgE had the highest diagnostic accuracy for discrimination of sputum eosinophilia among asthma patients. Pollen allergy and the severity of airway obstruction by spirometry were independent predictors of eosinophilic asthma. Conclusion Patients with eosinophilic asthma had more severe airway obstruction, lower ACT scores, higher serum IgE level, and serum eosinophil count. Pollen allergy and obstructive pattern by spirometry were independent predictors of eosinophilic asthma.

Abstract Background Coronavirus disease 2019 (COVID-19) can present with pulmonary and non-pulmonary manifestations, or it may be asymptomatic. Asymptomatic patients have a major impact on transmission of the disease, and prediction of their outcome and prognosis is challenging. We aim to identify the predictors of intensive care unit (ICU) admission and mortality in hospitalized COVID-19 patients with initially asymptomatic presentation. Methods This was a prospective multicenter study using cohort data that included all admitted patients aged 21 years and above, with different clinical presentations other (than pulmonary manifestation) and were discovered to have COVID-19. Demographic data, clinical data and progression were reported. Univariate analysis and logistic regression analysis were performed to predict ICU admission and mortality during hospitalization. Results One hundred forty-nine consecutive patients, 92 (61.7% males) were included in our study, Median age (IQR) was 59.00 (43–69]. Only 1 patient (0.7%) had a contact with a confirmed case of COVID-19. 58 patients (39%) were admitted to ICU and 22 patients (14.8%) have died. High ferritin level (more than 422.5), low oxygen saturation (less than 93%), and in need of non-invasive ventilation (NIV) have 3.148, 8.159 and 26.456 times likelihood to be admitted to ICU, respectively. Patients with high CO-RADS, low oxygen saturation (less than 92.5%), and in need for mechanical ventilation (MV) have 82.8, 15.9, and 240.77 times likelihood to die, respectively. Conclusion Initially asymptomatic hospitalized patients with COVID-19 have a great impact on health system with high ICU admission and mortality rate. We identified the predictors that may help in early management and improving prognosis. Trial registration Trial was registered in Clinicaltrials.gov, registration number is NCT05298852 , 26 March 2022, retrospectively registered.