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BackgroundAfter recovery from acute infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), many patients experience long-term symptoms in different body systems. The aim of the present study was to identify these symptoms, their severity, and their duration as a first step in building a system to classify post-recovery long-term symptoms of coronavirus disease 2019 (COVID-19).MethodsAn online-based cross-sectional survey was administered between September and October 2020. Data regarding the severity of post-recovery symptoms and their duration were collected using an Arabic questionnaire divided into six categories encompassing the 20 most prevalent symptoms.ResultsA total of 979 patients recovered from COVID-19 in Saudi Arabia in the study period, of whom 53% were male and 47% were female. The most common symptoms included general fatigue and weakness (73% each), with moderate severity of neurological symptoms including mood changes (41%) and insomnia (39%). Among the special senses, loss of smell and taste of marked severity were reported by 64% and 55% among respiratory symptoms, cough of mild severity (47%), and dyspnea of moderate severity (43%). Loss of appetite of moderate severity was reported in 42%, and diarrhea, abdominal pain, and nausea of mild severity were reported by 53%, 50%, and 44% of respondents, respectively.ConclusionsLong-term symptoms after recovery from COVID-19 warrant patient follow-up. The authors propose a classification system as a starting point to guide the identification and follow-up of long-term symptoms post-recovery, and recommend larger-scale studies to broaden the definition of recovery from COVID-19, which appears to have two phases, acute and chronic.

Abstract Background patients with acute AECOPD show an abrupt worsening of baseline ventricular function and pulmonary hypertension, using clear predictors or markers for severity in such patients is critical to be early stratified and properly managed. Aim Assess the value of BNP as A predictor for severity in patients with AECOPD represented by need for intensive care admission, invasive and non-invasive mechanical ventilation, pulmonary hypertension, hospital and 3 months mortality. Study design Prospective study Methods A prospective Cohort study in tertiary level hospital conducted on 88 patients with AECOPD and 88 healthy control subjects, patients were divided into 2 subgroups: ICU admitted and ward admitted Patient were subjected to clinical, electrocardiographic, radiological and laboratory evaluation and observation of the clinical course during admission and 3 months following hospital discharge. Results The study revealed higher BNP in AECOPD patients compared with healthy control subjects and in ICU admitted compared with ward patients (P, 0.001). positive correlation with age, smoking index, Paco2, SPAP, RVD, need for ICU , IMV, hospital stay and overall Mortality (r coefficient: 0.398, 0.533, 0.605, 0.635, 0.732, -0.617, 0.577, 0.728 0.030, respectivly), we revealed negative correlation with ABGs parameters (Pao2, PH and o2 saturation), with r. coefficient of (-0.616, -0.609, -0.630, respectively), linear regression revelled that BNP is significant predictors for ICU admission , ROC curve revealed that BNP more than 425pg/ml had sensitivity , specificity of (70.8% and, 100%) to predict need for ICU admission. Conclusion BNP may be considered as an accessible, useful, non-invasive and low-cost marker of severity COPD exacerbations.

Backgroundː: Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), within few months of being declared as a global pandemic by WHO, the number of confirmed cases has been over 75 million and over 1.6 million deaths since the start of the Pandemic and still counting, there is no consensus on factors that predict COVID-19 case progression despite the diversity of studies that reported sporadic laboratory predictive values predicting severe progression. We review different biomarkers to systematically analyzed these values to evaluate whether are they are correlated with the severity of COVID-19 disease and so their ability to be a predictor for progression. Methods: The current meta-analysis was carried out to identify relevant articles using eight different databases regarding the values of biomarkers and risk factors of significance that predict progression of mild or moderate cases into severe and critical cases. We defined the eligibility criteria using a PICO model. Results: Twenty-two relevant articles were selected for meta-analysis the following biomarkers C-reactive protein, interleukin-6, LDH, neutrophil, %PD-1 expression, D-dimer, creatinine, AST and Cortisol all recorded high cut-off values linked to severe and critical cases while low lymphocyte count, and low Albumin level were recorded. Also, we meta- analyzed age and comorbidities as a risk factors of progression as hypertension, Diabetes and chronic obstructive lung diseases which significantly correlated with cases progression (p < 0.05). Conclusions: ː The current meta-analysis is the first step for analysing and getting cut-off references values of significance for prediction COVID-19 case progression. More studies are needed on patients infected with SARS-CoV-2 and on a larger scale to establish clearer threshold values that predict progression from mild to severe cases. In addition, more biomarkers testing also help in building a scoring system for the prediction and guiding for proper timely treatment.

Abstract Background Vitamin D deficiency is widespread and associated with increased risk of chronic diseases. The relation between chronic obstructive pulmonary disease (COPD) and vitamin D is complex owing to comorbidities, which are affected by vitamin D. Patients with low vitamin D showed higher risk for exacerbations. Aim The aim was to study the status of vitamin D in patients during exacerbation of chronic obstructive pulmonary disease (AECOPD). Patients and methods The study included 205 patients presented with AECOPD and 150 controls. Patients and controls were subjected to full clinical history and examination, pulmonary function testing, and vitamin D [hydroxyvitamin D, 25(OH)D] examination by Liaison 25 OH Vitamin D assay (direct competitive chemiluminescence immunoassay, DiaSorin Inc, Stillwater, Minnesota, USA) in serum. Symptom scoring was done using modified Medical Research Council (mMRC) and combined assessment of Global Initiative for Chronic Obstructive Lung Disease COPD classification, with division into groups A, B, C, and D. Data related to severity of exacerbation, site of care, and hospital days were gathered. Statistics Pearson’s χ2-test was used to compare the prevalence of categorical variables between patients with COPD and control groups. t-Test was used to compare differences in the levels of continuous variables between the two groups. R2-test was used to measure how close the data are to be fitted in the regression line. Results 25(OH)D was significantly lower in patients with AECOPD than control group (mean: 39.5±32.5 vs. 56.3±43.7 nmol/l, P? 0.05). Vitamin D insufficiency (25–75 nmol/l) was significantly higher in patients than controls [115 (56.09%) patients vs. 51 (34%) controls, P50%) showed higher 25(OH)D (69.4±23.1) than patients with severe and very severe COPD (forced expiratory volume in first second