Background The aim of this study is to develop and validate a scoring system as a tool for predicting the in-hospital mortality in COVID-19 patients in early stage of disease. Methods This retrospective cohort study, conducted on 893 COVID-19 patients in Tehran from February 18 to July 20, 2020. Potential factors were chosen via stepwise selection and multivariable logistic regression model. Cross-validation method was employed to assess the predictive performance of the model as well as the scoring system such as discrimination, calibration, and validity indices. Results The COVID-19 patients’ median age was 63 yrs (54.98% male) and 233 (26.09%) patients expired during the study. The scoring system was developed based on 8 selected variables: age ≥55 yrs (OR = 5.67, 95% CI: 3.25–9.91), males (OR = 1.51, 95% CI: 1.007–2.29), ICU need (OR = 16.32, 95% CI 10.13–26.28), pulse rate >90 (OR = 1.89, 95% CI: 1.26–2.83), lymphocytes <17% (OR = 2.33, 95%CI: 1.54–3.50), RBC ≤4, 10 6 /L (OR = 2.10, 95% CI: 1.35–3.26), LDH >700 U/L (OR = 1.68, 95%CI: 1.13–2.51) and troponin I level >0.03 ng/mL (OR = 1.75, 95%CI: 1.17–2.62). The AUC and the accuracy of scoring system after cross-validation were 79.4% and 79.89%, respectively. Conclusion This study showed that developed scoring system has a good performance and can use to help physicians for identifying high-risk patients in early stage of disease .

Parkinson's disease is a neurodegenerative disorder predominately affecting midbrain dopaminergic neurons that results in a broad range of motor and non-motor symptoms. Sleep complaints are among the most common nonmotor symptoms, even in the prodromal period. Sleep alterations in Parkinson's disease patients may be associated with dysregulation of circadian rhythms, intrinsic 24-h cycles that control essential physiological functions, or

Objective: Our aim is to assess the effective factors on hospitalization costs of COVID-19 patients. Methods: Data related to clinical characteristics and cost of hospitalized COVID-19 patients from February 2020 until July 2020, in a public teaching hospital in Tehran, Iran was gathered in a retrospective cohort study. The corresponding factors influencing the diagnostic and therapeutic costs were evaluated, using a generalized linear model. Results: The median COVID-19 related diagnostic and therapeutic costs in a public teaching hospital in Iran, for one hospitalized COVID-19 patient was equal to 271.1 US dollars (USD). In patients who were discharged alive from the hospital, the costs increased with patients’ pregnancy (P<0.001), loss of consciousness during hospitalization (P<0.001), a history of drug abuse (P=0.006), history of chronic renal disease (P<0.001), end stage renal disease (P=0.002), history of brain surgery (P=0.001), history of migraine (P=0.001), cardiomegaly (P=0.033) and occurrence of myocardial infarction during hospitalization (P<0.001). In deceased patients, low age P<0.001), history of congenital disease (P=0.024) and development of cardiac dysrhythmias during hospitalization (P=0.044) were related to increase in therapeutic costs. Conclusion: Median diagnostic and therapeutic costs in COVID-19 patients, hospitalized in a public teaching hospital in Iran were 271.1 USD. Hoteling and medications made up most of the costs. History of cardiovascular disease and new onset episodes of such complications during hospitalization were the most important factors contributing to the increase of therapeutic costs. Moreover, pregnancy, loss of consciousness, and renal diseases are of other independent factors affecting hospitalization costs in COVID-19 patients.

Objective: In this study, we have evaluated the occurrence and risk factors of cardiac dysrhythmia on admission and during hospitalization in COVID-19 patients. Methods: This study was conducted as a retrospective cohort in which 893 electrocardiograms (ECGs) taken at the time of admission, and 328 ECGs taken during hospitalization were evaluated. These ECGs were assessed for cardiac dysrhythmias by a cardiologist. Finally, relationships between clinical characteristics and the occurrence of cardiac dysrhythmias in patients were assessed. Results: Most common cardiac dysrhythmias on admission were sinus tachycardia (64.8%), atrial fibrillation (13.5%), and sinus bradycardia (11.3%). Multivariate regression analysis showed that a history of metformin use (RR=0.83; P=0.042) was independently associated with reduced risk of cardiac dysrhythmias on admission, while male sex (RR=1.16; P=0.018), history of cardiovascular diseases (RR=1.16; P=0.017), history of cancer (RR=1.40; P=0.004) and QT interval prolongation on ECG (RR=1.18; P=0.017) were associated with a higher risk of cardiac dysrhythmias on admission. Also, among the 328 patients that had a second ECG, 185 (56.4%) experienced cardiac dysrhythmias during their hospitalization. Multivariate analysis showed that presence of cardiac dysrhythmias on admission (RR=1.85; 95% CI: 1.49,2.35; P<0.001) was the only independent prognostic factor for the occurrence of cardiac dysrhythmias during hospitalization. No significant relationships were observed between treatment regimens and the incidence of cardiac dysrhythmias. Conclusion: The present study showed that more than half of COVID-19 patients have cardiac dysrhythmias on admission. Our analyses illustrated that a history of metformin use was associated with a lower risk of cardiac dysrhythmias on admission, while male sex, history of cardiovascular diseases, history of cancer, and QT interval prolongation were associated with a higher rate of cardiac dysrhythmias. Hydroxychloroquine use along with azithromycin and kaletra (lopinavir-ritonavir) had no association with the development of cardiac dysrhythmias during hospitalization.