ABSTRACT
BACKGROUND: Corona Virus Disease 2019 (COVID-19) presentations range from those similar to the common flu to severe pneumonia resulting in hospitalization with significant morbidity and/or mortality. In this study, we made an attempt to develop a predictive scoring model to improve the early detection of high risk COVID-19 patients by analyzing the clinical features and laboratory data available on admission. METHODS: We retrospectively included 480 consecutive adult patients, aged 21-95, who were admitted to Faghihi Teaching Hospital. Clinical and laboratory features were collected from the medical records and analyzed using multiple logistic regression analysis. The final data analysis was utilized to develop a simple scoring model for the early prediction of mortality in COVID-19 patients. The score given to each associated factor was based on the coefficients of the regression analyses. RESULTS: A novel mortality risk score (COVID-19 BURDEN) was derived, incorporating risk factors identified in this cohort. CRP (> 73.1 mg/L), O2 saturation variation (greater than 90%, 84-90%, and less than 84%), increased PT (> 16.2 s), diastolic blood pressure (≤ 75 mmHg), BUN (> 23 mg/dL), and raised LDH (> 731 U/L) were the features constituting the scoring system. The patients are triaged to the groups of low- (score < 4) and high-risk (score ≥ 4) groups. The area under the curve, sensitivity, and specificity for predicting mortality in patients with a score of ≥ 4 were 0.831, 78.12%, and 70.95%, respectively. CONCLUSIONS: Using this scoring system in COVID-19 patients, the patients with a higher risk of mortality can be identified which will help to reduce hospital care costs and improve its quality and outcome.
Subject(s)
COVID-19 , Adult , Humans , SARS-CoV-2 , Retrospective Studies , Hospitalization , Risk Factors , Hospital Mortality , Prognosis , Risk AssessmentABSTRACT
BACKGROUND: The prevalence of mental health disorders is increasing globally, and the prevalence of COVID-19 has made it worse. Evidence has indicated a major mental health burden and elevated anxiety associated with the new coronavirus outbreak in the general population. This study aims to evaluate an evidence-based web application (Naranj) for stress management among Iranian college students. METHODS AND DESIGN: This study aims to present a protocol related to a randomized controlled trial among Iranian college students. The study will be conducted on 100 students from two colleges of Shiraz University of Medical Sciences in Iran. The participants will be randomly assigned to the intervention and control groups. The intervention group participants will be provided with a web application, whereas the control group ones will be provided with an app unrelated to stress management. The primary outcome for this study will be the Perceived Stress Scale, and the two groups will be compared with respect to stress level and sleep quality. DISCUSSION: A web application will be developed according to psychological theories and will be scientifically approved for managing college students' stress and improving their sleep quality during the COVID-19 outbreak. TRIAL REGISTRATION: Iranian Registry of Clinical Trials IRCT20160427027647N2 . Registered on 14 May 2020.