The epidemiology and treatment outcomes of COVID-19 patients admitted to an intensive care unit in an Iranian hospital in Neyshabur city.

Abstract

The COVID-19 pandemic and the infection of numerous individuals from diverse societies have emerged as major global challenges. Given the limited resources in intensive care units, effective bed management and resource allocation require a deep understanding of the disease. This study aimed to assess the epidemiology and treatment outcomes of COVID-19 patients admitted to an intensive care unit in an Iranian hospital in Neyshabur city. This cross-sectional study was conducted on COVID-19 patients hospitalized in intensive care units in Razavi Khorasan, Iran in 2021. Census sampling was used to include all intensive care units. Of the initial 480 cases, 54 cases were excluded based on the exclusion criteria, leaving 426 cases for the study. Data were collected with the help of a data collection form that was designed by the researcher and its content validity and reliability were measured with Cronbach's alpha coefficient (α = 89%.). Data were analyzed with SPSS version 20 software. Descriptive and inferential statistics were used to analyze the data. Mean, standard deviation, and interquartile range indicators were used for descriptive statistics, and absolute frequency and relative frequency (percentage) were used to show numbers and ratios. The mean (SD) age of the patients was 66.33 (15.05) years, and 49.3% were female. The results showed that arterial blood oxygen saturation, respiratory rate, and Alzheimer's disease were significant variables for predicting mortality. Furthermore, arterial blood oxygen saturation, respiratory rate, and the need for transfusion of blood products were significant variables in predicting hospitalization and the risk of acute respiratory distress syndrome (ARDS). This study demonstrated that arterial blood oxygen saturation, respiratory rate, and Alzheimer's disease are crucial variables for predicting death. Furthermore, arterial blood oxygen saturation and respiratory rate are significant factors in predicting the risk of ARDS.