Recognizing COVID-19 patients at a greater risk of mortality assists medical staff to identify who benefits from more serious care. We developed and validated prediction models for two-week mortality of inpatients with COVID-19 infection based on clinical predictors. A prospective cohort study was started in February 2020 and is still continuing. In total, 57,705 inpatients with both a positive reverse transcription-polymerase chain reaction test and positive chest CT findings for COVID-19 were included. The outcome was mortality within 2 weeks of admission. Three prognostic models were developed for young, adult, and senior patients. Data from the capital province (Tehran) of Iran were used for validation, and data from all other provinces were used for development of the models. The model Young, was well-fitted to the data (p < 0.001, Nagelkerke R 2 = 0.697, C-statistics = 0.88) and the models Adult (p < 0.001, Nagelkerke R 2 = 0.340, C-statistics = 0.70) and Senior (p < 0.001, Nagelkerke R 2 = 0.208, C-statistics = 0.68) were also significant. Intubation, saturated O 2 < 93%, impaired consciousness, acute respiratory distress syndrome, and cancer treatment were major risk factors. Elderly people were at greater risk of mortality. Young patients with a history of blood hypertension, vomiting, and fever; and adults with diabetes mellitus and cardiovascular disease had more mortality risk. Young people with myalgia; and adult patients with nausea, anorexia, and headache showed less risk of mortality than others.
Introduction: COVID-19 pandemic led to various consequences in medical care that had been long provided for the patients referred to the hospitals. Objective: We conducted this study to derive and validate a new scoring system that can accurately differentiate COVID-19 patients who may have a worse outcome from others at the prehospital stage. Methods: This study was performed on probable/confirmed COVID-19 patients, who were transferred to the hospitals by Tehran emergency medical services (EMS). Occurrence of one of the items including: in-hospital death, intensive care unit (ICU) admission, or hospitalization for more than 20 days was considered to indicate a “severe disease”. Univariate and multivariate logistic regression were used for assessment of the relationship between all independent variables and the outcome. In the validity assessment step, area under the receiver operating characteristic (ROC) curve was calculated for a data set independent from the data based on which the model was designed. The sensitivity and specificity were also presented based on the best suggested cutoff point. Results: In this study, the data of 557 cases were analyzed in the derivation step and 356 cases were assessed in the validation step. The univariate logistic regression showed that age, weakness and fatigue, disease history, systolic blood pressure, SpO2, respiratory rate, and Glasgow coma scale (GCS) were statistically significant in severe disease group. The area under the ROC curve (AUC-ROC) of the tool was 0.808 (95% CI: 0.779, 0.834). The best cut-off point for screening was the score of ≥4, in which the sensitivity and specificity of the tool for the best cut-off point were 71.87% and 78.06%, respectively. In the validation step, the AUCROC of the tool was 0.723. Conclusions: Seven criteria of severe COVID-19 (SCSC) tool could properly differentiate probable/confirmed COVID-19 patients with severe outcomes in the pre-hospital stage.
Background: COVID-19 pandemic, which started in late 2019, has brought various ups and downs worldwide. Planned policies were highly useful in the first wave of the COVID-19 pandemic in Iran. However, due to several reasons, the country faced the second wave. Objectives: The current study aimed to compare patients’ features in the first two waves of the COVID-19 pandemic in the city of Tehran, Iran. Methods: Following a retrospective, cross-sectional design, the current study was carried out on 5000 suspected/confirmed COVID-19 cases who were randomly selected from all cases transferred by ambulance to hospitals located in the city of Tehran. The first wave of the COVID-19 epidemic was from February 20 to May 04, 2020, and the second wave was from May 05 to August 05, 2020. Data for both waves, were collected using a researcher-made checklist. Results: In this study, data of 5000 suspected/confirmed COVID-19 cases were analyzed (2773 cases belonged to the first wave and 2227 to the second one). The mean age of patients (P < 0.001), the frequency of cigarette smoking (P < 0.001), opium abuse (P = 0.004), and the presence of underlying diseases (P < 0.05) were more frequent in the second wave than in the first one. The notable finding in this study was the significant increase of non-respiratory symptoms of patients in the second wave. The number of cases who reported close contact with COVID-19 patients was higher in the second wave. Also, hypoxia, intubation during the hospital stay, length of hospitalization, and mortality rates were significantly lower in the second wave. During the second wave, the odd ratio of positive findings in lung CT-scan was 3.4 (95% confidence interval: 2.51 to 4.55) compared to the first wave (P < 0.001). Conclusions: This study demonstrated considerable differences between the first and second waves of the COVID-19 pandemic concerning the patients’ features.
Objective This study aims to assess the prognosis of inpatients with COVID-19 infection who have a history of sulfur mustard exposure. Methods We started a cohort study in October 2020 and ended in May 2021 on inpatients with COVID-19 infection who had been admitted to university healthcare centers. The analytic sample included 960 inpatients having COVID-19 infection (192 with; and 768 without sulfur mustard exposure). The exposed patients were male war veterans, and the unexposed patients were male individually age-matched people. All patients had a positive RT-PCR test and a positive chest CT for COVID-19. The outcome was death within 28 days of admission, and the predictors were clinical features recorded at patients' bedsides. Results There was a significantly higher prevalence for asthma ( p = 0.026) and pulmonary disease other than asthma ( p < 0.001) in patients with the exposure. Sulfur mustard exposure was associated with increased risk for mortality of COVID-19 [hazard ratio (95% CI) = 1.92 (1.14,3.24), p = 0.013]. Early intubation signified a poor prognosis [hazard = 7.34 (4.65,11.58), p < 0.001]. However, individuals with higher PaO2 [hazard = 0.97 (0.95,0.98), p < 0.001], or people undergoing O2 therapy early upon admission [hazard = 0.58 (0.38,0.89), p = 0.011] showed lower risks for mortality. Individuals with asthma were at higher risk for mortality [hazard = 3.76 (1.69,8.36), p = 0.001]. Conclusion Individuals with COVID-19 infection and sulfur mustard exposure should be considered high-risk patients and that, healthcare settings should be ready to provide critical care for them, including O 2 therapy. They are more likely to have asthma or other pulmonary diseases.
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