Background The epidemiology, clinical course, and outcomes of COVID-19 patients in the Russian population are unknown. Information on the differences between laboratory-confirmed and clinically-diagnosed COVID-19 in real-life settings is lacking. Methods We extracted data from the medical records of adult patients who were consecutively admitted for suspected COVID-19 infection in Moscow, between April 8 and May 28, 2020. Results Of the 4261 patients hospitalised for suspected COVID-19, outcomes were available for 3480 patients (median age 56 years (interquartile range 45-66). The commonest comorbidities were hypertension, obesity, chronic cardiac disease and diabetes. Half of the patients (n=1728) had a positive RT-PCR while 1748 were negative on RT-PCR but had clinical symptoms and characteristic CT signs suggestive of COVID-19 infection.No significant differences in frequency of symptoms, laboratory test results and risk factors for in-hospital mortality were found between those exclusively clinically diagnosed or with positive SARS-CoV-2 RT-PCR.In a multivariable logistic regression model the following were associated with in-hospital mortality; older age (per 1 year increase) odds ratio [OR] 1.05 (95% confidence interval (CI) 1.03 - 1.06); male sex (OR 1.71, 1.24 - 2.37); chronic kidney disease (OR 2.99, 1.89 – 4.64); diabetes (OR 2.1, 1.46 - 2.99); chronic cardiac disease (OR 1.78, 1.24 - 2.57) and dementia (OR 2.73, 1.34 – 5.47). Conclusions Age, male sex, and chronic comorbidities were risk factors for in-hospital mortality. The combination of clinical features were sufficient to diagnoseCOVID-19 infection indicating that laboratory testing is not critical in real-life clinical practice.
Федеральный дистанционный консультативный центр анестезиологии и реаниматологии на базе Первого МГМУ им. И.М. Сеченова
Цель. Изучение летальности и факторов риска смерти больных с COVID-19, госпитализированных для респираторной поддержки в отделения реанимации и интенсивной терапии (ОРИТ) лечебных учреждений Российской Федерации. Материал и методы. Ретроспективное исследование было выполнено в Федеральном дистанционном консультативном центре анестезиологии и реаниматологии для взрослых пациентов с COVID-19 на базе Первого МГМУ им. И.М. Сеченова. В исследование включали всех пациентов с известными исходами (смерть от любых причин или выздоровление) SARS-CoV-2 пневмонии, осложнившейся острым респираторным дистресс синдромом (ОРДС), которые были проконсультированы с 16 марта по 3 мая 2020 г. Факторы риска смерти анализировали с помощью многофакторной регрессионной модели Кокса. Результаты. В исследование были включены 1522 пациента, 864 (56,8%) мужчины и 658 (43,2%) женщин. Медиана возраста-62 года. 922 (60,6%) больных находились в ОРИТ стационаров Москвы и Московской области, 600 (39,4%)-лечебных учреждений в 70 регионах Российской Федерации. У 995 (65,4%) больных диагноз SARS-CoV-2 инфекции был подтвержден с помощью ПЦР. Умерли 995 (65,4%) пациентов, выжили 527 (34,6%). Основными причинами смерти были ОРДС (93,2%), сер
Aim. In a retrospective study, we evaluated factors associated with the early development of septic shock in patients with severe COVID-19. Materials and methods. We collected medical records of the intensive care unit patients submitted by the local COVID-19 hospitals across Russia to the Federal Center for the Critical Care at the Sechenov First Moscow State Medical University (Sechenov University). Septic shock in crticially ill patients requiring mechanical ventilation was defined as a need in vasopressors to maintain blood pressure. Results. We studied 1078 patients with severe COVID-19 who were admitted to the intensive care units for respiratory support. There were 611 males and 467 females. The mean age was 61.013.7 years. Five hundred twenty five medical records (48.7%) were received from the Moscow hospitals, 159 (14.7%) from the Moscow region, and 394 (36.5%) from the hospitals located in 58 regions of the Russian Federation. In 613 (56.9%) patients, diagnosis of SARS-CoV-2 infection was confirmed by PCR, and in the other cases it was established on the basis of the clinical picture and the results of the chest CT scan. Septic shock developed in 214 (19.9%) of 1078 patients. In the logistic regression model, the risk of septic shock in patients older than 50 years was higher than in patients of a younger age (OR 2.34; 95% CI 1.533.67; p0.0001). In patients with more severe SARS-CoV-2 infection, there was an increase in the prevalence of cardiovascular diseases, including coronary heart disease and atrial fibrillation, type 2 diabetes and malignant tumors. The risk of septic shock in patients with three or more concomitant diseases was higher than in patients without any concomitant chronic diseases (OR 1.76; 95% CI 1.762.70). Conclusion. The risk of septic shock in patients with acute respiratory distress syndrome induced by SARS-CoV-2 is higher in patients older than 50 years with concomitant diseases, although a severe course of the disease is also possible in younger patients without any concomitant disorders.
Large population studies using statistical analysis and mathematical computer modeling could be an effective tool in studying COVID-19. The use of prognostic scales developed using correlation of changes in clinical and laboratory parameters and morphological data, can help in early prediction of disease progression and identification of patients with high risk of unfavorable outcome.Aim of the review. To assess the risk factors for severe course and unfavorable outcome of COVID-19 and to evaluate the existing tools for predicting the course and outcome of the novel coronavirus infection. PubMed, Medline, and Google Scholar were searched for the relevant sources. This review contains information on existing tools for assessing the prognosis and outcome of the disease, along with the brief data on the etiology, pathogenesis of the novel coronavirus infection and the known epidemiological, clinical and laboratory factors affecting its course.Conclusion. It is essential to develop predictive models tailored to specific settings and capable of continuous monitoring of the situation and making the necessary adjustments. The discovery of new and more sensitive early markers and developing marker-based predictive assessment tools could significantly impact improving the outcomes of COVID-19.
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