The dissertation is devoted to the prediction of the severe course of coronavirus disease COVID-19 in hospitalised patients of different ages.
The purpose of the research is to improve the diagnosis and prognosis of COVID-19 based on the study of age, clinical and laboratory, genetic factors and the identification of predictors of severe disease.
We conducted a prospective cohort study and a case-control study. Data from inpatient records were analysed and an in-depth comprehensive examination of 151 patients treated at the Poltava Regional Clinical Infectious Diseases Hospital of the Poltava Regional Council and the 3rd City Clinical Hospital of the Poltava City Council was conducted between April 2020 and March 2021.
The diagnosis was verified by detecting SARS-CoV-2 virus RNA in the nasopharyngeal swab material by PCR.
The population control group consisted of 82 apparently healthy individuals from the Poltava region.
All patients (n=151) were divided into groups according to age (middle-aged and elderly), AT1R gene A1166C polymorphism (patients with AA genotype and combined AC+CC genotype), and COVID-19 severity (moderate and severe and critical).
It was found that in elderly patients, coronavirus disease COVID-19 was accompanied by an increase in the frequency of certain symptoms, such as dyspnoea (p=0.000) and nausea (p=0.023) and comorbidities (cardiovascular disease (p=0.000), coronary heart disease (p=0.000), hypertension (p=0.000), chronic heart failure (p=0.000)); longer duration of generalised weakness (p=0.001) and anaemia (p=0.043); increased frequency of laboratory abnormalities: leukocytosis (p=0.011), increased urea level (p=0.000), increased AST level (p=0.031)); prevalence of severe (2.3 times, p=0.001) and critical (7.2 times, p=0.023) disease course compared to middle-aged patients.
In middle-aged patients, the course of COVID-19 was accompanied by an increase in the frequency of headache (p=0.049); longer duration of diarrhoea (p=0.045) and ague (p=0.022); and a 1.8-fold (p=0.000) prevalence of moderate COVID-19 compared with elderly patients.
In patients with COVID-19, the genotypes of the AT1R gene (rs5186) were distributed as follows: 38.4% homozygous AA genotype, 46.4% AC genotype, and 15.2% homozygous CC genotype, which did not differ from the population control group in Poltava region (p=0.803).
The clinical course of COVID-19 in individuals with the A1166C polymorphism of the AT1R gene (rs5186) was typical except for some features: patients with the combined AC+CC genotype had a longer duration of dyspnoea (p=0.010), cough (p=0.017), sputum with blood impurities (p=0.018); increased frequency of severe + critical COVID-19 (p=0.016) compared to patients with the AA genotype.
The development of COVID-19 complications and, in particular, respiratory failure was recorded more frequently in elderly patients: ARDS by 3.7 times (p=0.010), ARF by 6.4 times (p=0.042), respiratory failure by 2.0 times (p=0.000) and death by 6.4 times (p=0.042) compared to middle-aged patients.
Correction of respiratory failure in patients with COVID-19 required oxygen support of varying degrees. Elderly patients were 2.0 times more likely to require oxygen support (p=0.000), namely a face mask with an oxygen flow of <5 l/min (p=0.031) and invasive mechanical ventilation (9.6% vs. 1.5%, p=0.042) compared with middle-aged patients.
Patients with AC+CC genotypes of the AT1R gene (rs5186) were more likely to require oxygen therapy and have signs of acute respiratory failure (67.7% vs. 44.8%, p=0.005), including 1.7 times more often with the use of a face mask (p=0.009) compared with those with AA genotype.
Clinical and genetic predictors of severe COVID-19 were found to be Older age (OR 2.991, p=0.012), carriage of the 1166C allele of the AT1R gene (OR 2.767, p=0.020), leukaemia (OR7.347, p=0.004) and lymphocytopenia (OR 3.188, p=0.006) at the time of hospitalisation, presence of comorbidities (type II diabetes mellitus (OR 3.6981, p=0.014), chronic heart failure (OR 3.003, p=0.017). Based on the obtained factors, a prognostic model for the development of severe COVID-19 was created, which demonstrated statistical significance (χ² = 51.85, p < 0.000) with high operational characteristics (sensitivity - 75.0%, specificity - 80.2%) and good prognostic quality (AUC ROC curve - 0.8298).
The results obtained have significantly improved the understanding of the clinical course of COVID-19 in patients of different age groups and helped to identify new factors that contribute to the progression of COVID-19 to severe and/or critical conditions.
