Научная статья на тему 'Prognostic factors for the severe course of COVID-19 in the different COVID-19 peak periods in Central Kazakhstan'

Prognostic factors for the severe course of COVID-19 in the different COVID-19 peak periods in Central Kazakhstan Текст научной статьи по специальности «Клиническая медицина»

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Ключевые слова
COVID-19 / coronavirus disease / prognosis / risk factors

Аннотация научной статьи по клинической медицине, автор научной работы — Lyudmila Turgunova, Irina Mekhantseva, Irina Bacheva, Dana Amirkhanova, Maria Butyugina

Introduction: COVID-19 has become the cause of a pandemic that has swept the entire world. Considering the genetic variability of the virus, the development and implementation of antiviral therapies, and the acquisition of a society's immune defenses through past infection or vaccination, the course of COVID-19 may change over time. The research aim was to study the prognostic significance of clinical and laboratory parameters with severe COVID-19 in 2020 and 2021 in Central Kazakhstan. Material and methods: A cohort of 1556 patients with COVID-19 admitted to the infection hospitals of Karaganda from May to July 2020 and 2021 year was retrospectively analyzed. The association of clinical and laboratory parameters with the severe disease was analyzed using univariate and multivariate logistic regression, and independent predictors were established for each factor. Results: The comparative analysis of the prognostic significance of demographic, clinical, and laboratory parameters in different periods of the pandemic showed a reduction in developing severe COVID-19 among hospitalized patients in 2021 compared to 2020. The essential value of comorbidity, especially chronic renal failure, and chronic heart failure remained significant against the background of decreasing prognostic significance of age, gender, and clinical and laboratory indicators of inflammation for the severe course of COVID-19.

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Текст научной работы на тему «Prognostic factors for the severe course of COVID-19 in the different COVID-19 peak periods in Central Kazakhstan»

JQYK) JOURNAL OF CLINICAL MEDICINE OF KAZAKHSTAN

Original Article

(E-ISSN 2313-1519)

Prognostic factors for the severe course of COVID-19 in the different COVID-19 peak periods in Central Kazakhstan

Lyudmila Turgunova, Irina Mekhantseva, Irina Bacheva, Dana Amirkhanova, Maria Butyugina, Nadezhda Samoilova

Department of Internal Medicine, Karaganda Medical University, Karaganda, Kazakhstan

Abstract

Introduction: COVID-19 has become the cause of a pandemic that has swept the entire world. Considering the genetic variability of the virus, the development and implementation of antiviral therapies, and the acquisition of a society's immune defenses through past infection or vaccination, the course of COVID-19 may change over time. The research aim was to study the prognostic significance of clinical and laboratory parameters with severe COVID-19 in 2020 and 2021 in Central Kazakhstan.

Material and methods: A cohort of 1556 patients with COVID-19 admitted to the infection hospitals of Karaganda from May to July 2020 and 2021 year was retrospectively analyzed. The association of clinical and laboratory parameters with the severe disease was analyzed using univariate and multivariate logistic regression, and independent predictors were established for each factor.

Results: The comparative analysis of the prognostic significance of demographic, clinical, and laboratory parameters in different periods of the pandemic showed a reduction in developing severe COVID-19 among hospitalized patients in 2021 compared to 2020. The essential value of comorbidity, especially chronic renal failure, and chronic heart failure remained significant against the background of decreasing prognostic significance of age, gender, and clinical and laboratory indicators of inflammation for the severe course of COVID-19.

Key words: COVID-19, coronavirus disease, prognosis, risk factors

Received: 2022-04-13. Accepted: 2022-07-11

This work is licensed under a Creative Commons Attribution 4.0 International License

J Clin Med Kaz 2022; 19(4):53-58

Corresponding author: Irina Mekhantseva. E-mail: mehanceva@qmu.kz; ORCID: 0000-0001-6601-8172

Introduction

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the cause of the coronavirus disease-2019 (COVID-19) initiated a pandemic that swept the whole world. The first cases of COVID-19 in Kazakhstan were confirmed on 13 March 2020 in Nur-Sultan and Almaty. On March 16, 2020, the government declared an emergency throughout the country [1-3].

The result of the meta-analysis shows that the frequency of severe cases of COVID-19 variated according to different researchers from 7,2 to 49,1%, deaths from 3,1% to 61,5% [4-6]. Most of the evidence-based research analysis where most participants were from China and later were published research from the USA, Europe, and other countries [7,8]. Big Kazakhstan's study which included hospitalized patients between February and April 2020 showed that the frequency of severe manifestations was about 4% [2].

For the 2020 year the predictive value of demographic, clinical, and laboratory parameters in predicting the severity of the course, the necessity for artificial lung ventilation (ALV), and patient mortality has been studied in many research [9-11]. Given the genetic variability of the virus, the development, and deployment of antiviral drugs, and the acquisition of a society's immune defenses through past infection or vaccination, it is not surprising that the course of COVID-19 can change over time. We didn't find research that studied the association of clinical and laboratory factors with the risk of developing a severe course of COVID-19 for different periods of the pandemic in Kazakhstan.

The investigation aimed to study the prognostic significance of clinical and laboratory parameters with severe COVID-19 associated pneumonia in 2020 and 2021 in Central Kazakhstan.

Materials and methods

A cohort of 1556 patients with COVID-19 from all of Central Kazakhstan (the total number of adult population of this region is 1 043 983 people [12]) admitted to the Regional clinical hospital and Medical University clinic in Karaganda from May to July 2020 and 2021 year was retrospectively analyzed. Patients with a positive nasopharyngeal PCR test for COVID-19 were included in the study. We collected data from electronic medical records for all patients: demographic data, presence or absence of active smoking, comorbidities, anthropometric parameters, blood pressure (BP), heart rate (HR), respiratory rate (RR), and oxygen saturation. Laboratory tests performed on admission included a complete blood count, and biochemical parameters (alanine aminotransferase, aspartate aminotransferase, bilirubin, creatinine, glucose, D-dimer), laboratory tests were carried out in the same certified laboratory in Karaganda. In all patients, we calculated body mass index, Charlson comorbidity index [13,14], and performed a chest CT scan. Of 1556 patients, 270 were excluded: 34 patients had no oxygen saturation data, in 122 patients - creatinine and blood glucose values, in 114 - the results of computed tomography of the lungs. In total, 1286 patients were included: 872 in 2020 and 414 in 2021. According to the WHO criteria, patients were divided into 4 groups depending on the severity: mild - 91 (7,1%), moderate - 999 (77,7%), severe - 182 (14,2%) and critically severe - 14 (1,1%). Patients with mild and moderate severity were combined into 1 group - 1090 (84,8%), and patients with severe and critically severe degrees constituted group 2 - 196 (15,2%). The study design was approved by the ethics committee of Karaganda Medical University dated April 14, 2021, No. 18.

Statistical analysis

Data were analyzed by using SPSS 21.0. The normal distribution was checked by the Kolmogorov-Smirnov test. Gender, smoking, presence of arterial hypertension (HTA), myocardial infarction (MI), diabetes mellitus (DM), chronic obstructive pulmonary disease (COPD), chronic kidney disease (CKD), pulmonary embolism (PE), bronchial asthma (BA), acute stroke (AS), presence of symptoms, severity, 30-day mortality were introduced as dichotomous variables. Descriptive statistics used the Mann-Whitney U-test for independent samples to compare quantitative variables; categorical variables were analyzed by Pearson's %2. Continuous variables were reported as median (interquartile range), and categorical variables were presented as absolute frequency (relative frequency, %). We used univariate and multivariate logistic regression to establish an association of clinical and laboratory parameters and severe COVID-19 parameters of was d using, established independent predictors and odds ratios (ORs) at 95% confidence intervals (CI) for each factor. Covariates with p<0,05 or if they changed positive effect by >10% were included in multivariate analysis. Considering the strong correlation between systolic blood pressure (SBP) and diastolic blood pressure (DBP) (r=0.604), the variable SBP*DBP was included in the multivariate analysis, which reflects the relationship of these predictors. P-values <0,05 were considered as significant.

Results

In this study, we analyzed data from 872 and 414 hospitalized patients with COVID-19 of the first and second waves of the pandemic in two hospitals in Karaganda. The clinical characteristics of patients are presented in Table 1. In 2020 and especially in 2021, women predominated among

inpatients - 54% and 60,4% respectively; the age of patients in 2020 was significantly younger: 32.3% were persons aged 4559, in 2021 - 45.4% of patients were aged 60-74 (Table 1). The most common symptoms during both periods were complaints of general weakness, fever, cough, and shortness of breath. In 2021, complaints of myalgia were significantly more frequent than in 2020- 1,6 times (p=0,003), general weakness - 1,1 times (p=0,001), joint pain - 2,4 times (p=0,01), ageusia - 261 times (p=0,042). The Charlson comorbidity index between groups differed due to the prevalence in 2021 of patients with comorbidity 2-3 points compared to 2020; groups with severe comorbidity (3 points or more) were comparable - 14,7% in 2021 and 15,9% in 2020. In the structure of comorbidities, a higher frequency of HTA and CHF was revealed in 2021 compared to

2020, the frequency of DM, COPD, MI, CKD, and BA did not differ significantly between the groups.

In 2020, COVID-19 was characterized by a more severe course compared to 2021: 2,3 times more likely to have severe and extremely severe severity, 2,2 times more need for ventilation, 3.2 higher in-hospital mortality compared to 2021. The percentage of lung tissue damage was higher in 2020 (Me 30% Q2-Q3 (20-60) compared to 2021 - (Me 25% Q2-Q3 (12-40); p=0,0001). The frequency of MI, stroke, and PE did not differ significantly between the groups. More than a third of patients noted taking antibacterial drugs before hospitalization, anticoagulant intake ranged from 3,9 to 6,1% with no significant difference between 2020 and 2021.

Laboratory parameters are shown in Table 2. In 2020 compared to 2021, patients had higher levels of leukocytes, platelets, and NLR (neutrophil-lymphocyte ratio), from biochemical parameters - AST level. We did not find significant differences in ALT, and creatinine levels between patients in 2020 and 2021. In 2021, patients had significantly higher levels of bilirubin and glucose compared to 2020. D-dimer levels did not differ between groups.

The results of the unadjusted odds ratio for the variables showed that in 2020 the risk of developing a severe degree of the disease increased significantly with the age of the patient (odds ratio [OR]: 1,053 95% CI: 1,040 - 1,066, p<0,0001) and did not depend on gender (odds ratio [OR]: 1,397 95% CI: 0,993 - 1,965, p<0,055). In 2021, we found no predictive significance of age (p=06323) and sex (p=06731) for severe COVID-19 risk in univariate analysis. HTA, CHF, and diabetes mellitus prevailed in the structure of concomitant conditions. The presence of comorbid diseases such as hypertension, CHF, DM, and CKD had a significant predictive value for the severity of COVID-19 in patients in 2020 and 2021. In 2020 increased temperature, instability of blood pressure, and decreased oxygen saturation were associated with severe course of the disease, in

2021, only reduced oxygen saturation remained significant for severe COVID-19 (odds ratio [OR]: 0,727 95% CI: 0,654-0,808, p=0,0001). From laboratory parameters, the most significant increase in the risk of severe COVID-19 was associated with an increase in NLR and creatinine levels.

The results of multivariate logistic regression models for assessing the relationship of various indicators that are statistically significant in a univariate analysis with the risk of developing severe degree of COVID-19 in 2020 and 2021 are presented in Table 3. In 2020, a stratified analysis showed that the risk of severe COVID-19 is associated with age (odds ratio [OR]: 1,034 95% CI: 1,015-1,054, p=0,001), increased temperature (odds ratio [OR]: 1,527 95% CI: 1,087-2,145, p=0,015), decreased oxygen saturation (odds ratio [OR]: 0,866 95% CI: 0,840-0,893, p=0,0001) and increased NLR (odds ratio

Table 1

Clinical characteristics (% and median value (interquartile range)) of COVID19 inpatients in 2020 and 2021.

Parameter 2020 year (n=872) 2021 year (n=414) Z p-value

Age, years 57 (45-68) 62 (52-70) 4.038 0.0001

Age categories: 18-44 45-59 60-74 75 and older 216 (24.8%) 282 (32.3%) 260 (29.8%) 114 (l3.1%) 74 (17.9%) 96 (23.2%) 188 (45.4%) 56 (13.5%) 4.27 0.0001

Gender: female male 471 (54%) 401 (46%) 250 (60.4%) 164 (39.6%) 2.151 0.031

Smoker no data 37 (4.2%) 298 (34.2%) 19 (4.6%) 215 (51.9%) 1.45 0.146

Temperature >38°C 635 (72.8%) 317 (76.6%) 1.432 0.152

Myalgia 81 (9.3%) 62 (15.0%) 2.97 0.003

General weakness 728 (83.5%) 373 (90.1%) 3.6 0.001

Loss of appetite 170 (19.5%) 100 (24.2%) 1.938 0.053

Sore throat 140 (16.1%) 62 (15.0%) 0.556 0.578

Cough 603 (69.2%) 295 (71.3%) 1.035 0.301

Dyspnea 309 (35.4%) 190 (45.9%) 0.975 0.330

Joint pain 14 (1.6%) 16 (3.9%) 2.589 0.010

Chest pain 106 (12.1%) 43 (10.4%) 0.932 0.351

Anosmia 53 (6.1%) 29 (4.3%) 0.635 0.525

Ageusia 20 (2.3%) 18 (4.9%) 2.032 0.042

Stomach ache 18 (2.1%) 8 (1.9%) 0.151 0.880

Stool disorders 34 (3.9%) 15 (3.6%) 1.015 0.310

Stroke 10 (1.1%) 6 (1.4%) 0.457 0.648

PE 14 (1.6%) 8 (1.9%) 0.422 0.673

MI 22 (2.5%) 17 (4.1%) 1.546 0.122

HTA 399 (45.8%) 225 (54.3%) 2.879 0.004

CHF 251 (28.8%) 149 (36.0%) 2.607 0.009

BA 11 (1.3%) 4 (1.0%) 0.461 0.645

COPD 20 (2.3%) 7 (1.7%) 0.704 0.481

CKD 41 (4.7%) 13 (3.1%) 1.304 0.192

DM 124 (14.2%) 72 (17.4%) 1.478 0.139

Comorbidity index, score 0-1 2-3 4 or more 548 (62.8%) 185 (21.2%) 139 (15.9%) 226 (54.6%) 127 (30.7%) 61 (14.7%) 2.154 0.031

Temperature, °C 36.8 (36.6-37.4) 36.8 (36.5-37.2) 1.972 0.049

BMI, kg/m2 27.7 (24.6-31.6) 30.8 (27.0-34.6) 4.316 0.0001

SBP, mmHg 120.0 (120.0-130.0) 120.0 (115.0-130.0) 1.475 0.140

DBP, mmHg 80 (70-80) 80 (70-80) 4.091 0.0001

HR, beats/min 80 (76-88) 80 (76-89) 0.568 0.570

RR, in min 19 (18-22) 19 (18-20) 2.263 0.024

Sat O2, % 95 (92-97) 95 (93-97) 1.283 0.200

Severity degree 1 2 709 (81.3%) 163 (18.7%) 381 (92,0%) 33 (8,0%) 4.996 0.0001

Lung damage, % 30 (20-60) 25 (12-40) 5.671 0.0001

ALV 73 (8.4%) 16 (3.9%) 3.647 0.001

Mortality 75 (8.6%) 11 (2.7%) 3.985 0.0001

Bed days 11 (9-13) 10 (9-11) 4.429 0.0001

Antibiotics before hospitalization 308 (35.3%) 125 (30.2%) 1.817 0.069

Anticoagulants before hospitalization 53 (6.1%) 16 (3.9%) 1.645 0.10

Abbreviations: ALV - artificial lung ventilation, BA - bronchial asthma, BMI - body mass index

CKD - chronic kidney disease, COPD - chronic obstructive pulmonary disease, CHF - chronic heart failure, DBP - diastolic blood pressure, DM - diabetes mellitus, HR - heart rate, HTA - Arterial hypertension, MI - myocardial infarction, PE - pulmonary embolism, RR - respiratory rate, SaO2 - Oxygen saturation, SBP - systolic blood pressure

[OR]: 1,078 95% CI: 1,022-1,138, р=0,006). Of the comorbid conditions in the multivariate model for patients in 2020, the presence of CKD and COPD preserved predictive value. The presence of other comorbid conditions in 2020 lost predictive value for COVID-19 severity after correction. In 2021, after correction in the multivariate model, the presence of CHF

(odds ratio [OR]: 4,580 95% CI: 1,028-20,409, р=0,046), CKD (odds ratio [OR]: 7,728 95% CI: 1,707-34,993, р=0,008) and a decrease in oxygen saturation (odds ratio [OR]: 0,724 95% CI: 0,636-0,824, р=0,0001) retained a significant association with the risk of developing severe COVID-19.

Table 2

Laboratory parameters in patients hospitalized with COVID-19 in 2020 and 2021

Parameter 2020 year (n=872) 2021 year Z (n=414) p-value

Me (Q25-Q75) Me (Q25-Q75)

Leukocytes, 109/^ 5.50 (4.40-7.50) 5.10 (3.97-6.37) 4,527 0.0001

Neutrophils, 109/^ 3.56 (2.45-5.25) 3.20 (2.29-4.36) 3.924 0.0001

Lymphocytes, 109/^ 1,28 (0,92-1,77) 1.21 (0.94 -1.66) 1.379 0.168

NLR 2.75 (1.74-4.81) 2.52 (1.72-3.73) 2.425 0.015

Platelets, 109/a 200.0 (173-259) 188 (166-214) 5.048 0.0001

ESR, mm/h 20 (10-32) 13 (9-21) 7.593 0.0001

AST, U/l 30.7 (23.0-47,0) 27 (23-37) 3.181 0.001

ALT, U/l 27.5 (19.0-40.0) 29 (21-33) 0.619 0.536

Creatinine, ^mol/l 84.9 (71.0-99.0) 88.0 (78.3-96.0) 1.765 0.078

Bilirubin total, ^mol/l 11.20 (9.70-14.37) 13.1 (11.8-16.0) 8.728 0.0001

Glucose, mmol/l 5.7 (5.0-7.3) 6.5 (5.50-8.0) 6.092 0.0001

D-dimer, ng/ml 315.0 (198.7-476.5) 310.0 (183.0-470.0) 0.657 0.511

Abbreviations: ALT - alanine aminotransferase, AST - Aspartate aminotransferase, ESR - Erythrocyte Sedimentation Rate, NLR - Neutrophil-to-lymphocyte

Table 3

Univariate and multivariate logistic regression analyses of risk variables for association with severe COVID-19 in 2020 and 2021

Parameter 2020 (n=872) 2021(n=414)

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unadjusted OR (95% CI) p value aOR (95% CI) p value unadjusted OR (95% CI) p value aOR (95% CI) p value

Age, years 1.053 (1.040-1.066) 0.0001 1.034 (1.015-1.054) 0.001 1,012 (0,988-1,038) 0.323 -

Male 1.397 (0.993-1.965) 0.055 - 1,135 (0,552-2,332) 0.731 -

HTA 7.383 (4.830-11.286) 0.0001 2.141 (1.071-4.279) 0.031 2.828 (1.244-6.429) 0.013 0.360 (0.073-1.773) 0.209

CHF 6.285 (4.362-9.054) 0.0001 1.639 (0.881-3.050) 0.119 4.655 (2.150-10.078) 0.0001 4.580 (1.028-20.409) 0.046

DM 2.202 (1.436-3.377) 0.0001 1.218 (0.638-2.326) 0.549 2.623 (1.210-5.687) 0.015 1.811 (0.580-5.652) 0.307

CKD 7.846 (4.082-15.084) 0.0001 3.725 (1.441-9.625) 0.007 16.827 (5.272-53.710) 0.0001 7.728 (1.707-34.993) 0.008

COPD 5.629 (2.292-13.820) 0.0001 6.705 (1.810-24.843) 0.004 1.953 (0.228-16.726) 0.541 -

MI 2.076 (0.832-5.177) 0.117 - - 3.894 (1.193-12.707) 0.024 2.720 (0.645-11.469) 0.173

SBP 1.023 (1.006-1.041) 0.008 0.981 (0.957-1.005)* 0.116 1.020 (0.990-1.050) 0,192 -

DBP 0.989 (0.967-1.010) 0.303 - 1.024 (0.971-1.080) 0.374 -

Temperature, °C 1.749 (1.403-2.181) 0.0001 1.527 (1.087-2.145) 0.015 0.997 (0.962-1.033) 0.860 -

Sat02, % 0.846 (0.822-0.870) 0.0001 0.866 (0.840-0.893) 0.0001 0.727 (0.654-0.808) 0.0001 0.724 (0.636-0.824) 0.0001

Platelets 1.003 (1.001-1.005) 0.004 1.002 (0.999-1.005) 0.238 0.996 (0.990-1.002) 0.244 -

AST, U/l 1.002 (0.999-1.005) 0.181 - 1.000 (0.997-1.004) 0.910 -

Creatinin, ^mol/l 1.001 (1.000-1.003) 0.081 - 1.011 (1.003-1.020) 0.010 1.001 (0.989-1.013) 0.836

Glucose, mmol/l 1.000 (0.999-1.001) 0.740 - 1.095 (1.016-1.180) 0.016 0.985 (0.872-1.114) 0.813

NLR 1.245 (1.189-1.302) 0.0001 1.078 (1.022-1.138) 0.006 1.084 (1,011-1.163) 0.024 0.984 (0.891-1.086) 0.745

Odds ratios were given with 95% CI and p values * variable SBP*DBP

Abbreviations: AST - Aspartate aminotransferase, CKD - chronic kidney disease, COPD - chronic obstructive pulmonary disease, CHF - chronic heart failure, DBP - diastolic blood pressure, DM - diabetes mellitus, HTA - Arterial hypertension, MI - myocardial infarction, SaO2 - Oxygen saturation, SBP -systolic blood pressure, NLR - Neutrophil-to-lymphocyte ratio

Discussion

The first wave of the pandemic in Kazakhstan began in March 2020 and quickly spread over its territory [15]. In this research for the first time, we compared the predictive value of clinical and laboratory parameters for the risk of severe COVID-19 between patients in 2020 and 2021. We found that in 2020-year patients' age, gender, presence of CKD, COPD, fever, increase in NLR, and decrease in oxygen saturation had significant predictive value for COVID-19 severity. The data obtained are consistent with numerous results of other works were shown the predictive value of age [16], gender [17], comorbidity [18-20], clinical symptoms of disease [21], and increase of NLR [22] for the prognosis of severity and death.

Interestingly, we didn't find predictive value for age and gender in COVID-19 patients in 2021. The lack of age difference cannot be attributed to the younger age of patients because the median age in 2021 is significantly higher compared to patients in 2020. We did not find a male predominance among hospitalized patients.

The predictive value of comorbid conditions for the severity of COVID-19 is supported by the results of many studies. The highest significance after correction in the multivariate model both in 2020 (odds ratio [OR]: 3,725 95% CI: 1,441-9,625, p=0,007) and in 2021 (odds ratio [OR]: 7,728 95% CI: 1,70734,9, p=0,008) had CKD. A meta-analysis of geographical differences in the association of comorbidity with the severity of COVID-19 showed that in Asia, compared with Europe and the United States, the most common cause of COVID-19 severity was the presence of CKD [19] (68%; 95% CI: 46-87%), while liver disease (50%; 95% CI: 1-99%) in European and Latin American studies, and malignancies in US researches (38%; 95% CI: 18-60%).

Since the beginning of the pandemic, many authors have investigated the role of NLR in predicting COVID-19 and have shown its utility as a biomarker. The lack of predictive value of NLR for COVID-19 severity in 2021 cannot be fully explained by demographic differences. Our data are consistent with those of Monica Gelzo et al [23] who observed no significant difference in NLR between the WHO severity stage in COVID-19 patients during wave II in Italy (September 2020-April 2021) in contrast to the first wave of the pandemic. These differences between two wave COVID-19 patients were not associated with younger age in wave II patients, as age did not significantly affect NLR and neutrophils across different COVID-19 severity levels. The authors hypothesized that the differences between the two waves were probably related to the prescription of steroid therapy which was the only independent variable associated with NLR and neutrophils.

In our opinion, a significant decrease in the severity of the course of COVID-19, mortality, percentage of lung tissue damage in 2021 compared to 2020 in the absence of significant changes in clinical symptoms, comorbidity suggests a dependence on various factors including the introduction of various methods of therapy, the acquisition of tolerance to infection, organization and practical experience in managing the management of patients with COVID-19 infection since the beginning of the pandemic. In Kazakhstan, the first version of the guideline for diagnosing and treatment of COVID-19 was made on February 3rd 2020 year. By July 2021 in the country were held more than 10 editions which included constantly updated information on the course and treatment of the disease.

The limitations of our research were including patients from only two centers in the Karaganda region. Given the differences

in the severity of the course and the prognostic significance of clinical and laboratory factors in different periods of the pandemic, an in-depth study seems relevant in future studies, depending on the therapy and the immune status of patients.

Conclusion

The COVID-19 pandemic has become a challenge for healthcare in almost all countries, including Kazakhstan due to the high incidence, severity, and mortality of patients. A comparative analysis of the prognostic significance of demographic, clinical, and laboratory parameters in different periods of the pandemic showed a decrease in the severity of the course among inpatients in 2021 compared to 2020. Against the background of a decrease in the prognostic significance of age, gender, and clinical and laboratory indicators of inflammation, the significant significance of comorbidity, especially CKD and CHF, for the severe course of COVID-19 remained. There is a relevance for future studies to assess the impact of therapy and immune status on the course and outcomes of COVID-19 infection.

Abbreviations:

ALT - alanine aminotransferase

ALV - artificial lung ventilation

AS - acute stroke

AST - Aspartate aminotransferase

BA - bronchial asthma

BP - blood pressure

CKD - chronic kidney disease

COPD - chronic obstructive pulmonary disease

COVID-19 - coronavirus disease 2019

CHF - chronic heart failure

CRF - chronic renal failure

CT - computed tomography

DBP - diastolic blood pressure

DM - diabetes mellitus

ESR - Erythrocyte Sedimentation Rate

HR - heart rate

HTA - Arterial hypertension

MI - myocardial infarction

NLR - Neutrophil-to-lymphocyte ratio

PCR - polymerase chain reaction

PE - pulmonary embolism

RR - respiratory rate

SARS-CoV-2 - Severe acute respiratory syndrome-related coronavirus 2

SaO2 - Oxygen saturation SBP - systolic blood pressure WHO - World Health Organization

Disclosures: There is no conflict of interest for all authors. Acknowledgments: None.

Funding: This research is being funded by the Ministry of Health of the Republic of Kazakhstan (Program No. BR11065386).

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