Epidemiology, clinical characteristics, and virologic features of COVID-19 patients in Kazakhstan: A nation-wide retrospective cohort study

Metagenomic profiling of nasopharyngeal samples from adults with acute respiratory infection

Diagnosis of acute respiratory infections (ARIs) is challenging due to the broad diversity of potential microbial causes. We used metagenomic next-generation sequencing (mNGS) to analyze the nasopharyngeal virome of ARI patients, who had undergone testing with a clinical multiplex PCR panel (Amplisens ARVI-screen-FRT). We collected nasopharyngeal swabs from 49 outpatient adults, 32 of whom had ARI symptoms and were PCR-positive, and 4 asymptomatic controls in Kazakhstan during Spring 2021. We assessed the biodiversity of the mNGS-derived virome and concordance with PCR results. PCR identified common ARI viruses in 65% of the symptomatic cases. mNGS revealed viral taxa consisting of human, non-human eukaryotic and bacteriophage groups, comprising 15, 11 and 28 genera, respectively. Notable ARI-associated human viruses included rhinovirus (16.3%), betaherpesvirus 7 (14.3%) and Epstein-Barr virus (8.16%). The primary phage hosts were Streptococcus spp. (32.7%), Pseudomonas aeruginosa (24.5%) and Burkholderia spp. (20.4%). In total, 47% of ARIs were linked solely to bacterial pathogens, a third to viral-bacterial co-infections, and less than 10% to only viral infections by mNGS. PCR showed low concordance with mNGS, except for rhinovirus. These results underscore the importance of broad diagnostic methods and question the effectiveness of commonly used PCR panels in ARI diagnosis.

RT-qPCR investigation of post-mortem tissues during COVID-19

In 2020, there were numerous cases in Kazakhstan with clinical symptoms of COVID-19 but negative PCR results in nasopharyngeal and oropharyngeal swabs. The diagnosis was confirmed clinically and by CT scans (computed tomography). The problem with such negative PCR results for SARS-CoV-2 infection confirmation still exists and indicates the need to confirm the diagnosis in the bronchoalveolar lavage in such cases. There is also a lack of information about confirmation of SARS-CoV-2 infection in deceased patients. In this study, various tissue materials, including lungs, bronchi, and trachea, were examined from eight patients who died, presumably from SARS-CoV-2 infection, between 2020 and 2022. Naso/oropharyngeal swabs taken from these patients in hospitals tested PCR negative for SARS-CoV-2. This study presents a modified RNA isolation method based on a comparison of the most used methods for RNA isolation in laboratories: QIAamp Viral RNA Mini Kit and TRIzol-based method. This modified nucleic acid extraction protocol can be used to confirm SARS-CoV-2 infection by RT-qPCR in the tissues of deceased patients in disputed cases. RT-qPCR with RNA of SARS-CoV-2 re-extracted with such method from post-mortem tissues that were stored at -80 °C for more than 32 months still demonstrated high-yielding positive results.

Application of MALDI-TOF MS and machine learning for the detection of SARS-CoV-2 and non-SARS-CoV-2 respiratory infections

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) could aid the diagnosis of acute respiratory infections (ARIs) owing to its affordability and high-throughput capacity. MALDI-TOF MS has been proposed for use on commonly available respiratory samples, without specialized sample preparation, making this technology especially attractive for implementation in low-resource regions. Here, we assessed the utility of MALDI-TOF MS in differentiating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vs non-COVID acute respiratory infections (NCARIs) in a clinical lab setting in Kazakhstan. Nasopharyngeal swabs were collected from inpatients and outpatients with respiratory symptoms and from asymptomatic controls (ACs) in 2020-2022. PCR was used to differentiate SARS-CoV-2+ and NCARI cases. MALDI-TOF MS spectra were obtained for a total of 252 samples (115 SARS-CoV-2+, 98 NCARIs, and 39 ACs) without specialized sample preparation. In our first sub-analysis, we followed a published protocol for peak preprocessing and machine learning (ML), trained on publicly available spectra from South American SARS-CoV-2+ and NCARI samples. In our second sub-analysis, we trained ML models on a peak intensity matrix representative of both South American (SA) and Kazakhstan (Kaz) samples. Applying the established MALDI-TOF MS pipeline "as is" resulted in a high detection rate for SARS-CoV-2+ samples (91.0%), but low accuracy for NCARIs (48.0%) and ACs (67.0%) by the top-performing random forest model. After re-training of the ML algorithms on the SA-Kaz peak intensity matrix, the accuracy of detection by the top-performing support vector machine with radial basis function kernel model was at 88.0%, 95.0%, and 78% for the Kazakhstan SARS-CoV-2+, NCARI, and AC subjects, respectively, with a SARS-CoV-2 vs rest receiver operating characteristic area under the curve of 0.983 [0.958, 0.987]; a high differentiation accuracy was maintained for the South American SARS-CoV-2 and NCARIs. MALDI-TOF MS/ML is a feasible approach for the differentiation of ARI without specialized sample preparation. The implementation of MALDI-TOF MS/ML in a real clinical lab setting will necessitate continuous optimization to keep up with the rapidly evolving landscape of ARI.IMPORTANCEIn this proof-of-concept study, the authors used matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and machine learning (ML) to identify and distinguish acute respiratory infections (ARI) caused by SARS-CoV-2 versus other pathogens in low-resource clinical settings, without the need for specialized sample preparation. The ML models were trained on a varied collection of MALDI-TOF MS spectra from studies conducted in Kazakhstan and South America. Initially, the MALDI-TOF MS/ML pipeline, trained exclusively on South American samples, exhibited diminished effectiveness in recognizing non-SARS-CoV-2 infections from Kazakhstan. Incorporation of spectral signatures from Kazakhstan substantially increased the accuracy of detection. These results underscore the potential of employing MALDI-TOF MS/ML in resource-constrained settings to augment current approaches for detecting and differentiating ARI.

Demographics, clinical characteristics, and outcomes in hospitalized patients during six waves of COVID‑19 in Northern Iran: a large cohort study

Since the first report of coronavirus disease 2019 (COVID-19) in Iran, our country has experienced several waves of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Northern Iran was one of the most affected regions of the country by COVID-19. In the current study, the demographic and clinical characteristics and outcomes of hospitalized patients were determined over a 2-year period (during six waves of SARS-CoV-2). This is a large cohort study investigating hospitalized patients with suspected and probable, and confirmed SARS-CoV-2 infection in Babol district, northern Iran, during the two years of COVID-19. The study population included patients admitted to four hospitals affiliated with Babol University of Medical Sciences between March 7, 2020 (start of the first wave) and March 20, 2022 (end of the sixth wave). Epidemiological and demographic characteristics, real-time PCR, cycle thresholds, clinical data and outcomes of COVID-19 were analyzed in 24,287 hospitalized patients. A total of 24,287 hospitalized patients were included in the study: 13,250 (46.6%) patients were suspected of having COVID-19, 11037(45.4%) were confirmed COVID-19 cases. The mean age of confirmed COVID-19 patients was 54.5 ± 18.9 years and 5961 (54%) were female. The median length of hospitalization for COVID-19 survivors and non-survivors was 5 (interquartile range [IQR] 4-8) and 7 (IQR 3-15) days, respectively. Of the patients with confirmed COVID-19, 714 (6.5%) died during hospitalization. In addition, the mortality rate from the first to the sixth wave was 22.9%, 8.1%, 9.9%, 6.8%, 2.7% and 3.5% in confirmed COVID-19 patients. The patients in the fifth wave were significantly younger than the others (mean age and SD of 51.1 ± 17.4 versus 59.2 ± 16.9, 54.7 ± 19.9, 58.4 ± 17.9, 53.5 ± 16.8 and 58.5 ± 25.1 years; p<0.001). The highest in-hospital mortality rate was 22.9% (126/551) in the first wave and the lowest in the fifth wave was 2.7% (96/3573) of cases. In conclusion, in the present study, the in-hospital mortality rate was 6.5% and more than half of the deceased patients were ≥65 years old. Male gender, advanced age and comorbidities significantly increased the mortality rate. The patients in the fifth wave were significantly younger than those in the other waves, and the lowest mortality rate and intensive care unit admission were also observed in the fifth wave.

The impact of Gam-COVID-Vac, an Adv5/Adv26 COVID-19 vaccine, on the biomarkers of endothelial function, coagulation and platelet activation

COVID-19 vaccines have played a critical role in controlling the COVID-19 pandemic. Although overall considered safe, COVID-19 vaccination has been associated with rare but severe thrombotic events, occurring mainly in the context of adenoviral vectored vaccines. A better understanding of mechanisms underlying vaccine-induced hypercoagulability and prothrombotic state is needed to improve vaccine safety profile. We assessed changes to the biomarkers of endothelial function (endothelin, ET-1), coagulation (thrombomodulin, THBD and plasminogen activator inhibitor, PAI) and platelet activation (platelet activating factor, PAF, and platelet factor 4 IgG antibody, PF4 IgG) within a three-week period after the first (prime) and second (boost) doses of Gam-Covid-Vac, an AdV5/AdV26-vectored COVID-19 vaccine. Blood plasma collected from vaccinees (n = 58) was assayed using ELISA assays. Participants were stratified by prior COVID-19 exposure based on their baseline SARS-CoV-2-specific serology results. We observed a significant post-prime increase in circulating ET-1, with levels sustained after the boost dose compared to baseline. ET-1 elevation following dose 2 was most pronounced in vaccinees without prior COVID-19 exposure. Prior COVID-19 was also associated with a mild increase in post-dose 1 PAI. Vaccination was associated with elevated ET-1 up to day 21 after the second vaccine dose, while no marked alterations to other biomarkers, including PF4 IgG, were seen. A role of persistent endothelial activation following COVID-19 vaccination warrants further investigation.

Characterization of viral pathogens associated with symptomatic upper respiratory tract infection in adults during a low COVID-19 transmission period

Background

The epidemiology of respiratory tract infections (RTI) has dramatically changed over the course of the COVID-19 pandemic. A major effort in the clinical management of RTI has been directed toward diagnosing COVID-19, while the causes of other, common community RTI often remain enigmatic. To shed light on the etiological causes of RTI during a low COVID-19 transmission period in 2021, we did a pilot study using molecular testing for virologic causes of upper RTI among adults with respiratory symptoms from Almaty, Kazakhstan.

Methods

Adults presenting at two public hospitals with respiratory symptoms were screened using SARS-CoV-2 PCR on nasopharyngeal swabs. A subset of RTI+, COVID-19-negative adults (n = 50) was then tested for the presence of common RTI viruses and influenza A virus (IAV). Next generation virome sequencing was used to further characterize the PCR-detected RTI pathogens.

Results

Of 1,812 symptomatic adults, 21 (1.2%) tested SARS-CoV-2-positive. Within the COVID-19 negative outpatient subset, 33/50 subjects (66%) had a positive PCR result for a common community RTI virus, consisting of human parainfluenza virus 3-4 (hPIV 3-4) in 25/50 (50%), rhinovirus (hRV) in 2 (4%), hPIV4-hRV co-infection in four (8%) and adenovirus or the OCR43/HKU-1 coronavirus in two (4%) cases; no IAV was detected. Virome sequencing allowed to reconstruct sequences of most PCR-identified rhinoviruses and hPIV-3/human respirovirus-3.

Conclusions

COVID-19 was cause to a low proportion of symptomatic RTI among adults. Among COVID-negative participants, symptomatic RTI was predominantly associated with hPIV and hRV. Therefore, respiratory viruses other than SARS-CoV-2 should be considered in the clinical management and prevention of adult RTI in the post-pandemic era.

A high scale SARS-CoV-2 profiling by its whole-genome sequencing using Oxford Nanopore Technology in Kazakhstan

Severe acute respiratory syndrome (SARS-CoV-2) is responsible for the worldwide pandemic, COVID-19. The original viral whole-genome was sequenced by a high-throughput sequencing approach from the samples obtained from Wuhan, China. Real-time gene sequencing is the main parameter to manage viral outbreaks because it expands our understanding of virus proliferation, spread, and evolution. Whole-genome sequencing is critical for SARS-CoV-2 variant surveillance, the development of new vaccines and boosters, and the representation of epidemiological situations in the country. A significant increase in the number of COVID-19 cases confirmed in August 2021 in Kazakhstan facilitated a need to establish an effective and proficient system for further study of SARS-CoV-2 genetic variants and the development of future Kazakhstan’s genomic surveillance program. The SARS-CoV-2 whole-genome was sequenced according to SARS-CoV-2 ARTIC protocol (EXP-MRT001) by Oxford Nanopore Technologies at the National Laboratory Astana, Kazakhstan to track viral variants circulating in the country. The 500 samples kindly provided by the Republican Diagnostic Center (UMC-NU) and private laboratory KDL “Olymp” were collected from individuals in Nur-Sultan city diagnosed with COVID-19 from August 2021 to May 2022 using real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR). All samples had a cycle threshold (Ct) value below 20 with an average Ct value of 17.03. The overall average value of sequencing depth coverage for samples is 244X. 341 whole-genome sequences that passed quality control were deposited in the Global initiative on sharing all influenza data (GISAID). The BA.1.1 (n = 189), BA.1 (n = 15), BA.2 (n = 3), BA.1.15 (n = 1), BA.1.17.2 (n = 1) omicron lineages, AY.122 (n = 119), B.1.617.2 (n = 8), AY.111 (n = 2), AY.126 (n = 1), AY.4 (n = 1) delta lineages, one sample B.1.1.7 (n = 1) belongs to alpha lineage, and one sample B.1.637 (n = 1) belongs to small sublineage were detected in this study. This is the first study of SARS-CoV-2 whole-genome sequencing by the ONT approach in Kazakhstan, which can be expanded for the investigation of other emerging viral or bacterial infections on the country level.

Sputnik-V reactogenicity and immunogenicity in the blood and mucosa: a prospective cohort study

Sputnik-V (Gam-COVID-Vac) is a heterologous, recombinant adenoviral (rAdv) vector-based, COVID-19 vaccine now used in > 70 countries. Yet there is a shortage of data on this vaccine's performance in diverse populations. Here, we performed a prospective cohort study to assess the reactogenicity and immunologic outcomes of Sputnik-V vaccination in Kazakhstan. COVID-19-free participants (n = 82 at baseline) were followed at day 21 after Sputnik-V dose 1 (rAd5) and dose 2 (rAd26). Self-reported local and systemic adverse events were captured using questionnaires. Blood and nasopharyngeal swabs were collected to perform SARS-CoV-2 diagnostic and immunologic assays. We observed that most of the reported adverse events were mild-to-moderate injection site or systemic reactions, no severe or potentially life-threatening conditions were reported, and dose 1 appeared to be more reactogenic than dose 2. The seroconversion rate was 97% post-dose 1, remaining the same post-dose 2. The proportion of participants with detectable virus neutralization was 83% post-dose 1, increasing to 98% post-dose 2, with the largest relative increase observed in participants without prior COVID-19 exposure. Dose 1 boosted nasal S-IgG and S-IgA, while the boosting effect of dose 2 on mucosal S-IgG, but not S-IgA, was only observed in subjects without prior COVID-19. Systemically, vaccination reduced serum levels of growth regulated oncogene (GRO), which correlated with an elevation in blood platelet count. Overall, Sputnik-V dose 1 elicited both blood and mucosal SARS-CoV-2 immunity, while the immune boosting effect of dose 2 was minimal. Thus, adjustments to the current vaccine dosing regimen are necessary to optimize immunization efficacy and cost-effectiveness. While Sputnik-V reactogenicity is similar to that of other COVID-19 vaccines, the induced alterations to the GRO/platelet axis warrant investigation of the vaccine's effects on systemic immunology.

High SARS-CoV-2 seroprevalence in Karaganda, Kazakhstan before the launch of COVID-19 vaccination

COVID-19 exposure in Central Asia appears underestimated and SARS-CoV-2 seroprevalence data are urgently needed to inform ongoing vaccination efforts and other strategies to mitigate the regional pandemic. Here, in a pilot serologic study we assessed the prevalence of SARS-CoV-2 antibody-mediated immunity in a multi-ethnic cohort of public university employees in Karaganda, Kazakhstan. Asymptomatic subjects (n = 100) were recruited prior to their first COVID-19 vaccination. Questionnaires were administered to capture a range of demographic and clinical characteristics. Nasopharyngeal swabs were collected for SARS-CoV-2 RT-qPCR testing. Serological assays were performed to detect spike (S)-reactive IgG and IgA and to assess virus neutralization. Pre-pandemic samples were used to validate the assay positivity thresholds. S-IgG and -IgA seropositivity rates among SARS-CoV-2 PCR-negative participants (n = 100) were 42% (95% CI [32.2-52.3]) and 59% (95% CI [48.8-69.0]), respectively, and 64% (95% CI [53.4-73.1]) of the cohort tested positive for at least one of the antibodies. S-IgG titres correlated with virus neutralization activity, detectable in 49% of the tested subset with prior COVID-19 history. Serologically confirmed history of COVID-19 was associated with Kazakh ethnicity, but not with other ethnic minorities present in the cohort, and self-reported history of respiratory illness since March 2020. Overall, SARS-CoV-2 exposure in this cohort was ~15-fold higher compared to the reported all-time national and regional COVID-19 prevalence, consistent with recent studies of excess infection and death in Kazakhstan. Continuous serological surveillance provides important insights into COVID-19 transmission dynamics and may be used to better inform the regional public health response.

Epidemiology, Clinico-Pathological Characteristics, and Comorbidities of SARS-CoV-2-Infected Pakistani Patients

SARS-CoV-2 is a causative agent for COVID-19 disease, initially reported from Wuhan, China. The infected patients experienced mild to severe symptoms, resulting in several fatalities due to a weak understanding of its pathogenesis, which is the same even to date. This cross-sectional study has been designed on 452 symptomatic mild-to-moderate and severe/critical patients to understand the epidemiology and clinical characteristics of COVID-19 patients with their comorbidities and response to treatment. The mean age of the studied patients was 58 ± 14.42 years, and the overall male to female ratio was 61.7 to 38.2%, respectively. In total, 27.3% of the patients had a history of exposure, and 11.9% had a travel history, while for 60% of patients, the source of infection was unknown. The most prevalent signs and symptoms in ICU patients were dry cough, myalgia, shortness of breath, gastrointestinal discomfort, and abnormal chest X-ray (p < 0.001), along with a high percentage of hypertension (p = 0.007) and chronic obstructive pulmonary disease (p = 0.029) as leading comorbidities. The complete blood count indicators were significantly disturbed in severe patients, while the coagulation profile and D-dimer values were significantly higher in mild-to-moderate (non-ICU) patients (p < 0.001). The serum creatinine (1.22 μmol L^-1; p = 0.016) and lactate dehydrogenase (619 μmol L^-1; p < 0.001) indicators were significantly high in non-ICU patients, while raised values of total bilirubin (0.91 μmol L^-1; p = 0.054), C-reactive protein (84.68 mg L^-1; p = 0.001), and ferritin (996.81 mg L^-1; p < 0.001) were found in ICU patients. The drug dexamethasone was the leading prescribed and administrated medicine to COVID-19 patients, followed by remdesivir, meropenem, heparin, and tocilizumab, respectively. A characteristic pattern of ground glass opacities, consolidation, and interlobular septal thickening was prominent in severely infected patients. These findings could be used for future research, control, and prevention of SARS-CoV-2-infected patients.

Demographics, clinical characteristics, and outcomes of 27,256 hospitalized COVID-19 patients in Kermanshah Province, Iran: a retrospective one-year cohort study

BACKGROUND

Since the first official report of SARS-CoV-2 infection in Iran on 19 February 2020, our country has been one of the worst affected countries by the COVID-19 epidemic in the Middle East. In addition to demographic and clinical characteristics, the number of hospitalized cases and deaths is an important factor for evidence-based decision-making and disease control and preparing the healthcare system to face the future challenges of COVID-19. Therefore, this cohort study was conducted to determine the demographics, clinical characteristics, and outcomes of hospitalized COVID-19 patients in Kermanshah Province, west of Iran.

METHODS

This multicenter retrospective cohort study included all suspected, probable, and confirmed cases of COVID-19 hospitalized in Kermanshah Province, Iran during the first year of the COVID-19 pandemic. Demographics, clinical characteristics, outcomes and other additional information of hospitalized patients were collected from the COVID-19 database of the Medical Care Monitoring Center (MCMC) of Kermanshah Province.

RESULTS

Kermanshah Province experienced three waves of COVID-19 infection considering the hospitalization and mortality rates between February 20, 2020 and February 19, 2021. A total of 27,256 patients were included in the study: 5203 (19.09%) subjects were suspected, 9136(33.52%) were probable, and 12,917 (47.39%) were confirmed COVID-19 cases. The mean age of the patients was 53.34 ± 22.74 years and 14,648 (53.74%) were male. The median length of hospital stay among COVID-19 survivors and non-survivors patients were 4 (interquartile range [IQR] 1-6) and 4 (IQR 1-8) days, respectively. Among patients with COVID-19, 2646 (9.71%) died during hospitalization. A multivariable logistic regression revealed that odds of death among patients ≥ 85 years was significantly greater than among patients < 15 years (adjusted odds ratio [aOR] 4.79, 95% confidence interval [CI] = 3.43-6.71, p≤ 0.001). Patients with one (aOR 1.38, 95% CI 1.21-1.59, p = 0.04), two (aOR 1.56, 95% CI 1.27-1.92, p = 0.001) or more (aOR 1.50, 95% CI 1.04-2.17, p = 0.03) comorbidities had higher odds of in-hospital death compared to those without comorbidities. The male sex (aOR 1.20, 95% CI 1.07- 1.35, p = 0.002), ICU admission (aOR 4.35, 95% CI 3.80-4.97, p < 0.001), intubation (aOR 11.09, 95% CI 9.58-12.84, p < 0.001), respiratory distress (aOR 1.40, 95% CI 1.22-1.61, p < 0.001), loss of consciousness (aOR 1.81, 95% CI 1.45-2.25, p < 0.001), anorexia (aOR 1.36, 95% CI 1.09-1.70, p = 0.006) and peripheral oxygen saturation (SpO2) < 93(aOR 2.72, 95% CI 2.34-3.16, p < 0.001) on admission were associated with increased risk of death in patients with SARS-CoV-2 infection. Having cough (aOR 0.82, 95% CI 0.72-0.93, p = 0.003) and headache (aOR 0.70, 95% CI 0.50-0.97, p = 0.03) decreased the odds of death.

CONCLUSION

The mortality rate of the patients admitted to the general wards and ICU can be a guide for allocating resources and making appropriate plans to provide better medical interventions during the COVID-19 pandemic. Several risk factors are associated with the in-hospital mortality of COVID-19, including advanced age, male sex, ICU admission, intubation, having comorbidity, SpO2 < 93, respiratory distress, loss of consciousness, headache, anorexia, and cough. These risk factors could help clinicians identify patients at high risk for death.

Sero-prevalence of SARS-CoV-2 in certain cities of Kazakhstan

Background and Aims

Seroprevalence studies are needed to determine the cumulative prevalence of SARS-CoV-2 infection and to develop pandemic mitigation strategies. Despite the constant monitoring and surveillance, the true level of infection in the population of Kazakhstan remains unknown. The aim of this study was to determine the sero-prevalence of SARS-CoV-2 in the main cities of Kazakhstan.

Methods

The research was conducted as a cluster-randomized cross-sectional national household study in three cities of Kazakhstan. The study covered the period: from October 24, 2020, to January 11, 2021. A total of 5739 people took part in the study. All participants agreed to be tested for antibodies to IgM/IgG. Demographic characteristics were analyzed. The presence of symptoms of respiratory diseases and the results of polymerase chain reaction (PCR) testing were determined. The antibodies to the SARS-CoV-2 virus were detected using the method of enzyme-linked immunosorbent assay (ELISA).

Results

There was significant geographic variability with a higher prevalence of IgG/IgM antibodies to SARS-CoV-2 in Almaty 57.0%, in Oskemen 60.7% than in Kostanay 39.4%. There were no significant differences in prevalence between men and women (p ≥ 0.05). In Almaty, only 19% of participants with antibodies reported the presence of respiratory symptoms during a pandemic. At the same time, the percentage of patients with antibodies who had respiratory symptoms was 36% in Oskemen and 27% in Kostanay.

Conclusion

The findings indicate that despite reasonable level of seroprevalence, the country has not yet reached the baseline minimum of herd immunity scores. The prevalence estimates for asymptomatic or subclinical forms of the disease ranged from 64% to 81%. Thus, given that almost half of the population of Kazakhstan remains vulnerable, the importance of preventive strategies such as social distancing, the use of medical masks, and vaccination to protect the population from the transmission of SARS-CoV-2 is highly critical.

Towards an Accurate Estimation of COVID-19 Cases in Kazakhstan: Back-Casting and Capture–Recapture Approaches

Background and Objectives: Coronavirus disease 19 (COVID-19) has emerged as the most devastating syndemic of the 21st century, with worrisome and sustained consequences for the entire society. Despite the relative success of vaccination programs, the global threat of the novel coronavirus SARS-CoV-2 is still present and further efforts are needed for its containment and control. Essential for its control and containment is getting closer to understanding the actual extent of SARS-CoV-2 infections. Material and Methods: We present a model based on the mortality data of Kazakhstan for the estimation of the underlying epidemic dynamic—with both the lag time from infection to death and the infection fatality rate. For the estimation of the actual number of infected individuals in Kazakhstan, we used both back-casting and capture–recapture methods. Results: Our results suggest that despite the increased testing capabilities in Kazakhstan, official case reporting undercounts the number of infections by at least 60%. Even though our count of deaths may be either over or underestimated, our methodology could be a more accurate approach for the following: the estimation of the actual magnitude of the pandemic; aiding the identification of different epidemiological values; and reducing data bias. Conclusions: For optimal epidemiological surveillance and control efforts, our study may lead to an increased awareness of the effect of COVID-19 in this region and globally, and aid in the implementation of more effective screening and diagnostic measures.

Mortality predictors of hospitalized patients with COVID-19: Retrospective cohort study from Nur-Sultan, Kazakhstan

BACKGROUND

First reported case of Severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) in Kazakhstan was identified in March 2020. Many specialized tertiary hospitals in Kazakhstan including National Research Cardiac Surgery Center (NRCSC) were re-organized to accept coronavirus disease 2019 (COVID-19) infected patients during summer months of 2020. Although many studies from worldwide reported their experience in treating patients with COVID-19, there are limited data available from the Central Asia countries. The aim of this study is to identify predictors of mortality associated with COVID-19 in NRCSC tertiary hospital in Nur-Sultan, Kazakhstan.

METHODS

This is a retrospective cohort study of patients admitted to the NRCSC between June 1st-August 31st 2020 with COVID-19. Demographic, clinical and laboratory data were collected from electronic records. In-hospital mortality was assessed as an outcome. Patients were followed-up until in-hospital death or discharge from the hospital. Descriptive statistics and factors associated with mortality were assessed using univariate and multivariate logistic regression models.

RESULTS

Two hundred thirty-nine admissions were recorded during the follow-up period. Mean age was 57 years and 61% were males. Median duration of stay at the hospital was 8 days and 34 (14%) patients died during the hospitalization. Non-survivors were more likely to be admitted later from the disease onset, with higher fever, lower oxygen saturation and increased respiratory rate compared to survivors. Leukocytosis, lymphopenia, anemia, elevated liver and kidney function tests, hypoproteinemia, elevated inflammatory markers (C-reactive protein (CRP), ferritin, and lactate dehydrogenase (LDH)) and coagulation tests (fibrinogen, D-dimer, international normalized ratio (INR), and activated partial thromboplastin time (aPTT)) at admission were associated with mortality. Age (OR 1.2, CI:1.01-1.43), respiratory rate (OR 1.38, CI: 1.07-1.77), and CRP (OR 1.39, CI: 1.04-1.87) were determined to be independent predictors of mortality.

CONCLUSION

This study describes 14% mortality rate from COVID-19 in the tertiary hospital. Many abnormal clinical and laboratory variables at admission were associated with poor outcome. Age, respiratory rate and CRP were found to be independent predictors of mortality. Our finding would help healthcare providers to predict the risk factors associated with high risk of mortality. Further investigations involving large cohorts should be provided to support our findings.

Predictive role of FAR ratio in COVID-19 patients

OBJECTIVE

No effective treatment has yet been found for SARS-Cov-2, which caused a pandemic outbreak in 2019. It is crucial to detect the progression of COVID-19 in patients as early as possible. Fibrinogen to albumin ratio (FAR) has been used as a new inflammatory marker. We aimed to find out whether the use of the FAR as a predictor of mortality in COVID-19 patients provides clinical benefit.

MATERIALS AND METHODS

Data from 590 patients with COVID-19 from March 15, 2020 to January 15, 2021 in medicine wards and intensive care units (ICU) were retrospectively analysed. Demographic data and other laboratory markers were collected from the electronic medical records. Relationship between FAR was investigated between patients in the survivor/non-survivor patients.

FINDINGS

The mean FAR levels in patients who were non-survivor was 24.44 ± 30.3 (n = 272 and 11.29 ± 6.29 (n = 275) (P = .000) in patients survivor COVID-19 infection. In ROC curve for FAR, the threshold FAR that may pose a risk for mortality was determined as 13.84 ((AUC: 0.808 (0.771-0.844)); 74.9% sensitivity, 74.6% specificity; P = .000)).

RESULT

As a result of this study, increased FAR were found to be important markers in determining the mortality levels in COVID-19 patients.

Home Management of the Device Detected Atrial Fibrillation during COVID-19 Pandemic: A Case Report

BACKGROUND: Patients with heart failure (HF) and implanted heart devices constitute a vulnerable category during the coronavirus disease –2019 (COVID-19) pandemic. The remote monitoring function allows the physician to detect atrial fibrillation (AF) in these patients and to prevent thromboembolic complications by prescribing anticoagulants. Under quarantine conditions, such patients can receive fully remote consultation and treatment, which will protect them from the risk of infection, and also reduce the burden on medical institutions. CASE REPORT: A 56-year-old man presented to the clinic with shortness of breath when climbing the second floor, moderate non-specific fatigue, general weakness, and a decrease in exercise tolerance. The patient received standard treatment for HF for at least 3 months (ACEI, beta blockers, MR antagonists, and loop diuretics) in individually selected adequate doses. ECG on admission showed a QRS of 150 ms, left bundle branch block (LBBB). Echo showed dilatation of all heart chambers, diffuse hypokinesis of the walls with akinesis of the apical, middle anterior LV segments, as well as hypokinesis of the basal, middle apical, and anterior septal segment of the LV. The ejection fraction was reduced to 35%. RV function is reduced. After a detailed discussion with the team, it was decided to do implantation of a cardioverter-defibrillator with resynchronization function, equipped with remote monitoring (Biotronik, and Home monitoring). Date of implantation is June 19, 2014. Due to the fact that the patient was connected to the remote monitoring system, May 5, 2020, he was diagnosed with asymptomatic AF. The episode lasted 1 min 22 s. On the following days of monitoring, episodes of AF were also recorded. The duration of the episodes ranged from a few seconds to 12 h/day. The patient received a doctor’s consultation through phone call, his risk of stroke was four when assessed using the CHA2DS2VASc scale. In treatment, it was recommended to add antiarrhythmic drugs (amiodarone 600 mg a day) and oral anticoagulants (rivaroxaban 20 mg × 1 time/day). Later, periodic IEGM showed absence of AF. CONCLUSION: In the context of the COVID-19 pandemic, health-care providers should rethink their approach to managing patients with implanted heart devices. Modern cardiovascular implantable electronic devices allow the physician to monitor the status of patients and immediately respond to situations requiring a change in treatment. Consultations can be carried out completely online.