SARS-CoV-2 PCR-positive and PCR-negative cases of pneumonia admitted to the hospital during the peak of COVID-19 pandemic: analysis of in-hospital and post-hospital mortality

Gaipov, Abduzhappar; Gusmanov, Arnur; Abbay, Anara; Sakko, Yesbolat; Kadyrzhanuly, Kainar; Yermakhanova, Zhanar; Aliyeva, Lazzat; Kashkynbayev, Ardak; Moldaliyev, Iklas; Crape, Byron; Sarría‐Santamera, Antonio

doi:10.1186/s12879-021-06154-z

Cited by 15 publications

(15 citation statements)

References 31 publications

(18 reference statements)

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“…This study is limited by the small sample size, missing data for some variables and high proportion of cases not confirmed by PCR. Recent study from Kazakhstan also reported the 85% of SARS-CoV-2 PCR negative cases of pneumonia during the peak of COVID-19 infection [ 25 ]. In addition, the study was conducted in a very specialized tertiary hospital, which limits generalizability of the results.…”

Section: Discussionmentioning

confidence: 99%

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

Pya¹,

Bekbossynova²,

Gaipov

et al. 2021

PLoS ONE

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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.

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Section: Discussionmentioning

confidence: 99%

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

Pya¹,

Bekbossynova²,

Gaipov

et al. 2021

PLoS ONE

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“…One additional report by Gaipov et al [27] identified a 24% higher risk of death in males than females and older patients compared to younger ones. In addition, patients residing in rural areas had a 66% higher risk of death than city residents and being treated in a provisional hospital was associated with 1.9-fold increased mortality compared to those treated in infectious disease hospitals.…”

Section: Discussionmentioning

confidence: 97%

Survival of COVID-19 with Multimorbidity Patients

et al. 2021

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Background: The outbreak of SARS-CoV-2 abruptly disseminated in early 2020, overcoming the capacity of health systems to respond the pandemic. It was not until the vaccines were launched worldwide that an increase in survival was observed. The objectives of this study were to analyse the characteristics of survivors and their relationship with comorbidities. We had access to a database containing information on 16,747 hospitalized patients from Mexico, all infected with SARS-CoV-2, as part of a regular follow-up. The descriptive analysis looked for clusters of either success or failure. We categorized the samples into no comorbidities, or one and up to five coexisting with the infection. We performed a logistic regression test to ascertain what factors were more influential in survival. The main variable of interest was survival associated with multimorbidity factors. The database hosted information on hospitalized patients from Mexico between March 2020 through to April 2021. Categories 2 and 3 had the largest number of patients. Survival rates were higher in categories 0 (64.8%), 1 (57.5%) and 2 (51.6%). In total, 1741 (10.5%) patients were allocated to an ICU unit. Mechanical ventilators were used on 1415 patients, corresponding to 8.76%. Survival was recorded in 9575 patients, accounting for 57.2% of the sample population. Patients without comorbidities, younger people and women were more likely to survive.

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“…COVID-19 remains a global public health concern and is especially pernicious in regions with limited public health infrastructure that suffer from inadequate epidemiologic surveillance and delayed implementation of pandemic countermeasures. In the Central Asian states, such as Kazakhstan, substantial underestimations (of ~14-fold) of COVID-19 incidence and associated mortality [ 1 – 3 ] have led to public distrust and slow uptake of public health measures, including vaccination [ 4 ]. To date, the extent of community exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Kazakhstan is incompletely understood.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, as of 7 August 2021 (when analysis presented in this work was completed [ 5 ]), the officially reported number of all-time COVID-19 cases in Kazakhstan was 689,402 (626,402 of which were PCR-confirmed, while the rest were diagnosed based on clinical disease manifestations). These figures represented a cumulative prevalence of ~3.7% [ 6 ]- a prevalence that appears low given the substantial excess of infections and mortality estimated for Kazakhstan consistent with COVID-19 [ 2 , 3 ].…”

Section: Introductionmentioning

confidence: 99%

“…Similar to its neighbouring Central Asian and Eastern European states, Kazakhstan’s healthcare and vital registration systems have struggled to keep a consistent tally of COVID-19 incidence and mortality. This was especially evident at the onset of the pandemic in Spring-Summer of 2020 when cases were counted solely if COVID-19 was identified as the main cause of hospitalization and/or death, resulting in a significant undercounting of undiagnosed pneumonia cases, which most likely were COVID-19-associated [ 1 , 3 , 8 ].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2022

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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.

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SARS-CoV-2 PCR-positive and PCR-negative cases of pneumonia admitted to the hospital during the peak of COVID-19 pandemic: analysis of in-hospital and post-hospital mortality

Cited by 15 publications

References 31 publications

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

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

Survival of COVID-19 with Multimorbidity Patients

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

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