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

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0261272
Author(s):  
Yuriy Pya ◽  
Makhabbat Bekbossynova ◽  
Abduzhappar Gaipov ◽  
Timur Lesbekov ◽  
Timur Kapyshev ◽  
...  
Keyword(s):  
Cohort Study ◽  
Respiratory Rate ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Laboratory Data ◽  
Disease Onset ◽  
Tertiary Hospital ◽  
Hospital Death ◽  
Factors Associated ◽  
Predictors Of Mortality

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.

scholarly journals Characteristics, outcomes and risk factors for mortality of 522 167 patients hospitalised with COVID-19 in Brazil: a retrospective cohort study

BMJ Open ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. e049089
Author(s):  
Marcia C Castro ◽  
Susie Gurzenda ◽  
Eduardo Marques Macário ◽  
Giovanny Vinícius A França
Keyword(s):  
Risk Factors ◽  
Cohort Study ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Cox Proportional Hazards ◽  
Secondary Outcome ◽  
Hospital Death ◽  
Factors Associated ◽  
Icu Admission ◽  
Hospitalised Patients

ObjectiveTo provide a comprehensive description of demographic, clinical and radiographic characteristics; treatment and case outcomes; and risk factors associated with in-hospital death of patients hospitalised with COVID-19 in Brazil.DesignRetrospective cohort study of hospitalised patients diagnosed with COVID-19.SettingData from all hospitals across Brazil.Participants522 167 hospitalised patients in Brazil by 14 December 2020 with severe acute respiratory illness, and a confirmed diagnosis for COVID-19.Primary and secondary outcome measuresPrevalence of symptoms and comorbidities was compared by clinical outcomes and intensive care unit (ICU) admission status. Survival was assessed using Kaplan Meier survival estimates. Risk factors associated with in-hospital death were evaluated with multivariable Cox proportional hazards regression.ResultsOf the 522 167 patients included in this study, 56.7% were discharged, 0.002% died of other causes, 30.7% died of causes associated with COVID-19 and 10.2% remained hospitalised. The median age of patients was 61 years (IQR, 47–73), and of non-survivors 71 years (IQR, 60–80); 292 570 patients (56.0%) were men. At least one comorbidity was present in 64.5% of patients and in 76.8% of non-survivors. From illness onset, the median times to hospital and ICU admission were 6 days (IQR, 3–9) and 7 days (IQR, 3–10), respectively; 15 days (IQR, 9–24) to death and 15 days (IQR, 11–20) to hospital discharge. Risk factors for in-hospital death included old age, Black/Brown ethnoracial self-classification, ICU admission, being male, living in the North and Northeast regions and various comorbidities. Age had the highest HRs of 5.51 (95% CI: 4.91 to 6.18) for patients≥80, compared with those ≤20.ConclusionsCharacteristics of patients and risk factors for in-hospital mortality highlight inequities of COVID-19 outcomes in Brazil. As the pandemic continues to unfold, targeted policies that address those inequities are needed to mitigate the unequal burden of COVID-19.

scholarly journals Admission biochemical test associated with the prognosis of COVID-19: a multi-centered retrospective cohort study

2020 ◽  
Author(s):  
Qi Long ◽  
Chen-liang Zhou ◽  
Ye-ming Wang ◽  
Bin Song ◽  
Xiao-bin Cheng ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cohort Study ◽  
Blood Glucose ◽  
Regression Model ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Fasting Blood Glucose ◽  
Biochemical Test ◽  
Hospital Death ◽  
Factors Associated

Abstract Objectives: Since December 2019, a outbreak of Corona Virus Disease-2019(COVID-19) started in Wuhan, China. Now we comprehended much more about the troublesome disease from studies than the beginning. But more details between admission laboratory test and prognosis of COVID-19 were still confusing. So we focused on the admission biochemical test, and tried to verify their influence to the prognosis of COVID-19.Method: 522 patients from 4 hospitals were enrolled in this retrospective cohort study. We collected demographic information, comorbidities and laboratory biochemical indicators, then compared them between survivors’ and nonsurvivors’ group. Logistic regression methods were used to explore the risk factors associated with in-hospital death. Linear regression and receiver operating characteristic curve(ROC-curve) was applied to assess the efficiency of risk factors and regression model.Results:Age of nonsurvivors’ group(68.9) was older than survivors group(50.0). Diabetes(68.7%) was the most common comorbidity in the nonsurvivors’ group. In univariate regression analysis, most biochemical tests were related to the mortality except lipid metabolic results. Age, fasting blood glucose and blood urea nitrogen(BUN) were with a p-value less than 0.001 in multivariate regression model.Conclusion:Age, BUN and fasting blood glucose were risk factors associated with the prognosis of COVID-19 related pneumonia.Authors Qi Long, Chen-liang Zhou, Ye-ming Wang, Bin Song, Xiao-bin Cheng, Qiu-fen Dong, and Liu-lin Wang contributed equally to this work.

scholarly journals 387. Markers for Mortality in COVID-19 Patients with Atrial Fibrillation or Flutter

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S262-S262
Author(s):  
Kok Hoe Chan ◽  
Bhavik Patel ◽  
Iyad Farouji ◽  
Addi Suleiman ◽  
Jihad Slim
Keyword(s):  
Atrial Fibrillation ◽  
Logistic Regression ◽  
Cohort Study ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Prognostic Markers ◽  
Univariate Analysis ◽  
Laboratory Data ◽  
Significant Difference ◽  
New Onset

Abstract Background Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection can lead to many different cardiovascular complications, we were interested in studying prognostic markers in patients with atrial fibrillation/flutter (A. Fib/Flutter). Methods A retrospective cohort study of patients with confirmed COVID-19 and either with existing or new onset A. Fib/Flutter who were admitted to our hospital between March 15 and May 20, 2020. Demographic, outcome and laboratory data were extracted from the electronic medical record and compared between survivors and non-survivors. Univariate and multivariate logistic regression were employed to identify the prognostic markers associated with mortality in patients with A. Fib/Flutter Results The total number of confirmed COVID-19 patients during the study period was 350; 37 of them had existing or new onset A. Fib/Flutter. Twenty one (57%) expired, and 16 (43%) were discharged alive. The median age was 72 years old, ranged from 19 to 100 years old. Comorbidities were present in 33 (89%) patients, with hypertension (82%) being the most common, followed by diabetes (46%) and coronary artery disease (30%). New onset of atrial fibrillation was identified in 23 patients (70%), of whom 13 (57%) expired; 29 patients (78%) presented with atrial fibrillation with rapid ventricular response, and 2 patients (5%) with atrial flutter. Mechanical ventilation was required for 8 patients, of whom 6 expired. In univariate analysis, we found a significant difference in baseline ferritin (p=0.04), LDH (p=0.02), neutrophil-lymphocyte ratio (NLR) (p=0.05), neutrophil-monocyte ratio (NMR) (p=0.03) and platelet (p=0.015) between survivors and non-survivors. With multivariable logistic regression analysis, the only value that had an odds of survival was a low NLR (odds ratio 0.74; 95% confidence interval 0.53–0.93). Conclusion This retrospective cohort study of hospitalized patients with COVID-19 demonstrated an association of increase NLR as risk factors for death in COVID-19 patients with A. Fib/Flutter. A high NLR has been associated with increased incidence, severity and risk for stroke in atrial fibrillation patients but to our knowledge, we are first to demonstrate the utilization in mortality predictions in COVID-19 patients with A. Fib/Flutter. Disclosures Jihad Slim, MD, Abbvie (Speaker’s Bureau)Gilead (Speaker’s Bureau)Jansen (Speaker’s Bureau)Merck (Speaker’s Bureau)ViiV (Speaker’s Bureau)

scholarly journals Clinical characteristics and outcome of influenza virus infection among adults hospitalized with severe COVID-19: a retrospective cohort study from Wuhan, China

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xunliang Tong ◽  
Xiaomao Xu ◽  
Guoyue Lv ◽  
He Wang ◽  
Anqi Cheng ◽  
...  
Keyword(s):  
Influenza Virus ◽  
Cohort Study ◽  
Clinical Features ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Cox Regression ◽  
Influenza Virus Infection ◽  
Chronic Respiratory Disease ◽  
Hospital Death ◽  
New City

Abstract Background Coronavirus disease 2019 (COVID-19) is an emerging infectious disease that rapidly spreads worldwide and co-infection of COVID-19 and influenza may occur in some cases. We aimed to describe clinical features and outcomes of severe COVID-19 patients with co-infection of influenza virus. Methods Retrospective cohort study was performed and a total of 140 patients with severe COVID-19 were enrolled in designated wards of Sino-French New City Branch of Tongji Hospital between Feb 8th and March 15th in Wuhan city, Hubei province, China. The demographic, clinical features, laboratory indices, treatment and outcomes of these patients were collected. Results Of 140 severe COVID-19 hospitalized patients, including 73 patients (52.14%) with median age 62 years were influenza virus IgM-positive and 67 patients (47.86%) with median age 66 years were influenza virus IgM-negative. 76 (54.4%) of severe COVID-19 patients were males. Chronic comorbidities consisting mainly of hypertension (45.3%), diabetes (15.8%), chronic respiratory disease (7.2%), cardiovascular disease (5.8%), malignancy (4.3%) and chronic kidney disease (2.2%). Clinical features, including fever (≥38 °C), chill, cough, chest pain, dyspnea, diarrhea and fatigue or myalgia were collected. Fatigue or myalgia was less found in COVID-19 patients with IgM-positive (33.3% vs 50/7%, P = 0.0375). Higher proportion of prolonged activated partial thromboplastin time (APTT) > 42 s was observed in COVID-19 patients with influenza virus IgM-negative (43.8% vs 23.6%, P = 0.0127). Severe COVID-19 Patients with influenza virus IgM positive have a higher cumulative survivor rate than that of patients with influenza virus IgM negative (Log-rank P = 0.0308). Considering age is a potential confounding variable, difference in age was adjusted between different influenza virus IgM status groups, the HR was 0.29 (95% CI, 0.081–1.100). Similarly, difference in gender was adjusted as above, the HR was 0.262 (95% CI, 0.072–0.952) in the COX regression model. Conclusions Influenza virus IgM positive may be associated with decreasing in-hospital death.

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