Clinical characteristics and risk factors for mortality in patients with coronavirus disease 2019 in intensive care unit: a single- center, retrospective, observational study in China

Sai, Fangfang; Li, Lanyu; Yan, Ye; Zhu, Changqing; Ying, Hongmei; Huang, Conghua; Tian, Lei; Huang, Huan; Xu, Xinhui

doi:10.21037/apm-20-1575

Cited by 9 publications

(4 citation statements)

References 22 publications

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“…Pneumonia, multiorgan failure, and acute respiratory distress syndrome (ARDS), which can be fatal, are common symptoms in severe cases. Elderly people and those with underlying medical disorders, such as cardiovascular disease, diabetes, and respiratory illnesses, are especially vulnerable to severe forms of the illness, resulting in increased fatality rates within this population [3]. In the present study, comorbid conditions had no effect on the prognosis of COVID-19 patients.…”

Section: Discussioncontrasting

confidence: 45%

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Exploring the Relationship of Comorbidities, Smoking Status, HRCT Findings With COVID-19 Disease Severity and Outcomes

Khan Raja,

Rafique Shiekh,

Arshad Abbasi

et al. 2024

Cureus

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Introduction: Coronavirus disease 2019 (COVID-19) is a serious illness that can affect multiple organs including the lungs. The COVID-mortality risk is attributed to the quick transmission of the virus, the severity of disease, and preclinical risk factors, such as the presence of comorbidities. High-resolution computed tomography (HRCT) can predict disease severity in COVID-19 patients.Methodology: This was a retrospective cohort study in which data were obtained from COVID centers at tertiary care hospitals in Azad Jammu and Kashmir. Details of clinical characteristics and HRCT findings along with details of smoking and comorbid history were obtained.Results: Fever at hospital admission, HRCT findings, and having a partner predicted disease severity showed a significant p-value of <0.05. Old age and living in a combined household were associated with severe outcomes (p<0.05). Symptoms of shortness of breath (SOB) on hospital admission could predict the need for ICU admission in COVID-19 patients.Conclusion: HRCT has a good predictive value for disease severity in patients with COVID-19, and old age is a risk factor. Although, limited associations were established in the analysis, in this study hyperlipidemia and hypertension significantly affected the course of disease. Further studies should be done to explore the relationship.

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Section: Discussioncontrasting

confidence: 45%

“…The high risk of mortality associated with COVID-19 is partly due to the virus's propensity for rapid spread. The severity of illness in some people is another important factor that significantly affects mortality in COVID-19 patients [3]. Comorbidities are crucial for the development of severe diseases in COVID-19 patients [4,5].…”

Section: Introductionmentioning

confidence: 99%

Exploring the Relationship of Comorbidities, Smoking Status, HRCT Findings With COVID-19 Disease Severity and Outcomes

Khan Raja,

Rafique Shiekh,

Arshad Abbasi

et al. 2024

Cureus

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“…Some biomarkers, such as albumin, Lactate Dehydrogenase (LDH), Alanin Aminotransferase (ALT or SGPT), Aspartate Aminotransferase (AST or SGOT), Blood Urea Nitrogen (BUN), and Creatinine (Cr), have been associated with exacerbated outcomes in other viral infections. There is a tremendous research interest in investigating those factors in patients with COVID-19 [20,21].…”

Section: Introductionmentioning

confidence: 99%

Routine Laboratory Parameters as a Tool for Predicting Death in Patients With COVID-19

et al. 2022

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Background: The complexity of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) makes the clinical course of the disease develop rapidly, causing severe and deadly complications. Identifying effective laboratory biomarkers able to predicting patients based on their risk. This study aimed to look for those serobiomarkers in hospitalized patients with Coronavirus Disease 2019 (COVID‐19). Materials and Methods: In this retrospective observational study, 114 patients with COVID-19, admitted to Valian hospital in Aligudarz, City, Iran from October to December 2020 were examined. The disease outcome was followed along with the hospital course of every patient at the time of analysis. Laboratory investigations of all patients were monitored at the time of admission. A comparative analysis was done between the survivors (n=73) and non-survivors (n=41). Statistical analysis was conducted using SPSS. Results: Of the 114 patients, 40.4% (n=41) were non-survivor, and there were significant differences in Hemoglobin (Hb), Hematocrit (Hct), Platelet (PLT), Alkaline Phosphatase (ALP), Total Bilirubin, Fasting Blood Suger (FBS), Total Iron-Binding Capacity (TIBC), Lactate Dehydrogenase (LDH), Blood Urea Nitrogen (BUN), Creatinine (Cr), Albumin (ALB), and C-Reactive Protein (CRP) between survivors and non-survivors. Conclusion: The laboratory parameters have fundamental roles in poor prognosis and mortality prediction rated among patients with COVID-19 in the first admission. Thus, it is highly recommended to collaborate among hematologists, health managers, and clinical especialists.

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“…Scoring systems can be used for early identification of high-risk patients, accurate assessment of disease severity, prediction of disease progress and determination of patient specific treatment approach [ 16 , 18 , 44 , 45 ].…”

Section: Introductionmentioning

confidence: 99%

Comparison of Pneumonia Severity Indices, qCSI, 4C-Mortality Score and qSOFA in Predicting Mortality in Hospitalized Patients with COVID-19 Pneumonia

Akıllı

Bilge

Guz

et al. 2022

JPM

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This is a retrospective and observational study on 1511 patients with SARS-CoV-2, who were diagnosed with COVID-19 by real-time PCR testing and hospitalized due to COVID-19 pneumonia. 1511 patients, 879 male (58.17%) and 632 female (41.83%) with a mean age of 60.1 ± 14.7 were included in the study. Survivors and non-survivors groups were statistically compared with respect to survival, discharge, ICU admission and in-hospital death. Although gender was not statistically significant different between two groups, 80 (60.15%) of the patients who died were male. Mean age was 72.8 ± 11.8 in non-survivors vs. 59.9 ± 14.7 in survivors (p < 0.001). Overall in-hospital mortality was found to be 8.8% (133/1511 cases), and overall ICU admission was 10.85% (164/1511 cases). The PSI/PORT score of the non-survivors group was higher than that of the survivors group (144.38 ± 28.64 versus 67.17 ± 25.63, p < 0.001). The PSI/PORT yielding the highest performance was the best predictor for in-hospital mortality, since it incorporates the factors as advanced age and comorbidity (AUROC 0.971; % 95 CI 0.961–0.981). The use of A-DROP may also be preferred as an easier alternative to PSI/PORT, which is a time-consuming evaluation although it is more comprehensive.

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Clinical characteristics and risk factors for mortality in patients with coronavirus disease 2019 in intensive care unit: a single- center, retrospective, observational study in China

Cited by 9 publications

References 22 publications

Exploring the Relationship of Comorbidities, Smoking Status, HRCT Findings With COVID-19 Disease Severity and Outcomes

Exploring the Relationship of Comorbidities, Smoking Status, HRCT Findings With COVID-19 Disease Severity and Outcomes

Routine Laboratory Parameters as a Tool for Predicting Death in Patients With COVID-19

Comparison of Pneumonia Severity Indices, qCSI, 4C-Mortality Score and qSOFA in Predicting Mortality in Hospitalized Patients with COVID-19 Pneumonia

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