Dataset Information

Factors Defining the Development of Severe Illness in Patients with COVID-19: A Retrospective Study.

ABSTRACT:

Objective

Early triage of patients with coronavirus disease 2019 (COVID-19) is pivotal in managing the disease. However, studies on the clinical risk score system of the risk factors for the development of severe disease are limited. Hence, we conducted a clinical risk score system for severe illness, which might optimize appropriate treatment strategies.

Methods

We conducted a retrospective, single-center study at the JinYinTan Hospital from January 24, 2020 to March 31, 2020. We evaluated the demographic, clinical, and laboratory data and performed a 10-fold cross-validation to split the data into a training set and validation set. We then screened the prognostic factors for severe illness using the least absolute shrinkage and selection operator (LASSO) and logistic regression, and finally conducted a risk score to estimate the probability of severe illness in the training set. Data from the validation set were used to validate the score.

Results

A total of 295 patients were included. From 49 potential risk factors, 3 variables were measured as the risk score: neutrophil to lymphocyte ratio ( OR, 1.27; 95% CI, 1.15-1.39), albumin ( OR, 0.76; 95% CI, 0.70-0.83), and chest computed tomography abnormalities ( OR, 2.01; 95% CI, 1.41-2.86) and the AUC of the validation cohort was 0.822 (95% CI, 0.7667-0.8776).

Conclusion

This report may help define the potential of developing severe illness in patients with COVID-19 at an early stage, which might be related to the neutrophil to lymphocyte ratio, albumin, and chest computed tomography abnormalities.

SUBMITTER: Xiong YB

PROVIDER: S-EPMC8747433 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Publications

Factors Defining the Development of Severe Illness in Patients with COVID-19: A Retrospective Study.

Xiong Yi Bai YB Tian Ya Xin YX Ma Yan Y Yang Wei W Liu Bin B Ruan Lian Guo LG Lu Cheng C Huang Lu Qi LQ

Biomedical and environmental sciences : BES 20211201 12

<h4>Objective</h4>Early triage of patients with coronavirus disease 2019 (COVID-19) is pivotal in managing the disease. However, studies on the clinical risk score system of the risk factors for the development of severe disease are limited. Hence, we conducted a clinical risk score system for severe illness, which might optimize appropriate treatment strategies.<h4>Methods</h4>We conducted a retrospective, single-center study at the JinYinTan Hospital from January 24, 2020 to March 31, 2020. We ...[more]

PMID: 34981721

Similar Datasets

Project description:BackgroundThe Covid-19 pandemic threatens to overwhelm scarce clinical resources. Risk factors for severe illness must be identified to make efficient resource allocations.ObjectiveTo evaluate risk factors for severe illness.DesignRetrospective, observational case series.SettingSingle-institution.ParticipantsFirst 117 consecutive patients hospitalized for Covid-19 from March 1 to April 12, 2020.ExposureNone.Main outcomes and measuresIntensive care unit admission or death.ResultsIn-hospital mortality was 24.8% and average total length of stay was 11.82 days (95% CI: 10.01 to 13.63 days). 30.8% of patients required intensive care unit admission and 29.1% required mechanical ventilation. Multivariate regression identified the amount of supplemental oxygen required at admission (OR: 1.208, 95% CI: 1.011-1.443, p = .037), sputum production (OR: 6.734, 95% CI: 1.630-27.812, p = .008), insulin dependent diabetes mellitus (OR: 11.873, 95% CI: 2.218-63.555, p = .004) and chronic kidney disease (OR: 4.793, 95% CI: 1.528-15.037, p = .007) as significant risk factors for intensive care unit admission or death. Of the 48 patients who were admitted to the intensive care unit or died, this occurred within 3 days of arrival in 42%, within 6 days in 71%, and within 9 days in 88% of patients.ConclusionsAt our regional medical center, patients with Covid-19 had an average length of stay just under 12 days, required ICU care in 31% of cases, and had a 25% mortality rate. Patients with increased sputum production and higher supplemental oxygen requirements at admission, and insulin dependent diabetes or chronic kidney disease may be at increased risk for severe illness. A model for predicting intensive care unit admission or death with excellent discrimination was created that may aid in treatment decisions and resource allocation. Early identification of patients at increased risk for severe illness may lead to improved outcomes in patients hospitalized with Covid-19.

Dataset Information

Factors Defining the Development of Severe Illness in Patients with COVID-19: A Retrospective Study.

Objective

Methods

Results

Conclusion

Publications

Factors Defining the Development of Severe Illness in Patients with COVID-19: A Retrospective Study.

Similar Datasets

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