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Evaluation of mortality predictors in hospitalized COVID-19 patients: Retrospective cohort study

Melahat Uzel Şener1, Murat Yıldız1, Suna Kavurgacı1

  • 1Clinic of Chest Diseases, University of Health Sciences, Atatürk Chest Diseases and Chest Surgery Training and Research Hospital, Ankara, Turkey.

Tuberkuloz Ve Toraks
|July 14, 2021
PubMed

Insights

Predicting COVID-19 mortality is crucial for treatment. Key risk factors for 30-day mortality in hospitalized patients include advanced age, heart failure, low oxygen saturation, high fever, and elevated ferritin levels.

Area of Science:

  • Infectious Diseases
  • Critical Care Medicine
  • Epidemiology

Background:

  • Accurate prognosis prediction in Coronavirus Disease 2019 (COVID-19) is essential for effective treatment strategies.
  • Identifying clinical, radiological, and laboratory parameters influencing mortality aids in risk stratification.
  • Understanding risk factors is vital for managing healthcare resources during the COVID-19 pandemic.

Purpose of the Study:

  • To identify clinical, radiological, and laboratory parameters that significantly affect 30-day mortality in COVID-19 patients.
  • To evaluate independent risk factors associated with mortality in hospitalized COVID-19 cases.
  • To inform treatment strategies and healthcare resource allocation based on prognostic indicators.

Main Methods:

  • A retrospective study included 360 patients hospitalized with COVID-19 in September 2020.
  • Clinical features, laboratory results, and radiological findings at admission were systematically recorded.
  • Statistical analysis, including multiple logistic regression, was employed to assess the relationship between parameters and 30-day mortality.

Main Results:

  • The overall 30-day mortality rate among the studied patients was 14.4%.
  • Independent risk factors identified for 30-day mortality included advanced age, presence of heart failure, low admission oxygen saturation, body temperature exceeding 38.2°C, and high ferritin levels.
  • These factors were significant predictors in the multiple logistic regression analysis.

Conclusions:

  • Clinical and laboratory markers are critical for orienting healthcare services and determining appropriate treatment strategies during the COVID-19 pandemic.
  • Early identification of high-risk patients based on parameters like age, comorbidities, and specific lab values can improve patient outcomes.
  • This study underscores the importance of a comprehensive assessment of clinical and laboratory data for effective COVID-19 patient management.
Abstract

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