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Observational Study
. 2022 May-Jun:53:1-10.
doi: 10.1016/j.hrtlng.2022.01.013. Epub 2022 Jan 24.

Clinical and laboratory predictors at ICU admission affecting course of illness and mortality rates in a tertiary COVID-19 center

Andrea Kukoč  1 , Antonija Mihelčić  1 , Ivan Miko  1 , Andrea Romić  1 , Marko Pražetina  1 , Danijela Tipura  1 , Željka Drmić  1 , Marcela Čučković  1 , Maja Ćurčić  1 , Vanja Blagaj  1 , Hrvoje Lasić  1 , Emil Dolenc  1 , Sonja Hleb  1 , Hani Almahariq  1 , Jasminka Peršec  2 , Andrej Šribar  2
Affiliations
Observational Study

Clinical and laboratory predictors at ICU admission affecting course of illness and mortality rates in a tertiary COVID-19 center

Andrea Kukoč et al. Heart Lung. 2022 May-Jun.

Abstract

Background: Survival rates of critically ill COVID-19 patients are affected by various clinical features and laboratory parameters at ICU admission. Some of these predictors are universal but others may be population specific.

Objective: To determine utility of baseline clinical and laboratory parameters in a multivariate regression model to predict outcomes in critically ill COVID-19 patients in a tertiary hospital in Croatia.

Methods: 692 critically ill COVID-19 patients treated during a 10-month period were included in this retrospective observational trial to assess the risk factors determining mortality rates. Various anthropometric features, comorbidities, laboratory parameters, clinical features and therapeutic interventions were included in the analysis. ICU mortality rates and length of ICU stay were primary endpoints analyzed in this study.

Results: After multivariate adjustment, only the SOFA score, PaO2/FiO2 and history of arterial hypertension had an effect on ICU mortality, as well as the need to initiate invasive mechanical ventilation. Increase in PaO2/FiO2 over the first 7 days was present in survivors, while reverse applied to SOFA. Length of ICU stay was 9 (4-14) days. Factors affecting survival times were admission from wards, congestive heart failure, invasive mechanical ventilation, bacterial superinfections, age > 75 years, SOFA score, and serum ferritin, CRP and IL-6 values at ICU admission.

Conclusion: Elevated inflammatory biomarkers and SOFA score at ICU admission were detected as significant predictors of ICU mortality in this cohort, while initiation of invasive mechanical ventilation is the most relevant interventional mortality risk factor in critically ill COVID-19 patients.

Keywords: COVID-19; Critical care; Risk factors; Survival analysis.

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Conflict of interest statement

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. On behalf of the authors: Andrea Kukoč, Antonija Mihelčić, Ivan Miko, Andrea Romić, Marko Pražetina, Danijela Tipura, Željka Drmić, Marcela Čučković, Maja Ćurčić, Vanja Blagaj, Hrvoje Lasić, Emil Dolenc, Sonja Hleb, Hani Almahariq, Jasminka Peršec, Andrej Šribar Corresponding author: Andrej Šribar, MD, PhD

Figures

Fig. 1
Fig. 1
Sankey plot depicting distribution and outcomes of patients treated in the ICU according to their origin of admission.
Fig. 2
Fig. 2
Sankey plot depicting relationship and distribution between patients receiving HFNO, IMV and their survival rates.
Fig. 3
Fig. 3
Forest plot depicting odds-ratios and 95% confidence intervals of survival risk factors present at ICU admission.
Fig. 4
Fig. 4
differences in change of PaO2/FiO2 and SOFA over time in survivors and non-survivors. Estimated marginal means with 95% confidence intervals as error bars.
Fig. 5
Fig. 5
Forest plot depicting odds ratios and 95% confidence intervals of therapeutic interventions and complications during ICU stay.
Fig. 6
Fig. 6
Hazard regression plot depicting hazard ratios and 95% confidence interval for ICU survival time.
Fig. 7
Fig. 7
Kaplan-Meier plot depicting adjusted survival curve after multivariate adjustment for age groups.
Fig. 8
Fig. 8
Kaplan-Meier plot depicting adjusted survival curve after multivariate adjustment for mechanically ventilated patients.
Fig. 9
Fig. 9
Kaplan-Meier plot depicting adjusted survival curve after multivariate adjustment for patients with bacterial superinfections.
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