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. 2022 Aug 15:9:958291.
doi: 10.3389/fmed.2022.958291. eCollection 2022.

Calibration and validation of the Pneumonia Shock Score in critically ill patients with SARS-CoV-2 infection, a multicenter prospective cohort study

Thomas A Carmo  1   2   3 , Isabella B B Ferreira  2   3 , Rodrigo C Menezes  2   3   4   5 , Márcio L T Pina  3 , Roberto S Oliveira  3 , Gabriel P Telles  3 , Antônio F A Machado  1 , Tércio C Aguiar  1 , Juliana R Caldas  6 , María B Arriaga  2   4   5 , Kevan M Akrami  2   4   5   7 , Nivaldo M Filgueiras Filho  1   8 , Bruno B Andrade  1   2   3   5
Affiliations

Calibration and validation of the Pneumonia Shock Score in critically ill patients with SARS-CoV-2 infection, a multicenter prospective cohort study

Thomas A Carmo et al. Front Med (Lausanne). .

Abstract

Background: Prognostic tools developed to stratify critically ill patients in Intensive Care Units (ICUs), are critical to predict those with higher risk of mortality in the first hours of admission. This study aims to evaluate the performance of the pShock score in critically ill patients admitted to the ICU with SARS-CoV-2 infection.

Methods: Prospective observational analytical cohort study conducted between January 2020 and March 2021 in four general ICUs in Salvador, Brazil. Descriptive statistics were used to characterize the cohort and a logistic regression, followed by cross-validation, were performed to calibrate the score. A ROC curve analysis was used to assess accuracy of the models analyzed.

Results: Six hundred five adult ICU patients were included in the study. The median age was 63 (IQR: 49-74) years with a mortality rate of 33.2% (201 patients). The calibrated pShock-CoV score performed well in prediction of ICU mortality (AUC of 0.80 [95% Confidence Interval (CI): 0.77-0.83; p-value < 0.0001]).

Conclusions: The pShock-CoV score demonstrated robust discriminatory capacity and may assist in targeting scarce ICU resources during the COVID-19 pandemic to those critically ill patients most likely to benefit.

Keywords: COVID-19; critical care; mortality; prognosis; risk factors.

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Conflict of interest statement

Authors TC, IF, RM, MA, KA, and BA were employed by fellows from Multinational Organization Network Sponsoring Translational and Epidemiological Research Initiative. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flow chart of study enrollment and analyzed population.
Figure 2
Figure 2
General study population description and Calibration of pShock-CoV score. (A) Scatter plots depicting the distribution of age, hematocrit, leukocytes, urea, lowest Glasgow coma score, highest respiratory rate and highest FiO2 in non-survivors and survivors. Lines represent median and interquartile range values. The Mann-Whitney U test was employed to compare the values detected between the study groups. Use of vasopressors and use of mechanical ventilation variables are shown as frequency (%) and compared using the Fisher's exact test. (B) Adjusted and unadjusted binary regression model for ICU mortality. Multivariable regression adjusted for differences in baseline characteristics (variables of p ≤ 0.05 identified in univariable analysis).
Figure 3
Figure 3
Discrimation of pShock-CoV in critically ill patients with SARS-CoV-2 infection and comparison with other severity models. (A) Receiver operating characteristic (ROC) curve analysis of pShock-CoV for prediction of ICU mortality in the ICU original sample and comparison of area under the ROC curve (Δ AUC) with pShock in the derivation cohort. (B) Overlap between ROC curves showing pShock-CoV performance and comparing with CURB-65 and qSOFA in COVID patients. Differences between AUC-ROCS were accessed by the DeLong test.
Figure 4
Figure 4
Discrimation of pShock-CoV over prediction of 30-day mortality for patients with COVID in ICU and comparison with other severity models. (A) Perfomance of the pShock-CoV score in predicting 30-day mortality in the intensive care unit, and comparison with discrimination capacity for overall mortality. (B) Comparison pShock-CoV with CURB-65 and qSOFA for prediction of ICU 30-day mortality in COVID patients. Differences between AUC-ROCS were accessed by the DeLong test.
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