Added value of chest CT images to a personalized prognostic model in acute respiratory distress syndrome: a retrospective study.

ABSTRACT:

Background

Acute respiratory distress syndrome (ARDS) is a critical disease in the intensive care unit (ICU) with high morbidity and mortality. The accuracy for predicting ARDS patients' outcome with mechanical ventilation is limited, and most based on clinical information.

Methods

The patients diagnosed with ARDS between January 2014 and June 2019 were retrospectively recruited. Radiomics features were extracted from the upper, middle, and lower levels of the lung, and were further analyzed with the primary outcome (28-day mortality after ARDS onset). The univariate and multivariate logistic regression analyses were applied to figure out risk factors. Various predictive models were constructed and compared.

Results

Of 366 ARDS patients recruited in this study, 276 (m

SUBMITTER: Wang YC 

PROVIDER: S-EPMC9884509 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature