Dataset Information

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 (median age, 64 years [interquartile range, 54-75 years]; 208 male) survive on the Day 28. Among all factors, the APACHE II Score (OR 2.607, 95% CI 1.896-3.584, P < 0.001), the Radiomics_Score of the middle lung (OR 2.230, 95% CI 1.387-3.583, P = 0.01), the Radiomics_Score of the lower lung (OR 1.633, 95% CI 1.143-2.333, P = 0.01) were associated with the 28-day mortality. The clinical_radiomics predictive model (AUC 0.813, 95% CI 0.767-0.850) show the best performance compared with the clinical model (AUC 0.758, 95% CI 0.710-0.802), the radiomics model (AUC 0.692, 95% CI 0.641-0.739) and the various ventilator parameter-based models (highest AUC 0.773, 95% CI 0.726-0.815).

Conclusions

The radiomics features of chest CT images have incremental values in predicting the 28-day mortality in ARDS patients with mechanical ventilation.

Supplementary information

The online version contains supplementary material available at 10.1007/s42058-023-00116-x.

SUBMITTER: Wang YC

PROVIDER: S-EPMC9884509 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Publications

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

Wang Yuan-Cheng YC Zhang Shu-Hang SH Lv Wen-Hui WH Wang Wei-Lang WL Huang Shan S Qiu Yue Y Xie Jian-Feng JF Yang Yi Y Ju Shenghong S

Chinese journal of academic radiology 20230129 1

<h4>Background</h4>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.<h4>Methods</h4>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 furth ...[more]

PMID: 36741827

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Dataset Information

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

Background

Methods

Results

Conclusions

Supplementary information

Publications

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

Similar Datasets

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