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INTRODUCTION: Within primary ARDS, SARS-CoV-2-associated ARDS (C-ARDS) emerged in late 2019, reaching its peak during the subsequent two years. Recent efforts in ARDS research have concentrated on phenotyping this heterogeneous syndrome to enhance comprehension of its pathophysiology. METHODS AND RESULTS: A retrospective study was conducted on C-ARDS patients from April 2020 to February 2021, encompassing 110 participants with a mean age of 63.2 ± 11.92 (26-83 years). Of these, 61.2% (68) were male, and 25% (17) experienced severe ARDS, resulting in a mortality rate of 47.3% (52). Ventilation settings, arterial blood gases, and chest X-ray (CXR) were evaluated on the first day of invasive mechanical ventilation and between days two and three. CXR images were scrutinized using a convolutional neural network (CNN). A binary logistic regression model for predicting C-ARDS mortality was developed based on the most influential variables: age, PaO2/FiO2 ratio (P/F) on days one and three, CNN-extracted CXR features, and age. Initial performance assessment on test data (23 patients out of the 110) revealed an area under the receiver operating characteristic (ROC) curve of 0.862 with a 95% confidence interval (0.654-0.969). CONCLUSION: Integrating data available in all intensive care units enables the prediction of C-ARDS mortality by utilizing evolving P/F ratios and CXR. This approach can assist in tailoring treatment plans and initiating early discussions to escalate care and extracorporeal life support. Machine learning algorithms for imaging classification can uncover otherwise inaccessible patterns, potentially evolving into another form of ARDS phenotyping. The combined features of these algorithms and clinical variables demonstrate superior performance compared to either element alone.
RESUMO
Chronic obstructive pulmonary disease is a chronic condition that requires the engagement of our patients in lifestyle changes and pharmacological treatment. Although there are guidelines on many aspects of chronic obstructive pulmonary disease management, the challenge of engaging our patients persists. We propose a simple mnemonic that we hope will make it easier for patients and clinicians to achieve this goal together.
A doença pulmonar obstrutiva crónica é uma patologia crónica cujo tratamento depende do envolvimento dos doentes em mudanças de estilo de vida e tratamento farmacológico. Embora existam recomendações clínicas no tratamento da doença pulmonar obstrutiva crónica, o desafio em envolver os doentes persiste. Propomos uma mnemónica simples que esperamos contribuir para alcançar esse objetivo comum a médicos e doentes.
