![]() ![]() ![]() The RT-PCR results were extracted from the patients’ electronic medical records in the hospital information system. Xiong), with 20 years of cardiothoracic imaging experience, helped to resolve differences to reach consensus. Two radiologists independently reviewed each half of the 1051 cases (F. Four radiologists, each with 5–10 years of experience in thoracic radiology and direct clinical experience with COVID-19 chest CT cases, reviewed and assessed the CT scans. The open-source data containing chest CT images and clinical metadata of COVID-19 patients confirmed by molecular PCR were directly downloaded from the China National Center for Bioinformation ( ). The identified CT scans were directly downloaded from the hospital Picture Archiving and Communications System (PACS). Using chest CT and clinical data, this study aimed to develop an artificial intelligence (AI) system to predict future deterioration to critical illness in COVID-19 patients. Due to the characteristic signs of COVID-19 on chest CT, artificial intelligence (AI) may have utility in ascribing disease severity status and prognosis to patients. Patients with severe disease will generally have diffuse multi-lobe involvement, pleural effusion, consolidation, bronchial wall thickening, and poor lung aeration on chest CT. For example, chest CT severity score has been developed and shown to correlate disease severity and/or emergent status in COVID-19 patients. However, it remains challenging to predict when a COVID-19 patient will progress to critical illness.īeyond patient demographics and laboratory parameters, chest CT has been instrumental in distinguishing severe from non-severe cases of COVID-19. ![]() Progression to critical illness in COVID-19 occurs across all patients, especially those with comorbidities such as obesity, cardiovascular disease, chronic lung disease, hypertension, or cancer. More importantly, an early determination of patient prognosis is useful when implementing new treatments such as remdesivir, convalescent plasma transfusion, ruxolitinib, and other emerging therapies, leading to better outcomes. Because of the shortage of mechanical ventilators and ICU care, it is crucial to accurately and timely predict COVID-19 patients who will require critical care. For example, patients with acute-respiratory distress syndrome (ARDS) from COVID-19 often require intubation and intensive care unit (ICU) care, which are resource intensive. AI system can predict time to critical illness for patients with COVID-19 by using CT imaging and clinical data.Ĭoronavirus disease 2019 (COVID-19) causes severe respiratory complications, including acute respiratory failure and has put significant strain on healthcare systems worldwide to accommodate the massive influx of critically ill patients.AI has the potential to accurately triage patients and facilitate personalized treatment. Using CT imaging and clinical data, the AI system successfully predicted time to critical illness for individual patients and identified patients with high risk. The AI system successfully stratified the patients into high-risk and low-risk groups with distinct progression risks ( p < 0.0001). The AI system achieved a C-index of 0.80 for predicting individual COVID-19 patients’ to critical illness. Of them, 282 patients developed critical illness, which was defined as requiring ICU admission and/or mechanical ventilation and/or reaching death during their hospital stay. ResultsĪ multi-institutional international cohort of 1,051 patients with RT-PCR confirmed COVID-19 and chest CT was included in this study. MethodsĪn artificial intelligence (AI) system in a time-to-event analysis framework was developed to integrate chest CT and clinical data for risk prediction of future deterioration to critical illness in patients with COVID-19. This study aimed to develop an artificial intelligence system to predict future deterioration to critical illness in COVID-19 patients. However, it is challenging to predict when COVID-19 patients will progress to critical illness. Early recognition of coronavirus disease 2019 (COVID-19) severity can guide patient management.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |