Comparative Assessment of Chest X-ray Interpretations by AI Model and Radiologist Vs Pulmonologist in Predicting the Clinical Status of Covid-19 Pneumonia Patients

Abstract

Objective: Pneumonia is most prevalent and acute respiratory disorder. Chest radiography is the gold standard to confirm the clinical condition and the progress. The use of AI in diagnostic workflow proved to be useful. In this study, quantitative assessment by the AI device is compared with the qualitative assessment by the radiologists.

Methods: This retrospective cohort study involved 100 patients and 535 chest radiographs of the admitted COVID-19 pneumonia. The patients selected with at least one follow-up chest x-ray. The level of agreement between radiologists & the software were defined, and the patients are classified into three categories: deteriorating, stable, and improving. The minor criteria include respiratory rate ≥ 30 breaths/min, PaO2/FiO2 ratio ≤ 250, t count < 100,000/μl, hypothermia (core temperature < 36°C), hypotension and the major criteria include septic shock, respiratory failure, infection. The other possible co-morbid or demographic factors like age, gender, body mass index, cigarette smoking status, patient’s history of diabetes, chronic obstructive pulmonary disease (COPD), cerebrovascular disease, etc. are also analyzed to further subdivide the groups and study the impact of them on the patients.

Results: Among the patients in this study, 51% had diabetes, 43% had a history of cardiovascular disease and 44.21% were obese. 17 patients had other respiratory complications at baseline.. No obvious trend is noted, and software-radiologist had higher agreement similar to analysis by visit. Analysis of factors related to death showed only age to be associated with mortality. Patients who died were significantly older (59.25 vs 48.26; p 0.001).

Conclusion: The higher agreement was found between the radiologist and the software. The obtained agreement was also consistent even across the subgroups, only patient age appears to be associated with high-risk mortality. Obesity and diabetes were independent predictors of mortality with susceptibility to develop acute respiratory failure and pulmonary embolism. Explore a study comparing AI and radiologist assessments in diagnosing COVID-19 pneumonia. Discover factors influencing patient outcomes.