Prognostic Factors for Covid-19 on Admission Profile and Air Pollutants.

Kikue Sato, Taiki Furukawa, Satoshi Yamashita, Daisuke Kobayashi, Shintaro Oyama, Yoshimune Shiratori

Studies in health technology and informatics 2023 May 18

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It has been reported that the severity and lethality of Covid-19 are associated with coexisting underlying diseases (hypertension, diabetes, etc.) and cardiovascular diseases (coronary artery disease, atrial fibrillation, heart failure, etc.) that increase with age, but environmental exposure such as air pollutants may also be a risk factor for mortality. In this study, we investigated patient characteristics at admission and prognostic factors of air pollutants in Covid-19 patients using a machine learning (random forest) prediction model. Age, Photochemical oxidant concentration one month prior to admission, and level of care required were shown to be highly important for the characteristics, while the cumulative concentrations of air pollutants SPM, NO2, and PM2.5 one year prior to admission were the most important characteristics for patients aged 65 years and older, suggesting the influence of long-term exposure.

Citation

Kikue Sato, Taiki Furukawa, Satoshi Yamashita, Daisuke Kobayashi, Shintaro Oyama, Yoshimune Shiratori. Prognostic Factors for Covid-19 on Admission Profile and Air Pollutants. Studies in health technology and informatics. 2023 May 18;302:901-902