AI-based disease risk score for community-acquired pneumonia hospitalization

Saeed Shakibfar; Morten Andersen; Maurizio Sessa

doi:10.1016/j.isci.2023.107027

AI-based disease risk score for community-acquired pneumonia hospitalization

iScience. 2023 Jun 7;26(7):107027. doi: 10.1016/j.isci.2023.107027. eCollection 2023 Jul 21.

Authors

Saeed Shakibfar¹, Morten Andersen¹, Maurizio Sessa¹

Affiliation

¹ Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark.

Abstract

Community-acquired pneumonia (CAP) is an acute infection involving the parenchyma of the lungs, which is acquired outside of the hospital. Population-wide real-world data and artificial intelligence (AI) were used to develop a disease risk score for CAP hospitalization among older individuals. The source population included residents in Denmark aged 65 years or older in the period January 1, 1996, to July 30, 2018. 137344 individuals were hospitalized for pneumonia during the study period for which, 5 controls were matched leading to a study population of 620908 individuals. The disease risk had an average accuracy of 0.79 based on 5-fold cross-validation in predicting CAP hospitalization. The disease risk score can be useful in clinical practice to identify individuals at higher risk of CAP hospitalization and intervene to minimize their risk of being hospitalized for CAP.

Keywords: Association analysis; Medical informatics; Risk factor.