16: Group-Based Trajectory Modeling of Serum Potassium Levels in Terminal Phase Gastrointestinal Cancer Patients

Music City Center 

In recent years, electronic medical record data has been increasingly utilized, and there is a growing need for trajectory and classification of electrolyte concentration data obtained from patients' routine blood drawings.
In this study, Group-Based Trajectory Modeling (GBTM) was applied to medical record data of patient in the terminal phase of the disease in Japan.
It is important to predict the prognosis and sudden change of condition of terminally ill patients, and the classification of trajectories and their eventual inclusion in the medical record will be useful for patient prediction.
The study utilized blood collection data from 4,981 terminally ill patients admitted to a Japanese university hospital between 2008 and 2016.
Focusing on potassium levels, which are known to decrease significantly at the end of life, GBTM was applied. The five groups that best fit the BIC were: very low [1] (7.2%), low [2] (32.5%), normal [3] (15.6%), high [4] (32.9%), and very high [5] (11.8%).

Utilization of Electronic Medical Records

Group-Based Multivariate Trajectory Modeling

end-stage potassium 

Isolated Statisticians