Bayesian modelling of oxygen saturation (SpO2) of cardiac patients using the asymmetric generalized error distribution.

Abstract

Background: Oxygen saturation (SpO₂) is a crucial parameter for monitoring the health of cardiac patients. It measures the percentage of hemoglobin in the blood that is saturated with Oxygen. The study aims to analyze longitudinal Oxygen saturation (SpO₂) levels and identify its determinants among cardiac patients.

Methods: Bayesian linear mixed-effects model with the asymmetric generalized error distribution (AGED) was used to analyze the data. The data comprises 323 children diagnosed with cardiac disease. AGED outperforms the others distributions and indicates robust and effective choice to analysis the data.

Results: The estimated shape parameters of AGED are significant [Formula: see text] (95% CI: 2.31, 2.58) which is degree of asymmetry, and [Formula: see text] (95% CI: 3.18, 3.46) is associated with peakedness of the distribution. The finding reveals that corrective surgery, pulmonary hypertension, cardiomyopathy, anemia, nutritional status, and hemoglobin levels are significantly associated with Oxygen saturation (SpO₂). Pulmonary hypertension, cardiomyopathy, and under nutrition are found to lower SpO₂. In contrast, higher hemoglobin and corrective surgery are significantly associated with higher SpO₂. The AGED fitted to the data, and found to be important for analyzing data characterized by asymmetry and excess kurtosis.