The analysis of asthma control using Markov models: MOSAR study (Multicenter Observational Study of Asthma in Rabat-Morocco)

Abstract

Background This study aimed to analyze the probabilities of transitioning between controlled, uncontrolled, and partially controlled states of asthma patients and investigate the influence of age, smoking, dust allergy, and obesity on these probabilities. Methods This study aimed to analyze the probabilities of transitioning between controlled, uncontrolled, and partially controlled states of asthma patients and investigate the influence of age, smoking, dust allergy, and obesity on these probabilities. Results Results showed that controlled patients were more likely to remain in that state, with approximately 79 out of 100 patients expected to stay in optimal control in the long term. A discrete nonhomogeneous time Markov Model with the stationarity criterion was used to examine the factors affecting patient states and transitions. Patients seen during the spring and summer seasons were more likely to move into a controlled state compared with those seen in the fall and winter seasons. Patients with dust allergies and obesity significantly impacted asthma exacerbation, with overweight patients more likely to transition into a controlled state. The study estimated the transition intensities matrix under certain conditions, assuming the regularity of patients. In the long term, the probability of an asthmatic patient being in a controlled state was approximately 0.8. Conclusion This study provided insights into the probabilities and factors influencing asthma progression in Morocco. Dust allergy and obesity were identified as significant contributors to asthma exacerbation, emphasizing the need for effective management strategies.