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.
ABSTRACT
BACKGROUND: The purpose of the study is to describe the profile of patients with asthma and to identify the signifiant risks and the protective factors associated with asthma control. METHODS: A prospective epidemiological study was conducted in three hospitals of Rabat-Morocco and included 396 patients with asthma. Differences in characteristics across the levels of asthma control were compared by the one-way analysis of variance for continuous variables, and chi-square test was used for categorical variables. The risk and protective factors associated with the asthma control levels were determined by Proportional Odds Model (POM) for bivariate and multivariate ordinal logistic regression, also expressed as Odds Ratios (OR) and 95% Confidence Intervals (95% CI). RESULTS: From 7440 patients screened by 28 physicians, 396 were included in study. 53% of the particiants sufferd controlled, 18% had partly controlled and 29% had uncontrolled asthma symptoms. A multivariate ordinal logistic regression analysis showed that having respiratory infections (AOR = 5.71), suffering from concomitant diseases (AOR = 3.36) and being allergic to animals (AOR = 2.76) were positively associated with poor control of asthma. However, adherence to treatement (AOR = 0.07), possession of health insurance (AOR = 0.41) and having more than 2 children (AOR = 0.47) were associated with good asthma control. CONCLUSION: The study established a clinical-epidemiological profile of asthmatic patients in Rabat region in Morocco. By ordinal logistic regression we found that 6 factors - respiratory infections, concomitant diseases, animals allergy, adherence to treatment, health insurance and having more than two children - were associated with asthma control.
