Multi-state Markov model in expressing the outcome of mild cognitive impairment among community-based elderly residents

Abstract

To introduce the Multi-state Markov model in studying the outcome prediction of mild cognitive impairment (MCI). Based on the intelligence quotient (IQ) changes that reflecting the trends in cognitive function in the patients under follow-up program, we constructed a four states model and used Multi-state Markov model to analyze the patients. Among 600 MCI patients, there were 174 (29.0%) males and 426 (71.0%) females, with age range of 65-90 years-old (average 69.7 ± 6.6). For univariate analysis, gender, age, education level, marital status, smoking, household income, cerebral hemorrhage, hypertension, high cholesterol, diabetes, LDL-C, SBP and DBP were found to be associated with cognitive function. For multivariate analysis, female, older age, cerebral hemorrhage and higher SBP were shown to be the risk factors for transition from the state of cognitive stability to the state of severe deterioration, and their coefficients were 0.762, 0.366, 0.885, and 0.069, respectively. Age (0.038) could influence the transition from the state of cognitive stability to slight deterioration. Higher education level was shown to be the protective factor for these transitions (-0.219 and -0.297). Transition intensity from the state of cognitive stability to the state of slight and severe deterioration was 1.2 times that of transition to the state of improving. Transition intensity from state of slight deterioration to cognitive stability was 11.4 times that of transition to severe deterioration. Multi-state Markov model was an effective tool in dealing with longitudinal data.