Construction of a prediction model for relapse in patients with alcohol-induced mental disorders and its effect on cognitive function

Objective To analyze the influencing factors of relapse in patients with alcohol-induced mental disorders after 1 year of discharge, establish a risk prediction model, and explore the relationship between relapse and cognitive function.

Methods A total of 163 patients with alcohol-induced mental disorders were selected as the study subjects.The patients were divided into the repeated drinking group and non-repeated drinking group according to whether they drank again or not 1 year after discharge.The independent influencing factors of repeated drinking were analyzed, the goodness of fit and prediction effect of the model of repeated drinking were tested.The differences of cognitive function were compared between two groups, and the effects of redrinking on cognitive function was investigated.

Results Among 163 patients, 103 cases had relapse within 1 year, and the relapse rate was 63.19%.Drinking years, alcohol craving, depression, family caring and emotional regulation were the independent risk factors of relapse(OR=1.110-5.882, 95%CI=1.063-24.564, P < 0.05), while the educational background was the independent protective factor(OR=0.311, 95%CI=0.132-0.733, P < 0.01).The fit of prediction model was good(χ²=11.82, P>0.05), and AUC was 0.966(P < 0.01, 95%CI=0.943-0.989), The sensitivity, specificity, Youden index, optimal critical value and actual application accuracy were 88.3%, 96.7%, 0.850, 0.756 and 90.2%, respectively.The scores of immediate memory, speech function, attention function, delayed memory and cognitive function in the repeated drinking were lower than those in non-repeated drinking group(P < 0.01).

Conclusions Patients with mental disorders caused by alcohol have a high rate of relapse after discharge.Clinical attention should be paid to patients with low education, long drinking years, strong alcohol craving, depression, low family care and weak emotional regulation.The constructed risk prediction model has a good predictive effect on relapse.The medical staff should improve the cognitive function of patients by effective intervention to reduce the relapse rate.