Based on random fasting plasma glucose (FPG), glycosylated hemoglobin A1c (HbA1c) and glycosylated serum protein (GSP) and cluster analysis to construct a classification discriminant prediction model for middle-aged outpatients with schizophrenia (SP), which could provide reference for the early diagnosis and treatment, monitoring management and cost control strategies of SP patients with comorbidity of glucose metabolism.

from December 1, 2013 to May 31, 2020, the data of gender, age, outpatient diagnosis, FPG, HbA1c and GSP test results of SP patients in the outpatient department of Brain Hospital Affiliated to Guangzhou Medical University were reviewed, and the clustering and discriminant analysis were conducted, and the classified data were compared and analyzed.

(1) A total of 2047 patients were included in the study. The proportion of abnormal blood glucose indexes was higher in middle-aged patients with SP, HbA1c (5.898 ± 1.354), GSP (1.877 ± 1.354), FPG (7.055 ± 430); (2) In the short-term blood glucose monitoring, the proportion of male increased was higher, the difference was statistically significant (P<0.05); (3) The cluster can be divided into three categories, and the discriminant classification prediction model is constructed, the first kind is Y₁=-24.477+4.496HbA1c+6.781GSP+1.641FPG, the second kind is Y₂=-139.639+6.404HbA1c+8.733GSP+8.592FPG, the third one is Y₃=-49.354+5.502HbA1c+6.747GSP+3.831FPG; (4) Comparing the three groups of data based on clustering, it was found that there were significant differences in age, HbA1c, GSP and Glu among the three groups (P<0.05).

The results show that the management of blood glucose in outpatients with SP is generally poor, especially in the management of short-term blood glucose indicators of men; the classification discrimination prediction model based on blood glucose index and clustering method has a good effect, which can be used to explore the implementation of individualized monitoring for middle-aged patients with SP in outpatient department, so as to provide early diagnosis and treatment for patients with abnormal glucose metabolism.