1.Effect of dexmedetomidine combined with nutritional intervention in the cognitive function recovery and prognosis of patients in ICU severe cranial traumatic brain injury
Yanpin SONG ; Zhuling WANG ; Li HUA
Chinese Journal of Biochemical Pharmaceutics 2017;37(8):208-209,211
Objective To explore the effect of dexmedetomidine combined with nutritional intervention on cognitive function recovery and prognosis of patients with severe cranial traumatic brain injury in ICU. Methods A total of 100 patients with severe cranial traumatic brain injury from February 20, 2016 to December 30, 2016 in our hospital ICU were selected and randomly divided into two groups, the control group were given nutrition intervention, the experimental group combined with dexmedetomidine and nutritional intervention. Results The difference of PACHE Ⅱscore, GCS score, mechanical ventilation time, and hospitalization timebetween the 2 groups was statistically significant (P<0.05); The recovery of cognitive function in the experimental group was better than that in the control group (P<0.05). Conclusion The value of dexmedetomidine and nutritional intervention in patients with severe cranial traumatic brain injury in ICU is higher.
2.Influencing factors of metabolic syndrome among adults in Nanjing, China: an analysis based on decision tree and logistic regress models
Yinghao CHEN ; Zhuling YAO ; Zhiyong WANG ; Fei XU
Shanghai Journal of Preventive Medicine 2023;35(1):8-14
ObjectiveWe analyzed the prevalence of metabolic syndrome in adult residents of Nanjing and explored its influencing factors in order to provide technical references for the prevention of metabolic syndrome. MethodsBased on the data of the Nanjing adult chronic disease thematic survey from January 2017 to June 2018, the influencing factors of metabolic syndrome were analyzed using multifactorial logistic regression model and decision tree model. ResultsThe weighted prevalence of metabolic syndrome among people aged 18 years and over in Nanjing was 16.14%(95%CI:16.12%‒16.16%). Prevalence of metabolic syndrome was statistically different(P<0.05)among respondents with different demographic characteristics. Logistic regression model analysis showed that age, gender, education, physical activity level, marriage status, smoking status, drinking status, weight status, diabetes and hypertension family history were the influencing factors for the prevalence of metabolic syndrome(P<0.05). The results of the decision tree model showed that weight status was the most influential factor for metabolic syndrome, followed by age, gender, diabetes family history and smoking status. ConclusionThe prevalence of metabolic syndrome is high among the adult population in Nanjing, and special attention should be paid to middle-aged and elderly men who are overweight and obese, have a family history of diabetes and smoking.