Construction And Verification Of Risk Prediction Model For Restlessness In Patients With General Anesthesia

ObjectiveThe purpose of this study is to investigate the current situation of emergence agitation?EA?in patients with general anesthesia,identify the influencing factors that may affect EA in patients with general anesthesia,and establish a logistic regression prediction model that can predict the restlessness early.Formula for the probability of agitation.The agitation risk prediction model of patients in the awake period was applied to the nursing work in the awake room.This allows rapid screening of high-risk patients at risk of agitation among patients underwent general anesthesia.MethodsIn this study,after reviewing a large number of literatures,collating and analysing the literatures,a"surgical agitation risk questionnaire for patients under general anesthesia"was constructed according to the expert meeting method.According to strict inclusion and exclusion criteria,a convenient sampling method was selected from January 2019.-In August 2019,500 patients who were admitted to the anesthesia recovery room after general anesthesia in the operating room of a tertiary Class A general hospital in Qingdao City,Shandong Province,were taken as research subjects.The clinical data of anaesthesia and the state of EA of patients with general anesthesia recovery in postanesthesia care unit?PACU?were investigated by field investigation method using agitation risk questionnaire and agitation score table.Using SPSS 22.0 statistical software,the relevant data of the 333 patients underwent general anesthesia in the modeling group were collated for single factor analysis.The significant influencing factors of the general anesthesia patients during the awake period were analyzed using the backward-Wald stepwise selection method.Multivariate Logistic regression analysis,excluding the influence variables corresponding to the minimum Wald value,the variables finally obtained reached a significant level.The established logistic regression prediction model of agitation risk in patients with general anesthesia was established,and Hosmer-Lemeshow test was used to verify the goodness of fit of the model.P>0.05 indicated that the model fits well.The model was applied to the verification group to obtain the AUC value?area under the curve?.The accuracy,sensitivity,and specificity of the model for predicting agitation risk in patients with general anesthesia recovery were drawn by plotting the ROC curve?receiver working characteristic curve?.prediction probability P=0.5 is the decision point.P value greater than 0.5 is considered to be agitation.The closer the area AUC under the ROC curve is to 1,the better the prediction effect of the model.Results1.Single-factor Logistic regression analysis of agitation in general anesthesia patients:age?P<0.001,t=34.7?,gender?P<0.001,c2=30.88?,body mass index?BMI??P<0.001,t=43.58?,preoperative anxiety?P<0.001,c2=45.19?,anesthesia method?P<0.001,c2=15.73?,ultrasound block guided nerve block?P<0.001,c2=36.52?,type of operation?P<0.001,c2=23.82?,type of surgery?P<0.001,c2=65.927?,urinary catheter?P<0.001,c2=85.711?,awakening drugs?P<0.001,c2=77.565?,intraoperative The amount of bleeding?P<0.05,t=6.04?,intravenously controlled analgesia?P<0.001,c2=71.8?,NRS score?P<0.001,t=87.83?.2.Further multivariate two-class Logistic regression analysis obtained the influencing factors of EA:type of surgery X₆?P=0.004,OR=1.499,95%CI:1.142-1.967?,urinary catheter X₈?P=0.003,OR=2.645,95%CI:1.396-5.010?,intravenously controlled analgesia X₁₀?P<0.001,OR=0.007,95%CI:0.01-0.062?,NRSscoreX₁₁?P<0.001,OR=3.670,95%CI:2.285-5.897?,3.The logistic regression model for the final prediction of agitation risk in patients with general anesthesia:Logit?Y?=ln?p/1-p?=-11.069-2.112*X₅-4.929*X₁₀+0.405*X₆+0.972*X₈+1.300*X₁₁Probability of agitation:P=Exp(-11.069-2.112*X₅-4.929*X₁₀+0.405*X₆+0.972*X₈+1.300*X₁₁)/[1+Exp(-11.069-2.112*X₅-4.929*X₁₀+0.405*X₆+0.972*X₈+1.300*X₁₁]4.Verification of agitation risk prediction model in patients with general anesthesia during the awake period:The goodness of fit is feasible after Hosmer-Lemeshow test,its?2=1.712,df=8,P=0.989;the area under the ROC curve of the modeling group model is AUC=88.1%,The test module model verifies that the area under the ROC curve is AUC=80.7%,sensitivity is 83.87%?26/31?,specificity is 83.08%?113/136?,and accuracy is 83.23%?139/167?.Conclusion:Operation type,catheters,vein self-control analgesia,NRS score and ultrasound guided nerve block is awakening period occurred in patients with general anesthesia is an independent predictor of restlessness,type of surgery,catheter,a risk factor for NRS score is restless,vein self-control analgesia,ultrasound guided nerve block is restless protection factors.The risk prediction model for restlessness in the recovery period of general anesthesia has been established and verified to be of good prediction value.This prediction model is convenient and feasible,and its prediction performance is relatively stable,which can provide guidance for the staff in the anesthesia recovery room to effectively predict and screen restlessness in the recovery period of general anesthesia.