Establishment of nomogram prediction model of the occurrence risk for catheter-associated urinary tract infection in ICU patients
Objective To establish the nomogram prediction model of risk for ICU patients suffering from catheter-associated urinary tract infection(CAUTI).Methods A total of 821 ICU patients with indwelling urethral catheter were enrolled,therein 589 cases were regarded as modeling group,and 232 cases as validation group.The occurrence states of CAUTI in patients were recorded,and the clinical data before CAUTI occurrence were collected.The multivariate Logistic regression model was used to analyze the influencing factors for ICU patients suffering from CAUTI based on the data from the modeling group.The nomogram prediction model was established according to the influencing factors.In the validation group,the internal and external validations of the model were performed by employing the receiver operating characteristic(ROC)curve and Hosmer-Lemeshow test.Results The incidence rate of CAUTI among 821 patients was 4.99％(41/821).Indwelling duration for urethral catheter,comorbidity of diabetes mellitus,serum albumin level,and urine positive for nitrite were the influencing factors for ICU patients suffering from CAUTI(P＜0.05).The nomogram prediction model was established based on the aforementioned 4 indices,and both internal and external validations results indicated that the model had a good degree of fit(the results of Hosmer-Lemeshow test revealed that x2=4.347,P=0.739,x2=4.632,P=0.796).Areas under the ROC curve were 0.890 and 0.781,respectively.Conclusions Indwelling duration of urethral catheter≥ 7 days,concomitant diabetes mellitus,serum albumin level＜40 g/L,urine positive for nitrite increase the risk of ICU patients suffering from CAUTI.The nomogram prediction model established based on the aforementioned factors is helpful for medical and nursing personnel to screen high-risk ICU patients suffering from CAUTI,so as to formulate prevention measures to reduce the risk of infection as soon as possible.
Catheter-associated urinary tract infectionPrediction modelNomogramNursingIntensive care unit
万方数据
维普
