Research Assembling
Prediction of urinary infection risks and its predictive nursing measures for benign prostatic hyperplasia
Qie Dongmei, Wang Xin, Ji Peng, Zhang Linlin
Published 2017-06-16
Cite as Chin J Mod Nurs, 2017,23(17): 2226-2229. DOI: 10.3760/cma.j.issn.1674-2907.2017.17.006
Abstract
ObjectiveTo predict the urinary infection factors by classification tree model for benign prostatic hyperplasia (BPH) patients with postoperative urinary tract, and put forward nursing measures toward these risk factors.
MethodsBy the methods of medical records information acquisition and prevalence study, patients were collected, who saw a doctor and accepted the TURP for the treatment of urinary tract infection with 112 cases infected and 2 586 cases not infected retrospectively in 7 hospitals in Daqing. All information acquired by recording or documents. The model was constructed that whether occurred postoperative urinary tract infection was set up as outcome variable and the possible risks for postoperative urinary tract infections was established as independent variable. According to the model result, model risk factors will be put forward.
ResultsCatheter indwelling time, age, degree of anxiety, diabetes and smoking were the main risk factors for postoperative BPH urinary tract infection (t=14.23, 11.30, 10.42, 6.23, 8.27, 7.29; P<0.05) , and catheter indwelling time had the largest effect.
ConclusionsFor patients with different ages, to shorten the time for placing a urinary catheter, anxiety levels and blood glucose control, strict quitting smoking can reduce the incidence of postoperative BPH urinary tract infection.
Key words:
Benign prostatic hyperplasia; Urinary tract infection; Risk factor; Predictive nursing measure
Contributor Information
Qie Dongmei
Surgery Department, Daqing Oil Field General Hospital, Daqing 163312, China
Wang Xin
Surgery Department, Daqing Oil Field General Hospital, Daqing 163312, China
Ji Peng
Surgery Department, Daqing Oil Field General Hospital, Daqing 163312, China
Zhang Linlin
Daqing Campus, Harbin Medical University, Daqing 163312, China