Distribution of Infectious Pathogens in Maintenance Hemodialysis Patients and Influencing Factors
GUO Limin
GUO Shan
YUAN Yan
BU Haixia
Abstract：Objective To investigate the distribution of infectious pathogens and influencing factors in maintenance hemodialysis(MHD)patients.Methods The data of 210 MHD patients admitted to Xinxiang Central Hospital from January 2020 to December 2022 were collected through medical record collection.According to the pathogen infection status of the patients,they were divided into an infected group(63 cases)and an uninfected group(147 cases).The distribution of pathogenic bacteria and the influencing factors of infection were analyzed,and the risk prediction model was constructed.The distinction of risk prediction model was analyzed by receiver operating characteristic(ROC)curve,and the fit degree of risk prediction model was evaluated by H-L.Results A total of 75 strains of pathogens were isolated from 63 patients with MHD infection,including 40 strains of Gram negative bacteria,32 strains of Gram positive bacteria,and 3 strains of fungi.The proportion of patients with diabetes,hypertension,anemia,hospital stay ≥ 30 days,urea clearance index＜1.2 in the infection group were higher than those in the non infection group,and controlling nutritional status(CONUT)score,blood phosphorus,C-reactive protein(CRP),and interleukin-6(IL-6)were higher than those in the non infection group,with statistically significant differences(P＜0.05).Diabetes,anemia,hospital stay ≥ 30 days,Urea clearance index＜1.2,CONUT score,CRP,IL-6 were all the influencing factors of infection in MHD patients(P＜0.05).The H-L goodness of fit test of the MHD infection risk prediction model was P＞0.05.The area under the ROC curve is 0.853(95％CI:0.815-0.916),with a sensitivity of 89.72％,a specificity of 75.23％,and a Youden index of 0.651.Conclusion Diabetes,anemia,length of stay ≥30 d,Urea clearance index＜1.2,CONUT score,CRP and IL-6 are all influential factors for infection in MHD patients,and the risk prediction model constructed based on these factors has high predictive value for infection and is helpful to guide clinical treatment.
Keywords：maintenance hemodialysisinfectionpathogenic bacteriainfluencing factor
Publication Date：2025-06-28
Online Publishing Date：2026-09-12(First online date of this platform, not the publication date of the document)
Pages：4( 2190-2193 )