| Objective:In this study,we retrospectively collected the new inflammatory indicators,clinical characteristics,laboratory indicators,pathogenic bacteria spectrum and drug sensitivity results of patients with peritoneal dialysis-associated peritonitis(PDAP),and compared the new inflammatory indicators,clinical characteristics,laboratory indicators,pathogenic bacteria spectrum and drug sensitivity results of patients with frequent and occasional PDAP.Objective To explore the risk factors,pathogen distribution and drug resistance of peritoneal dialysis-associated peritonitis patients with frequent peritoneal dialysis.In addition,this study also established an effective prediction model for frequent peritoneal dialysis-associated peritonitis by analyzing the risk factors for frequent peritoneal dialysis-associated peritonitis in peritoneal dialysis patients,which can provide reference for clinicians to make treatment decisions.Methods:This study was a single-center retrospective study.Patients with peritoneal dialysis-associated peritonitis who were followed up from January 1,2015 to December 31,2021 in the Department of Nephrology,Hainan People’s Hospital were selected as the study subjects.According to the number of cases of peritoneal dialysis-associated peritonitis,patients were divided into an occasional group(one PDAP/ year)and a frequent group(two or more PDAP/ year).Data of patients with peritoneal dialysis-associated peritonitis were collected.General data included ethnicity,sex,age,body mass index,primary disease of end-stage renal disease,peritoneal dialysis month of age,combined diabetes,and disease outcome.Laboratory data included :1)Collection and calculation of the new inflammatory indicators in peritoneal dialysis-associated peritonitis,These include neutrophil to lymphocyte ratio(NLR),monocyte to lymphocyte ratio(MLR),platelet to lymphocyte ratio(PLR),systemic inflammatory Response Index(SIRI),red blood cell distribution width(RDW),red blood cell distribution width to platelet count ratio(RPR),and C-reactive protein to albumin ratio(CAR).And total bilirubin(TBIL);2)The peripheral blood white blood cell count,neutrophil count,lymphocyte count,monocyte count,platelet count,hemoglobin,blood urea nitrogen,blood creatinine,C-reactive protein,blood potassium,albumin,blood calcium,blood uric acid,weekly total urea nitrogen clearance rate in the occurrence of peritoneal dialysis-associated peritonitis(total Kt/V),complete parathyroid hormone(IPTH),triacylglycerol,total cholesterol.3)Results of pathogenic bacteria spectrum and drug sensitivity of peritoneal dialysate before treatment.Firstly,the simple correlation analysis of the above indicators was performed,single factor analysis was used to screen out statistically significant indicators,and then binary Logistic regression analysis was used for multivariate analysis to obtain risk factors.Patients with peritoneal dialysis-related peritonitis were randomly divided into a modeling cohort and a validation cohort at a ratio of 7:3 using R software.Based on the risk factors,a nomogram prediction model for frequent peritoneal dialysis-related peritonitis was constructed in the modeling cohort.The receiver operating characteristic(ROC)curve was used to evaluate the discrimination of the model,the Hosmer-Lemeshow test and calibration curve were used to evaluate the calibration of the model,and the clinical decision curve was used to evaluate the benefit of the model.Finally,a validation cohort was used to verify the discrimination,accuracy and benefit of the model.Results1.From January 1,2015 to December 31,2021,261 patients with PDAP were followed up in the Department of Nephrology of our hospital,and a total of 457 cases of peritonitis occurred.A total of 138 PDAP patients met the inclusion and exclusion criteria were screened,and a total of 225 cases of peritonitis occurred in the two groups.Among them,98 patients in the single group had 117 cases of peritonitis,and 40 patients in the frequent group had 108 cases of peritonitis.From January 2015 to December 2021,the incidence of peritonitis in the Department of Nephrology of our hospital fluctuated from 0.107 to 0.148times/patient/year.2.The new inflammatory indicators in both groups included neutrophil to lymphocyte ratio(NLR),monocyte to lymphocyte ratio(MLR),platelet to lymphocyte ratio(PLR),systemic inflammatory response index(SIRI),red blood cell distribution width(RDW),red cell distribution width to platelet count(RPR),C-reactive protein to albumin ratio(CAR),and total bilirubin(TBIL),without statistically significant differences(P> 0.05).3.There was no significant difference in the general data of the two groups,including gender,ethnicity,age,body mass index,peritoneal dialysis month of age,combined diabetes and disease outcome(P>0.05).Comparison of primary disease and peritoneal dialysis regimen between the two groups showed statistically significant differences(P<0.05).4.There were no significant differences in white blood cell count,neutrophil count,lymphocyte count,monocyte count,platelet count,blood urea nitrogen,serum creatinine,C-reactive protein,serum potassium,prealbumin,serum uric acid,weekly total Kt/V,parathyroid hormone,triglyceride and total cholesterol between the two groups(P>0.05).The peripheral blood hemoglobin and albumin in the frequent group were lower than those in the occasional group,and the serum calcium level in the frequent group was higher than that in the occasional group(P<0.05).5.Multivariate logistic regression analysis showed that low hemoglobin,low albumin and high blood calcium were independent risk factors for frequent PDAP(P<0.05).6.The positive rate of pathogen culture was 50.4% in the occasional group and 59.3% in the frequent group.There were no significant differences in the types of culture-negative,Gram-positive,Gram-negative bacteria and fungi between the two groups(P> 0.05).7.Analysis of drug resistance of pathogenic bacteria: the highest drug resistance rate was 65.8% for macrolides,followed by 42.6% for sulfonamides.The lowest drug resistance rate of pathogenic bacteria was0% for polypeptide and 0% for oxazolidone.The highest drug resistance rate of gram-positive bacteria was erythromycin 65.3%,followed by cefoxitin 62.5%.The lowest drug resistance rates were cefoperazone/sulbactam 0%,ciprofloxacin 0%,minocycline 0%,vancomycin 0% and linezolid 0%.The drug resistance rate of gram-negative bacteria was the highest,penicillin 100.0% and erythromycin 100.0%,followed by cotrimoxazole 53.6%.The lowest drug resistance rates were cefoperazone/sulbactam 0%,meropyram 0%,vancomycin 0%,linezolid 0% and clindamycin 0%.8.Construction and verification of Nomogram prediction model: 158 cases of modeling queue and 67 cases of verification queue.Based on the joint predictors(hemoglobin,albumin and serum calcium),the column graph prediction model of the diagnosis of frequent PDAP was established.The area under ROC curve of the prediction model was0.739(95%CI 0.661--0.817)and 0.703(95%CI 0.578--0.828),respectively,indicating that the model had a good degree of differentiation.Hosmer-Lemeshow test and correction curve showed that the predicted probability of diagnosing frequent PDAP was in good agreement with the actual probability,indicating that the calibration degree of the model was good.The clinical decision curve shows that the decision made by this model can bring benefits to patients.Conclusions1.There was no correlation between frequent PDAP and the new inflammatory indicators.2.Low hemoglobin,low albumin and high serum calcium are risk factors for frequent PDAP,and their combination as predictors has high sensitivity and specificity,which is of great value for the prediction,prevention and treatment of PDAP.3.The pathogenic bacteria of PDAP patients have high resistance to macrolides and sulfonamides,and low resistance to peptides and oxazolidinones.4.The prediction model of frequent PDAP constructed and verified in this study has good discrimination ability,calibration and clinical benefit,which can be used as a clinical prediction tool. |
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