Establishment of a risk prediction model for multidrug-resistant bacteria in deceased organ donors: a retrospective cohort study in China

Author:

Shen Guojie,Zhang Li,Fan Weina,Lv Haifeng,Wang Feifei,Ye Qingqing,Lin Miaozuo,Yu Xia,Cai Hongliu,Wu Xiaoliang

Abstract

BackgroundMultidrug resistance in bacteria is a serious problem in organ transplantations. This study aimed to identify risk factors and establish a predictive model for screening deceased organ donors for multidrug-resistant (MDR) bacteria.MethodsA retrospective cohort study was conducted at the First Affiliated Hospital of Zhejiang University School of Medicine from July 1, 2019 to December 31, 2022. The univariate and multivariate logistic regression analysis was used to determine independent risk factors associated with MDR bacteria in organ donors. A nomogram was established based on these risk factors. A calibration plot, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) were used to estimated the model.ResultsIn 164 organ donors, the incidence of MDR bacteria in culture was 29.9%. The duration of antibiotic use ≥3 days (odds ratio [OR] 3.78, 95% confidence interval [CI] 1.62–8.81, p=0.002), length of intensive care unit (ICU) stay per day(OR 1.06, 95% CI 1.02–1.11, p=0.005) and neurosurgery (OR 3.31, 95% CI 1.44–7.58, p=0.005) were significant independent predictive factors for MDR bacteria. The nomogram constructed using these three predictors displayed good predictive ability, with an area under the ROC curve value of 0.79. The calibration curve showed a high consistency between the probabilities and observed values. DCA also revealed the potential clinical usefulness of this nomogram.ConclusionsThe duration of antibiotic use ≥3 days, length of ICU stay and neurosurgery are independent risk factors for MDR bacteria in organ donors. The nomogram can be used to monitor MDR bacteria acquisition risk in organ donors.

Publisher

Frontiers Media SA

Subject

Infectious Diseases,Microbiology (medical),Immunology,Microbiology

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