New microbes and new infections · 2026
A practical nomogram for predicting multidrug-resistant organism infection in a tertiary county-level hospital to guide antimicrobial therapy.
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Han Lianxiu, Zhao Haoyu, Cheng Jun, Gao Yufeng
Аннотация
BACKGROUND: The prevalence of multidrug-resistant organisms (MDROs) varies geographically, and uniform standards for its management are lacking.
METHODS: This retrospective single-center study included 1045 unique patients after excluding duplicate isolates from 1304 non-repetitive strains collected between January and December 2023. Multivariable logistic regression was used to identify MDRO predictors and construct a nomogram. Model performance was assessed by ROC curve, calibration curve, and decision curve analysis, with bootstrap internal validation (1000 resamples). A sensitivity analysis excluding ESBL was also performed.
RESULTS: Six independent risk factors were identified: age ≥60 years (OR = 1.47), urinary tract infection(UTIs) (OR = 1.79), ESBL production(OR = 15.18), Pseudomonas aeruginosa (OR = 3.66), S. aureus (OR = 29.23), and E. faecium (OR = 55.48). The bootstrap-corrected AUC was 0.82 (95%CI: 0.79-0.85), with a sensitivity of 85%, specificity of 70%, PPV of 47%, and NPV of 94%. Calibration was satisfactory (slope = 1.000, intercept = 0.000, Brier = 0.136, HL P = 0.926). After ESBL exclusion, the AUC decreased to 0.70, suggesting that other variables retained independent predictive value.
CONCLUSIONS: Age ≥60 years, urinary tract infection, ESBL production, P. aeruginosa, S. aureus, and E. faecium were independent risk factors for MDRO infection. The nomogram demonstrated good discrimination and calibration in this cohort and may serve as a reference for MDRO risk stratification in county-level hospitals, though external validation is warranted.
METHODS: This retrospective single-center study included 1045 unique patients after excluding duplicate isolates from 1304 non-repetitive strains collected between January and December 2023. Multivariable logistic regression was used to identify MDRO predictors and construct a nomogram. Model performance was assessed by ROC curve, calibration curve, and decision curve analysis, with bootstrap internal validation (1000 resamples). A sensitivity analysis excluding ESBL was also performed.
RESULTS: Six independent risk factors were identified: age ≥60 years (OR = 1.47), urinary tract infection(UTIs) (OR = 1.79), ESBL production(OR = 15.18), Pseudomonas aeruginosa (OR = 3.66), S. aureus (OR = 29.23), and E. faecium (OR = 55.48). The bootstrap-corrected AUC was 0.82 (95%CI: 0.79-0.85), with a sensitivity of 85%, specificity of 70%, PPV of 47%, and NPV of 94%. Calibration was satisfactory (slope = 1.000, intercept = 0.000, Brier = 0.136, HL P = 0.926). After ESBL exclusion, the AUC decreased to 0.70, suggesting that other variables retained independent predictive value.
CONCLUSIONS: Age ≥60 years, urinary tract infection, ESBL production, P. aeruginosa, S. aureus, and E. faecium were independent risk factors for MDRO infection. The nomogram demonstrated good discrimination and calibration in this cohort and may serve as a reference for MDRO risk stratification in county-level hospitals, though external validation is warranted.