Published in:
Open Access
01-12-2020 | Research
Predicting the occurrence of multidrug-resistant organism colonization or infection in ICU patients: development and validation of a novel multivariate prediction model
Authors:
Li Wang, Xiaolong Huang, Jiating Zhou, Yajing Wang, Weizhang Zhong, Qing Yu, Weiping Wang, Zhiqiao Ye, Qiaoyan Lin, Xing Hong, Ping Zeng, Minwei Zhang
Published in:
Antimicrobial Resistance & Infection Control
|
Issue 1/2020
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Abstract
Background
Multidrug-resistant organisms (MDROs) have emerged as an important cause of poor prognoses of patients in the intensive care unit (ICU). This study aimed to establish an easy-to-use nomogram for predicting the occurrence of MDRO colonization or infection in ICU patients.
Methods
In this study, we developed a nomogram based on predictors in patients admitted to the ICU in the First Affiliated Hospital of Xiamen University from 2016 to 2018 using univariate and multivariate logistic regression analysis. We externally validated this nomogram in patients from another hospital over a similar period, and assessed its performance by calculating the area under the receiver operating characteristic (ROC) curve (AUC) and performing a decision curve analysis.
Results
331 patients in the primary cohort and 181 patients in the validation cohort were included in the statistical analysis. Independent factors derived from the primary cohort to predict MDRO colonization or infection were male sex, higher C-reactive protein (CRP) levels and higher Pitt bacteremia scores (Pitt scores), which were all assembled in the nomogram. The nomogram yielded good discrimination with an AUC of 0.77 (95% CI 0.70–0.84), and the range of threshold probabilities of decision curves was approximately 30–95%.
Conclusion
This easy-to-use nomogram is potentially useful for predicting the occurrence of MDRO colonization or infection in ICU patients.