Journal Article

An interactive nomogram to predict healthcare-associated infections in ICU patients: A multicenter study in GuiZhou Province, China

Wu, Kaiming, Li, Dan, Xu, Yan, Chao, Jianqian, He, Min, Zhang, Man, Wang, Lu, Mou, Xia, Cheng, Juan, Zhang, Qunling, Yang, Huai, Wu, Wenjuan

2019

Overview

To develop and validate an interactive nomogram to predict healthcare-associated infections (HCAIs) in the intensive care unit (ICU). A multicenter retrospective study was conducted to review 2017 data from six hospitals in Guizhou Province, China. A total of 1,782 ICU inpatients were divided into either a training set (n = 1,189) or a validation set (n = 593). The patients' demographic characteristics, basic clinical features from the previous admission, and their need for bacterial culture during the current admission were extracted from electronic medical records of the hospitals to predict HCAI. Univariate and multivariable analyses were used to identify independent risk factors of HCAI in the training set. The multivariable model's performance was evaluated in both the training set and the validation set, and an interactive nomogram was constructed according to multivariable regression model. Moreover, the interactive nomogram was used to predict the possibility of a patient developing an HCAI based on their prior admission data. Finally, the clinical usefulness of the interactive nomogram was estimated by decision analysis using the entire dataset. The nomogram model included factor development (local economic development levels), length of stay (LOS; days of hospital stay), fever (days of persistent fever), diabetes (history of diabetes), cancer (history of cancer) and culture (the need for bacterial culture). The model showed good calibration and discrimination in the training set [area under the curve (AUC), 0.871; 95% confidence interval (CI), 0.848-0.894] and in the validation set (AUC, 0.862; 95% CI, 0.829-0.895). The decision curve demonstrated the clinical usefulness of our interactive nomogram. The developed interactive nomogram is a simple and practical instrument for quantifying the individual risk of HCAI and promptly identifying high-risk patients.

• Publisher: Public Library of Science,Public Library of Science (PLoS)
• Subject: Acinetobacter baumannii / Acinetobacter Infections - diagnosis / Acinetobacter Infections - epidemiology / Adult / Aged / Area Under Curve / Calibration / Cancer / China - epidemiology / Confidence intervals / Cross infection / Cross Infection - diagnosis / Cross Infection - epidemiology / Culture / Decision analysis / Decision Support Techniques / Demographics / Diabetes / Diabetes mellitus / Disease control / Disease prevention / Economic development / Economic models / Education / Electronic Health Records / Electronic medical records / Electronic records / Electronic surveillance / Engineering / Environmental health / Female / Fever / Health care / Hospital patients / Hospitalization / Hospitals / Humans / Infection / Infections / Infectious diseases / Inpatients / Intensive care / Intensive Care Units / Laboratories / Length of Stay / Male / Medical records / Medical research / Medicine / Medicine and Health Sciences / Middle Aged / Mortality / Nomograms / Nomographs / Nosocomial infections / Patients / Public health / Regression analysis / Regression models / Research and Analysis Methods / Respiratory Tract Infections - diagnosis / Respiratory Tract Infections - epidemiology / Retrospective Studies / Risk analysis / Risk Factors / Risk groups / ROC Curve / Seasons / Services / Social Sciences / Statistical analysis / Training