Machine-learning based prediction of prognostic risk factors in patients with invasive candidiasis infection and bacterial bloodstream infection: a singled centered retrospective study

Yaling Li,Jingyi Li,Xiuhao Guan,Mingsui Tang,Bing Song,Yali Gao,Xueli Niu,Ruiqun Qi,Ying Yang,Xinghua Gao,Hongduo Chen,Chang Fu,Yutong Wu

doi:10.1186/s12879-022-07125-8

Abstract

BackgroundInvasive candidal infection combined with bacterial bloodstream infection is one of the common nosocomial infections that is also the main cause of morbidity and mortality. The incidence of invasive Candidal infection with bacterial bloodstream infection is increasing year by year worldwide, but data on China is still limited.MethodsWe included 246 hospitalised patients who had invasive candidal infection combined with a bacterial bloodstream infection from January 2013 to January 2018; we collected and analysed the relevant epidemiological information and used machine learning methods to find prognostic factors related to death (training set and test set were randomly allocated at a ratio of 7:3).ResultsOf the 246 patients with invasive candidal infection complicated with a bacterial bloodstream infection, the median age was 63 years (53.25–74), of which 159 (64.6%) were male, 109 (44.3%) were elderly patients (> 65 years), 238 (96.7%) were hospitalised for more than 10 days, 168 (68.3%) were admitted to ICU during hospitalisation, and most patients had records of multiple admissions within 2 years (167/246, 67.9%). The most common blood index was hypoproteinemia (169/246, 68.7%), and the most common inducement was urinary catheter use (210/246, 85.4%). Moreover, the most frequently infected fungi and bacteria were Candida parapsilosis and Acinetobacter baumannii, respectively. The main predictors of death prognosis by machine learning method are serum creatinine level, age, length of stay, stay in ICU during hospitalisation, serum albumin level, C-Reactive protein (CRP), leukocyte count, neutrophil count, Procalcitonin (PCT), and total bilirubin level.ConclusionOur results showed that the most common candida and bacteria infections were caused by Candida parapsilosis and Acinetobacter baumannii, respectively. The main predictors of death prognosis are serum creatinine level, age, length of stay, stay in ICU during hospitalisation, serum albumin level, CRP, leukocyte count, neutrophil count, PCT and total bilirubin level.

Highlights

Invasive candidal infection combined with bacterial bloodstream infection is one of the common nosocomial infections that is the main cause of morbidity and mortality
Our results showed that the most common candida and bacteria infections were caused by Candida parapsilosis and Acinetobacter baumannii, respectively
A study from China reported that Candida albicans was the causative agent in only 44.9% of invasive candidal infection cases [13], which is consistent with our previous study, which revealed that Candida albicans is no longer the most common invasive fungus [14]

Summary

Introduction

Invasive candidal infection combined with bacterial bloodstream infection is one of the common nosocomial infections that is the main cause of morbidity and mortality. The incidence of invasive Candidal infection with bacterial bloodstream infection is increasing year by year worldwide, but data on China is still limited. Bacterial bloodstream infection is the seventh leading cause of death in North America and Europe [5]. In these regions, the average annual mortality is 29 cases per 100,000 population, and the total mortality is between 13 and 20% [5]. In previous studies, the epidemiological characteristics and risk factors of invasive fungal infections complicated with bacterial bloodstream infections were rarely discussed, possibly owing to the limited capacity of some methods in analysing large datasets

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Conclusion