Jingwen Zhang,1,2,* Guoqiang Zhang,1,2,* JiaJia Wang,1,2,* Yun Xiao,1,2 Xinxin Lu,1,2 Xunhong Lan,1,2 Yan Zhang,1,2 Zhang Dai1,2 

1Centre of Clinical Laboratory, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, People’s Republic of China; 2Institute of Infectious Disease, School of Medicine, Xiamen University, Xiamen, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Yan Zhang; Zhang Dai, Centre of Clinical Laboratory, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, People’s Republic of China, Tel +86-0592-2293046, Email zy1983@xmu.edu.cn; 180219034@qq.com

Background: Nosocomial candidemia is a life-threatening condition, and the incidence has increased in recent years. Thorough epidemiological data is still lacking in China.
Methods: A retrospective cohort study was conducted to investigate the patients admitted to Zhongshan Hospital Xiamen University from 1 January 2004 to 31 December 2022. This study included 205 individuals who were diagnosed with candidemia as subjects. Additionally, 303 cases with blood cultures were negative during the same period and were from the same department as a control group. We randomly assigned them to the training and validation groups in a 7:3 ratio. The least absolute shrinkage and selection operator regression, univariate and multivariate logistic regression analyses were used to filtrate independent factors associated with nosocomial candidemia. A nomogram model was established based on the selected variables. Receiver operating characteristic (ROC) curve, calibration plots and decision curve analysis (DCA) were used to evaluate clinical utility.
Results: Two hundred and five nosocomial candidemia patients were reported, containing a high proportion of Candida albicans (n = 91,44.39%), followed by Candida parapsilosis (n = 40, 19.51%), Candida tropicalis (n = 37,18.05%), Candida glabrata (n = 23, 11.22%) and Candida guilliermondii (n = 9,4.39%). Multiple organ dysfunction syndrome (OR = 10.372, 95% CI: 4.745– 24.14 P < 0.001), increased urea nitrogen of serum (OR=1.088,95% CI: 1.039– 1.144 P< 0.001), decreased albumin of serum (OR = 0.922 95% CI: 0.850– 0.997 P=0.045), mechanical ventilation (OR=4.074,95% CI: 1.397– 12.77 P=0.012), central venous indwelling catheter (OR=7.422,95% CI: 3.189– 18.41 P< 0.001) and solid tumor (OR = 3.036 95% CI: 1.276– 7.359 P=0.012) were identified as independent risk factors of candidemia. The area under the curve (AUC) of the nomogram model was 0.925 (95% CI: 0.898– 0.952) in the training group and 0.946 (95% CI: 0.881– 0.963) in the validation group. The calibration curve revealed good agreement between the probability and the observed values. DCA indicated that this nomogram might be clinically beneficial.
Conclusion: The nomogram including multiple organ dysfunction syndrome, elevated blood urea nitrogen, decreased albumin, mechanical ventilation, central venous indwelling catheter and solid tumor could provide reference value to clinicians for identifying nosocomial candidemia.

Keywords: candidemia, risk factors, nomogram model, ROC curve