Invasive candidiasis (IC) refers to a bloodstream (termed candidemia) and deep-seated infection with Candida spp. (Pappas et al., 2016; Bassetti et al., 2019). Candidemia is the second most common nosocomial bloodstream infection, with a mortality rate of 49% (McCarty et al., 2021). Approximately 1/3 of candidemia cases occur in the intensive care unit (ICU), and IC is the most common fungal disease in ICU patients (Logan et al., 2020). Patients admitted to the ICU have numerous risk factors significantly associated with IC, such as wide use of broad-spectrum antibiotics (Thomas-Ruddel et al., 2022), prolonged duration of corticosteroid use, post-aggressive immune paralysis (Jung et al., 2021), and higher utilization of intravenous catheters (Kullberg and Arendrup, 2015; Pappas et al., 2018). The overall mortality rate of ICU-associated IC is up to 55%, and has even been documented at 98% when septic shock develops (Kullberg and Arendrup, 2015). Previous studies and guidelines have mostly focused on immunodeficient patients, such as those with hematological malignancies and solid organ transplants (Donnelly et al., 2020). However, most patients in the ICU are immunocompetent at the onset of infection (Bassetti et al., 2021). Therefore, there is a lack of strong evidence to guide early recognition and timely initial antifungal therapy for IC among immunocompetent ICU patients.

Notably, delayed antifungal treatment can further increase the mortality of ICU-related IC, especially when not initiated 24–48 h after the first positive culture (Playford et al., 2016). Most ICU patients have hemodynamic instability, thrombocytopenia, or coagulation disorders, which may complicate tissue sampling. Furthermore, current pathogen detection methods for IC have limitations and cannot achieve timely and accurate diagnosis at the onset of infection. Culture-based techniques require more than 1–2 days to obtain results and have low sensitivity (Clancy and Nguyen, 2013). The most common non-culture-based method, testing for 1,3-β-D-glucan (BDG), has narrow specificity and sensitivity (Lamoth et al., 2012). Multiplex Candida real-time polymerase chain reaction (PCR) and metagenomics second-generation gene sequencing have great advantages in etiological diagnosis; however, they have some limitations, such as cost and the need for skilled personnel, and it is difficult to carry out routine etiological examinations (Bassetti et al., 2019). Therefore, the early recognition of IC in ICU patients is problematic. Hence, it is necessary and urgent to construct a tailored, prompt, and easy-to-use diagnostic clinical model.

Candida invades the human body and activates innate immune cells to produce many proinflammatory cytokines and chemokines (Pappas et al., 2018). Previous studies have found that plasma levels of inflammatory cytokines [Interleukin-1β (IL-1β), Tumor necrosis factor-α (TNF-α), and Interferon-γ (IFN-γ)] and clinical inflammatory markers [C-reactive protein (CRP) and neutrophils] are significantly increased in patients with IC (Chumpitazi et al., 2014; Akin et al., 2015; Wunsch et al., 2021). Furthermore, several previous studies have shown that patients with IC in the ICU are at a high risk of malnutrition, which is associated with poor clinical prognosis (Piazza et al., 2004; Lee et al., 2021). Therefore, patients with IC in the ICU exhibit extremely severe systemic inflammation and poor nutritional status. Novel serological markers derived from a combination of two or more laboratory indicators, such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), CRP-to-albumin ratio (CAR), and systemic immune-inflammation index (SII), represent inflammation and immune response (Xue et al., 2020). The prognostic nutritional index (PNI) symbolizes the nutritional status of the patients (Xue et al., 2020). However, changes in these novel serological biomarkers and their clinical value in IC remain unclear. In this retrospective study, we aimed to evaluate the associations between novel serological biomarkers, disease severity, and prognosis and to develop a simple predictive scoring system based on clinical risk factors and new biomarkers for the early diagnosis of IC in ICU patients to guide timely initial antifungal therapy.

At present, the guidelines and studies related to IC are mainly focused on people with immunodeficiency but less on immunocompetent populations (Donnelly et al., 2020). However majorities of critically ill patients are immunocompetent (Bassetti et al., 2021). Thus, early diagnosis of IC remains challenging among immunocompetent, critically ill patients, resulting in delayed antifungal treatment and increased mortality. Clinicians urgently need a tailored and prompt diagnostic method to recognize IC in ICU patients and instruct timely antifungal therapy. In this study, we found that new biomarkers, CAR, NLR, and PNI, were significantly altered in patients with IC. Furthermore, these biomarkers were significantly associated with disease severity and prognosis of ICU patients. Finally, we developed a scoring system for the early diagnosis of IC in immunocompetent patients in the ICU. The scoring system, based on sepsis, TPN, broad-spectrum antibiotics, high SOFA score, BDG positivity, high NLR, and high CAR, had a good identifiable value for IC, with an AUC of 0.883.

The burden of invasive fungal disease in ICU patients is increasing, of which 80% is caused by Candida species (Bassetti et al., 2017). In this study, the incidence of IC in immunocompetent ICU patients was 4.56% (84/1841), similar to previous studies (Zhang et al., 2022). The all-cause mortality of IC is reported to be approximately 49% (Kollef et al., 2012). However, the overall mortality rate of IC in our study population was 21.4% (18/84), which was lower than the published data. This may be related to the exclusion of immunodeficient patients in our study. In addition, we showed that patients with IC had a significantly higher disease severity score, 30-day mortality rate, hospitalization expenses, and longer hospital and ICU lengths of stay than those non-IC patients. Therefore, patients with IC have a higher mortality and socioeconomic burden.

Delayed antifungal treatments could further increase the mortality of ICU patients with IC (Martin-Loeches et al., 2019). Therefore, timely diagnosis of IC is crucial to guide targeted antifungal therapy and to improve the prognosis of ICU patients. Nevertheless, early diagnosis of IC in the ICU setting remains difficult. First, tissue biopsy, the gold standard for diagnosing IC, is difficult to accomplish in ICU patients because of their unstable vital signs and/or coagulation disorders. Second, noninvasive diagnostic methods have their respective limitations. For example, BDG is a cell wall component of Candida, which can be continuously released into blood in the process of IC (Clancy and Nguyen, 2018; Yoshida, 2021). So the detection of BDG is a common diagnostic method for IC. However, the detection methodologies are diverse, such as turbidimetry, colorimetry, or chemiluminescence immunoassay (Clancy and Nguyen, 2018; Yoshida, 2021). And colorimetry includes endpoint colorimetry and dynamic colorimetry, while turbidimetry also includes endpoint turbidimetry and dynamic turbidimetry. So the thresholds of BDG testing are different, ranging from 11 pg./ml to 95 pg./ml, making it difficult to reach a consensus (White et al., 2019; Bamba et al., 2021; Lamoth et al., 2021; Lass-Florl et al., 2021). Additionally, BDG detection has a high false-positive rate (Karageorgopoulos et al., 2011; Haydour et al., 2019) and can be influenced by blood product perfusion, Candida spp. colonization, and disturbed GI mucosa (Logan et al., 2020).

Critically ill IC patients exhibit extremely severe systemic inflammation and poor nutritional status. Novel markers derived from a combination of two or more laboratory indicators, such as NLR, PLR, MLR, CAR, and SII, represent inflammation and immune responses (Xue et al., 2020). Meanwhile, PNI symbolizes the nutritional status (Xue et al., 2020). Higher levels of NLR, PLR, MLR, CAR, and SII and lower levels of PNI are correlated with the severity of various diseases, such as COVID-19, cancer, and rheumatic diseases (Gasparyan et al., 2019; Fois et al., 2020; Huang et al., 2020; Nost et al., 2021). In our study, we found that NLR and CAR were higher in patients with IC, whereas PNI was lower. Correlation analysis showed that CAR, NLR, and MLR were positively correlated with SOFA scores, while PNI and PLR were reversed. Furthermore, CAR, NLR, MLR, PLR, and SII were higher and PNI was lower in the non-survivor group. Therefore, our study revealed that these new biomarkers are closely related to IC, and the disease severity and clinical outcomes of ICU patients. In addition, multivariate logistic regression analysis showed that high NLR (OR: 2.608, 95% CI: 1.212–5.609, p = 0.014) and high CAR (OR: 1.952, 95% CI: 1.045–3.646, p = 0.036) were independent risk factors for IC. Therefore, NLR and CAR may be potential biomarkers for IC.

The most common mycosis in ICU patients is IC (Pappas et al., 2018). The risk factors for IC are closely related to the patient’s physical condition, disease, and iatrogenic treatment. At present, common risk factors for IC include long-term use of corticosteroids, broad-spectrum antibiotics, TPN, indwelling CVC, any type of dialysis, invasive mechanical ventilation, and surgery (Pappas et al., 2018; Martin-Loeches et al., 2019). ICU patients are more likely to be exposed to these risk factors, which leads to a higher incidence of IC in ICU patients. Our study also demonstrated that TPN and broad-spectrum antibiotic were independent risk factors for IC. As for TPN, lipid and glucose contained in nutrient solutions could propagate biofilm formation of Candida spp. (Kuwahara et al., 2010). Furthermore, blocked intestinal peristalsis leads to changes in the intestinal epithelial barrier function and promotes the translocation of intestinally attached Candida into the bloodstream (Pierre, 2017). Broad-spectrum antibiotics would increase the colonization rate of Candida spp. and change the interaction between bacteria and fungi, leading to enhanced pathogenicity of Candida (Guinan et al., 2019). In addtion, our study found that sepsis is a risk factor for IC. Previous studies have suggested that patients with sepsis are more likely to receive long-term antibiotics and invasive medical devices, which are definite risk factors for IC (Meng et al., 2017; Wang et al., 2021). Moreover, sepsis induces immune paralysis, predisposing the host to Candida infection (Jung et al., 2021).

Based on traditional BDG, combined biomarker NLR, CAR, and classical clinical risk factors (sepsis, TPN, broad-spectrum antibiotic, and SOFA), we established a bedside risk-scoring model for predicting the risk of IC. The model performed excellently with an AUC of 0.883 in the development cohort and was well validated in the validation cohort (AUC = 0.892). The estimated score was highly positively related to the actual risk of IC. Furthermore, the discriminative value of our scoring model was higher than that of the Candida scoring system. The above parameters included in the model are available, economical, and reliable in clinical practice and are usually included in routine admission examinations among ICU patients. Thus, this scoring model can be extensively used, even in grassroots hospitals. Therefore, it is convenient for physicians to evaluate the risk of IC for patients at the bedside.

However, our study has some limitations. First, this was a single-center retrospective study; therefore, we lacked another hospital validation cohort to validate our scoring system. However, the validation in our study exhibited a satisfactory AUC and calibration in both the development and validation cohorts, even with a higher discriminative value than the Candida score. Second, although the scoring system can early and accurately diagnose IC among ICU patients, the clinical benefits of the clinical management strategy based on our scoring system need to be confirmed. In the future, a larger prospective cohort involving multicenter hospitals is needed to evaluate the clinical performance of our scoring system.

In conclusion, our results demonstrated that NLR, CAR, and PNI were significantly associated with IC and disease severity in immunocompetent critically ill patients. We established a parsimonious score based on NLR, CAR, clinical risk factors (sepsis, TPN, broad-spectrum antibiotic), SOFA, and BDG, which can diagnose IC in immunocompetent ICU patients early and accurately to guide clinical physicians to initiate antifungal therapy at an early stage and improve the prognosis of IC.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving human participants were reviewed and approved by the Ethics Committee of the Xiangya Hospital, Central South University (No. 202104005). Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.

YL and PP conceived, supervised the study and approved the final version of manuscript. YL revised the manuscript. PP provided funds. WL and GC analyzed data, prepared figures, tables and drafted the manuscript. FL and HY provided codes for statistical analysis. YC, RL, CS, and HL collected data. All authors read and approved the final manuscript.

This study was supported by Key R&D Program of Hunan Province (No. 2022SK2038), Project Program of National Clinical Research Center for Geriatric Disorders (Xiangya Hospital, Grant No. 2020LNJJ05), National Natural Science Foundation of China (No. 82000089, No. 82100100 and No. 82200099), Hunan Natural Science Youth Foundation (No.2022JJ40810 and No. 2022JJ40775), The National Key Clinical Specialist Construction Programs of China (No. z047-02), Scientific research project of Hunan Health Commission (No. 202103020612) and Science and Technology Projects in Guangzhou (No. 202201010012).

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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