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Combination of serum and peritoneal 1.3-beta-d-glucan can rule out intra-abdominal candidiasis in surgical critically ill patients: a multicenter prospective study

Abstract

Background

Intra-abdominal candidiasis (IAC) is difficult to predict in critically ill patients with intra-abdominal infection, leading to the overuse of antifungal treatments. Serum and peritoneal 1.3-beta-d-glucan (sBDG and pBDG) have been proposed to confirm or invalidate the diagnosis of IAC, but clinical studies have reported inconsistent results, notably because of heterogeneous populations with a low IAC prevalence. This study aimed to identify a high-risk IAC population and evaluate pBDG and sBDG in diagnosing IAC.

Methods

This prospective multicenter noninterventional French study included consecutive critically ill patients undergoing abdominal surgery for abdominal sepsis. The primary objective was to establish the IAC prevalence. The secondary objective was to explore whether sBDG and pBDG could be used to diagnose IAC. Wako® beta-glucan test (WT, Fujifilm Wako Chemicals Europe, Neuss, Germany) was used for pBDG measurements. WT and Fungitell® beta-d-glucan assay (FA, Associate of Cape Cod, East Falmouth, USA) were used for sBDG measurements.

Results

Between 1 January 2020 and 31 December 2022, 199 patients were included. Patients were predominantly male (63%), with a median age of 66 [54–72] years. The IAC prevalence was 44% (87/199). The main IAC type was secondary peritonitis. Septic shock occurred in 63% of cases. After multivariate analysis, a nosocomial origin was associated with more IAC cases (P = 0.0399). The median pBDG level was significantly elevated in IAC (448 [107.5–1578.0] pg/ml) compared to non-IAC patients (133 [16.0–831.0] pg/ml), P = 0.0021. For a pBDG threshold of 45 pg/ml, the negative predictive value in assessing IAC was 82.3%. The median sBDG level with WT (n = 42) at day 1 was higher in IAC (5 [3.0–9.0] pg/ml) than in non-IAC patients (3 [3.0–3.0] pg/ml), P = 0.012. Similarly, median sBDG level with FA (n = 140) at day 1 was higher in IAC (104 [38.0–211.0] pg/ml) than in non-IAC patients (50 [23.0–141.0] pg/ml), P = 0.009. Combining a peritonitis score < 3, sBDG < 3.3 pg/ml (WT) and pBDG < 45 pg/ml (WT) yielded a negative predictive value of 100%.

Conclusion

In critically ill patients with intra-abdominal infection requiring surgery, the IAC prevalence was 44%. Combining low sBDG and pBDG with a low peritonitis score effectively excluded IAC and could limit unnecessary antifungal agent exposure.

Trial registration: The study was registered with ClinicalTrials.gov (ID number 03997929, first registered on June 24, 2019).

Graphical abstract

Take-home message

  • Critically ill patients with nosocomial secondary peritonitis and a peritonitis score ≥3 are a population of interest for intra-abdominal candidiasis studies, with a prevalence of 44%.

  • The combination of serum and peritoneal 1.3-beta-d-glucan with the peritonitis score emerged as a potent strategy for effectively excluding intra-abdominal candidiasis and thereby minimizing unnecessary exposure to antifungal agents.

Introduction

Intra-abdominal candidiasis (IAC) is defined by the detection of Candida in peritoneal fluid obtained through direct puncture, intraoperative sampling, or drainage from an intra-abdominal drain inserted in the past 24 h, along with compatible signs and symptoms of intra-abdominal infection [1, 2]. The definitive diagnosis of IAC relies on the isolation of Candida species through conventional mycological culture. IAC carries a cumulative incidence of 1.84 cases per 1000 intensive care unit (ICU) admissions [3] and is associated with a mortality rate of up to 60% [4].

IAC is difficult to predict in critically ill patients with intra-abdominal infection and could lead to delayed [4] or excessive use of antifungal treatments [5]. Indeed, conventional culture could take several days to yield results [6]. Considering the worse prognosis of patients with delayed introduction, antifungals are usually introduced before the results of the culture are obtained, based on clinical scores or context. However, none of the current clinical scores are able to identify patients at risk for IAC, leading to antifungal overuse [5, 7]. Unnecessary antifungal exposure has been associated with increased antifungal resistance, including against echinocandins, the first class used for IAC treatment [8].

To optimize the diagnosis of IAC, the measurement of 1.3-beta-d-glucan (BDG) in the serum (sBDG) and peritoneal fluid (pBDG) has gained interest [9,10,11,12]. BDG is a crucial constituent of the cell wall of various fungal species, including Candida. In IAC, sBDG is associated with a negative predictive value (NPV) ranging from 70 to 90% [13, 14], and two measurements in 48 h are needed. For pBDG, three studies have reported higher concentrations in IAC patients than in non-IAC individuals [10,11,12]. However, the statistical significance of these differences in pBDG concentrations has not been consistently established. In addition, the actual prevalence of IAC in these studies was < 30%. Thus, the literature does not provide a definitive conclusion regarding the utility of pBDG in confirming or excluding IAC.

Furthermore, all these studies employed the Fungitell® beta-d-glucan assay (FA, Associate of Cape Cod, East Falmouth, Inc., United States of America) for pBDG measurement. The Wako® beta-glucan test (WT, Fujifilm Wako Chemicals Europe, Neuss, Germany) has not been assessed in this context before. The WT has been validated for both serum and plasma matrices. This BDG test is technically less complex to operate than the FA (Fungitell assay) and is simpler to execute and interpret [15]. Therefore, it is plausible that the WT would be more suitable for the medium represented by peritoneal fluid.

The present study sought to identify a high risk of IAC in critically ill patients and to evaluate pBDG measurements using the beta-glucan test from Wako® for the diagnosis of IAC. This study aimed to address some of the limitations of prior research, such as patient population heterogeneity and insufficient confirmed IAC cases, which can introduce bias and ambiguity into the results [16].

Material and methods

Study design: setting

This was a French prospective multicenter noninterventional study conducted at four tertiary teaching hospitals (Dijon, Metz, Nancy and Strasbourg). The protocol for the pBDG2 study has been previously published [17] and summarized in the Fig. 1.

Fig. 1
figure 1

Study design and inclusion criteria. Abbreviations: BDG: 1.3 beta-d-glucan; IAC: intra-abdominal infection; IAI: intra-abdominal infection. Risk factors according to [19,20,21,22], Peritonitis score according to [23]

The initial recruitment period spanned from January 1st, 2020, to December 31st, 2021. However, due to the COVID-19 outbreak, this period was subsequently extended by 1 year. The management of patients and their anti-infective strategies were left to the discretion of the attending physicians but were required to adhere to the current guidelines for the management of invasive candidiasis [18, 19].

Participants

Critically ill adult patients with an intra-abdominal infection that necessitated surgical intervention and risk factors IAC [19,20,21,22] were included consecutively (Fig. 1).

The primary focus of the study was the diagnostic assessment of pBDG, and consequently, patient follow-up was limited to their duration of stay in the ICU.

Gold standard test for the diagnosis of IAC

The definition of IAC relied on positive culture findings of peritoneal fluid collected under sterile conditions for Candida species. The assessment of Candida growth was conducted using Sabouraud chloramphenicol medium (BioMerieux, Craponne, France) at a temperature of 35 ± 2 °C. Additional species identification was carried out employing mass spectrometry, and the cultures were retained for a period of up to 8 days.

Serum and peritoneal BDG.

Serum (sBDG) concentrations were collected on Day 1 and Day 3 following abdominal surgery, aligning with established expert guidelines [24] (see Additional file 1 for details of the test used).

For pBDG, any residual peritoneal fluid after routine analysis was preserved at each center using BDG-free containers at a temperature of − 20 °C until the conclusion of the recruitment period. Subsequently, all these samples were shipped to the Nancy Center, where BDG measurements using the WT were conducted between May and June 2023.

Objectives

The primary objective was to estimate the prevalence of IAC in the studied population. The secondary objectives were (1) to compare the pBDG concentrations between patients with and without IAC, (2) to identify the risk factors associated with the development of IAC, (3) to assess the diagnostic accuracy of pBDG for the early detection of IAC, using Candida culture as the reference standard, and (4) to assess the diagnostic performances of pBDG, both alone and in combination with sBDG and the peritonitis score, to assess the presence of IAC. sBDG results were considered negative (indicating a low risk of IAC) when levels were less than 80 pg/ml (using FA) or less than 3.3 pg/ml (using WT) on two consecutive measurements, according to the literature [25, 26].

Data collection

We collected data on demographics, comorbidities, type of intra-abdominal infection, and IAC management from electronic medical records during patients' ICU stays (see Additional file 1 for details). Previous Candida colonization was defined as the isolation of Candida in cultures obtained from ≥ 2 of the following sources: respiratory tract secretions, stool, skin, wound sites, urines, and drains that have been in place for 24 h or less [1].

Statistical analysis

According to the literature, the prevalence of IAC in severe intra-abdominal infection is estimated to be between 20 and 40% [10, 27]. The expected prevalence of IAC in our sample was 30%, based on our previous study [10]. The inclusion of 200 patients enabled us to estimate this expected prevalence with an absolute precision of 6.5%.

Descriptive statistics were used to summarize the baseline characteristics of the study population, including counts and percentages for categorical variables and the mean ± standard deviation or median [interquartile range/IQR] for continuous variables, depending on the data distribution. Statistical tests such as the chi-squared or Fisher’s exact tests were employed to compare categorical variables, while the nonparametric Mann‒Whitney U test and Kruskal‒Wallis test were used for continuous variables. The prevalence of IAC was calculated based on Candida culture results, along with the 95% confidence interval.

Regarding the secondary objectives, initial sBDG and pBDG concentrations were compared using the Wilcoxon test. Risk factors for IAC were identified through bivariate logistic regression. Factors with a significance threshold of 0.10 were considered candidates in a multivariable regression model, with significance defined as a P value of < 0.05 in two-sided tests.

To assess the diagnostic performance of pBDG, a receiver operating characteristic (ROC) curve analysis was conducted, and a new cutoff value was determined, considering the highest Youden index (sensitivity + specificity − 1). For sBDG, analyses were performed based on the test used and previously published thresholds [25]. All statistical analyses were carried out by an independent biostatistician using SAS v9.4 (SAS Institute, Inc., Cary, NC), with a significance level of P < 0.05.

Results

Demographic and characteristics

Figure 2 illustrates the study’s flow chart.

Fig. 2
figure 2

Flow chart of the study

Table 1 presents the clinical characteristics of the 199 patients included in the analysis. Patients were predominantly male (63%), with a median age of 66 [54–72] years. Intra-abdominal infections were community-acquired in 27% of cases (n = 54).

Table 1 Critically ill patients clinical characteristics

Antibiotic exposure for more than 72 h prior to surgery and a peritonitis score ≥ 3 were significantly more common in the IAC group (P = 0.003 and P = 0.03, respectively). One-third of the cohort was considered immunocompromised, mainly due to active solid tumors (n = 52/77). Two-thirds of the patients were admitted to the ICU for urgent intra-abdominal infection, with secondary peritonitis accounting for 96% of cases (n = 192), originating primarily from the colon (n = 71/36%) and small bowel (n = 67/33%). Surgery was predominantly performed by laparotomy (n = 184/92%). Approximately 64% (n = 123) of cases received antibiotic therapy before surgical incision. Eight patients received antifungal treatment before surgery.

During and after surgery, an antifungal treatment was started for 127 patients (64%) primarily empirically (74% of cases). In the IAC group, 30 patients (35%) received antifungal treatment after Candida documentation. Regarding the non-IAC group, 42 patients (37%) received unnecessary antifungal therapy. All patients received an echinocandin as empirical therapy, which was de-escalated to fluconazole in 47% of cases. The overall median duration of antifungal therapy was 8 [8] days in the IAC group versus 5 [3,4,5,6,7,8] days in the non-IAC group (P < 0.0001). The median ICU length of stay was 8 [4,5,6,7,8,9,10,11,12,13,14] days, and the ICU mortality rate was 14% (n = 27).

Primary objective

The prevalence of IAC was 44% (n = 87/199; 95% CI [37–51]). There was no statistically significant difference in Candida risk factors between the two groups except for prior antibiotic exposure longer than 72 h (Table 1). A total of 101 Candida-positive species were recovered from the 87 PF samples: 65 C. albicans, 19 C. glabrata, 7 C. tropicalis, 4 C. kefyr, 3 C. krusei, and 2 C. parapsilosis. The IAC was polymicrobial in 72% (n = 63) of cases. The most encountered bacteria were Escherichia coli and Enterococcus faecalis (see Additional file 1: Table S1 for the whole bacterial documentation). Direct examination for yeast was positive for 34 patients (17%). There were only 3 cases of candidemia (3%).

Secondary objectives

Peritoneal BDG

pBDG results (Fig. 3A) were obtained for 196 PF samples, among which 72 (36%) displayed values higher than 600 pg/ml (the upper limit of the calibration curve). The median pBDG concentration was significantly higher in patients with IAC (448 [107.5–1578.0] pg/ml) than in those without IAC (133 [16.0–831.0] pg/ml) (P = 0.0021). The median pBDG levels depending on the results of the peritoneal fluid culture (bacteria, sterile) are provided in aDditional file 1: Fig. S1. Among the risk factors for IAC, after multivariate analysis, a pBDG level ≥ 284 pg/ml and the nosocomial origin of the patient were significantly associated with the presence of IAC (OR 2.5 [1.3–4.5]; P = 0.003) and OR 2.1 [1.2–3.9]; P = 0.014), respectively (see Additional file 1: Tables S3/S4).

Fig. 3
figure 3

Serum and peritoneal 1.3 beta-d-glucan concentrations in IAC patients versus non-IAC. A Box and whiskers with median, 10 and 90% percentile of peritoneal BDG between confirmed IAC and non-IAC patients (Wako® beta-glucan test, Fujifilm Wako Chemicals Europe, Neuss, Germany). Dotted line represents the threshold of 45 pg/ml. B Box and whiskers with median, 10 and 90% percentile of serum BDG measured with the Wako® beta-glucan test (Fujifilm Wako Chemicals Europe, Neuss, Germany) at Day 1 between confirmed IAC and non-IAC patients. Dotted line represents the threshold of 3.3 pg/ml (WT). C Box and whiskers with median, 10 and 90% percentile of serum BDG measured with the Fungitell® beta-d-glucan assay (FA, Associate of Cape Cod, East Falmouth, Inc., United States of America) at Day 1 between confirmed IAC and non-IAC patients. Dotted line represents the threshold of 80 pg/ml (FA). Abbreviations: IAC: intra-abdominal candidiasis; BDG: 1.3 beta-d-glucan; WT: Wako® beta-glucan test (Fujifilm Wako Chemicals Europe, Neuss, Germany); FA: Fungitell® beta- d-glucan assay (Associate of Cape Cod, East Falmouth, Inc., United States of America)

Serum BDG

Using the WT (n = 42, Fig. 3B), in IAC patients, the median sBDG concentration was significantly higher than that in non-IAC patients, measuring 5 [3.0–9.0] pg/ml versus 3 [3.0–3.0] pg/ml, P = 0.012. Patients with sBDG < 3.3 pg/ml had a significantly lower occurrence of IAC (P = 0.004).

Using the FA (n = 140, Fig. 3C), in IAC patients, the median sBDG concentration was significantly higher than that in non-IAC patients, measuring 104 [38.0–211.0] pg/ml versus 50 [23.0–141.0] pg/ml, P = 0.0094. Patients with sBDG < 80 pg/ml had a significantly lower occurrence of IAC (P = 0.087).

The Additional file 1: Fig. S2 shows the distribution of sBDG on Day 1 and 3 in both groups.

Diagnostic performance

The diagnostic performance of pBDG, sBDG, and the peritonitis score is reported in Table 2. Combining diagnostic tests was the best approach to obtain an NPV of 90% (sBDG measured with the FA) and 100% (sBDG measured with the WT) for ruling out IAC.

Table 2 Diagnostic performance of tests used alone and combined considering the Candida culture of peritoneal samples

The ROC curve for the diagnostic performance of pBDG and sBDG in the diagnosis of IAC is shown in Fig. 4. Using a cutoff value of 45 pg/ml (determined by the highest Youden index), the NPV was 82.3%. With this threshold, 9 cases of IAC would have been missed. The time to positivity of the Candida culture in these 9 cases was 4 days.

Fig. 4
figure 4

Peritoneal and serum 1.3 beta-d-glucan to rule out intra-abdominal candidiasis in secondary peritonitis. Receiver operating characteristic curve of peritoneal and serum 1.3 beta-d-glucan for identification of intra-abdominal candidiasis (A—peritoneal BDG (n = 196)/B—serum BDG at Day 1 according to the test used (Wako test® N = 42 and Fungitell® beta-d-glucan assay N = 140). Abbreviations: FA: Fungitell® beta-d-glucan assay (Associate of Cape Cod, East Falmouth, Inc., United States of America); pBDG: peritoneal 1.3 beta-d-glucan; sBDG: serum 1.3 beta-d-glucan; WT: Wako® beta-glucan test (Fujifilm Wako Chemicals Europe, Neuss, Germany)

Discussion

In this large cohort of critically ill patients who had undergone urgent abdominal surgery for intra-abdominal infection, the prevalence of IAC was 44%. The study's findings revealed that a pBDG threshold of 45 pg/ml exhibited an NPV of 82.3% (area under the curve (AUC) of 0.63). When combining peritoneal BDG < 45 pg/ml and low serum BDG with a peritonitis score < 3, the negative predictive value reached an impressive 100%.

No demographic data or Candida risk factors emerged as predictors for IAC in our study, consistent with previous research [7]. Only the nosocomial origin was associated with more IAC occurrences. This could be explained by the high rate of postoperative infection and prior antibiotic exposure in the cohort, two recognized risk factors for IAC [20]. Interestingly, we did not observe a higher rate of supramesocolic origin in the IAC group. This could be attributed to a lower prevalence of gastrointestinal origin (16%) and more colorectal origin. De Ruiter et al. reported high rates of Candida during the initial week of intra-abdominal infection originating from colorectal origin [31], aligning with the timeframe of post-operative peritonitis. Additionally, we noted a balanced distribution of community origin between IAC and non-IAC patients, consistent with previous findings [12, 31, 32]. This underscores the importance of considering community origin when contemplating the initiation of empirical antifungal therapy, particularly in the presence of immunosuppression [19] and/or septic shock [22]. Additionally, because we only included patients with intra-abdominal infection requiring surgery, the prevalence of IAC increased. Indeed, Dupont et al. reported a 30% prevalence of IAC in a population with complicated intra-abdominal infection requiring surgery [11]. In contrast, Nourry et al. included patients with intra-abdominal infection managed by radiology and reported a prevalence of 21% [12]. Recent literature consistently supports the idea of focusing on selected ICU populations when evaluating the diagnostic performance of biomarkers for IAC such as pBDG [1, 9, 21]. Consequently, studying ICU populations that necessitate surgical source control emerges as a promising approach for assessing biomarkers for IAC.

Two studies with an IAC prevalence of 21% reported promising results when measuring pBDG in critically ill patients to rule out IAC [10, 12]. In the first retrospective study including 33 nosocomial secondary peritonitis cases, the authors reported a 98% NPV [10]. Recently, Nourry et al. conducted a prospective study with 113 patients and reported a 100% NPV [12]. In our study using the WT, the NPV of pBDG was notably lower, at 82.3%. First, as the NPV depends on the prevalence of the disease, its value decreases with increasing prevalence. Additionally, it is important to consider that in previous studies, the actual number of patients with IAC whose pBDG concentrations fell below the obtained threshold was low, at 3 patients in the first study and 12 patients in the second study. Furthermore, in the study by Nourry et al., the authors acknowledged that 21 samples had been exposed to antifungal treatment, which could lead to negative fungal culture results and/or reduced yeast quantities [12]. In our study, using pBDG alone with a threshold of 42 pg/ml would have led to nine missed cases. Notably, the mean time to positivity of the Candida culture in these nine cases was four days, suggesting a low inoculum. Thus, the quantity of yeast present might have influenced the diagnostic performance of pBDG.

The pBDG levels were higher in cases of polymicrobial IAC and lower in negative samples, which is consistent with previous findings [10, 12]. Similarly to previous study [4, 31], we reported a high bacterial documentation of 72%. Bacteria, especially gram-negative and enterococci are known to be associated with false-positive results for BDG [33], which could explain the high rate of false-positive peritoneal BDG results observed in our study. With a threshold of ≥ 45 pg/ml, 68 patients would have received unnecessary antifungal treatment.

Thus, we reaffirmed the limited positive predictive performance of both peritoneal and serum BDG. In the ICU setting, numerous confounding factors for sBDG exist, including antibiotics, albumin infusion, and transfusions, among others, which are known to be associated with false-positive results [33]. Additionally, Szyszkowitz et al. highlighted increased levels of sBDG in the peri- and post-operative period, diminishing the significance of its positive value [34]. Conversely, the risk of false-negative values is less likely to occur, particularly in the peritoneal fluid. False negatives are typically caused by a low inoculum or prior exposure to antifungals [35]. In the case of IAC, clinical studies have reported a low rate of antifungal initiation before surgical incision [5], and the peritoneal diffusion of antifungals has been demonstrated to be low (approximately 30%) [36].

The results of our study regarding sBDG differed from previously published data [11]. In the study by Dupont et al., the sBDG determined with the FA showed an AUC of 0.52, P = 0.77, indicating poor diagnostic performance. In our study, both tests demonstrated significantly lower levels of sBDG in non-IAC cases, with reported AUCs of 0.63 and 0.72 for the FA and WT, respectively. Previously, sensitivity values of approximately 70% have been documented for both tests in ICU patients with IAC and no concurrent candidemia [25]. Interestingly, the diagnostic performance of the WT alone and combined with the other markers was superior to that of the FA in our study. Additionally, our study confirmed the superior sensitivity of the WT when using a lower cutoff of 3.3 pg/ml compared to 7 pg/ml, as demonstrated previously in critically ill patients with noncandidemic IAC [25].

While our study has highlighted the limitations of using serum and pBDG and the Peritonitis score as standalone markers for initiating antifungal therapy, it has also emphasized the importance of combining tests to rule out IAC [9, 37]. Specifically, the combination of low pBDG and sBDG with a peritonitis score < 3 demonstrated a sensitivity and NPV of 100% and could be used for discontinuing unnecessary treatment in patients with IAC. In our study, we corroborated the limited performance of the peritonitis score when used on its own [11, 12, 38]. However, its combination with BDG demonstrated the potential to enhance diagnostic efficacy (Additional file 1: Table S6). This assessment tool is not only easy-to-use at the bedside but also cost-effective and globally accessible. Furthermore, the current BDG tests (WT or Fungitell STAT assay®) permit individual patient testing with a swift turnaround time (less than 90 min) [15]. Consequently, an algorithm grounded in the peritonitis score and individual BDG tests could swiftly exclude IAC within two days, averting unnecessary antifungal exposure linked to escalating antifungal resistance and elevated costs [39]. It is noteworthy that this timeframe necessitates further clinical validation in real-life ICU conditions.

The major strengths of our study include its sample size, multicenter nature, and high number of consecutively included patients with pBDG results, allowing for a high prevalence of IAC. Certainly, there are some limitations to consider. Firstly, there is a risk of misclassification between IAC and non-IAC due to the sensitivity of the peritoneal culture. However, all participating centers followed a local protocol that recommended direct inoculation of the peritoneal sample into a favorable culture medium and storage of all cultures for up to 8 days to detect delayed positivity, which helps mitigate this risk to some extent. Secondly, the COVID-19 outbreak affected our study, and we had to extend the inclusion period. However, the management of IAC remained consistent during this time, which should minimize any potential impact on our results. Thirdly, the peritonitis score was the exclusive scoring system employed in this non-interventional study, aligning with the standard practice across all participating centers and in accordance with the French guidelines [19]. Consequently, the assessment of alternative Candida risk factor scores was precluded due to the prevailing routine in the involved centers.

Last, our study did not evaluate patient survival but rather focused on surrogate markers to optimize the detection of Candida in peritoneal fluid. The role of Candida as a true pathogen in IAC is still debated [40, 41], and the effectiveness of antifungal treatment in IAC remains inconclusive in previous studies [4, 42, 43].

Conclusion

In critically ill patients with secondary peritonitis, the IAC prevalence was 44%. Our study advocates for a comprehensive strategy involving a peritoneal BDG measurement below 45 pg/ml (Wako® beta-glucan test), coupled with a Peritonitis score below 3 and low serum BDG levels on day 1, to effectively exclude Candida infection within a span of two days. Nonetheless, further clinical validation in ICU real-life is warranted.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Abbreviations

AUC:

Area under the curve

BDG:

1.3 Beta-d-glucan

FA:

Fungitell® beta-d-glucan assay (Associate of Cape Cod, East Falmouth, Inc., USA)

IAC:

Intra-abdominal candidiasis

ICU:

Intensive care unit

NPV:

Negative predictive value

pBDG:

Peritoneal 1.3 beta-d-glucan

pBDG2:

Prospective evaluation of the interest of 1.3-beta-d-glucan in the peritoneal fluid for the diagnosis of intra-abdominal candidiasis in critically ill patients

ROC:

Receiving operating characteristic

sBDG:

Serum 1.3 beta-d-glucan

WT:

Wako® beta-glucan test (Fujifilm Wako Chemicals Europe, Neuss, Germany)

References

  1. Bassetti M, Azoulay E, Kullberg B-J, et al. EORTC/MSGERC definitions of invasive fungal diseases: summary of activities of the intensive care unit working group. Clin Infect Dis. 2021;72:S121–7. https://doi.org/10.1093/cid/ciaa1751.

    Article  PubMed  Google Scholar 

  2. Montravers P, Dupont H, Eggimann P. Intra-abdominal candidiasis: the guidelines—forgotten non-candidemic invasive candidiasis. Intensive Care Med. 2013;39:2226–30. https://doi.org/10.1007/s00134-013-3134-2.

    Article  PubMed  Google Scholar 

  3. Bassetti M, Giacobbe DR, Vena A, et al. Incidence and outcome of invasive candidiasis in intensive care units (ICUs) in Europe: results of the EUCANDICU project. Crit Care. 2019;23:219. https://doi.org/10.1186/s13054-019-2497-3.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Vergidis P, Clancy CJ, Shields RK, et al. Intra-abdominal candidiasis: the importance of early source control and antifungal treatment. PLoS ONE. 2016;11: e0153247. https://doi.org/10.1371/journal.pone.0153247.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Leroy O, Bailly S, Gangneux J-P, et al. Systemic antifungal therapy for proven or suspected invasive candidiasis: the AmarCAND 2 study. Ann Intensive Care. 2016;6:2. https://doi.org/10.1186/s13613-015-0103-7.

    Article  CAS  PubMed  Google Scholar 

  6. Alves J, Alonso-Tarrés C, Rello J. How to identify invasive candidemia in ICU—a narrative review. Antibiotics (Basel). 2022;11:1804. https://doi.org/10.3390/antibiotics11121804.

    Article  CAS  PubMed  Google Scholar 

  7. Bailly S, Leroy O, Dupont H, Timsit J-F. Secondarily documented invasive candidiasis is unpredictable using traditional risk factors in non transplant—non-neutropenic adult ICU patients. Int J Infect Dis. 2017;54:31–3. https://doi.org/10.1016/j.ijid.2016.11.403.

    Article  PubMed  Google Scholar 

  8. Pristov KE, Ghannoum MA. Resistance of Candida to azoles and echinocandins worldwide. Clin Microbiol Infect. 2019;25:792–8. https://doi.org/10.1016/j.cmi.2019.03.028.

    Article  CAS  PubMed  Google Scholar 

  9. De Pascale G, Martin-Loeches I, Nseir S. Antifungal stewardship in critically ill patients. Intensive Care Med. 2023. https://doi.org/10.1007/s00134-023-07034-7.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Novy E, Laithier F-X, Machouart M-C, et al. Determination of 1,3-β-D-glucan in the peritoneal fluid for the diagnosis of intra-abdominal candidiasis in critically ill patients: a pilot study. Minerva Anestesiol. 2018;84:1369–76. https://doi.org/10.23736/S0375-9393.18.12619-8.

    Article  PubMed  Google Scholar 

  11. Dupont H, Malaquin S, Villeret L, et al. Is ß-d-glucan relevant for the diagnosis and follow-up of intensive care patients with yeast-complicated intra-abdominal infection? J Fungi (Basel). 2022;8:487. https://doi.org/10.3390/jof8050487.

    Article  CAS  PubMed  Google Scholar 

  12. Nourry É, Wallet F, Darien M, et al. Use of 1,3-beta-d-glucan concentration in peritoneal fluid for the diagnosis of intra-abdominal candidiasis in critically ill patients. Med Mycol. 2023;61:myad029. https://doi.org/10.1093/mmy/myad029.

    Article  CAS  Google Scholar 

  13. Tissot F, Lamoth F, Hauser PM, et al. β-glucan antigenemia anticipates diagnosis of blood culture-negative intraabdominal candidiasis. Am J Respir Crit Care Med. 2013;188:1100–9. https://doi.org/10.1164/rccm.201211-2069OC.

    Article  PubMed  Google Scholar 

  14. Kritikos A, Poissy J, Croxatto A, et al. Impact of the beta-glucan test on management of intensive care unit patients at risk for invasive candidiasis. J Clin Microbiol. 2020;58:e01996-e2019. https://doi.org/10.1128/JCM.01996-19.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Fang W, Wu J, Cheng M, et al. Diagnosis of invasive fungal infections: challenges and recent developments. J Biomed Sci. 2023;30:42. https://doi.org/10.1186/s12929-023-00926-2.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Montravers P, Leroy O, Eckmann C. Intra-abdominal candidiasis: it’s still a long way to get unquestionable data. Intensive Care Med. 2015;41:1682–4. https://doi.org/10.1007/s00134-015-3894-y.

    Article  PubMed  Google Scholar 

  17. Novy E, Laithier F-X, Riviere J, et al. Protocol for the pBDG2 study: prospective evaluation of 1.3-β-D-glucan in the peritoneal fluid for the diagnosis of intra-abdominal candidiasis in critically Ill patients. Microbiol Res. 2021;12:196–203. https://doi.org/10.3390/microbiolres12010015.

    Article  Google Scholar 

  18. Martin-Loeches I, Antonelli M, Cuenca-Estrella M, et al. ESICM/ESCMID task force on practical management of invasive candidiasis in critically ill patients. Intensive Care Med. 2019;45:789–805. https://doi.org/10.1007/s00134-019-05599-w.

    Article  PubMed  Google Scholar 

  19. Montravers P, Dupont H, Leone M, et al. Guidelines for management of intra-abdominal infections. Anaesth Crit Care Pain Med. 2015;34:117–30. https://doi.org/10.1016/j.accpm.2015.03.005.

    Article  PubMed  Google Scholar 

  20. Bassetti M, Vena A, Giacobbe DR, et al. Risk factors for intra-abdominal candidiasis in intensive care units: results from EUCANDICU Study. Infect Dis Ther. 2022;11:827–40. https://doi.org/10.1007/s40121-021-00585-6.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Bassetti M, Marchetti M, Chakrabarti A, et al. A research agenda on the management of intra-abdominal candidiasis: results from a consensus of multinational experts. Intensive Care Med. 2013;39:2092–106. https://doi.org/10.1007/s00134-013-3109-3.

    Article  PubMed  Google Scholar 

  22. Sartelli M, Catena F, Abu-Zidan FM, et al. Management of intra-abdominal infections: recommendations by the WSES 2016 consensus conference. World J Emerg Surg. 2017;12:22. https://doi.org/10.1186/s13017-017-0132-7.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Dupont H, Bourichon A, Paugam-Burtz C, et al. Can yeast isolation in peritoneal fluid be predicted in intensive care unit patients with peritonitis? Crit Care Med. 2003;31:752–7. https://doi.org/10.1097/01.CCM.0000053525.49267.77.

    Article  PubMed  Google Scholar 

  24. Cornely OA, Bassetti M, Calandra T, et al. ESCMID* guideline for the diagnosis and management of Candida diseases 2012: non-neutropenic adult patients. Clin Microbiol Infect. 2012;18(Suppl 7):19–37. https://doi.org/10.1111/1469-0691.12039.

    Article  CAS  PubMed  Google Scholar 

  25. Kritikos A, Caruana G, Poissy J, et al. Comparison of three β-glucan tests for the diagnosis of invasive candidiasis in intensive care units. J Clin Microbiol. 2023. https://doi.org/10.1128/jcm.01691-22.

    Article  PubMed  PubMed Central  Google Scholar 

  26. De Carolis E, Marchionni F, Torelli R, et al. Comparative performance evaluation of Wako β-glucan test and Fungitell assay for the diagnosis of invasive fungal diseases. PLoS ONE. 2020;15:e0236095. https://doi.org/10.1371/journal.pone.0236095.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. De Waele J, Lipman J, Sakr Y, et al. Abdominal infections in the intensive care unit: characteristics, treatment and determinants of outcome. BMC Infect Dis. 2014;14:420. https://doi.org/10.1186/1471-2334-14-420.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Knaus WA, Zimmerman JE, Wagner DP, et al. APACHE-acute physiology and chronic health evaluation: a physiologically based classification system. Crit Care Med. 1981;9:591–7. https://doi.org/10.1097/00003246-198108000-00008.

    Article  CAS  PubMed  Google Scholar 

  29. McCABE WR, Jackson GG. Gram-negative bacteremia: I. Etiology and ecology. Arch Intern Med. 1962;110:847–55. https://doi.org/10.1001/archinte.1962.03620240029006.

    Article  Google Scholar 

  30. Singer P, Blaser AR, Berger MM, et al. ESPEN guideline on clinical nutrition in the intensive care unit. Clin Nutr. 2019;38:48–79. https://doi.org/10.1016/j.clnu.2018.08.037.

    Article  PubMed  Google Scholar 

  31. de Ruiter J, Weel J, Manusama E, et al. The epidemiology of intra-abdominal flora in critically ill patients with secondary and tertiary abdominal sepsis. Infection. 2009;37:522–7. https://doi.org/10.1007/s15010-009-8249-6.

    Article  PubMed  Google Scholar 

  32. Blot S, Antonelli M, Arvaniti K, et al. Epidemiology of intra-abdominal infection and sepsis in critically ill patients: “AbSeS”, a multinational observational cohort study and ESICM Trials Group Project. Intensive Care Med. 2019;45:1703–17. https://doi.org/10.1007/s00134-019-05819-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Finkelman MA. Specificity influences in (1→3)-β-d-glucan-supported diagnosis of invasive fungal disease. J Fungi (Basel). 2020;7:14. https://doi.org/10.3390/jof7010014.

    Article  PubMed  Google Scholar 

  34. Szyszkowitz A, Zurl C, Herzeg A, et al. Serum 1,3-beta-d-glucan values during and after laparoscopic and open intestinal surgery. Open Forum Infect Dis. 2018;5:296. https://doi.org/10.1093/ofid/ofy296.

    Article  CAS  Google Scholar 

  35. Lo Cascio G, Koncan R, Stringari G, et al. Interference of confounding factors on the use of (1,3)-beta-d-glucan in the diagnosis of invasive candidiasis in the intensive care unit. Eur J Clin Microbiol Infect Dis. 2015;34:357–65. https://doi.org/10.1007/s10096-014-2239-z.

    Article  CAS  PubMed  Google Scholar 

  36. Maseda E, Martín-Loeches I, Zaragoza R, et al. Critical appraisal beyond clinical guidelines for intraabdominal candidiasis. Crit Care. 2023;27:382. https://doi.org/10.1186/s13054-023-04673-6.

    Article  PubMed  PubMed Central  Google Scholar 

  37. León C, Ruiz-Santana S, Saavedra P, et al. Contribution of Candida biomarkers and DNA detection for the diagnosis of invasive candidiasis in ICU patients with severe abdominal conditions. Crit Care. 2016;20:149. https://doi.org/10.1186/s13054-016-1324-3.

    Article  PubMed  Google Scholar 

  38. Montravers P, Perrigault PF, Timsit JF, et al. Antifungal therapy for patients with proven or suspected Candida peritonitis: Amarcand2, a prospective cohort study in French intensive care units. Clin Microbiol Infect. 2017;23:117.e1-117.e8. https://doi.org/10.1016/j.cmi.2016.10.001.

    Article  CAS  PubMed  Google Scholar 

  39. Logan C, Martin-Loeches I, Bicanic T. Invasive candidiasis in critical care: challenges and future directions. Intensive Care Med. 2020;46:2001–14. https://doi.org/10.1007/s00134-020-06240-x.

    Article  CAS  PubMed  Google Scholar 

  40. Sandven P, Qvist H, Skovlund E, et al. Significance of Candida recovered from intraoperative specimens in patients with intra-abdominal perforations. Crit Care Med. 2002;30:541–7. https://doi.org/10.1097/00003246-200203000-00008.

    Article  PubMed  Google Scholar 

  41. Novy E, Esposito M, Birckener J, et al. Reappraisal of intra-abdominal candidiasis: insights from peritoneal fluid analysis. Intensive Care Med Exp. 2023;11:67. https://doi.org/10.1186/s40635-023-00552-0.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Lagunes L, Borgatta B, Martín-Gomez MT, et al. Predictors of choice of initial antifungal treatment in intraabdominal candidiasis. Clin Microbiol Infect. 2016;22:719–24. https://doi.org/10.1016/j.cmi.2016.06.005.

    Article  CAS  PubMed  Google Scholar 

  43. Dupont H, Paugam-Burtz C, Muller-Serieys C, et al. Predictive factors of mortality due to polymicrobial peritonitis with Candida isolation in peritoneal fluid in critically ill patients. Arch Surg. 2002;137:1341–46; discussion 1347.

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Acknowledgements

All intensivists of the participating centers for patient recruitment. All mycologists of the participating centers: Pierre Vermeulen (Nancy), Louise Basmaciyan and Frédéric Dalle (Dijon), Valérie Bru (Strasbourg), Charlotte Stephan and Pascale Perez (Metz).

Funding

The study was funded by a grant from MSD. The funding source was not involved in the study at any stage, including manuscript preparation. We are grateful to Sobioda® (Montbonnot Saint Martin, France) and Fujifilm Wako® Chemicals Europe (Neuss, Germany) for a discount on the pricing of the kits and devices for the Wako β-glucan test®.

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Authors and Affiliations

Authors

Contributions

EN (conceptualization, investigation, methodology, data curation, data analysis and interpretation, writing-original draft, writing-review and editing), JR (conceptualization, investigation, methodology, data curation), MN and BB (investigation, data curation), GA, SH and JP (investigation, data curation), GL (investigation, data curation), AG (investigation, methodology), FL (conceptualization, investigation), MRL (conceptualization, investigation), AD (data curation, data analysis and interpretation), HR (data management), YB (project administration), CB (methodology), AL (statistical analysis), JB (investigation, data curation), MM (conceptualization, investigation, methodology, data curation, validation, supervision), and PG (investigation, data analysis and interpretation, validation, writing-original draft, writing-review and editing, supervision). AD supervised peritoneal glucan assays.

Corresponding author

Correspondence to Emmanuel Novy.

Ethics declarations

Ethics approval and consent to participate

The pBDG2 study was classified as noninterventional. Consequently, the need for informed consent was waived, and patients or substitute decision-makers were only asked if they declined to participate. The study was conducted according to the guidelines of the Declaration of Helsinki and was approved by the local ethics committee of Nancy, France (N°334). All personal and medical information is being collected and shared in accordance with medical confidentiality as well as French and European regulations regarding data protection. Furthermore, all data are being recorded in a secured database for statistical analysis with deidentification (number of the center, first letter of name and last name).

The study was registered with ClinicalTrials.gov (ID number 03997929, first registered on June 24, 2019).

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Not applicable.

Competing interests

The authors have disclosed that they do not have any conflicts of interest.

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Supplementary Information

Additional file 1:

Combination of serum and peritoneal 1.3-beta-D-glucan can rule out intra-abdominal candidiasis in surgical critically ill patients: A multicenter prospective study. File format: pdf. Including further details on Results with seven tables (Table S1 “Bacteriology data”, S2 “Antibiotic therapy”, S3 “Risk factors for intra-abdominal candidiasis (univariate analysis)”, S4 “Risk factors for intra-abdominal candidiasis (multivariate analysis)”, S5 “Diagnostic performance of different serum and peritoneal beta-d-glucan threshold considering the Candida culture of peritoneal samples”, S6 “Influence of the peritonitis score on the diagnostic performance of serum and peritoneal 1.3 beta-d-glucan”, S7 “Peritoneal 1.3 beta-d-glucan results depending on the community and nosocomial origin of intra-abdominal infection”) and two figures (Figure S1 “Peritoneal 1.3 beta-d-glucan concentrations according to the culture of peritoneal fluid sample”, S2 “Distribution of serum BDG at Day 1 and Day 3 according to the test used”), on the Participating centers, on Methods, and the checklists from STROBE and STARD reporting guidelines.

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Novy, E., Rivière, J., Nguyen, M. et al. Combination of serum and peritoneal 1.3-beta-d-glucan can rule out intra-abdominal candidiasis in surgical critically ill patients: a multicenter prospective study. Crit Care 27, 470 (2023). https://doi.org/10.1186/s13054-023-04761-7

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