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. 2026 Oct 2;16:1952600. doi: 10.3389/fcimb.2026.1952600

Mortality of Candida auris candidemia compared with non-auris candidemia: a systematic review and meta-analysis

Jing Chen 1,†, Na Xiao 1,†, Qian Xiang 1, Yan Luo 1, Hui Wang 1,*,‡, Tian-fen Liao 1,*,‡
PMCID: PMC13672011  PMID: 42890631

Abstract

Background

Candida auris has emerged as a globally significant healthcare-associated fungal pathogen. Although descriptive studies have reported high mortality for candidemia caused by C. auris, whether the mortality differs from non-auris candidemia remains unclear. We conducted this meta-analysis to compare the mortality between patients with C. auris and non-auris candidemia.

Methods

We searched PubMed (including MEDLINE), Embase, and Web of Science databases for relevant studies published before June 2026. A random-effects model was used for meta-analysis.

Results

A total of 16 articles were included in this meta-analysis. In the pooled crude analysis, mortality was significantly lower in patients with C. auris candidemia than in those with non-auris candidemia (OR = 0.77, 95% CI 0.67-0.90). Subgroup analyses showed significant geographic variation (P for interaction = 0.019), with lower mortality observed in studies from Turkey, the Middle East and the Americas, but not in South Asia and Africa. Despite lower mortality, C. auris candidemia was associated with prolonged hospitalization in descriptive analysis.

Conclusion

In this meta-analysis of crude estimates, mortality was significantly lower in patients with C. auris candidemia than in those with non-auris candidemia. However, prolonged hospitalization in C. auris infection highlights its medical resource burden. For clinicians, management of C. auris candidemia should focus on timely diagnosis, appropriate antifungal therapy, and strengthened infection prevention, especially in cases of long-term hospitalization.

Keywords: bloodstream infection (BSI), Candida auris, candidemia, meta-analysis, mortality

Introduction

Candidemia remains a common healthcare-associated infection that can lead to poor prognosis, prolonged hospitalization, and increased medical costs, and has become a global public health concern (Magill et al., 2014). Despite advances in antifungal therapy, the mortality rate of candidemia remains high, overall exceeding 30% and reaching up to 40% in intensive care unit (ICU) patients (Kang et al., 2017; Koehler et al., 2019). The risk of developing candidemia is closely tied to healthcare exposure and impaired host defenses, with broad-spectrum antibacterial use, central venous catheters, major surgery, total parenteral nutrition and prolonged ICU stay considered as risk factors (Kullberg and Arendrup, 2015; Pappas et al., 2018). Once candidemia develops, advanced age, greater illness severity, and delayed or inadequate antifungal therapy are associated with severe disease and increased mortality (Pappas et al., 2018). In the past, Candida albicans was the main pathogen of candidemia. However, the epidemiological characteristics seem to have changed in recent years, with an increasing incidence of invasive infections caused by non-albicans Candida species, which urgently needs attention (Deorukhkar et al., 2014; da Matta et al., 2017; Schroeder et al., 2020; Kitaya et al., 2023). In this case, Candida auris becomes an emerging pathogen that can cause healthcare-associated infections. Since its first identification in 2009, Candida auris has caused multiple outbreaks globally and has become a major public health concern due to its multidrug resistance and high transmissibility (Satoh et al., 2009; Schelenz et al., 2016; Mulet Bayona et al., 2020; Liu et al., 2024; Cornely et al., 2025). For example, a persistent intensive care unit outbreak in the United Kingdom from 2015 to 2017 was terminated only after removal of the temperature probes, and a European tertiary care hospital reported 41 invasive candidaemia during 2016-2017 (Eyre et al., 2018; Ruiz-Gaitan et al., 2018). Unlike other Candida species, C. auris exhibits strong capacity for long-term environmental survival, persistent skin colonization, biofilm formation, and resistance to routine disinfection, thereby promoting nosocomial transmission (Sherry et al., 2017; Welsh et al., 2017; Forsberg et al., 2019). Patients can remain colonized with C. auris for weeks to months or longer, often without symptoms (Preventing the Spread of C. auris). This asymptomatic carriage facilitates silent spread within healthcare settings and complicates outbreak control efforts. In 2022, the World Health Organization (WHO) listed C. auris as a priority fungal pathogen of concern (Parums, 2022).

C. auris infection poses a challenge to clinicians due to its difficulties in laboratory identification, antifungal resistance, and ability of environmental persistence and transmission (Welsh et al., 2017). A meta-analysis of cases from different countries between 2009 and 2019 reported that a crude mortality rate of 45% for C. auris candidemia, indicating a high mortality burden in candidemia caused by C. auris (Chen et al., 2020). However, it remains unclear whether mortality associated with C. auris candidemia is higher than that of candidemia caused by non-auris Candida species. Some studies have reported significantly lower 30-day mortality in patients with C. auris candidemia compared to those with non-auris candidemia (Ortiz-Roa et al., 2023; Arslan et al., 2026), while others have found mortality rates comparable to those of candidemia caused by non-auris Candida species (Simon et al., 2023; Gulten et al., 2025). This inconsistency may stem from differences in population characteristics, geographic regions, healthcare settings, medical conditions, and antifungal treatment strategies. Beyond mortality, previous studies have reported several clinical differences between C. auris and non-auris Candida candidemia. Patients with C. auris infection usually have longer hospital stay before infection, higher rates of prior antifungal exposure, higher rates of mechanical ventilation and urinary catheter use (Alvarez-Moreno et al., 2023; Athavale-Wad et al., 2025; Gulten et al., 2025; Arslan et al., 2026). To date, whether C. auris candidemia has a different risk of death compared to other Candida species remains unresolved.

Therefore, we conducted a meta-analysis to compare the mortality rates between patients with C. auris and non-auris Candida candidemia. The primary objective was to compare the mortality rates of candidemia caused by C. auris and non-auris Candida, and the secondary objective was to evaluate the difference in duration of hospitalization between the two groups.

Methods

Search strategy

We systematically searched PubMed (including MEDLINE), Embase, and Web of Science databases for relevant studies up to June 30, 2026. The following keywords were combined to search for literature: (Candida auris or C. auris) and (candidemia or bloodstream infection or fungemia) and (mortality or survival or outcome). The complete search strategies are provided in Supplementary File S1. All identified records were compiled and duplicate records were removed manually before screening. We also scanned the reference lists of the paper to identify additional studies. Two authors independently reviewed these studies, and any disagreements were resolved through discussion and consensus. This review was not prospectively registered on PROSPERO, as a similar protocol had already been registered at the time we attempted to register. Nonetheless, we followed the PRISMA 2020 guidelines to ensure methodological transparency, and the completed PRISMA checklist was provided as Supplementary File S2.

Study selection

Two independent reviewers screened the titles and abstracts of the retrieved search records based on inclusion and exclusion criteria, and then reviewed the full texts of potential eligible articles to confirm their eligibility. The third reviewer resolved any disagreements. Studies were included if they met the following criteria based on the PICOS framework: Population (P): Hospitalized patients diagnosed with microbiologically confirmed candidemia, defined as at least one positive blood culture for Candida species. Intervention/Exposure (I): Candidemia caused by Candida auris. Comparator (C): Candidemia caused by non-auris Candida species, including but not limited to C. albicans, C. glabrata, C. parapsilosis, and C. tropicalis. Outcome (O): The primary outcome was all-cause mortality, reported at any measurable time point (e.g., 30-day, 28-day, 90-day, or in-hospital mortality). The secondary outcome was length of hospital stay. Study design (S): Observational studies (retrospective or prospective cohort studies, case-control studies) or randomized controlled trials that provided comparative data between C. auris and non-auris Candida groups. Studies were excluded if they met one or more of the following criteria: (1) reported only on C. auris colonization or infection at non-bloodstream sites without providing candidemia data; (2) included only a single-group design (C. auris only) without comparison with non-auris; (3) case reports, case series with <10 cases per group, reviews, editorials, or conference abstracts; (4) without sufficient data for analysis; (5) non-English published studies.

Data extraction

Data were extracted independently and cross-checked by two reviewers. Disagreements between the two reviewers were resolved through discussion. If consensus could not be reached, a third reviewer was consulted. The following information was extracted: first author, publication year, the country where the study was conducted, study design, clinical setting, study period, mortality rate of candidemia by C. auris and non-auris, and the definition of outcome. When feasible, corresponding authors were contacted for missing or ambiguous data.

Quality assessment

We assessed the methodological quality of all included studies using the Newcastle Ottawa scale (NOS) for the quality assessment of cohort studies and case–control studies (Stang, 2010). The total score of each article was the sum of all items assessed as positive. Studies were categorized as high quality (7–9 points), moderate quality (4–6 points) and low quality (1–3 points) based on the score.

Statistical analysis

All statistical analyses were performed with Statistical Software-Stata, version 15.0. Odds ratios (ORs) with 95% confidence intervals (CIs) were used as the primary effect measure for all-cause mortality. Crude ORs were used as the primary effect measure because adjusted estimates were not uniformly reported across studies, and using crude ORs ensured a consistent analytical approach and maximized the number of studies available for the primary analysis. Adjusted estimates, where reported, were not pooled due to the heterogeneity in effect measures and adjusted covariates. Crude ORs were derived from 2×2 tables for each study, using the number of events and total patients in each group (C. auris vs. non-auris). For studies that did not report crude event counts but presented Kaplan-Meier curves, mortality data were reconstructed using the method described by Tierney et al. (2007), which extracts time-to-event data from published survival curves. When multiple time points were reported, 30-day mortality was preferentially extracted if available; otherwise, the time point closest to 30 days (e.g., 28-day mortality) was used. To evaluate the impact of pooling different time points of mortality, we performed a sensitivity analysis limited to studies reporting 28-day or 30-day mortality. To improve clinical interpretability, we also performed a sensitivity analysis using risk ratios (RR). The statistical heterogeneity among studies was assessed using Cochran’s Q test and I2 statistic (Higgins and Thompson, 2002). P value of less than 0.10 for Q statistic and I2 greater than 50% was considered as statistically significant heterogeneity. Due to the expected heterogeneity of the included studies, a random-effects model was applied for all analyses. We performed subgroup analysis according to study setting (ICU-only vs. mixed hospital population) and geographic region (Turkey/Middle East vs. Americas vs. South Asia vs. Africa). Funnel plots and Egger regression test were used to evaluate publication bias, and a P value of less than 0.1 was considered indicative of significant publication bias.

Results

Search results

We identified 282 non-duplicate articles in the search. Following title and abstract screening, 29 articles were reviewed for full text. Ultimately, 16 articles were considered eligible and included for further analysis. The literature screening process was shown in Figure 1.

Figure 1.

Flowchart diagram of a study selection process showing: 1,008 records identified, 726 duplicates removed, 282 screened, 253 excluded by title, 29 full-text assessed, 13 excluded for various reasons, and 16 studies included in quantitative analysis.

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Screening and selection process of studies.

Study characteristics

The sixteen included studies were published between 2019 and 2026 (van Schalkwyk et al., 2019; Caceres et al., 2020; Sayeed et al., 2020; Moin et al., 2021; Parak et al., 2022; Alvarez-Moreno et al., 2023; Ortiz-Roa et al., 2023; Simon et al., 2023; Athavale-Wad et al., 2025; Chaari et al., 2025; Choudhury et al., 2025; Gulten et al., 2025; Arslan et al., 2026; Korkusuz et al., 2026; Park et al., 2026; Perez et al., 2026). The characteristics of the included studies were summarized in Table 1. Among these studies, three were conducted in Turkey (Gulten et al., 2025; Arslan et al., 2026; Korkusuz et al., 2026), three in Colombia (Caceres et al., 2020; Alvarez-Moreno et al., 2023; Ortiz-Roa et al., 2023), two in the United States (Simon et al., 2023; Perez et al., 2026), two in Pakistan (Sayeed et al., 2020; Moin et al., 2021), two in India (Athavale-Wad et al., 2025; Choudhury et al., 2025), two in South Africa (van Schalkwyk et al., 2019; Parak et al., 2022), one in Bahrain (Chaari et al., 2025) and one in Northern Emirates (Park et al., 2026). Among the included studies, 7 were multi-center studies (van Schalkwyk et al., 2019; Caceres et al., 2020; Alvarez-Moreno et al., 2023; Ortiz-Roa et al., 2023; Simon et al., 2023; Chaari et al., 2025; Perez et al., 2026), and the remaining 9 were single-center studies (Sayeed et al., 2020; Moin et al., 2021; Parak et al., 2022; Athavale-Wad et al., 2025; Choudhury et al., 2025; Gulten et al., 2025; Arslan et al., 2026; Korkusuz et al., 2026; Park et al., 2026). In terms of study design, 9 were cohort studies (van Schalkwyk et al., 2019; Sayeed et al., 2020; Moin et al., 2021; Ortiz-Roa et al., 2023; Chaari et al., 2025; Choudhury et al., 2025; Korkusuz et al., 2026; Park et al., 2026; Perez et al., 2026) and 7 were case-control studies (Caceres et al., 2020; Parak et al., 2022; Alvarez-Moreno et al., 2023; Simon et al., 2023; Athavale-Wad et al., 2025; Gulten et al., 2025; Arslan et al., 2026). The sixteen studies included a total of 16525 patients with candidemia, comprising 1409 cases of C. auris and 15116 cases of non-auris. Regarding mortality, ten studies reported 30-day mortality directly (Caceres et al., 2020; Sayeed et al., 2020; Parak et al., 2022; Alvarez-Moreno et al., 2023; Ortiz-Roa et al., 2023; Simon et al., 2023; Gulten et al., 2025; Arslan et al., 2026; Korkusuz et al., 2026; Perez et al., 2026); one additional study reported 30-day Kaplan-Meier estimates (Park et al., 2026), from which mortality data were reconstructed using the Tierney method. In addition, two studies reported 28-day mortality (Athavale-Wad et al., 2025; Chaari et al., 2025), two reported in-hospital mortality (van Schalkwyk et al., 2019; Moin et al., 2021), and one reported mortality during ICU stay (Choudhury et al., 2025).

Table 1.

Characteristics of included studies.

Author, year Country Study design Clinical setting Study period (year) Mortality rate (Candida auris/non-auris) Mortality definition
(Simon et al., 2023) USA Multicenter retrospective case-control Mixed 2016-2020 30.1%/38.9% 30-day
(Arslan et al., 2026) Turkey Single-center retrospective case-control ICU 2021-2023 63.3%/78.4% 30-day
(Moin et al., 2021) Pakistan Single-center retrospective cohort Mixed 2020 66.7%/65.0% In-hospital
(Athavale-Wad et al., 2025) India Single-center retrospective case–case study Mixed 2019-2024 36.5%/40.1% 28-day
(Sayeed et al., 2020) Pakistan Single-center retrospective cohort Mixed 2014-2017 62.2%/52.5% 30-day
(Gulten et al., 2025) Turkey Single-center retrospective case-control ICU 2022-2024 54.5%/69.1% 30-day
(Korkusuz et al., 2026) Turkey Single-center retrospective cohort Mixed 2021-2024 48.4%/60.2% 30-day
(Ortiz-Roa et al., 2023) Colombia Multicenter retrospective cohort Mixed 2016-2021 38.1%/51.1% 30-day
(Alvarez-Moreno et al., 2023) Colombia Multicenter prospective case–case study Mixed 2016–2017 31.8%/40.4% 30-day
(Park et al., 2026) Northern Emirates Single-center retrospective cohort Mixed 2019-2025 36.7%/37.5% 30-day
(Parak et al., 2022) South Africa Single-center retrospective case-control Mixed 2015-2018 42.2%/44.4% 30-day
(van Schalkwyk et al., 2019) South Africa Multicenter retrospective surveillance Mixed 2016-2017 45.1%/42.5% In-hospital
(Choudhury et al., 2025) India Single-center retrospective cohort ICU 2020-2023 31.6%/34.5% ICU mortality
(Perez et al., 2026) USA Multicenter retrospective cohort Mixed 2015-2024 29.6%/32.5% 30-day
(Chaari et al., 2025) Bahrain Multicenter retrospective cohort ICU 2022-2024 66.7%/87.5% 28-day
(Caceres et al., 2020) Colombia Multicenter retrospective case-case study ICU 2015-2016 42.5%/40.0% 30-day
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Study quality

Among the included studies, twelve studies had high quality (van Schalkwyk et al., 2019; Caceres et al., 2020; Parak et al., 2022; Ortiz-Roa et al., 2023; Simon et al., 2023; Athavale-Wad et al., 2025; Chaari et al., 2025; Gulten et al., 2025; Arslan et al., 2026; Korkusuz et al., 2026; Park et al., 2026; Perez et al., 2026), while the remaining four studies had moderate quality (Sayeed et al., 2020; Moin et al., 2021; Alvarez-Moreno et al., 2023; Choudhury et al., 2025)(Supplementary Figure S1).

Overall mortality

In the pooled crude analysis of all 16 studies, the mortality rate was significantly lower in the C. auris group compared with the non-auris group (OR = 0.77, 95% CI 0.67-0.90; I2 = 18.2%), with a low heterogeneity among these studies (Figure 2). In the sensitivity analysis limited to the 13 studies reporting 28-day or 30-day mortality, the pooled OR was 0.75 (95% CI: 0.65-0.87), consistent with the primary analysis and confirming the robustness of the results. A sensitivity analysis using RR yielded a pooled RR of 0.87 (95% CI 0.81-0.93), consistent with the primary OR estimate. At the individual study level, three studies reported significantly lower mortality in the C. auris group (Ortiz-Roa et al., 2023; Arslan et al., 2026; Korkusuz et al., 2026), while the remaining thirteen studies showed non-significant trends toward lower mortality or comparable mortality between groups (van Schalkwyk et al., 2019; Caceres et al., 2020; Sayeed et al., 2020; Moin et al., 2021; Parak et al., 2022; Alvarez-Moreno et al., 2023; Simon et al., 2023; Athavale-Wad et al., 2025; Chaari et al., 2025; Choudhury et al., 2025; Gulten et al., 2025; Park et al., 2026; Perez et al., 2026). No study reported a significant increase of mortality in the C. auris group.

Figure 2.

Forest plot showing individual and pooled odds ratios with 95 percent confidence intervals for sixteen studies, each represented by a square and horizontal line, with effect sizes scattered around one and an overall pooled odds ratio of zero point seventy-seven (zero point sixty-seven to zero point ninety) depicted by a diamond at the bottom. Study weights are listed on the right, and heterogeneity is low with I-squared equal to eighteen point two percent.

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Forest plot for mortality in C. auris vs. non-auris candidemia.

Subgroup analyses

Subgroup analyses were conducted by study setting and geographic region to explore potential sources of heterogeneity. According to the study setting, both ICU-only studies (k = 5; OR = 0.61, 95% CI 0.42-0.89) and mixed hospital population studies (k = 11; OR = 0.82, 95% CI 0.72-0.94) showed lower mortality in the C. auris group, with no significant difference between groups (P = 0.142) (Figure 3). The heterogeneity of both subgroups was low (I2 = 0%).

Figure 3.

Forest plot showing odds ratios with ninety-five percent confidence intervals for ICU and mixed hospital studies, grouped by subgroup and overall effect, with diamonds representing pooled effects and a vertical reference line at one.

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Forest plot of subgroup analysis for mortality in C. auris vs. non-auris candidemia stratified by study setting.

Geographic differences were observed. The mortality rate of C. auris group in Turkey/Middle East (k = 5; OR = 0.57, 95% CI 0.44-0.74) and the Americas (k = 5; OR = 0.80, 95% CI 0.68-0.95) was significantly lower, but there was no significant difference in South Asia (k = 4; OR = 0.98, 95% CI 0.68-1.40) and Africa (k = 2; OR = 1.06, 95% CI 0.75-1.50) (Figure 4). The test for subgroup difference was statistically significant (P = 0.019), and the heterogeneity of all regional subgroups was low (I2 = 0%).

Figure 4.

Forest plot graphic depicting odds ratios and confidence intervals by region—Turkey and Middle East, Americas, South Asia, and Africa—summarizing individual studies and subgroup analyses. Each study is represented by a black diamond and horizontal line indicating the confidence interval, with larger shaded boxes signifying higher weight. Subgroup and overall effects are displayed as blue diamonds; the overall pooled odds ratio is 0.77 with a 95 percent confidence interval of 0.67 to 0.90. Vertical line at one indicates no effect, and study weights are shown in the right column.

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Forest plot of subgroup analysis for mortality in C. auris vs. non-auris candidemia stratified by geographic region.

Publication bias

Publication bias was assessed using the Egger regression test, and no publication bias was found in the analysis (P = 0.634).

Length of hospital stay

Seven studies reported comparative data on length of hospital stay (LOS), including four in mixed hospital settings (total LOS) (van Schalkwyk et al., 2019; Sayeed et al., 2020; Parak et al., 2022; Ortiz-Roa et al., 2023) and three in ICU-only settings (ICU LOS) (Chaari et al., 2025; Choudhury et al., 2025; Arslan et al., 2026).Due to the difference in reporting methods of LOS, no quantitative summary analysis was conducted for this outcome. Among four studies reporting total LOS, three demonstrated significantly longer hospitalization in the C. auris group (van Schalkwyk et al., 2019; Sayeed et al., 2020; Parak et al., 2022), while one showed no significant difference (Ortiz-Roa et al., 2023). Three studies conducted only in ICU showed longer ICU stays in the C.auris group, with two of them reaching statistical significance (Chaari et al., 2025; Arslan et al., 2026). Overall, the above studies suggested a trend toward prolonged hospitalization in the C. auris group, although the results should be interpreted with caution.

Discussion

In this meta-analysis, we included 16 comparative studies involving 16,525 patients from 8 countries. The pooled crude analysis showed that the mortality was significantly lower in patients with C. auris candidemia than in those with non-auris candidemia, with low heterogeneity. This finding provides updated and quantified evidence on the comparative mortality of C. auris and non-auris candidemia.

These findings challenge the prevailing perception that C. auris carries a higher mortality risk than other Candida species. Previous systematic review reported that C. auris candidemia had a high crude mortality rate, but no comparative analysis had been conducted with non-auris species (Chen et al., 2020; Kim et al., 2024). Our study addresses this gap by pooling comparative studies and provides the first quantitative estimate of the relative mortality effect. In the crude analysis, the C. auris group had lower mortality than the non-auris group. Several possible mechanisms may explain the lower mortality rate observed in the C. auris group. Firstly, the increased clinical awareness of antifungal drug resistance and outbreak potential of C. auris may lead to earlier suspicion, faster diagnostic evaluation, and timely initiation of empirical antifungal therapy. Secondly, the detection of C. auris often triggers more active clinical management, including stricter contact precautions and enhanced environmental disinfection, which may indirectly improve patient prognosis. Thirdly, comparative animal models have suggested that C. auris may have lower virulence than C. albicans (Du et al., 2020). This reduced virulence is attributed to the inability of C. auris to form hyphae or pseudohyphae, which play an important role in invading tissues during infection (Yue et al., 2018).

Subgroup analysis showed that both ICU-only and mixed hospital populations studies had lower mortality in the C. auris group compared with the non-auris group, with no significant between-group difference. This consistency supports the robustness of our primary findings and suggests that the lower mortality observed in the C.auris group may not be limited to specific clinical environments. Another subgroup analysis observed significant geographical differences. In the crude analysis, the mortality rate of C. auris candidemia in Turkey/Middle East and the Americas was significantly lower than that of non-auris, while there was no significant difference in South Asia and Africa. This difference may reflect differences in epidemiological background, healthcare infrastructure, population characteristics, and the distribution of phylogenetic clades. Currently, C. auris contains six major phylogenetic clades related to geographic regions, among which Clade 1, 3, and 4 exhibit high levels of antifungal resistance (Lockhart et al., 2017; Forgacs et al., 2020; Suphavilai et al., 2024). Interestingly, South Asia clade (clade I) is the most common clade in Turkey/Middle East and Americas (Hu et al., 2021; Erkose Genc et al., 2024; Parnell et al., 2026). In Turkey and Middle East, where several studies were conducted during institutional outbreaks of C. auris, the combination of active surveillance and empiric echinocandin use may have contributed to the observed lower mortality (Erturk Sengel et al., 2023; Alanazi et al., 2025). In South Asia and Africa, the absence of significant differences in mortality rates may reflect limited clinical awareness, inadequate diagnostic ability, and restricted access to effective drugs. However, these interpretations remain speculative and should be confirmed by future studies.

Although mortality was lower with C. auris candidemia in the crude analysis, studies that reported length of stay consistently showed prolonged hospitalization. This may reflect the persistence of C. auris colonization, the need for prolonged antifungal therapy to achieve microbial clearance, and the time required for implementation of infection control measures before patient discharge, including single-room contact isolation, strict hand hygiene, dedicated medical equipment, active surveillance, and enhanced environmental disinfection. However, this finding should be interpreted with caution, as survivor bias may partly account for the observed longer length of hospital stay-patients who survive longer have the opportunity to be observed for longer hospital stays. Nevertheless, prolonged LOS also has an important impact on healthcare costs and bed resource utilization.

Several limitations of our study should be taken into consideration. Firstly, most of the included studies were retrospective observational studies, and none of them were randomized controlled trials. Although the heterogeneity was low, unmeasured or residual confounding factors could not be excluded. The lack of uniform individual patient-level data precluded adjustment for baseline differences in disease severity, comorbidities (e.g., diabetes mellitus, severe kidney disease, cardiovascular disease, and respiratory diseases), antifungal therapy, and hospital-related factors, the reporting of which varied across studies. In addition, the primary analysis was based on crude ORs, as adjusted effect estimates were not consistently reported across the included studies. Only a few studies reported adjusted estimates, and the covariates used for adjustment varied considerably, making a pooled analysis of adjusted estimates methodologically unreliable. Therefore, our findings represented crude associations rather than independent effects of C. auris candidemia on mortality. Secondly, the definition of mortality varied depending on the study (30-day, 28-day, or in-hospital mortality). Although we prioritized 30-day mortality when available, the heterogeneity in outcome definitions might introduce some variability. However, sensitivity analysis limited to 28-day or 30 day mortality yielded consistent results, suggesting that the heterogeneity in mortality definitions did not materially affect the primary findings. Thirdly, the species composition of the non-auris comparator groups varied across studies. Furthermore, the non-auris control group comprised various Candida species, among which C. albicans, C. glabrata, C. parapsilosis, and C. tropicalis were the most common. Future large scale, prospective, and multicenter studies are needed to clarify the prognostic differences between C. auris and different non-auris Candida species.

In conclusion, this meta-analysis suggests that the pooled crude mortality was significantly lower in patients with C. auris candidemia compared with those with non-auris candidemia. However, this unadjusted association does not imply that C. auris candidemia independently has a lower risk of mortality. The prognosis of C. auris infection is likely shaped by a complex interplay of host, pathogen, and healthcare system factors. Nevertheless, C. auris remains a major public health concern due to its transmissibility, environmental persistence, and multidrug resistance. Clinicians should recognize that for the management of C. auris, early suspicion, timely diagnosis, appropriate antifungal treatment, and strengthened infection prevention measures should be emphasized, and prolonged hospitalization and resource utilization should be anticipated. Future research is needed to further validate these findings and clarify the optimal management strategies for C.auris candidemia.

Acknowledgments

JC contributed to the study design and concept. JC, and NX completed the article evaluation and data extraction and drafted the initial manuscript. QX and YL contributed to the statistical analysis. TL and HW supervised the work. All authors read and approved the final manuscript.

Funding Statement

The author(s) declared that financial support was not received for this work and/or its publication.

Footnotes

Edited by: Zhi-Kai Yang, Guangzhou Medical University, China

Reviewed by: Shiori Kitaya, Kanazawa University Hospital, Japan

Sagarika Panda, Institute of Medical Sciences and Sum Hospital, India

Anda Baicus, Carol Davila University of Medicine and Pharmacy, Romania

Data availability statement

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

Author contributions

JC: Conceptualization, Data curation, Writing – original draft. NX: Writing – original draft. QX: Formal Analysis, Writing – review & editing. YL: Writing – review & editing. HW: Writing – review & editing, Supervision. TL: Supervision, Writing – review & editing.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that generative AI was not used in the creation of this manuscript.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fcimb.2026.1952600/full#supplementary-material.

Supplementary Figure 1

Study quality assessment.

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Supplementary File S1

Search Strategies.

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Supplementary File S2

PRISMA Checklist.

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Table1.docx (11.8KB, docx)
Table2.docx (267.7KB, docx)

References

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Figure 1

Study quality assessment.

Image1.png (315.6KB, png)
Supplementary File S1

Search Strategies.

Image1.png (315.6KB, png)
Supplementary File S2

PRISMA Checklist.

Image1.png (315.6KB, png)
Table1.docx (11.8KB, docx)
Table2.docx (267.7KB, docx)

Data Availability Statement

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

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