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Introduction
The 2019 global coronavirus (COVID-19) pandemic has led to a crisis in many health and health care areas. The clinical course of the disease ranges from mild upper respiratory tract disease to acute respiratory distress syndrome (ARDS), needing mechanical respiratory support and hospitalization in an intensive care unit (ICU) (Arastehfar et al. 2020a). Critically ill patients with COVID-19 admitted to the ICU become susceptible to bacterial and ICU fungal pathogens that cause hospital-acquired infections (da Silva et al. 2019). A high mortality rate for COVID-19 patients co-infected with pathogenic fungi has been reported (Arastehfar et al. 2020b).
Candida species cause 8–10% of all bloodstream infections (Wisplinghoff et al. 2004). Candidemia occurs in approximately 30–35% of critical care patients (Méan et al. 2008). High Acute Physiology and Chronic Health Assessment (APACHE) II score, use of broad-spectrum antibiotics, accompanying bacterial infection, parenteral nutrition, diabetes mellitus (DM), kidney failure, pancreatitis, hemodialysis, mechanical ventilation, a central vascular catheter (CVC), and immunosuppressive therapy are well-known risk factors for hospital candidemia (Mermutluoglu et al. 2016). There is growing evidence that the incidence of candidemia is higher after COVID-19 than before COVID-19 (Nucci et al. 2021). The mortality rate is high in COVID-19 patients with candidemia. In spite of anti-fungal treatment, mortality reached 83% (Villanueva-Lozano et al. 2021).
Candiduria is common in inpatients, and the development of infection is due to colonization by perineal or catheter Candida species, and a cure is not required (Revankar et al. 2011). Treatment is recommended only in immunocompromised individuals and patients with the anatomical disease (Pappas et al. 2016). The simultaneous existence of Candida species in blood and urine may mean the diffusion of infection through the same entrance portal. However, it can also be two independent situations (Drogari-Apiranthitou et al. 2017).
Understanding the etiological factors and antifungal susceptibility of COVID-19 patients with candiduria and candidemia is crucial for the optimal management of COVID-19 patients. This study was conducted in the hope of improving patient outcomes. It was planned to determine the risk factors, Candida species antifungal susceptibility, and distribution of the species in COVID-19 patients who developed candiduria and candidemia.
Experimental
Materials and Methods
This study was performed in COVID-19 ICUs of a Health Sciences University Kayseri City Hospital and was approved by the Health Sciences University Kayseri City Hospital Ethics Committee. This retrospective study included patients older than 18 hospitalized in the intensive care unit (ICU) with a definitive diagnosis of COVID-19 for seven months (30 March 2021 to 30 September 2021).
In routine clinical follow-up, a standardized patient form was used to track COVID-19 patients, all laboratory and clinical characteristics of the patients, diurnal changes in their clinical condition, and treatments managed. Data for this study were recorded prospectively. Intensive care specialists followed all patients in ICU up diurnal until death or recovery.
The patient form included demographic characteristics (gender, age, weight, and height), and underlying comorbidities of the patients (diabetes mellitus, hypertension, coronary artery disease, chronic/acute renal failure, chronic obstructive pulmonary disease, neurological disease, malignancy, transplantation, goiter and other diseases), radiological information, and laboratory test results. Culture outcomes were monitored closely. Invasive procedures, including urinary catheter, invasive mechanical ventilation, a central venous catheter (CVC), total parenteral nutrition (TPN), and other risk factors for candidemia and candiduria, were recorded. In addition, antibiotics, corticosteroids, anti-cytokine therapy, and immunosuppressive drugs were recorded. Furthermore, length of ICU stay, length of hospital stay, Sequential Organ Failure Assessment (SOFA) score (Jones et al. 2009), Acute Physiology and Chronic Health Assessment (APACHE) II score (Knaus et al. 1985), mortality rates, and identification of Candida species, and their antifungal susceptibility were recorded.
Patients with Candida growth in urine and blood cultures during their hospitalization were identified by querying the pathogen database maintained by the Mycology Department. COVID-19 was described based on positive real-time polymerase chain reaction (PCR) (Bioeksen, Turkey) tests and computed tomography (CT) images for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).
Study definitions. Patients with both candidemia and candiduria were identified and diagnosed with COVID-19. Patients with at least one Candida strain isolated in their blood and urine cultures 48 hours after acceptance to the intensive care unit were included in the study. Candidemia was defined as a blood culture positive for Candida species; candiduria was defined as a urine culture positive for Candida species with ≥ 10,000 CFU/ml. If more than one of the same agents was isolated in the blood culture taken from a patient simultaneously, this was considered as a single growth. Patients with candiduria were identified and analyzed for study variables. Positive urine cultures within one week before the reproduction date of the patients with Candida growth in their blood cultures were recorded. Patients with candidemia were defined as group 1, with candiduria as group 2, while patients with no candidemia/candiduria during their hospital stay were reported as group 3. Patients with candidemia in the urine cultures taken before Candida species growth in the blood culture were defined as group 4.
Case/ control matching. A control group was determined by randomly selecting one out of four ordinary patients with a diagnosis of COVID-19. They were accepted to a tertiary pandemic intensive care unit, had no reported candidemia/candiduria during their hospital stay, and were for whom complete clinical data was available (Group 3). Groups 1 and 2 were compared with group 3, the control group, in terms of all variables recorded for the study.
Mycological examination. Blood samples sent from various hospital departments to the microbiology laboratory were incubated in the BacT/ Alert 3D Automation System (bioMérieux, France). When a positive signal was obtained from the BACTEC automatic blood culture system, inoculation was made from vials in which yeast cells from Sabouraud Dextrose Agar (SDA; Oxoid, England) culture media (without or with antibiotics) were seen by Gram-staining. The isolates were identified by the germ tube test and VITEK® 2 (bioMérieux, France), and morphological images were obtained for the isolates grown on Tween-80-corn-meal agar. The guidelines for in vitro susceptibility of Candida species were taken from the Clinical and Laboratory Standards Institute document M27-A3 (CLSI 2008).
All isolates were cultured using SDA (Oxoid, United Kingdom). These isolates were tested for susceptibility against fluconazole (FLC), amphotericin B (AMB), caspofungin (CAS), and voriconazole (VRC) by the E-test (bioMérieux, France). Minimal inhibitory concentrations (MICs) of azole were the lowest concentrations providing an 80% reduction in growth. MICs of AMB were determined as the lowest concentration inhibiting any growth. MICs were also determined by the E-test method according to the manufacturer’s guidelines. E-test strips of FLC (0.016–256 μg/ml), AMB (0.002–32 μg/ml), CAS (0.002–32 μg/ml), and VRC (0.002–32 μg/ml) were placed perpendicular to each other on an RPMI 1640 medium (Sigma Chemical Company, USA) plate. In both tests, quality control was performed by the CLSI document M27-A3, using Candida parapsilosis ATCC® 22019™ and Candida krusei ATTC® 6258™ (CLSI 2008).
Statistical analysis. Histogram, Q-Q plots, and Shapiro-Wilk’s test were applied to assess the data normality. Levene’s test was used to test variance homogeneity. To compare the demographic and clinical parameters among the study groups, one-way analysis of variance (ANOVA) or Kruskal-Wallis H tests were applied for continuous variables, while Pearson chi-square analysis or Fisher-Freeman-Halton test were used for categorical variables. Bonferroni adjusted Dunn’s test, and Bonferroni adjusted z tests were performed for multiple comparison analysis. The risk factors of candidemia in Covid-19 patients were identified by univariate and multiple binary logistic regression analysis. Significant variables at p < 0.25 contingency level were included to the multiple models, and forward elimination was performed using Wald statistics to identify the independent risk factors of candidemia. The Hosmer-Lemeshow test and Nagelkerke’s R2 statistics assessed the model’s goodness-of-fit. Analyses were conducted using the statistical software of TURCOSA (Turcosa Analytics Ltd Co, Turkey, www.turcosa.com.tr) A p-value less than 5% was considered statistically significant.
Results
Of the 5,583 COVID-19 patients followed during the study period, 78 developed candidemia, and 189 developed candiduria. The incidence of candidemia (per 1,000 admissions) was determined to be 1.6. Within the specified period, 78 COVID-19 patients with Candida growth in a total of 89 blood cultures were defined as group 1, and 189 COVID-19 patients with Candida growth in 209 urine cultures were defined as group 2. Randomly selected COVID-19 patients, who did not grow Candida in their cultures, formed a total of 57 patients in the control group, group 3. 42 candidemia patients with Candida growth in urine culture before Candida growth in blood culture were named as group 4.
There were significant differences in gender and age between group 1, group 2, and group 3. Male gender dominated in group 3, which had a lower mean age (p < 0.05). When group 1 and group 2 were compared with group 3 longer length of stay in hospital and ICU was statistically significant (p < 0.05). There was no difference between the groups concerning APACHE II, SOFA scores, and mortality. Central venous catheter use was higher in the Candida growing groups (especially femoral catheters). The use of catheters was statistically significant for both candidemia and candiduria and was determined to be a risk factor. In the candiduria and candidemia groups, HT, goiter, malignancy, and neurological disease were more common than in the control group (p < 0.05). Mortality in group 1 and group 2 was higher than in group 3. However, this difference was not statistically significant. Intubation was less in the control group than in the other groups (p < 0.05). The use of broad-spectrum antibiotics (BSA), corticosteroids, and total parenteral nutrition (TPN) were also higher in the Candida growing groups (p < 0.05). Interleukin 6 (IL 6) receptor inhibitor use was higher in the candidemia group, but this difference was not statistically significant. Antifungal use was found to be 34 (43.5%) and 95 (50.2%) in groups 1 and 2, respectively. In the candidemia group, mortality was found to be relatively high (77.2%) in patients who did not use antifungals. Anti-fungal use reduced mortality in the candiduria group (Group 2). This difference in mortality was statistically significant (p < 0.05) (Table I). While the p-value in the last column expressed the comparison between groups, the p-value in the bottom represented the comparisons of AF+/ mortality and AF-/ mortality for each group.
Comparison of the demographic and clinical characteristics among the study groups.
Variable
Groups
p†
Group 1 (n = 78)
Group 2 (n = 189)
Group 3 (n = 57)
Gender (male)
54 (69.2)a
87 (46)b
29 (50.9)b
0.002
Age (year)
71.33 ± 13.67ab
73.42 ± 11.34a
68.51 ± 15.74b
0.035
APACHE II score
12 (7–19)
12 (7–19)
14 (9–19)
0.485
SOFA score
4 (2–6)
4 (2–6)
4 (3–6)
0.334
Hospital stay (day)
27 (18–43)a
22 (15–32)b
18 (13–26)b
< 0.001
ICU stay (day)
19 (10–27)a
14 (8–22)ab
10 (7–15)b
< 0.001
PCR (positive)
50 (64.1)
128 (67.7)
36(63.1)
0.889
Comorbidities
66 (84.6)a
162 (85.7)a
28(49.1)b
< 0.001
DM
23 (29.4)
70 (37)
16(28)
0.305
HT
30 (38.4)ab
97( 49.7)a
17 (29.8)b
0.008
COPD
14 (17.9)a
35 (18.5)a
3 (5.2)b
0.049
CAD
23 (29.4)
40 (21.1)
8 (14)
0.093
Malignancy
10 (12.8)a
15 (7.9)a
0 (0.0)b
0.022
Goitre
6 (7.7)a
2 (1.0)b
1 (1.7)ab
0.010
Kidney transplantation
0 (0.0)
2 (1.0)
0 (0.0)
0.487
Immunological disease
3 (3.8)
2(1.0)
0 (0.0)
0.142
Neurological disease
13 (16.6)a
30 (15.8)a
2 (3.5)b
0.044
CKF/AKF
14 (17.9)
26 (13.7)
6 (10.5)
0.226
Mortality
54 (69.2)
133 (60.4)
33 (57.8)
0.208
Intubation
49 (62.8)a
107 (85.2)a
21 (36.8)b
0.008
Central Catheter
42 (53.9)a
58 (30.7)b
7 (12.2)c
< 0.001
Juguler
13 (30.9)
18 (31.0)
4 (57.1)
0.139
Femoral
23 (54.7)
31 (53.4)
2 (28.5)
< 0.001
Dialysis
6 (14.2)
9 (15.5)
1 (14.2)
0.286
BSA
75 (96.1)a
178 (94.1)a
12 (21.0)b
< 0.001
Corticosteroid
49 (62.8)a
142 (75.1)b
15 (26.3)c
< 0.001
IL-6 receptor inhibitors
7 (9.0)
7 (3.7)
3 (5.2)
0.214
TPN
24 (30.8)a
59 (31.2)a
5 (8.7)b
0.003
AF
34 (43.5)
95 (50.2)
–
0.192
AF+/mortality
20 (58.8)
56 (58.9)
–
0.511
AF–/mortality
34 (77.2)
76 (80.8)
–
0.803
p‡
0.080
< 0.001
Values are expressed as n (%), mean ± SD or median (1st–3rd quartiles). Different superscripts among groups indicate a statistically significant difference between groups. Significant results are shown in bold.
p† – significance value for the between-group comparisons, p‡ – significance value for the within-group comparisons
AF– – no antifungal use, APACHE II score – acute physiology and chronic health evaluation score,
SOFA – sequential organ failure assessment score, ICU – intensive care unit, IL-6 – interleukin-6
Response variable categories (0: Control/ Group 3, 1: Candidemia/ Group 1) were taken when performing logistic regression. In the multiple analyses, the OR (95% CI) of ICU stay, comorbidity, and BSA were 1.06 (1.01–1.11), 6.94 (2.01–23.90), and 90.68 (21.84–376.53), respectively. For the built multiple models, Nagelkerke’s R2 statistic was calculated as 0.731. ICU stay, comorbidity, and BSA variables in the multiple models predicted 74.5% of the variability of candidemia. The Hosmer-Lemeshow test resulted as χ2 = 6.247, p = 0.620. These results reveal the built multiple binary logistic regression model’s appropriateness in predicting candidemia in Covid-19 patients (Table II).
Univariate and multiple binary logistic regression analysis in identifying candidemia in Covid-19 patients.
APACHE II score – acute physiology and chronic health evaluation score,
SOFA – sequential organ failure assessment score, ICU – intensive care unit,
OR – Odds ratio, CI – Confidence interval
Of the Candida species (n = 78), 43 (55.1%) were C. albicans, 14 (17.9%) were C. parapsilosis, 9 (11.5%) were Candida tropicalis, 7 (9%) were Candida glabrata, and 5 (6.4%) were other non-albicans Candida in group 1. Of the Candida species in group 2 (n = 189), 123 (65.1%) were C. albicans, 29 (15.3%) were C. parapsilosis, 22 (11.6%) were C. tropicalis, 9 (4.7%) were C. glabrata, and 6 (3.2%) were other non-albicans Candida. 53.8% (n = 42) were patients with Candida growth in their urine culture before Candida growth in the blood (Group 4). Of the Candida species in group 4 (n = 42), 26 (61.9%) were C. albicans, 10 (23.8%) were C. parapsilosis, 3 (7.1%) were C. tropicalis, and 3 (7.2%) were other non-albicans Candida. Candida strains grown in blood and urine were the same in 40 (95.2%) patients.
Fluconazole was the most commonly used antifungal in all groups (Table III). The Intensive Care Special
Candida species distribution and frequency of antifungal use in the study groups.
Total
FLC
CAS
ANI
MIC
AMB
Group 1
n
78
12
11
3
3
5
C. albicans
43 (55.1)
6 (50.0)
5 (45.5)
0 (0.0)
1 (33.3)
3 (60.0)
C. dubliniensi
1 (1.3)
0 (0.0)
0 (0.0)
0 (0.0)
0 (0.0)
0 (0.0)
C. glabrata
7 (9.0)
1 (8.3)
1 (9.1)
1 (33.3)
0 (0.0)
0 (0.0)
C. krusei
3 (3.8)
1 (8.3)
0 (0.0)
0 (0.0)
2 (66.7)
1 (20.0)
C. lusitaniae
1 (1.3)
0 (0.0)
0 (0.0)
0 (0.0)
0 (0.0)
0 (0.0)
C. parapsilosis
14 (17.9)
3 (25.0)
3 (27.3)
1 (33.3)
0 (0.0)
0 (0.0)
C. tropicalis
9 (11.5)
1 (8.3)
2 (18.2)
1 (33.3)
0 (0.0)
1 (20.0)
Group 2
n
189
46
32
9
4
4
C. albicans
123 (65.1)
34 (73.9)
22 (68.8)
7 (77.8)
3 (75.0)
0 (0.0)
C. glabrata
9 (4.7)
1 (2.2)
1 (3.1)
1 (11.1)
1 (25.0)
1 (25.0)
C. kefyr
2 (1.1)
2 (4.3)
0 (0.0)
0 (0.0)
0 (0.0)
1 (25.0)
C. krusei
2 (1.1)
0 (0.0)
1 (3.1)
0 (0.0)
0 (0.0)
0 (0.0)
C. lusitaniae
1 (0.5)
0 (0.0)
1 (3.1)
0 (0.0)
0 (0.0)
0 (0.0)
C. parapsilosis
29 (15.3)
4 (8.7)
3 (9.4)
0 (0.0)
0 (0.0)
1 (25.0)
C. tropicalis
22 (11.6)
5 (10.9)
4 (12.5)
1 (11.1)
0 (0.0)
1 (25.0)
Group 4 (53.8% of candidemia)
n
42
9
6
1
0
3
C. albicans
26 (61.9)
5 (55.6)
4 (66.7)
0 (0.0)
0 (0.0)
3 (100.0)
C. parapsilosis
10 (23.8)
3 (33.3)
2 (33.3)
0 (0.0)
0 (0.0)
0 (0.0)
C. glabrata
1 (2.4)
0 (0.0)
0 (0.0)
1 (100.0)
0 (0.0)
0 (0.0)
C. tropicalis
3 (7.1)
1 (11.1)
0 (0.0)
0 (0.0)
0 (0.0)
0 (0.0)
C. krusei
1 (2.4)
0 (0.0)
0 (0.0)
0 (0.0)
0 (0.0)
0 (0.0)
C. duplensie
1 (2.4)
0 (0.0)
0 (0.0)
0 (0.0)
0 (0.0)
0 (0.0)
Values are expressed as n (%).
FLC – fluconazole, CAS – caspofungin, ANI – anidulafungin, MIC – micafungin, AMB – amphotericin B
ist started all fluconazole treatment empirically. In our hospital, antifungals other than fluconazole are provided with the Infectious Diseases Specialist’s report and added to the treatment according to fungus species from the culture.
The antifungal susceptibility tests for the 78 yeast isolates included in the study are summarized in Table IV, and the relevant MIC values for antifungal resistance were not found against C. albicans, C. tropicalis, or C. parapsilosis and low MICs levels were observed against all antifungal agents. Seven isolates of five C. glabrata specie isolates had dose-dependent sensitivity to fluconazole. Voriconazole was determined to be the most sensitive drug based on antifungal MIC 90 values (Table IV).
Antifungal results against Candida species, reproduced in blood.
VRC μg/ml
FLC μg/ml
CAS μg/ml
AMB μg/ml
Species
GM
MIC50
MIC90
GM
MIC50
MIC90
GM
MIC50
MIC90
GM
MIC50
MIC90
C. albicans (n = 42)
0.42
0.25
0.75
2.42
2
4
0.74
0.75
1
0.59
0.25
1.5
C. parapsilosis (n = 13)
0.39
0.25
0.5
4.07
4
8
1.46
1
2
0.84
0.75
1.5
C. glabrata (n = 7)
0.42
0.47
0.5
22.5
16
48
1.02
1.5
1.5
0.53
0.5
0.75
C. tropicalis (n = 9)
0.35
0.38
0.5
3.22
2
4
0.75
0.5
2
0.91
0.38
2
C. krusei (n = 3)
0.21
0.25
0.38
74.6
64
128
0.75
0.75
1
0.59
0.75
1
VRC – voriconazole, FLC – fluconazole, CAS – caspofungin, AMB – amphotericin B,
GM – geometric mean, MIC – minimal inhibitory concentration
Discussion
This study aimed to determine the risk factors for diagnosed Candida infections in critically ill patients with COVID-19, as well as the epidemiology and anti-fungal sensitivity of isolated Candida species. This study has some limitations; first, it was a retrospective analysis of a single center, and, therefore, was subjected to the limitations of retrospective analysis.
Demographic results, laboratory values, and risk factors for COVID-19 patients who acquired Candida infections in the intensive care unit were examined. A study published 2021 reported that the incidence of candidemia in the COVID-19 period increased two times compared to the pre-COVID-19 period (Kayaaslan et al. 2021). In our study, the incidence of candidemia (per 1,000 admissions) was higher (1.6 in 2021) during the pandemic period than (0.61 in 2019) before. The incidence of candidemia was reported as 2.34 (Omrani et al. 2021), 4.4 (Kayaaslan et al. 2022) episodes per 1,000 ICU days in COVID-19 patients.
When all three groups were compared, and only candidemia cases were evaluated, it was determined that male gender, intensive care and hospital length of stay, intubation, TPN, and central venous catheter use were statistically significant (p < 0.05). It was previously known that endogenous colonization and invasive procedures, such as intubation and catheter use that develop after a prolonged stay in hospital increase, the risk of candidemia (Eggimann et al. 2015). In studies on COVID-19 patients, 70–90% of patients received antimicrobial therapy, and only 10% had fungal or bacterial infections (Lai et al. 2020; Rawson et al. 2020). It was concluded that long-term use of broad-spectrum antibiotics used in intensive care patients with a diagnosis of COVID-19 is a significant risk factor for fungal development (Coşkun and Durmaz 2021). In our study, antibiotic treatment was initiated empirically for each patient, and combined broad-spectrum antibiotics were used. The use of BSA was found to be an independent risk factor for the development of candidemia.
Some studies identified various comorbid conditions and risk factors for the development of candidemia in COVID-19 patients. A study in Brazil revealed that it was associated with chronic obstructive pulmonary disease and candidemia in patients with COVID-19 (Bastos et al. 2020). In another study, the prevalence of candidemia and diabetes mellitus were reported to be important in patients with COVID-19 (Chowdhary et al. 2020). In this study, chronic obstructive pulmonary disease, hypertension, chronic arterial disease, goiter, and malignancy were associated with candidemia and candiduria (p < 0.05). Systemic corticosteroid therapy reduces mortality and improves clinical outcomes in hospitalized patients with COVID-19 (van Paassen et al. 2020). Interleukin-6 receptor antagonists have been shown to be effective in treating patients with COVID-19 with mild and severe cytokine syndrome (Zhang et al. 2020). Corticosteroids are currently the norm of care for patients hospitalized due to COVID-19 and other immunosuppressive agents (e.g., tocilizumab, etanercept (Vallabhaneni and Chiller 2016)) are used in certain groups of subjects, potentially increasing the risk of opportunistic fungal infection (Saha et al. 2020; Segrelles-Calvo et al. 2021; Seagle et al. 2022).
Immunosuppressive agents have been demonstrated to allow the development of viral infections in treated patients, as reported for oncogenic viruses. Indeed, this notion corroborates that the immunosuppressive agents increased the risk of opportunistic fungal infection (Rotondo et al. 2017).
Our study identified corticosteroid use as a risk factor for candidemia and candiduria in patients with COVID-19. Concurrently, we examined the effects of interleukin-6 receptor antagonist (tocilizumab) on the development of fungal infections in our patients. Fourteen patients used tocilizumab, and no relationship was identified between tocilizumab and Candida infections.
Sepsis, including fungal sepsis, is generally defined as life-threatening organ dysfunction caused by dysregulated systemic host inflammatory responses to microbial infection (Esposito et al. 2017). Opportunistic Candida infections activate the inflammasome system. The inflammasome is a large cytoplasmic complex within the innate immune system. It performs the stimulation of inflammatory caspase 1–5. The formation of an inflammasome triggers inflammation. Inflammasome activation also plays a role in the development of programmed lytic cell death (pyronecrosis/pyroptosis). Phagocyte damage may benefit the fungus by host cell lysis (Kasper et al. 2018). Since our study was planned retrospectively, we could not obtain information about the pathogenesis of Candida infections.
Candida species colonize or develop infections in ICU patients when urinary tract catheters are inserted. The simultaneous presence of Candida in blood and urine may mean spreading infection through the same portal of entry (Drogari-Apiranthitou et al. 2017). Candiduria is not a trigger for candidiasis in many ICU patients, but multivariate analyses have confirmed that it is a risk factor for invasive disease (Kauffman 2005; Binelli et al. 2006). In this retrospective study, concurrent candiduria was present in 42 (53.8%) of candidemia. In 40 of 42 cases with positive Candida cultures in the bloodstream and urine, the species involved were the same, but we cannot presume that the portal of infection was the same. The second limitation in our study is the lack of genetic analysis of Candida species isolated from blood and urine.
C. albicans was the most frequently isolated species in Turkey, Greece, and Iran (Arastehfar et al. 2021; Kayaaslan et al. 2021; Kokkoris et al. 2021). A study in India reported that Candida auris species were also encountered in addition to the common species of Candida (Niyas et al. 2021). A study conducted in the United States determined that the most frequently isolated species was the non-albicans Candida (Bishburg et al. 2021). In our study, C. albicans appeared to be the most frequently isolated species in candidemia and candiduria. In particular, three C. krusei and seven C. glabrata were part of the species responsible for candidemia. Epidemiological data on candidemia in COVID-19 patients may differ between countries. Although this could not be fully explained, it was thought that the treatment protocols used by clinics and patient sub-diseases could be effective.
In our study, an E-test was performed for Candida species. The relevant MIC values for antifungal resistance were not found against C. albicans, C. parapsilosis, or C. tropicalis, and low MICs levels were observed against all antifungal agents. Seven isolates of five C. glabrata species isolates had dose-dependent sensitivity to fluconazole. A significant antifungal resistance profile was not found based on the MIC values. Antifungal use was found to be 34 (43.5%), and 95 (50.2%) in groups 1 and 2, respectively. Fluconazole was used as an in vivo anti-fungal in both groups. In the candidemia group, mortality was found to be relatively high (77.2%) in patients, who did not use antifungals. Antifungal use reduced mortality in the candiduria group (Group 2). This difference in mortality was statistically significant (p < 0.05).
The mortality rate was 80% in patients, who developed candidemia and were followed up in the tertiary ICU due to COVID-19 (Coşkun and Durmaz 2021). According to reports from Italy, 50% mortality has been reported in COVID-19 patients with candidemia (Mastrangelo et al. 2021). It has been reported that mortality can be reduced when COVID-19 treatment is combined with specific antifungals against Candida species in severe COVID-19 patients taking immunosuppressant (Segrelles-Calvo et al. 2021). In our study, mortality was 69.2% in group 1, 60.4% in group 2, and 57.8% in group 3. In addition, when we looked at the effect of antifungal use on the groups on mortality, we saw that antifungals reduced mortality (Fig. 1). Especially in group 2, the decrease in mortality was statistically significant (p < 0.05).
Fig. 1
Antifungal (AF) use/mortality graph.
In conclusion, our analysis found that Candida infections in patients with COVID-19 are associated with multifactorial risks. Besides the above risk factors, a certain number of candiduria was found in these patients before the candidemia diagnosis. Based on this result, although we believe that candiduria does not trigger candidemia, we still think that clinicians should keep this in mind, particularly in critical situations. With respect to epidemiological data, C. albicans was the most common species for candidemia and candiduria. Multiple-drug resistance was not found. Ongoing surveillance of Candida infections will be essential to inform changes in epidemiological characteristics and antifungal susceptibility in countries.
