Abstract
Background
Many risk factors, including COVID-19 infection, lead to the development of invasive Candida infection in intensive care unit patients. The aim of this study was to evaluate the risk factors affecting mortality along with the clinical characteristics of candidemia patients.
Methods
This retrospective study was conducted among patients hospitalized at the Anesthesiology and Reanimation Clinic between June 2020 and December 2021. The clinical and laboratory characteristics of 165 patients with candidemia were recorded. The difference between patients with and without COVID-19 infection was evaluated statistically. Multivariate analysis was performed to determine factors affecting mortality.
Results
A total of 165 patients were included in the study, 52.1% of whom were male. The mean age of the patients was 66.5 (median 18–97) years. The percentage of patients with COVID-19 infection was 70.9%. The mean leukocyte count and aspartate transaminase, alanine transaminase, C-reactive protein, lactate dehydrogenase, ferritin, and D-dimer levels were significantly greater in COVID-19 patients than non COVID-19 patients (p < 0.05). The mortality rate in patients with candidemia was 80.2%. The presence of comorbidities, corticosteroid use, advanced age, and high ferritin and D-dimer levels negatively affected mortality, according to the multivariate analysis results. C. albicans was the most frequently isolated Candida species.
Conclusions
We detected higher mortality rates in patients with candidemia who were elderly, had comorbidities, received corticosteroid treatment and had elevated ferritin and D-dimer levels. When steroids are used, it is necessary to remember that this drug is a double-edged sword and to be careful of fungal infections.
Keywords: Candida, Candidemia, COVID-19, Intensive care unit, Mortality
Background
Candidemia is one of the most common nosocomial bloodstream infections leading to increased morbidity and mortality in critically ill patients [1]. The use of broad-spectrum antibiotics, multiple invasive procedures, total parenteral nutrition (TPN) and prolonged intensive care unit (ICU) stay are among the risk factors for the development of candidemia [2].
The COVID-19 pandemic has led to an increased demand for intensive care for patients with severe disease, resulting in a greater burden on intensive care units [1]. Acute respiratory distress syndrome (ARDS) and immune dysregulation caused by the COVID-19 virus, immunosuppressive drugs used for treatment, deficiencies in ICU infection control measures, excessive use of antibiotics, and increased Candida translocation with disruption of the gastrointestinal mucosal barrier may increase the risk of Candida infection in COVID-19 patients [3, 4].
The mortality rate for candidemia patients without COVID-19 infection is typically between 10% and 40%. However, it has been reported that this rate increases to an average of 40–70% in cases of candidemia accompanying COVID-19 infection [4, 5]. This study aimed to identify the factors that contribute to mortality in Candida infection patients and to compare candidemia infections in patients with and without COVID-19 infection.
Methods
Study design
This retrospective study was conducted between June 2020 and December 2021 with 165 patients hospitalized at the Anesthesiology and Reanimation Clinic of Sancaktepe Şehit Prof. Dr. İlhan Varan Training and Research Hospital, which has a total bed capacity of 1600 beds. The study was approved by the Sancaktepe Şehit Prof. Dr. İlhan Varan Training and Research Hospital ethics committee (2021/254).
Patient selection and data collection
The clinical, microbiological, and demographic characteristics of patients aged 18 years and older with nosocomial candidemia were obtained from medical records. The standard forms included demographic information (age and sex) as well as underlying diseases, such as diabetes mellitus, hypertension, chronic renal failure, chronic lung disease, neurological disease, hematological malignancy, and solid organ tumors, as well as immunosuppressive drug use. This study collected information on the use of invasive medical devices, including mechanical ventilation, central venous catheters (CVCs) and urinary catheters, as well as surgical operations, transplantation history, neutropenia, broad-spectrum antibiotics, corticosteroids, and TPN.
This research examined the differences between patients diagnosed with COVID-19 and those who were not. In addition, a statistical analysis was performed to evaluate the factors affecting mortality in patients with candidemia.
Definition
Candidemia is defined as the growth of Candida species in at least one blood culture that develops 48 h after hospitalization in patients with findings compatible with infection [1]. In patients with recurrent Candida growth, the first growth reported in the patient is evaluated. The incidence of candidemia was calculated as the number of episodes per 1000 ICU days. Patients who tested positive for COVID-19 based on PCR or had findings typical of COVID-19 on thorax tomography were diagnosed with COVID-19 disease.
Microbiology
Blood samples from patients were inoculated into BacT/Alert automated blood culture bottles (bioMérieux, France). Positive signals from the bottles were used to passage the samples onto 5% sheep blood agar, Eosin-methylene blue (EMB) agar, and chocolate agar (bioMérieux, France). The samples were then incubated at 37 °C for 24–48 h. Gram staining was performed on the growth medium, and colonies found to be yeast were passaged on Sabouraud dextrose (SDA) agar (bioMérieux, France) and chromogenic agar (bioMérieux, France) and incubated at 37 °C for 24‒48 h. Colonies confirmed to be pure on SDA were processed for identification and examined according to the VITEK® MS (bioMérieux, France) device procedure which uses MALDI-TOF MS method. Identification was concluded by comparing the colonies on the chromogenic media.
Antifungal susceptibility testing was performed in accordance with the Clinical and Laboratory Standards Institute guidelines (CLSI) [6]. Minimal inhibitory concentration (MIC) and antifungal susceptibility results were determined using the Sensititre YeastOne Microdilution method (Thermo Scientific, USA). The Sensititre YeastOne is a colorimetric test. After a 24-hour incubation at 37 °C, MICs of antifungal drugs (amphotericin B, fluconazole, caspofungin, anidulafungin and micafungin) were recorded as per the manufacturer’s protocol. A total of 162 Candida strains were tested. Candida krusei ATCC 6258 and Candida parapsilosis ATCC 22,019 were employed as quality control strains to ensure test accuracy.
Statistical analysis
The means, standard deviations (SDs), numbers and percentages (%) of the measured patient characteristics and descriptive statistics are presented in the tables. The relationships between COVID-19 positivity and mortality status and categorical characteristics were evaluated using the Pearson Chi-square test or Fisher-Freeman-Halton exact test. The Mann‒Whitney U test was used to compare patients who died with those who survived and compare COVID-19-positive patients with COVID-19-negative patients.
Multiple binary logistic regression analysis was used to establish the multivariate model, and the stepwise variable selection method was used to select the variables. A statistical significance level of P < 0.05 was accepted. Calculations were performed using the SPSS (ver. 23) program.
Results
A total of 4507 patients were followed up between June 2020 and December 2021 in the Anaesthesiology and Reanimation Unit. A total of 165 patients who developed candidemia were included in the study, 86 (52.1%) of whom were male. The mean age of the patients was 66.5 (median 18–97) years.
The mean length of stay in the intensive care unit of the patients included in the study was 37.0 days. The incidence rate of candidemia was 3.6% during this period. The mean duration of antifungal treatment was 34.5 days.
Among patients diagnosed with COVID-19, 79.5% (93/117) had both PCR positivity and thoracic CT findings. The rate of patients diagnosed with COVID-19 disease exclusively based on thoracic CT findings was 17.9% (21/117), whereas 2.6% (3/117) had a positive PCR test without thoracic CT involvement.
The rate of COVID-19 positivity was significantly higher in patients admitted to the ICU from internal medicine clinics or after emergency admission than in those admitted from surgical clinics. COVID-19 patients had a significantly greater presence of comorbidities, sepsis, and ARDS. Additionally, the rate of corticosteroid use was significantly greater in COVID-19 patients. On the other hand, COVID-19 patients had a significantly lower history of surgical operation (Table 1).
Table 1.
The effect of COVID-19 disease on categorical variables in patients with candidemia
| Non-COVID-19 patients (n:48) | COVID-19 patients (n:117) | P | ||||
|---|---|---|---|---|---|---|
| n | % | n | % | |||
| Gender | Female | 22 | 27.8 | 57 | 72.2 | 0.736 |
| Male | 26 | 30.2 | 60 | 69.8 | ||
| Clinical follow-up before intensive care unit | Emergency unit | 25 | 33.3 | 50 | 66.7 | < 0.001 |
| Surgery clinic | 11 | 91.7 | 1 | 8.3 | ||
| Internal medicine clinic | 12 | 15.4 | 66 | 84.6 | ||
| Presence of comorbidity | No | 7 | 14.3 | 42 | 85.7 | 0.007 |
| Yes | 41 | 35.3 | 75 | 64.7 | ||
| Diabetes mellitus | No | 37 | 28.0 | 95 | 72.0 | 0.549 |
| Yes | 11 | 33.3 | 22 | 66.7 | ||
| Chronic renal failure | No | 41 | 29.1 | 100 | 70.9 | 0.993 |
| Yes | 7 | 29.2 | 17 | 70.8 | ||
| Hemodialysis | No | 44 | 29.5 | 105 | 70.5 | 0.705 |
| Yes | 4 | 25.0 | 12 | 75.0 | ||
| Chronic lung Disease | No | 35 | 26.9 | 95 | 73.1 | 0.237 |
| Yes | 13 | 37.1 | 22 | 62.9 | ||
| Neurological Disease | No | 34 | 25.8 | 98 | 74.2 | 0.060 |
| Yes | 14 | 42.4 | 19 | 57.6 | ||
| Solid Organ Tumor | No | 43 | 29.3 | 104 | 70.7 | 0.897 |
| Yes | 5 | 27.8 | 13 | 72.2 | ||
| Hematological malignancies | No | 48 | 29.4 | 115 | 70.6 | 0.362 |
| Yes | 0 | 0.0 | 2 | 100.0 | ||
|
History of immunosuppressive drug use |
No | 45 | 30.6 | 102 | 69.4 | 0.219 |
| Yes | 3 | 16.7 | 15 | 83.3 | ||
| Surgical operation (within the last 6 months) | No | 33 | 22.6 | 113 | 77.4 | < 0.001 |
| Yes | 15 | 78.9 | 4 | 21.1 | ||
| History of transplantation | No | 48 | 29.6 | 114 | 70.4 | 0.263 |
| Yes | 0 | 0.0 | 3 | 100.0 | ||
| Total parenteral nutrition | No. | 41 | 28.9 | 101 | 71.1 | 0.878 |
| Yes | 7 | 30.4 | 16 | 69.6 | ||
| Central venous catheter | No | 2 | 11.8 | 15 | 88.2 | 0.097 |
| Yes | 46 | 31.1 | 102 | 68.9 | ||
| Urinary catheter | No | 2 | 50.0 | 2 | 50.0 | 0.351 |
| Yes | 46 | 28.6 | 115 | 71.4 | ||
| Pulmonary embolism | No | 46 | 28.7 | 114 | 71.3 | 0.585 |
| Yes | 2 | 40.0 | 3 | 60.0 | ||
| Acute respiratory distress syndrome | No | 27 | 50.0 | 27 | 50.0 | < 0.001 |
| Yes | 13 | 15.3 | 72 | 84.7 | ||
| Unknown | 8 | 30.8 | 18 | 69.2 | ||
| Sepsis | No | 28 | 42.4 | 38 | 57.6 | 0.002 |
| Yes | 20 | 20.2 | 79 | 79.8 | ||
| Mechanical ventilation | No | 10 | 40.0 | 15 | 60.0 | 0.192 |
| Yes | 38 | 27.1 | 102 | 72.9 | ||
| Broad-spectrum antibiotic use | No | 1 | 12.5 | 7 | 87.5 | 0.290 |
| Yes | 47 | 29.9 | 110 | 70.1 | ||
| Corticosteroid use | No | 30 | 53.6 | 26 | 46.4 | < 0.001 |
| Yes | 18 | 16.5 | 91 | 83.5 | ||
| Tocilizumab Use | No | 47 | 29.9 | 110 | 70.1 | 0.290 |
| Yes | 1 | 12.5 | 7 | 87.5 | ||
| Presence of concurrent bacteremia | No | 30 | 27.5 | 79 | 72.5 | 0.536 |
| Yes | 18 | 32.1 | 38 | 67.9 | ||
| Presence of bacteremia before candidemia |
No Yes |
25 23 |
26.6 32.4 |
69 48 |
73.4 67.6 |
0.417 |
In COVID-19 patients, the duration of central venous catheter use, duration of hospitalization and ICU stay, and total number of antibiotic days were found to be significantly lower, and the duration of corticosteroid use was found to be longer (Table 2).
Table 2.
Risk factors for the development of candidemia according to COVID-19 status
| Non-COVID-19 disease | COVID-19 disease | P | |||||
|---|---|---|---|---|---|---|---|
| n | Mean ± SD | Median | n | Mean ± SD | Median | ||
| Age | 48 | 65 ± 18 | 71 | 117 | 15 ± 56 | 68 | 0.608 |
| Duration of central venous catheter | 48 | 49 ± 43 | 38 | 117 | 24 ± 24 | 18 | 0.001 |
|
Duration of antibiotic use (days) |
47 | 24 ± 16 | 20 | 116 | 19 ± 15 | 14 | 0.007 |
|
Duration of corticosteroid use |
48 | 4 ± 6 | 0 | 117 | 30 ± 236 | 9 | 0.001 |
|
Duration of antifungal treatment (days) |
36 | 34 ± 78 | 13 | 62 | 33 ± 85 | 10 | 0.250 |
| Duration of hospitalization | 48 | 60 ± 45 | 52 | 117 | 40 ± 53 | 26 | 0.001 |
| Length of stay in ICU | 48 | 52 ± 46 | 40 | 117 | 25 ± 27 | 17 | 0.001 |
| Length of stay outside of ICU | 48 | 8.13 ± 15.54 | 0.00 | 117 | 15.06 ± 45.52 | 2.00 | 0.060 |
The mean leukocyte count and aspartate transaminase (AST), alanine transaminase (ALT), C-reactive protein (CRP), lactate dehydrogenase (LDH), ferritin and D-dimer levels were significantly greater in COVID-19 patients (Table 3).
Table 3.
Laboratory results of candidemia patients with and without COVID-19 on the day of the candidemia diagnosis
| Non-COVID-19 disease n = 48 |
COVID-19 disease n = 117 |
|||||||
|---|---|---|---|---|---|---|---|---|
| n | Mean ± SD | Median | n | Mean ± SD | Median | p | ||
| White blood cell (/mm3) | 48 | 11,333 ± 10,602 | 9500 | 117 | 15,663 ± 9633 | 13,030 | 0.001 | |
| Lymphocyte count (/mm3) | 48 | 1110 ± 651 | 1020 | 117 | 1363 ± 1476 | 990 | 0.752 | |
| Platelet count (/mm3) | 48 | 229,042 ± 146,568 | 199,000 | 117 | 209,396 ± 133,573 | 201,000 | 0.445 | |
| Hemoglobin (g/dL) | 48 | 9.029 ± 1.466 | 8.950 | 116 | 9.753 ± 2.455 | 9.500 | 0.092 | |
| Glomerular filtration rate | 48 | 77.999 ± 42.973 | 88.000 | 117 | 63.575 ± 40.10 | 55.000 | 0.050 | |
| Aspartate transaminase (U/L) | 48 | 83.4 ± 242.1 | 27.0 | 117 | 380.3 ± 1252.5 | 44.0 | 0.003 | |
| Alanine transaminase (U/L) | 47 | 50.979 ± 80.876 | 18.000 | 117 | 186.682 ± 490.42 | 32.000 | 0.012 | |
| C-reactive protein (g/L) | 48 | 48.95 ± 68.92 | 17.86 | 117 | 91.24 ± 106.07 | 34.50 | 0.033 | |
| Ferritin (ng/mL) | 45 | 1297.24 ± 2205.01 | 675.00 | 115 | 3793.67 ± 10083.7 | 1235.00 | 0.001 | |
| Lactate dehydrogenase (U/L) | 47 | 379 ± 267 | 322 | 103 | 858 ± 1686 | 477 | 0.001 | |
| D-dimer (mg/L) | 44 | 3.158 ± 3.388 | 2.450 | 115 | 6.407 ± 7.373 | 3.150 | 0.002 | |
Among COVID-19 patients, mortality was significantly greater in those with comorbidities and a history of chronic renal failure. Mortality was also increased in patients with ARDS or sepsis, those requiring mechanical ventilation, and those receiving corticosteroid treatment. Our study revealed a mortality rate of 80.2%. Table 4 shows the factors that affect mortality.
Table 4.
Comparison of risk parameters among survivors and nonsurvivors
| Survivors (n:25) | Nonsurvivors (n:140) | P value | ||||
|---|---|---|---|---|---|---|
| n | % | n | % | |||
| Gender | Female | 12 | 15.2 | 67 | 84.8 | 0.989 |
| Male | 13 | 15.1 | 73 | 84.9 | ||
| COVID-19 disease | No | 14 | 29.2 | 34 | 70.8 | 0.001 |
| Yes | 11 | 9.4 | 106 | 90.6 | ||
| Clinical follow-up before intensive care unit | No | 7 | 9.3 | 68 | 90.7 | 0.063 |
| Surgery | 4 | 33.3 | 8 | 66.7 | ||
| Internal | 14 | 17.9 | 64 | 82.1 | ||
| Presence of comorbidity | No | 13 | 26.5 | 36 | 73.5 | 0.008 |
| Yes | 12 | 10.3 | 104 | 89.7 | ||
| Diabetes mellitus | No | 23 | 17.4 | 109 | 82.6 | 0.103 |
| Yes | 2 | 6.1 | 31 | 93.9 | ||
| Chronic renal failure | No | 25 | 17.7 | 116 | 82.3 | 0.025 |
| Yes | 0 | 0 | 24 | 100 | ||
| Hemodialysis | No | 24 | 16.1 | 125 | 83.9 | 0.296 |
| Yes | 1 | 6.3 | 15 | 93.8 | ||
| Chronic lung Disease | No | 21 | 16.2 | 109 | 83.8 | 0.489 |
| Yes | 4 | 11.4 | 31 | 88.6 | ||
| Neurological disease | No | 23 | 17.4 | 109 | 82.6 | 0.103 |
| Yes | 2 | 6.1 | 31 | 93.9 | ||
| Solid organ tumor | No | 24 | 16.3 | 123 | 83.7 | 0.229 |
| Yes | 1 | 5.6 | 17 | 94.4 | ||
| Hematologic malignancy | No | 25 | 15.3 | 138 | 84.7 | 0.548 |
| Yes | 0 | 0 | 2 | 100 | ||
| Immunosuppressive drug use | No | 25 | 17 | 122 | 83 | 0.058 |
| Yes | 0 | 0 | 18 | 100 | ||
| History of surgical operation (within the last 6 months) | No | 22 | 15.1 | 124 | 84.9 | 0.934 |
| Yes | 3 | 15.8 | 16 | 84.2 | ||
| Transplantation | No | 24 | 14.8 | 138 | 85.2 | 0.375 |
| Yes | 1 | 33.3 | 2 | 66.7 | ||
| ARDS | No | 12 | 22.2 | 42 | 77.8 | 0.010 |
| Yes | 6 | 7.1 | 79 | 92.9 | ||
| Unknown | 7 | 26.9 | 19 | 73.1 | ||
| Sepsis | No | 15 | 22.7 | 51 | 77.3 | 0.027 |
| Yes | 10 | 10.1 | 89 | 89.9 | ||
| Mechanical ventilation | No | 7 | 28 | 18 | 72 | 0.050 |
| Yes | 18 | 12.9 | 122 | 87.1 | ||
| Total parenteral nutrition | No | 24 | 16.9 | 118 | 83.1 | 0.119 |
| Yes | 1 | 4.3 | 22 | 95.7 | ||
| Central venous catheter | No | 3 | 17.6 | 14 | 82.4 | 0.762 |
| Yes | 22 | 14.9 | 126 | 85.1 | ||
| Broad-spectrum antibiotics use | No | 0 | 0 | 8 | 100 | 0.220 |
| Yes | 25 | 15.9 | 132 | 84.1 | ||
| Corticosteroid use | No | 14 | 25 | 42 | 75 | 0.011 |
| Yes | 11 | 10.1 | 98 | 89.9 | ||
| Antifungal treatment initiation | No | 8 | 11.4 | 62 | 88.6 | 0.252 |
The results of the multivariate analysis indicate that the presence of comorbidities, corticosteroid use, advanced age, and elevated ferritin and D-dimer levels are significant factors (Table 5).
Table 5.
Multivariate regression analysis of the risk factors for mortality
| OR | 95% CI for OR | P | ||
|---|---|---|---|---|
| Lower | Upper | |||
| Presence of comorbidity (Yes/No) | 4.550 | 1.109 | 18.672 | 0.035 |
| Corticosteroid use (Yes/No) | 6.530 | 1.613 | 26.431 | 0.009 |
| Age | 1.039 | 0.999 | 1.081 | 0.050 |
| Lymphocyte count | 0.999 | 0.999 | 1.000 | 0.008 |
| Ferritin level | 1.001 | 1.000 | 1.002 | 0.004 |
| D-dimer level | 1.178 | 0.980 | 1.417 | 0.050 |
| Constant | 0.004 | 0.006 | ||
CI: Confidence interval
The most commonly isolated Candida species were C. albicans (49.1%), C. parapisilosis (29.8%), and C. tropicalis (12.1%). One isolate each of C. auris, C. lusitaniae, C. dubliniensis, and C. inconspicua was detected. The antifungal susceptibilities of the isolated Candida species are shown in Table 6. However, no antifungal susceptibility testing was performed for C. auris, C. lusitaniae or C. dubliniensis.
Table 6.
Antifungal susceptibility results for Candida species
| Isolate n (%) |
Fluconazole (%) |
Amphotericin B (%) |
Anidulafungin (%) |
Caspofungin (%) |
Mikafungin (%) |
|
|---|---|---|---|---|---|---|
| C. albicans | 81 (49.1) | 100 | 98.5 | 100 | 100 | 97.1 |
| C. parapsilosis | 49 (29.8) | 77.5 | 100 | 100 | 100 | 100 |
| C. tropicalis | 20 (12.1) | 100 | 100 | 100 | 100 | 100 |
| C. glabrata | 7 (4.2) | 50 | 100 | 100 | 100 | 100 |
| C. kefyr | 4 (2.4) | 100 | 100 | 100 | 100 | 100 |
| C. inconspicua | 1 (0.6) | 0 | 100 | NA | 100 | 100 |
Candida was detected in urine samples from 35.2% of the patients (58/165). A total of 64 isolates, including two different Candida species, were obtained from the urine samples of six patients. The isolates were identified as follows: 56.3% as C. albicans, 18.7% as C. glabrata, 12.5% as C. tropicalis, 7.8% as C. kefyr and 4.7% as C. parapsilosis. The analysis revealed that the presence of candidiuria had no effect on mortality (p = 0.124).
Discussion
Candida spp is a significant cause of bloodstream infections in the ICU and poses a threat to the lives of ICU patients, particularly those with COVID-19 [7, 8]. Candidemia has a high mortality rate in COVID-19 patients, with reports indicating that it can reach 83% [8, 9]. In our study, the mortality rate was 82%, which was high. This may be related to the fact that our hospital serves as a center to which critically ill patients from surrounding hospitals are referred. The additional 1000-bed building of our hospital was built to serve COVID-19 patients as a pandemic hospital. Patients in our study were already critically ill, with 70% also having COVID-19, both of which had a negative impact on mortality outcomes.
In our study, the presence of comorbidities, corticosteroid use and advanced age were found to affect mortality in patients with candidemia. Other studies have reported that advanced age is a risk factor for mortality [1, 10]. The IDSA guidelines recommend steroid use in patients with severe COVID-19, and many patients have shown clinical improvement with this treatment [11]. However, steroids have immunosuppressive effects that increase the risk of Candida infection and worsen the prognosis [1, 12, 13].
In 2004, Tortorano et al. reported candidemia rates ranging from 0.20 to 0.38 per 1000 hospital admissions in a prospective study including seven European countries [14]. The incidence of candidemia has increased 2- to 10-fold during the COVID-19 pandemic because of the use of immunosuppressive drugs to stop the cytokine storm [12, 15–17]. In our study, the incidence of candidemia was 3.6%. The high number of patients infected with COVID-19 in this study also increased the incidence of candidemia.
A study comparing candidemia patients with and without COVID-19 infection reported higher rates of septic shock, total parenteral nutrition, central venous catheter use, corticosteroid therapy, and previous ICU admission in COVID-19 patients [18]. The presence of comorbidities, sepsis, ARDS and corticosteroid use were also found to be significantly greater in COVID-19 patients in our study.
Machado et al. [18] reported that COVID-19 infection rates were higher in patients hospitalized in the ICU and internal medicine clinic prior to the development of candidemia. However, there was no significant difference among patients hospitalized in surgical clinics. Additionally, patients without COVID-19 infection are more likely to have a history of gastrointestinal disease, liver disease, or abdominal surgery [18]. Our study revealed that the rate of COVID-19 positivity was significantly greater in patients admitted to the ICU from internal medicine clinics or after emergency admission than in those admitted from surgical clinics. Additionally, COVID-19 patients had a lower rate of surgical operation history. This finding is likely due to the impact of the COVID-19 pandemic. During the pandemic, hospitals postponed elective operations except for life-threatening emergencies. Physicians in all clinics support the treatment and follow-up of COVID-19 patients [19, 20]. Delaying elective operations for patients with COVID-19 infection reduce pulmonary complications and mortality [21].
In our study, several laboratory tests were more common in COVID-19 patients than in uninfected patients. The leukocyte count was significantly greater in patients with COVID-19 than in those without COVID-19. A high leukocyte count may be related to the prognosis of COVID-19 infection and may also be associated with steroid use [22, 23]. In COVID-19 patients, elevated liver enzyme levels are associated with inflammation and liver damage, which may weaken the immune system and increase the risk of candidemia [24]. Additionally, this relationship may be influenced by the use of corticosteroids in COVID-19 treatment. Therefore, elevated liver enzymes could serve as important markers for the development of candidemia. In cases of candidemia, in addition to heart and eye involvement, liver and spleen involvement may also occur [25]. In our study, no patients were diagnosed with hepatosplenic candidiasis. However, liver enzyme levels are elevated in patients without COVID-19. Given the many potential causes of elevated liver enzymes in intensive care unit patients, this increase should not be directly attributed to candidemia. Nonetheless, our study revealed that liver enzyme levels were elevated in both COVID-19 patients and non-COVID-19 patients, and the difference between these groups was statistically significant.
CRP, ferritin, LDH and D-dimer tests have prognostic value and are used during follow-up in patients with COVID-19 [23, 26, 27]. A study conducted by Beştepe et al. reported that elevated LDH levels were associated with candidemia in patients with severe COVID-19 [28]. In patients admitted to ICU, elevated CRP levels can serve as a predictive marker for candidemia [29]. In the study by Özmerdiven et al., which examined COVID-19-positive and negative patients, CRP levels were significantly greater in patients with COVID-19. Although ferritin and D-dimer levels are also increased in COVID-19 patients, no statistically significant elevation was observed [30]. We found that these levels were elevated in COVID-19 patients and that ferritin and D-dimer levels were significantly greater in patients with candidemia and a fatal outcome.
In critically ill patients with COVID-19, C. albicans is the most commonly isolated yeast species in most studies [31]. In our study, C. albicans was isolated in 49% of cases and was identified as the most frequent cause of candidemia. Dixit D et al. reported that the most common causative agent was C. albicans in 52.7% of 91 patients with COVID-19 and candida infection, and Nucci M et al. reported that the causative agent was C. albicans in 41.5% of patients [17, 32]. The prevalence of candidemia without COVID-19 disease in intensive care unit patients reported by Williams et al. was 0.99%, and the most commonly isolated Candida species was nonalbicans Candida [33].
The prevalence of candiduria in candidemia patients has been reported to range from 8%-44.5% in various studies [1, 34, 35]. In these studies, the prevalence of candiduria was 35.2%. The presence of diabetes mellitus, malignancy, broad-spectrum antibiotic use, nephrostomy and urinary catheters are important risk factors that play a role in the development of candiduria [36]. Candiduria may be a precursor to candidemia. In cases where Candida in the urinary tract spreads to the kidneys by the ascending route, especially in immunosuppressed people [37]. It was reported that patients who develop candidemia as a result of candiduria had lower mortality rates than patients who develop candidemia outside the urinary system did [34]. Similar to other studies, no effect of candiduria on mortality was observed in our study.
The retrospective nature of our study was considered a limitation. The COVID-19 pandemic has caused widespread destruction, resulting in the loss of approximately seven million lives worldwide [32]. The increase in COVID-19 patients during each wave resulted in an increase in the number of ICU beds. This condition has made it challenging to plan prospective studies during the pandemic. The lack of molecular analysis of Candida spp was considered as another limitation of the study.
Conclusions
Candidemia is a serious complication, especially in individuals receiving intensive care. This study revealed that mortality rates were higher among candidemic patients who were elderly, had comorbidities, were receiving corticosteroid treatment, and presented elevated ferritin and D-dimer levels. However, owing to the immunosuppressive properties of corticosteroids, there is a significant risk of developing candidemia. Therefore, patients receiving corticosteroids should be closely monitored for potential candidemia. Additionally, elevated ferritin and D-dimer levels should be considered as potential indicators of increased mortality risk in these patients.
Abbreviations
- ALT
Alanine Aminotransferase
- ARDS
Acute respiratory distress syndrome
- AST
Aspartate transferase
- COVID-19
Coronavirus Disease caused by SARS-CoV-2 virus
- CRP
C- reactive protein
- CVCs
Central venous catheters
- ICU
Intensive care unit
- LDH
Lactate dehydrogenase
- PCR
Polymerase Chain Reaction
- TPN
Total parenteral nutrition
Author contributions
Yılmaz Karadag F and Öztürk Engin D contributed equally to research design, data collection, writing, and manuscript review. Büber AA, Görmüş T, Arslan E, Şabablı Çetin A, Tekin S, Sayan İ, Bayri C, Odabaşı H and Bakan N were responsible for data collection and manuscript review before submission. Ankaralı H performed the formal analysis and manuscript preparation. All authors have read and approved the manuscript.
Funding
There was no specific funding received for this study.
Data availability
The raw data set will be shared with the editor if requested. For those interested in obtaining the study´s raw data for academic purporses, please contact the corresponding author, Fatma Yılmaz Karadağ, at dr_fatma@hotmail.com.Data is provided within related files.
Declarations
Ethics approval and consent to participate
The study was approved by the Sancaktepe Şehit Prof. Dr. İlhan Varan Training and Research Hospital ethics committee (2021/254). All procedures were carried out in conformity with the necessary standards. Permission to use the data in this study was given by the Anesthesiology and Reanimation Clinic.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Kayaaslan B, Eser F, Kaya Kalem A, Bilgic Z, Asilturk D, Hasanoglu I, Ayhan M, Tezer Tekce Y, Erdem D, Turan S, Mumcuoglu I, Guner R. Characteristics of candidemia in COVID-19 patients; increased incidence, earlier occurrence and higher mortality rates compared to non-COVID-19 patients. Mycoses. 2021. 10.1111/myc.13332 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Todd P, McCarty, Cameron M, White, Peter G, Pappas. Candidemia and invasive candidiasis. Infect Dis Clin North Am. 2021. 10.1016/j.idc.2021.03.007 [DOI] [PubMed] [Google Scholar]
- 3.Arastehfar A, Ünal N, Hoşbul T, Alper Özarslan M, Sultan Karakoyun A, Polat F, Fuentes D, Gümral R, Turunç T, Daneshnia F, Perlin DS, Lass-Flörl C, Gabaldón T, Ilkit M, Nguyen MH. Candidemia among coronavirus disease 2019 patients in Turkey admitted to intensive care units: a retrospective multicenter study. Open Forum Infect Dis. 2022. 10.1093/ofid/ofac078 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Buil JB, Schouten JA, Wauters J, van de Hoeven H, Verweij PE, CAC-SDD study group. Absence of candidemia in critically ill patients with COVID-19 receiving selective digestive decontamination. Intensive Care Med. 2022. 10.1007/s00134-022-06651-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Yılmaz Karadağ F, Ergen P, Aydın Ö, Doğru A, Tanıdır B, Vahaboğlu MH. Evaluation of epidemiological characteristics and risk factors affecting mortality in patients with candidemia. Turk J Med Sci. 2016. 10.3906/sag-1505-70 [DOI] [PubMed] [Google Scholar]
- 6.Bouza E, Muñoz P. Epidemiology of candidemia in intensive care units. Int J Antimicrob Agents. 2008. 10.1016/S0924-8579(08)70006-2 [DOI] [PubMed] [Google Scholar]
- 7.Clinical and Laboratory Standards Institute. Performance standards for antifungal susceptibility testing of yeasts. M 60 2nd ed. Wayne: PA, USA: CLSI; 2020. [Google Scholar]
- 8.Arastehfar A, Shaban T, Zarrinfar H, Roudbary M, Ghazanfari M, Hedayati MT, Sedaghat A, Ilkit M, Najafzadeh MJ, Perlin DS. Candidemia among Iranian patients with severe COVID-19 admitted to ICUs. J Fungi (Basel). 2021. 10.3390/jof7040280 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Colaneri M, Giusti EM, Genovese C, Galli L, Lombardi A, Gori A. Mortality of patients with candidemia and COVID-19: a systematic review with meta-analysis. Open Forum Infect Dis. 2023. 10.1093/ofid/ofad358 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Guimarães T, Nucci M, Mendonça JS, Martinez R, Brito LR, Silva N, Moretti ML, Salomão R, Colombo AL. Epidemiology and predictors of a poor outcome in elderly patients with candidemia. Int J Infect Dis. 2012. 10.1016/j.ijid.2012.02.005 [DOI] [PubMed] [Google Scholar]
- 11.Infectious Diseases Society of America (IDSA). https://www.idsociety.org/practice-guideline/covid-19-guideline-treatment-and-management. Accessed 21.01.2023.
- 12.Riche CVW, Cassol R, Pasqualotto AC. Is the frequency of candidemia increasing in COVID-19 patients receiving corticosteroids?? J Fungi. 2020. 10.3390/jof6040286 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Papadimitriou-Olivgeris M, Kolonitsiou F, Kefala S, Spiliopoulou A, Aretha D, Bartzavali C, Siapika A, Marangos M, Fligou F. Increased incidence of candidemia in critically ill patients during the coronavirus disease 2019 (COVID-19) pandemic Braz. J Infect Dis. 2022. 10.1016/j.bjid.2022.102353 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.AM, Tortorano J, Peman H, Bernhardt L, Klingspor CC, Kibbler O, Faure E, Biraghi E, Canton K, Zimmermann S, Seaton. R Grillot; ECMM working group on candidaemia epidemiology of candidaemia in Europe: results of 28-month European confederation of medical mycology (ECMM) hospital-based surveillance study. Eur J Clin Microbiol Infect Dis. 2004. 10.1007/s10096-004-1103-y [DOI] [PubMed] [Google Scholar]
- 15.El-Saber Batiha G, Al-Gareeb AI, Saad HM, Al-Kuraishy HM. Al-kuraishy. COVID-19 and corticosteroids: a narrative review. Inflammopharmacology. 2022. 10.1007/s10787-022-00987-z [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Rajni E, Singh A, Tarai B, Jain K, Shankar R, Pawar K, Mamoria V, Chowdhary A. A high frequency of Candida auris blood stream infections in coronavirus disease 2019 patients admitted to intensive care units, Northwestern India: a case control study. Open Forum Infect Dis. 2021. 10.1093/ofid/ofab452 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Nucci M, Barreiros G, Guimaraes LF, Deriquehem VAS, Castineiras AC, Nouer SA. Increased incidence of candidemia in a tertiary care hospital with the COVID-19 pandemic. Mycoses. 2021. 10.1111/myc.13225 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Machado M, Estévez A, Sánchez-Carrillo C, Guinea J, Escribano P, Alonso R, Valerio M, Padilla B, Bouza E, Muñoz P. Incidence of candidemia is higher in COVID-19 versus non-COVID-19 patients, but not driven by intrahospital transmission. J Fungi (Basel). 2022. 10.3390/jof8030305 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Mehta A, Awuah WA, Ng JC, Kundu M, Yarlagadda R, Sen M, Nansubuga EP, Abdul-Rahman T, Hasan MM. Elective surgeries during and after the COVID-19 pandemic: case burden and physician shortage concerns. Ann Med Surg (Lond). 2022. 10.1016/j.amsu.2022.104395 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Wady H, Restle D, Park J, Pryor A, Talamini M, Abdel-Misih S. The role of surgeons during the COVID-19 pandemic: impact on training and lessons learned from a surgical resident’s perspective. Surg Endosc. 2021. 10.1007/s00464-020-07790-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.COVIDSurg Collaborative. Delaying surgery for patients with a previous SARS-CoV-2 infection. Br J Surg. 2020. 10.1002/bjs.12050 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Frenkel A, Kachko E, Novack V, Klein M, Brotfain E, Koyfman L, Maimon N. The association of glucocorticosteroid treatment with WBC count in patients with COPD exacerbation. J Clin Med. 2019. 10.3390/jcm8101697 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Rai D, Ranjan A, Pandey HA. Clinical and laboratory predictors of mortality in COVID-19 infection: a retrospective observational study in a tertiary care hospital of Eastern India. Cureus. 2021. 10.7759/cureus.17660 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.de Lima IC, de Menezes DC, Uesugi JHE, Bichara CNC, da Costa Vasconcelos PF, Quaresma JAS, Falcão LFM. Liver function in patients with long-term coronavirus disease 2019 of up to 20 months: a cross-sectional study. Int J Environ Res Public Health. 2023. 10.3390/ijerph20075281 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Antinori S, Milazzo L, Sollima S, Galli M, Corbellino M. Candidemia and invasive candidiasis in adults: a narrative review. Eur J Intern Med. 2016. 10.1016/j.ejim.2016.06.029 [DOI] [PubMed] [Google Scholar]
- 26.Tiwari L, Gupta P, Banerjee NY, Kumar A, Singh Y, Ranjan PK, Singh A, Singh CM. Clinicodemographic profile and predictors of poor outcome in hospitalised COVID-19 patients: a single-centre, retrospective cohort study from India. BMJ Open. 2022. 10.1136/bmjopen-2021-056464 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Pink I, Raupach D, Fuge J, Vonberg RP, Hoeper MM, Welte T, Rademacher J. C-reactive protein and procalcitonin for antimicrobial stewardship in COVID-19. Infection. 2021. 10.1007/s15010-021-01615-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Beştepe Dursun Z, Sipahioğlu H, Civan Yüksel R, Sav H, Çelik İ. Risk factors and lethality associated with candidemia in severe COVID-19 patients. Curr Med Mycol. 2022. 10.18502/cmm.8.1.9212 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Altunisik Toplu S, Ersoy Y, Duman Y, Nalan Parmaksiz E, Belin Ozer A, Firat C. The role of procalcitonin and C-reactive protein in predicting candidemia in reanimation intensive care unit and burn unit patients. Annals Med Res. 2021. 10.5455/annalsmedres.2020.12.1158 [Google Scholar]
- 30.Özmerdiven GE, İrvem A, Şahin AS. Risk analysis of candidemia and its effect on mortality in COVID 19 and non COVID 19 patients. Iran J Microbiol. 2024. 10.18502/ijm.v16i2.15357 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Altinkaya Çavuş M, Sav H. Opportunistic Candida infections in critical COVID-19 patients. Pol J Microbiol. 2022. 10.33073/pjm-2022-036 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.World Health Organization Data. https://data.who.int/dashboards/covid19/deaths?n=o. Accessed 18.02.2024.
- 33.William A, Oberoi A, Dsouza D, et al. Prevalence of candidemia with susceptibility pattern in a tertiary care hospital in North India. J Evid Based Med Healthc. 2021. 10.18410/jebmh/2021/201 [Google Scholar]
- 34.Elbaz M, Chikly A, Meilik R, Ben-Ami R. Frequency and clinical features of Candida bloodstream infection originating in the urinary tract. J Fungi (Basel). 2022. 10.3390/jof8020123 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Drogari-Apiranthitou M, Anyfantis I, Galani I, Kanioura L, Daikos GL, Petrikkos G. Association between Candiduria and candidemia: a clinical and molecular analysis of cases. Mycopathologia. 2017. 10.1007/s11046-017-0180-2 [DOI] [PubMed] [Google Scholar]
- 36.Kauffman CA, Vazquez JA, Sobel JD, Gallis HA, McKinsey DS, Karchmer AW, Sugar AM, Sharkey PK, Wise GJ, Mangi R, Mosher A, Lee JY, Dismukes WE. Prospective multicenter surveillance study of Funguria in hospitalized patients. The National Institute for allergy and infectious diseases (NIAID) mycoses study group. Clin Infect Dis. 2000. 10.1086/313583 [DOI] [PubMed] [Google Scholar]
- 37.Kauffman CA, Candiduria. Clin Infect Dis. 2005. 10.1086/430918 [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The raw data set will be shared with the editor if requested. For those interested in obtaining the study´s raw data for academic purporses, please contact the corresponding author, Fatma Yılmaz Karadağ, at dr_fatma@hotmail.com.Data is provided within related files.