Impact of COVID-19 and earthquake disaster on candidemia in the ICU: mortality and treatment outcomes

Abstract

Background

Candidemia is a serious bloodstream infection with high mortality, particularly in intensive care unit (ICU) patients. Its epidemiology is influenced by evolving practices, resistance, and extraordinary circumstances such as pandemics and disasters. This study aimed to analyze candidemia epidemiology, risk factors, and outcomes, focusing on the impact of the COVID-19 pandemic and a major earthquake in southern Turkey.

Methods

We retrospectively analyzed 739 adult ICU patients diagnosed with candidemia between 2018 and 2023 at a tertiary referral center in Turkey. Patients were grouped as pre-pandemic, COVID-19, and post-earthquake periods. Clinical characteristics, Candida species distribution, antifungal treatment timing, and mortality rates were compared. Logistic regression was performed to identify independent predictors of 30-day mortality.

Results

There was a total of 739 documented cases, including 261 (35.32%) during the pre-pandemic period, 305 (41.27%) during the COVID-19 period, and 173 (23.41%) during the earthquake period. The overall 30-day mortality rate was 67.52%. Mortality was significantly higher during the COVID-19 period (78.36%) compared to the pre-pandemic (57.47%) and post-earthquake (63.58%) periods (p < 0.001). Non-albicans Candida species accounted for 70.77% of isolates, with C. parapsilosis being most frequent. Delayed initiation of antifungal therapy (> 48 h) and prolonged indwelling catheter duration were associated with increased mortality. Multivariable analysis identified higher Charlson comorbidity index, Candida score, septic shock, mechanical ventilation, and delayed antifungal therapy as independent predictors of mortality (AUC = 0.765).

Conclusion

Candidemia in ICU patients is associated with high mortality, particularly under crisis conditions such as the COVID-19 pandemic and earthquake disaster. Early antifungal initiation and prompt catheter removal remain critical to improving outcomes. These findings highlight the need for strengthened infection control strategies and disaster preparedness in a resource-challenged setting.

Clinical trial registration

Not applicable.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-026-13436-x.

Introduction

Candidemia, a serious bloodstream infection caused by Candida species, is a leading cause of morbidity and mortality in hospitalized patients, particularly those in intensive care units (ICUs) [1, 2]. The epidemiology of this infection is complex and dynamic, with reported changes in the prevalence of different Candida species and their susceptibility to antifungal agents [3, 4]. The risk factors for candidemia are multifactorial, including patient-related factors like age, comorbidities, and immune status, as well as healthcare-related factors such as prolonged ICU stay, surgical procedures, and the use of broad-spectrum antibiotics and invasive devices [5, 6]. Vazquez et al. state that among departments, ICUs, surgical units, and trauma units demonstrate the highest incidence of candidemia. Furthermore, they have indicated that 25–50% of all nosocomial candidemia occurs in ICUs [7]. According to US and European data, Candida species are responsible for 2–11% of nosocomial BSIs; particularly in ICUs this rate can be observed as high as 8.3%. Candidemia ranks as the fourth leading cause of nosocomial BSIs in the US and the fifth in Europe [8]. The clinical course and outcome of candidemia can be particularly severe in critically ill patients, where the infection is often difficult to diagnose and can lead to septic shock and multi-organ failure [9]. Early and effective antifungal therapy is crucial for improving patient outcomes, yet delays in diagnosis and treatment are common [10]. The selection of an appropriate antifungal agent is further complicated by the global rise of non-albicans Candida species (NACs) and the emergence of antifungal resistance [11, 12].

Furthermore, recent global events have introduced new complexities to the epidemiology of healthcare-associated infections. The SARS-CoV-2 pandemic, for instance, led to an increase in ICU admissions, prolonged hospital stays, and widespread use of immunosuppressive therapies, all of which are known to predispose patients to opportunistic fungal infections [13, 14]. Similarly, natural disasters can disrupt healthcare systems, leading to patient transfers and changes in infection control practices, which may influence the incidence and pattern of nosocomial infections [15, 16].

Despite the growing body of literature on candidemia, the combined impact of public health crises and natural disasters on its epidemiology and patient outcomes remains under-investigated. This study, therefore, aims to analyze the epidemiological and clinical characteristics of candidemia in ICU patients over a six-year period in a tertiary hospital in southern Turkey. We specifically sought to evaluate the impact of the SARS-CoV-2 pandemic and a major earthquake on the incidence, risk factors, species distribution, and mortality associated with candidemia. We hypothesized that these extraordinary circumstances would be associated with changes in candidemia patterns and increased mortality rates.

Methods

The retrospective study included the files of adult cases diagnosed with candidemia in the ICU at the Mersin City Training and Research Hospital between January 1, 2018, and November 30, 2023. The initial period was designated as the pre-pandemic era, extending up to March 11, 2020, when the first case of SARS-CoV-2 was officially reported in Turkey. The second period was defined as the pandemic period, spanning from March 11, 2020, to February 6, 2023. The third period took place in the aftermath of the February 6, 2023, Kahramanmaraş earthquakes and extended from February 6, 2023, to November 30, 2023.

The data were obtained from the medical records database and included age, gender, the length of stay in the ICU, the site of infection, and history of surgery, hypertension, diabetes, cardiovascular diseases, nervous system diseases, digestive system diseases, respiratory system diseases, urinary system diseases, kidney diseases, and solid malignancies. Methods of nutrition and invasive interventions, including mechanical ventilation, central venous and arterial catheterization, were also noted. In addition, the complete blood count, C-reactive protein, procalcitonin, alanine transaminase, and creatinine results, and use of antibiotics and antifungals were recorded. Files of patients whose Candida culture results were not yet confirmed and died within the first 48 h, and files with missing data were not included in the study.

Patients were grouped according to the presence of SARS-CoV-2 infection or earthquake-related injury.

Definitions

The diagnosis of candidemia was established in parallel to the IDSA and EORTC recommendations in cases where at least one positive blood culture was obtained, concomitant with symptoms and signs indicative of sepsis [17]. Positive blood culture results recorded within 15 days from the date of diagnosis were considered part of the initial candidemia episode, and the remaining results were considered as separate episodes. An episode of candidemia was defined as nosocomial if it occurred after 72 h following the initial admission. Additionally, it was classified as healthcare-associated if the patient had been hospitalized within the prior month or had undergone invasive procedures, such as dialysis, prior to the current admission. Neutropenia was defined as an absolute neutrophil count < 500/mm³; hypoalbuminemia was defined as a serum albumin level < 2.5 g/dL. The Candida score (CS) is a simple clinical scoring system used to predict the risk of candidemia in ICU patients. This score is based on criteria such as total parenteral nutrition, presence of surgical patients, multi-colonization, and severe sepsis. A total score ≥ 3 is considered high risk for candidemia [18]. Each patient’s CS was calculated retrospectively based on file records. The Charlson Comorbidity Index (CCI) is a validated scoring system that predicts 10-year mortality risk by assigning weights ranging from 1 to 6 points based on the patient’s accompanying chronic diseases. The CCI was calculated retrospectively for each patient based on relevant clinical data [19].

Hypotension was defined as a systolic blood pressure < 90 mmHg or a mean arterial pressure < 65 mmHg. Mortality was defined as death from any cause occurring within 30 days following the growth of Candida spp. in culture. Early mortality was defined as deaths occurring within the first 48 h after a diagnosis of candidemia.

Microbiological analysis

The microbiological analysis was executed in accordance with standard methodologies. Initially, culture samples were collected under aseptic conditions and subsequently placed into automated systems that rely on continuous monitoring, such as Bactec FX^® or BacT/Alert^®, where they were incubated for a maximum period of five days. Samples from bottles that exhibited a positive signal were then inoculated onto Sabouraud dextrose agar (SDA) and/or CHROMagar Candida^® (CHROMagar Company, France) media after undergoing Gram staining. These samples were subsequently incubated at temperatures ranging from 35 to 37 °C for a period of 24 to 48 h. The resulting colonies were evaluated using both macroscopic and microscopic analysis. The VITEK^® 2 Compact (bioMérieux, France) system was used to perform species-level identification. Conventional methods, including germ tube testing, were employed as necessary to validate the experimental results.

Ethics

The study was approved by the Clinical Research Ethics Committee of Toros University (Decision No: 26.01.2024/14). Due to the retrospective nature of the study and the use of anonymized data, the requirement for informed consent to participate was waived by the Ethics Committee. The study was conducted in accordance with the principles of the Declaration of Helsinki.

Statistics

Statistical analyses were performed using IBM SPSS Statistics version 22.0 (IBM Corp., Armonk, NY, USA) software. The distribution of continuous variables was assessed using the Kolmogorov–Smirnov test. The assessment of the non-normally distributed data for two groups was performed using the Mann–Whitney U test. The Kruskal–Wallis H test was employed to facilitate comparisons between more than two groups. For categorical variables, the Pearson chi-square test or Fisher’s exact test was used as appropriate. The initial step in the analysis involved the examination of variables associated with mortality using univariate logistic regression analysis. Subsequently, significant variables were incorporated into the multivariate model. ROC (Receiver Operating Characteristic) analysis was applied to evaluate the predictive performance of the model, and classification accuracy was measured by the area under the curve (AUC) value. The significance level was set at p < 0.05 for all analyses.

Results

The initial diagnostic search revealed that there were no cases that included all three diagnoses of candidemia, SARS-CoV-2, and earthquake-related injury. As a result, three groups emerged: candidemia cases with SARS-CoV-2, candidemia cases with earthquake-related injuries, and candidemia-only patients. There was a total of 739 documented cases, including 261 (35.32%) during the pre-pandemic period, 305 (41.27%) during the COVID-19 period, and 173 (23.41%) during the earthquake period. The demographic and clinical data analysis results of the subjects are presented in Table 1.

Table 1.

Initial analysis results of the demographic and clinical data

		Groups
		Candidemia& SARS-CoV-2		Candidemia& Earthquake-related injury		Candidemia only (pre-pandemic)		Total		p†
		n = 305	%	n = 173	%	n = 261	%	n = 739	%
Gender	Female	150	49.18	79	45.66	126	48.28	355	48.04	0.76
	Male	155	50.82	94	54.34	135	51.72	384	51.96
Intubated	Yes	153	50.16	82	47.4	106	40.61	341	46.14	0.07
TPN	Yes	256	83.93	128	73.99	190	72.8	574	77.67	0.003
CVC	Yes	287	94.1	154	89.02	232	88.89	673	91.07	0.053
Catheterization period (days)	1–3	49	16.07	36	20.81	63	24.14	148	20.03	0.004
	4–7	137	44.92	81	46.82	112	42.91	330	44.65
	> 7	101	33.11	37	21.39	57	21.84	195	26.39
	Not catheterized	18	5.9	19	10.98	29	11.11	66	8.93
Septic shock	Yes	135	44.26	62	35.84	100	38.31	297	40.19	0.146
Dialysis	Yes	44	14.43	20	11.56	37	14.18	101	13.67	0.652
Burns	Yes	12	3.93	7	4.05	13	4.98	32	4.33	0.812
Surgical intervention	Yes	57	18.69	34	19.65	19	7.28	110	14.88	0.0001
Kidney Failure	Yes	48	15.74	18	10.4	29	11.11	95	12.86	0.0001
Malignant neoplasm	Yes	66	21.64	38	21.97	64	24.52	168	22.73	0.691
Corticosteroid need	Yes	14	4.59	33	19.08	29	11.11	76	10.28	< 0.0001
Antifungal treatment	None	100	32.79	32	18.5	53	20.31	185	25.03	0.0006
	Anidulafungin	82	26.89	47	27.17	87	33.33	216	29.23
	Caspofungin	20	6.56	28	16.18	28	10.73	76	10.28
	Voriconazole/Amphotericin B	4	1.31	5	2.89	3	1.15	12	1.62
	Fluconazole	99	32.46	61	35.26	90	34.48	250	33.83
*Candida Species	Candida albicans	58	19.02	35	20.23	123	47.13	216	29.23	< 0.0001
	Candida glabrata	21	6.89	15	8.67	7	2.68	43	5.82
	Candida parapsilosis	129	42.3	72	41.62	88	33.72	289	39.11
	Candida tropicalis	84	27.54	40	23.12	41	15.71	165	22.33
	Other Candida spp	13	4.26	11	6.36	2	0.77	26	3.52
Albicans	Albicans	58	19.02	35	20.23	123	47.13	216	29.23	< 0.0001
	Non-Albicans	247	80.98	138	79.77	138	52.87	523	70.77
Mortality (30 days)	Deceased	239	78.36	110	63.58	150	57.47	499	67.52	< 0.0001
	Alive	66	21.64	63	36.42	111	42.53	240	32.48
C. albicans-related mortality	Deceased	58	100	25	71.43	62	50.41	145	67.13	< 0.0001
	Total	58		35		123		216
Non-Albicans related mortality	Deceased	196	79.35	71	51.45	88	63.77	355	67.88	< 0.0001
	Total	247		138		138		523
		Mean ± SD		Mean ± SD		Mean ± SD		Mean ± SD		p††
	Age	67.44 ± 18.24		65.86 ± 17.49		63.84 ± 17.78		65.8 ± 17.95		0.038
	Albumin	2.79 ± 0.53		2.82 ± 0.54		2.86 ± 0.58		2.82 ± 0.55		0.423
	ALT	52.81 ± 149.19		38.75 ± 96.91		43.26 ± 85.48		46.14 ± 118.18		0.640
	Creatinine	1.55 ± 1.29		1.31 ± 1.19		1.4 ± 1.22		1.44 ± 1.24		0.105
	WBC	13709.12 ± 10371.05		13378.18 ± 10824.7		12031.64 ± 9354.36		13039.2 ± 10149.6		0.060
	Neutrophils	7750.52 ± 7493.36		8656.09 ± 9923.37		7732.36 ± 9950.94		7956.1 ± 9006.43		0.376
	Lymphocytes	4354.51 ± 7549.41		3592.18 ± 5756.02		3763.43 ± 5697		3967.29 ± 6537.79		0.836
	Platelets	187091.48 ± 153273.16		225020.81 ± 154421.11		211674.33 ± 155513.93		204652.91 ± 154910.37		0.006
	Procalcitonin	8.6 ± 16.89		5.41 ± 12.01		8.19 ± 17.65		7.71 ± 16.2		0.002
	CRP	15.64 ± 9.5		12.92 ± 9.59		14.08 ± 9.72		14.45 ± 9.65		0.002
	Duration of hospitalization	22.82 ± 13.04		21.58 ± 11.35		21.1 ± 12.52		21.92 ± 12.49		0.243
	CCI score	1.19 ± 1.13		1.1 ± 1.05		1.25 ± 1.09		1.19 ± 1.1		0.355
	Candida Score	2.3 ± 1.07		1.86 ± 1.24		1.82 ± 1.26		2.03 ± 1.2		< 0.001

*The other Candida species group includes the following species: Candida auris, Candida ciferrii, Candida dubliniensis, Candida guilliermondii, Candida kefyr, Candida krusei, and Candida lusitaniae

ICU: Intensive care unit, TPN: Total parenteral nutrition, CVC: Central venous catheter, ALT: Alanine aminotransferase, WBC: white blood cell count, CRP: C-reactive protein, CCI: Charlson Comorbidity Index

†p value by Chi-square

††p value by One Sample T test

The mean age of patients was 65.8 ± 17.95 years, and 51.96% (n = 384) were male. In terms of comorbidities, 72.3% of patients exhibited at least one chronic disease. The most prevalent comorbidities identified were renal failure (39.2%), diabetes mellitus (27.7%), and malignancy (14.2%) (Supplemetantary Table 1). The mean duration of hospitalization was 21.92 ± 12.49 days and did not differ significantly between the groups (p = 0.243). A great number of cases were given TPN (n = 574, 77.67%), which also demonstrated a statistical difference when compared between groups (p < 0.0027). The catheterization duration analysis revealed considerable differences between the groups, indicating that fewer cases in the candidemia-only group required catheterization (p < 0.0037). Nevertheless, the majority of patients (n = 673, 91.07%) underwent catheterization, and for 44.65% (n = 330) of the patients, the duration of indwelling catheter lasted between four and seven days. The mean CCI was 1.19 ± 1.1. Despite the absence of statistical significance between the groups, a substantial discrepancy was observed in the mean values for the deceased and survivors (1.28 ± 1.09, and 0.98 ± 0.99, respectively, p = 0.001). The mean Candida score of the candidemia and SARS-CoV-2 cases group was considerably higher (2.3 ± 1.07, p < 0.0001). Besides, the comparison between the mean values for the deceased and survivors revealed a significant dissimilarity (2.36 ± 1.02 and 1.28 ± 1.24, respectively, p < 0.001).

The most frequently identified species among all candidemia cases was Candida parapsilosis (n = 289, 39.1%), followed by Candida albicans (n = 216, 29.2%). The distribution of Candida species among groups showed a statistically significant difference (p < 0.0001); while C. albicans was most common in candidemia-only cases, C. parapsilosis predominated in COVID-19 and earthquake-related cases.

In terms of mortality, SARS-CoV-2 period showed the highest rate with 78.36% (n = 239), followed by the earthquake period with 63.58% (n = 110), and with the lowest rate of 57.47% in the pre-pandemic period (n = 150). The comparison of 30-day mortality rates between species did not reveal statistical significance (p = 0.511). Mortality was numerically higher in C. glabrata (79.1%) and C. tropicalis (72.1%) infections, while similar rates were observed in C. albicans (67.13%) and other rare species. The comparison of overall mortality between C. albicans (67.13%) and non-albicans Candida species (67.88%) also showed no significant difference (p = 0.487).

In the study, fluconazole emerged as the predominant antifungal agent across all groups (n = 250, 33.83%), though notable variations in antifungal preference were observed. The highest proportion of patients not receiving antifungal therapy was observed in the candidemia and SARS-CoV-2 group (n = 100, 32.79%). The 30-day mortality rates based on antifungal treatment showed that in cases not receiving treatment, the rate was 83.2%, whereas the treated cases resulted in 64.6% (p < 0.0001). Furthermore, a statistically significant disparity in mortality was observed between cases where treatment was initiated after the third day and cases where antifungals were administered within 48 h (76.1% and 58.9%, respectively; p < 0.0001).

The analysis including the biomarkers revealed that the earthquake-related injury group had the lowest mean procalcitonin (5.41 ± 12.01, p = 0.0021) and CRP levels (12.92 ± 9.59, p = 0.0018). Conversely, the highest mean platelet count was observed in this group (225020.81 ± 154421.11, p = 0.0064).

Leukocyte count, creatinine, procalcitonin, and CRP levels were significantly higher in non-survivors compared to survivors (all p < 0.001). In contrast, lymphocyte and platelet counts were significantly lower in the non-survivor group (p = 0.011 and p < 0.001, respectively), while neutrophil count and ALT levels did not differ significantly between the groups (p = 0.068 and p = 0.643, respectively) (Supplementary Table 1).

Multivariate logistic regression analysis of independent risk factors associated with 30-day mortality demonstrated that the absence of antifungal therapy was independently associated with a threefold increase in mortality risk (OR: 2.91; 95% CI: 1.58–5.36; p < 0.001). Each mg/dL increase in serum creatinine was linked to higher mortality (OR: 1.23; 95% CI: 1.07–1.41; p < 0.001). The mortality risk increased by 28% for each unit increase in the Charlson Comorbidity Index (CCI) when analyzed as a continuous variable (OR: 1.28; 95% CI: 1.12–1.46; p = 0.001). Similarly, the categorical model showed a 34% increase per unit (OR: 1.34; 95% CI: 1.12–1.59; p = 0.001). Higher Candida scores (OR: 2.26; 95% CI: 1.91–2.68; p < 0.001), intubation (OR: 1.53; p = 0.027) and the presence of septic shock (OR: 1.66; p = 0.011) were also independently associated with mortality. The model’s AUC was 0.765 (95% CI: 0.73–0.81) indicating good discrimination (Fig. 1).

Fig. 1.

Receiver operating characteristic (ROC) curve for 30-day mortality prediction. The multivariate model achieved an AUC of 0.765 (95% CI: 0.73–0.81)

The 30-day mortality rates between the groups were significantly different (p < 0.001), with the highest mortality rate observed in the SARS-CoV-2 period by 78.36%, followed by the earthquake period by 63.58%, and the pre-pandemic period ranking last by 57.47%.

Discussion

This study, utilizing a comparative approach, analyzed candidemia attacks in patients with SARS-CoV-2, earthquake-related injuries, and candidemia-only cases. The objective was to analyze the impact of changes in various parameters, including laboratory tests, invasive interventions, organ function-related conditions, antifungal strategies, and pathogen diversity, on survival. Initially, it is evident that the elevated mean age and the presence of multiple comorbidities in the majority of cases underline the significance of host characteristics in candidemia. It is imperative to acknowledge that the course can be expected to progress more rapidly, particularly when additional conditions arise. The present findings are consistent with the literature indicating that advanced age and a high comorbidity burden are significant factors in the development of candidemia in individuals [20, 21].

The increased mortality rates in the study were similar to those observed in ICU cases of the same region where no Candida growth was detected during the same periods. Baykara et al. reported that mortality rates of patients with severe sepsis andseptic shock were 55.7% and 70.4%, respectively [22].In addition, in the study of Urfalı et al., the mortality rate was 50% [23].

The multivariate logistic regression analysis that included Candida score, CCI score, catheter duration, intubation, presence of septic shock, the Candida score was found to be an independent predictor of mortality, suggesting that the Candida score may be useful in identifying high-risk patients with a threshold value of ≥ 3 and may be particularly beneficial in early diagnosis similarly to the findings of León et al. and other studies’ findings [18]. Nevertheless, research findings emphasize that the negative predictive value of this score may be limited in ICU patients and that it must be supported by colony density (e.g. fungal load on the catheter surface) or biomarkers such as 1,3-β-D-glucan [24].

Catheter duration and the presence of intubation were notably associated with mortality and are consistent with previously reported cohort analyses [25]. Particularly, prolonged catheterization may contribute to the development of invasive infections by increasing Candida colonization. Intubation, on the other hand, increases the risk of secondary infections associated with mechanical ventilation [26]. Although TPN was more frequent in severe cases and is a recognized risk factor for invasive candidiasis, it was not retained in the final multivariable model because of concerns about collinearity with the Candida score. The presence of septic shock is indicative of hemodynamic instability and organ failure, while TPN has been shown to facilitate fungal translocation by disrupting gastrointestinal mucosal integrity and accelerate the development of infection [27].

Moreover, it was shown that the risk of mortality was significantly higher in cases not receiving antifungal treatment, that each point increase in the CCI score increased the risk of mortality, and that each mg/dL increase in creatinine level is associated with a significant increase in the risk of death. Although the area under the ROC curve (AUC) value of our model was calculated as 0.765, indicating that the model’s performance in predicting mortality is at a good level, the interpretation of these results must be approached with a degree of caution, as they may also be attributable to the general condition of the patients and the severity of their critical illness [28]. In this study, the mortality risk in cases where antifungal treatment was not initiated was found to be approximately three times higher. Not with standing the initiation of treatment, the preservation of life can become significantly more challenging, even in patients who receive antifungal treatment more than 48 h after the onset of symptoms [29].

Furthermore, an increase in the CCI score by one point was observed to result in a 28% increase in the risk of mortality, thereby demonstrating that the comorbidity burden is a critical determinant in the course of candidemia. As indicated by earlier research findings, an elevated CCI score has been demonstrated to serve as an independent predictor of mortality risk in patients diagnosed with candidemia [30].

In accordance with the results of a large-scale surveillance study, the present study identified a significant association between elevated creatinine levels and an increased mortality risk, with a 1 mg/dL increase in creatinine levels resulting in an odds ratio of 1.23, suggesting that renal dysfunction has a significant impact on prognosis [31]. The Area Under the ROC Curve (AUC) value of 0.765, which indicates the good performance of our multivariate model in predicting mortality, is similar to the findings of prognostic models previously developed in different ICU cohorts [32, 33]. However, the results of our model may also reflect the general critical condition of the patients and the additional risks they are exposed to in the intensive care unit; therefore, they should be interpreted with caution. Our findings show that the initiation of early antifungal treatment, comorbidity assessment, and close monitoring of organ functions are critical elements in predicting mortality, but the robustness of our model needs to be reinforced with external validation studies conducted in different centers.

In terms of the distribution of Candida species, non-albicans Candida (NAC) species were found to be predominant, with species such as C. parapsilosis being particularly prominent. This distribution is consistent with global trends, and the virulence traits of NAC species, such as azole resistance and biofilm formation, may contribute to differences in treatment response [12]. The delayed initiation of antifungal treatment, or the failure to initiate treatment, has been identified as a significant risk factor for mortality. A delay of more than two days between obtaining a positive culture sample and initiating treatment was found to be significantly associated with mortality, as has been previously reported in the literature [34, 35].

Laboratory parameters such as elevated creatinine, increased procalcitonin, and thrombocytopenia, which can be considered early indicators of clinical deterioration by reflecting the severity of sepsis and organ dysfunction, have been found to be associated with mortality, as in the results of other studies [36, 37].

A growing body of literature has emerged on the subject of co-occurring cases of SARS-CoV-2 and candidemia, referred to as COVID-19-associated candidemia (CAC), indicating a marked increase in candidemia rates, particularly among ICU patients. A recent series of systematic reviews have reported a CAC prevalence of around 4.3%, emphasizing that mortality occurred in approximately 61% of these cases [38]. This phenomenon is hypothesized to be attributable to the immunosuppressive effect of SARS-CoV-2, in conjunction with the concomitant administration of steroids and tocilizumab. As demonstrated in this study, which evaluates the impact of extraordinary circumstances, such as disasters and pandemics, on the incidence and mortality of candidemia, the mortality rate is notably higher in cases of candidemia accompanied by SARS-CoV-2, which is in parallel to the existing literature on the subject [39].

The increase in candidemia observed in the post-earthquake period is a topic that has received limited attention in the literature. Nevertheless, the literature has reported the increase in the incidence of fungal infections in the aftermath of natural disasters. Traumatic injuries, the increased need for intensive care, disruptions in healthcare infrastructure, and contaminated environmental conditions are shown as the main reasons for this rise in incidence rates, especially in the case of major earthquakes. Research undertaken following the Wenchuan earthquake revealed the presence of various fungal pathogens, including Candida species. In a similar manner, the 2008 Sichuan earthquake saw the identification of numerous fungal agents, chiefly Candida tropicalis. Furthermore, an escalation in mucormycosis and aspergillosis cases was documented in the aftermath of disasters such as tsunamis and tornadoes [40]. Research conducted in Turkey following the 2023 earthquake also detected a substantial surge in fungal infection rates, particularly among trauma patients admitted to intensive care units [41]. This study revealed a substantial increase in C. parapsilosis isolates following the earthquake, indicating a potential association between this species and the transmission via hospital equipment and healthcare workers’ hands as proposed in other studies [42]. In general, these findings suggest that the distribution of candidemia in earthquake-related cases in our study is consistent with those observed in studies conducted on invasive fungal infections in disaster conditions. Our findings underscore the significance of maintaining infection control practices during disaster situations, thereby reinforcing the importance of infection prevention strategies in healthcare settings.

Finally, a striking finding of approximately one out of four cases not receiving antifungal treatment (n = 153, 25.03%) is subject to discussion. Nevertheless, the reports present higher rates of series with no antifungal treatment despite microbiologically confirmed culture results. The ideas of reduced risk of death, consideration of unsuitability, lack of infectious diseases consultation were among the rationales for not starting antifungal treatment in a confirmed case. In recent studies, Alvarez et al. indicated 40.8% of 179 cases with confirmed candidemia did not receive antifungal treatment [43]. The authors highlighted that even experienced physicians, who were equipped with the necessary tests and tools, started therapy based on their clinical experience without following the algorithms and rules of the current guidelines. Moreover, Zilberberg et al., in a cohort of 90 cases with candidemia reported that antifungal therapy was inappropriate in 88.9%, with a delay of more than 24 h from the onset of candidemia [44]. In addition, Bourassa-Blanchette et al. showed that 18% (n = 31) of the critically ill cases did not receive any treatment, and proposed that in cases who did not receive infectious disease consultation did not receive antifungal therapy, highlighting the need of infectious disease consultation [45].

The study is subject to certain limitations. Primarily, due to the retrospective nature of the investigation, it was not possible to access all the clinical data; consequently, antifungal susceptibility test results could not be provided for the entire study group. Besides, having been conducted in a single center is a major limitation. In addition, not including the cases with Candida culture results were not yet confirmed and died within the first 48 h prevents a sound interpretation of mortality rates. Furthermore, the identification of species was not performed using molecular methods, but rather conventional methods, which has been demonstrated to increase the margin of error, particularly in the diagnosis of rare species and important pathogens such as C. auris [46, 47]. Moreover, the incorporation of advanced biomarker analyses, which have the potential to yield more reliable results with respect to negative predictive value, was not feasible within the scope of this study.

Conclusion

This study provides a comprehensive analysis that highlights the role of the Candida score in predicting mortality, in addition to known risk factors such as advanced age, high comorbidity score, intubation, catheter duration, presence of septic shock, and TPN use. The research also demonstrates changes in candidemia patterns during the SARS-CoV-2 pandemic and a major seismic event, and provides statistical support for the effect of antifungal treatment timing on mortality. The analysis reveals a correlation between the predominance of non-Candida albicans species and the emergence of antifungal resistance and treatment failure. It is hypothesized that the multivariate model with good predictive power presented in this study will contribute to the evaluation of empirical antifungal treatment decisions in high-risk intensive care patients in conjunction with clinical, microbiological, and epidemiological data.

Supplementary Information

Below is the link to the electronic supplementary material.

Abbreviations

ALT

Alanine aminotransferase

AUC

Area under the curve

CCI

Charlson Comorbidity Index

CRP

C-reactive protein

CS

Candida score

CVC

Central venous catheter

ICU

Intensive care unit

NAC

Non-albicans Candida

ROC

Receiver operating characteristic

SARS-CoV-2

Severe Acute Respiratory Syndrome Coronavirus-2

SD

Standard deviation

SPSS

Statistical Package for the Social Sciences

TPN

Total parenteral nutrition

WBC

White blood cell

Author contributions

MU conceived and designed the study. MU and BÇD performed data collection and statistical analysis. MU interpreted the data. MU and BÇD drafted the manuscript. All authors read and approved the final version.

Funding

No funding was received for this study.

Data availability

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

Declarations

Ethics approval and consent to participate

Ethical approval was obtained from the Clinical Research Ethics Committee of Toros University (Decision No: 26.01.2024/14). Due to the retrospective design of the study, the requirement for informed consent to participate was waived by the Ethics Committee. The study was conducted in accordance with the principles of the Declaration of Helsinki.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.