Patient characteristics
A total of 140 patients participated in the study, and baseline clinical characteristics were summarized in Table 1. The mean age of the patients was 65.98±14.63, and there was no significant difference in age between the two groups. Matching technique was used, and there was no significant difference in the location of patients at the time of SIRS occurrence between the case and control groups. At the onset of SIRS for both groups, 27 patients (38.6%) were in the ICU and 43 patients (61.4%) were in the general ward.
The most common underlying disease was solid cancer, followed by neurological disorders and diabetes. The assessment of severity of co-morbidities using the McCabe classification showed a greater number of rapidly fatal cases in the case group (5.7% vs. 0%, p=0.007). There was also a clear difference in the cause of infection between the two groups (Table 1). The most common cause of candidemia in the case group was catheter related infection (CRI), which accounted for 48 out of the 70 cases (68.6%). CRIs were followed by primary bacteremia at 28.6% (20/70 cases). In contrast, the major cause of SIRS in the control group was pneumonia, which accounted for 42.9% (31/70) of the cases. However, the severity of infection assessed by the Pitt bacteremia score, severe sepsis, or septic shock yielded no statistically significant difference between the two groups (Table 1). To measure CSs, the presence of candida colonization, total parenteral nutrition (TPN), and receipt of surgery were examined. The proportion of patients with Candida colonization and the proportion of patients who underwent surgery while hospitalized appeared to be significantly higher in the case group than in the control group (Table 1). All patients were administered with antibiotics at the time of participation in this study. The 14-day mortality of all the patients was 10.7% (15/140), and was significantly higher in the case group (18.6% vs. 2.9%, p=0.005).
Comparison of DNI and other indicators as predictive markers of candidemia
To evaluate DNI effectivenss as a predictive factor for candidemia, DNI, CRP, Procalcitonin, leukocyte, and CS>3 were compared between the case and control groups (Table 2). DNI_D1 value was 3.5% (0.5-3.3) in the case group, which was significantly higher than the 1.3% (0.1-2.4) of the control group (p<0.001). The DNI_48 value was also significantly higher in the case group (2.0%) than the control group (1.0%) (p<0.001). Procalcitonin was also higher in the case group (Table 2). However, CS>3, which is a known predictive factor for candidemia, showed no significant difference between the two groups.
Multivariate analyses were conducted to determine independent predictive factors for candidemia in the case and control groups, and the results are summarized in Table 3. The factors, which were significantly different in the univariate analysis, “Candida Score>3” used for predicting candidemia, and clinically important factors exhibiting insignificant differences in univariate analysis were included in the multivariate analysis conducted in this study.
In the multivariate analyses, DNI_D1 (OR, 2.183, 95% CI, 1.421-3.217, p<0.001) and candida colonization (OR, 7.361, 95% CI, 1.717-31.553), p=0.007) were identified to be useful indices for predicting candidemia (Table 3).
Optimal cutoff value of DNI for predicting candidemia
To determine the DNI_D1 cutoff value for predicting candidemia, the ROC curve and AUC analyses were conducted (Fig. 1). The optimal cutoff value for predicting candidemia was found to be 2.75%, and the AUC of DNI_D1 was 0.804 (95% CI, 0.719-0.890, p<0.001). The sensitivity and specificity in predicting candidemia were 72.9% and 78.6%, respectively, with a cutoff DNI value of 2.75%, and the positive and negative predictive values were 77.3% and 74.3%, respectively. For DNI_D1 >2.75%, the OR for the presence of candidemia was 9.842 (95% CI, 4.562-21.402, p<0.001).
Factors associated with 14-day mortality in patients with candidemia
To determine prognosis factors for mortality of patients with candidemia, various factors were comparatively analyzed according to 14-day mortality. Among a total of 70 candidemia patients, 13 died within 14 days of candidemia onset. There was no difference in age, sex, or patient location at the time of candidemia onset (p=0.210) between the survivor and non-survivor groups. Underlying diseases and site of infection also yielded no significant differences between the survivor and non-survivor groups. The non-survivor group showed significantly higher Pitt bacteremia score than the survivor group (4.0〔1.0-5.0〕vs 0.0 〔0.0-2.0, p<0.001), and a higher septic shock rate (61.5% vs 7.5%, p=0.003). The percentage of patients showing a CS ≥3 was higher in the non-survivor group than the survivor group (46.2% vs. 19.3%, p=0.042). DNI_D1 and DNI_48 values were also significantly higher in the non-survivor group, measuring 7.4% (4.0-22.0) and 6.1% (2.1-14.4), respectively. TTP was 31.0 hours (26.5-53.0) in the non-survivor group, which was shorter than the 48.0 hours (34.0-72.0) of the survivor group, but there was no statistical significance (p=0.066).
In the case of TAT, the non-survivor group showed a significantly shorter period at 36hours (12.5-42.0) than the survivor group at 60hours (42.0-96.0), showing that antifungal therapies were administered earlier to the non-survivor group than the survivor group (p=0.013). As seen in Table 4, a significant difference was not found in TAT between the survivor and non-survivor groups in the multivariate analysis. However, antifungal therapy tended to be administered faster with earlier Candida detection from blood cultures (r=0.56 p=0.044). In addition, TAT and 14-day mortality showed an inverse correlation (r=-0.330, p=0.011).
The duration until negative conversion of candidemia also showed no difference between the survivor and non-survivor groups (Table 4).
Multivariate analysis also confirmed that DNI_D1 value (OR, 1.156, 95% CI, 1.039-1.287, p=0.008) and the occurrence of septic shock were reliable prognosis factors for 14-day mortality. The DNI_D1 cutoff value for predicting 14-day mortality was 3.95% and AUC was 0.769 (95% CI, 0.624-0.914, p=0.001).