Candidemia on presentation to the hospital: development and validation of a risk score

Abstract

IntroductionCandidemia results in substantial morbidity and mortality, especially if initial antifungal therapy is delayed or is inappropriate; however, candidemia is difficult to diagnose because of its nonspecific presentation.MethodsTo develop a risk score for identifying hospitalized patients with candidemia, we performed a retrospective analysis of a large database of 176 acute-care hospitals in the United States. We studied 64,019 patients with bloodstream infection (BSI) on presentation from 2000 through 2005 (derivation cohort) and 24,685 from 2006 to 2007 (validation cohort). We used recursive partitioning (RPART) to identify the best discriminators for Candida as the cause of BSI. We compared three sets of models (equal-weight, unequal-weight, vs full model with additional variables from logistic regression model) for sensitivity analysis.ResultsThe RPART identified 6 variables as the best discriminators: age < 65 years, temperature ≤ 98°F or severe altered mental status, cachexia, previous hospitalization within 30 days, admitted from other healthcare facility, and need for mechanical ventilation. The prevalence for patients presented with 0 through 6 risk factors in the derivation cohort was 28.7%, 38.8%, 21.8%, 8.3%, 2.1%, 0.3%, and < 0.1% respectively. The corresponding candidemia rates were 0.4% (69/18,355), 0.8% (196/24,811), 1.6% (229/13,984), 3.2% (168/5,330), 4.2% (58/1,371), 9.6% (15/157), and 27.3% (3/11) respectively (P < 0.0001). Findings were similar in the validation cohort (P < 0.0001). The equal-weight risk score model, which signed 1 point to each risk factor, yielded good discrimination in both cohorts with areas under the receiver operating curve (AUROCs) of 0.70 versus 0.71 (derivation versus validation). AUROC values were similar for the unequal-weight model, which signed different weight to each risk factor based on multivariable logistic regression coefficient, (AUROCs, 0.70-0.72). Both equal-weight and unequal-weight models were well calibrated (all Hosmer-Lemshow P > 0.10, indicating predicted and observed candidemia rates did not differ significant across the 7 risk stratus). The full model with 16 risk factors had slightly higher AUROCs (0.74 versus 0.73 for derivation versus validation); however, 7 variables were no longer significant in the recalibrated model for the validation cohort, indicating that the additional items did not materially enhance the model.ConclusionsA simple equal-weight risk score differentiated patients' risk for candidemia in a graded fashion upon hospital presentation.

Efficacy and safety of anidulafungin in elderly, critically ill patients with invasive Candida infections: a post hoc analysis

“…Candidaemia was less common in elderly patients (65%) than in non-elderly patients (77%), which is consistent with a previous study indicating that age <65 years is a risk factor for candidaemia [21], and a retrospective cohort study reported that elderly ICU patients were less likely to have bloodstream infections than younger patients [10]. Data from a recent pooled analysis of clinical trial data with another echinocandin (micafungin) suggested that patients with candidaemia have a higher likelihood of treatment success with antifungal therapy than those with invasive candidiasis [22].…”

Development and validation of a clinical prediction rule for candidemia in hospitalized patients with severe sepsis and septic shock

“…We found that admission from a nursing home was a significant predictor variable emphasizing the importance of long-term care facilities as infection reservoirs. Transfer from another healthcare facility as a discriminator for patients admitted with candidemia has been identified previously [19]. However, we also uniquely identified having the lung as the source of infection as a significant protective factor.…”

“…Except for Shorr et al [19], the other studies describing Candida prediction rules only targeted critically ill patients with an ICU stay of at least 4 days [15][16][17][18]. The best AUROC (0.77) was obtained by the Nebraska Medical Center model [18].…”

“…Delays in initiating timely antifungal therapy, especially when septic shock is present, has repeatedly been demonstrated to be associated with excess mortality [6,7,[11][12][13][14]. Such delays in therapy have placed an emphasis on identifying patients at high risk for invasive candidiasis using clinical prediction models [15][16][17][18][19] or Candida colonization [20,21]. However, few attempts have been made to externally validate these prediction models or to focus on the prediction of Candida infection in septic shock [22][23][24][25].…”

Species Distribution and Antifungal Susceptibility Profile of Candida Species Isolated From Blood Stream Infections

“…This might be because of severely ill and immunocompromised patients being cared for in the unit with most of them being on life support systems. Wenzel and Gennings 20 and Shorr et al 21 have tried to develop risk assessment strategies and calculate "Candida scores" to predict the true risk of disease in patients admitted in ICU. Candida risk scores may help clinician to rule out candidemia and to identify the patients at high risk of developing Candida BSI in the hospital stay.…”