Early clinical and microbiological predictors of outcome in hospitalized patients with cryptococcal meningitis

Abstract

Background Cryptococcal meningitis causes high mortality in immunocompromised and immunocompetent patients. The objective of this study was to identify early predictors of clinical outcome, available at the first days of hospitalization, in patients with cryptococcal meningitis in a tertiary center in Brazil. Methods Ninety-six cases of cryptococcal meningitis with clinical, epidemiological and laboratory data, and identification and antifungal susceptibility of the strains were analyzed. Quantitative CSF yeast counts were performed by direct microscopic exam with a Fuchs-Rosenthal cell counting chamber using an institutional protocol. Univariable and multiple analyses using logistic regression were performed to identify predictors, available at the beginning of hospitalization, of in-hospital mortality. Moreover, we performed a secondary analysis for a composite outcome defined by hospital mortality and intensive care unit transfer. Results The species and the antifungal susceptibility were not associated with the outcomes evaluated. The variables significantly associated with the mortality were age (OR = 1.08, 95% CI 1.02–1.15), the cerebrospinal fluid (CSF) yeasts count (OR = 1.65, 95% CI 1.20–2.27), systemic arterial hypertension (OR = 22.63, 95% CI 1.64–312.91) and neurological impairment identified by computed tomography (OR = 41.73, 95% CI 3.10–561.65). At the secondary analysis, CSF yeast count was also associated with the composite outcome, in addition to the culture of Cryptococcus spp. from bloodstream and cerebral toxoplasmosis. The associations were consistent with survival models evaluated. Conclusions Age and CSF yeast count were independently associated with in-hospital mortality of patients with cryptococcal meningitis but Cryptococcus species identification and antifungal susceptibility were not associated with the outcomes. Quantitative CSF yeast counts used in this study can be evaluated and implemented in other low and middle-income settings.

Cryptococcal Meningitis in HIV-Negative Patients: A 12-Year Single-Center Experience in China

“…In an early study, 88 patients with CM were identified, and 37 (42%) were HIV-infected; they found patients who died had significantly lower CSF WBC, but this study contained HIV-positive patients, whom themselves had lower CSF WBC than HIV-negative patients [ 22 ]. In a recent study, early clinical and microbiological predictors of outcome in hospitalized patients with CM were evaluated [ 23 ], and older age and quantitative CSF yeast counts performed by direct microscopic exam were associated with mortality in multiple analyses by logistic regression [ 23 ]. We also found that male gender was significantly associated with mortality.…”

Poor long-term outcomes despite improved hospital survival for patients with cryptococcal meningitis in rural, Northern Uganda

“…However, no overall survival benefits were observed through CrAg screening [ 37 ], except for patients with CrAg titers ≥1:160, who had 2.6-fold higher 6-month mortality compared to patients with titers <1:160 [ 35 ]. Other laboratory tests such as quantitative CSF yeast count and clearance, CSF cytokines, CSF white cell count, and antifungal susceptibility have been reported in several studies to affect hospital outcomes [ 38 – 41 ]. These factors were not evaluated in this study because they were not routinely available for clinical care in this setting.…”

Development and Validation of a Machine Learning Model to Predict Prognosis in HIV-Negative Cryptococcal Meningitis Patients: A Multicentre Retrospective Study

“…Fungal burden has been associated with mortality in CM patients [17,[30][31][32][33][34]. However, fungal burden is formally evaluated with quantitative CSF cultures, but this methodology is usually unavailable in routine clinical practice in some low-and middle-income countries due to limited laboratory conditions [30,35]. Above all, cryptococcal culture of CSF samples often turns negative after CM early treatment but is not re ective of the therapeutic effect of CM [36].…”

“…The baseline CSF cryptococcal count was the most valuable predictor for prognosis in our prediction model. Some studies also indicated that the baseline CSF cryptococcal count could be used to predict outcome in CM patients [14,35,[37][38][39]. A previous study showed that the CSF cryptococcal count decreased rapidly in the early stage of treatment, while the cryptococcal count tended to stabilize after 2 weeks of treatment [32].…”