The clinical characteristics of adult cryptococcal meningitis patients who died within one year of treatment with a focus on those with early mortality

A Retrospective Analysis of Central and Peripheral Metabolic Characteristics in Patients with Cryptococcal Meningitis

INTRODUCTION

Most current treatment strategies and investigations on cryptococcal meningitis (CM) focus primarily on the central nervous system (CNS), often overlooking the complex interplay between the CNS and the peripheral system. This study aims to explore the characteristics of central and peripheral metabolism in patients with CM.

METHODS

Patients diagnosed with CM as per the hospital records of the Fourth People's Hospital of Nanning were retrospectively analyzed. Patients were divided into two groups, non-structural damage of the brain (NSDB) and structural damage of the brain (SDB), according to the presence of brain lesions as detected with imaging. Based on the presence of enlarged cerebral ventricles, the cases in the SDB group were classified into non-ventriculomegaly (NVM) and ventriculomegaly (VM). Various parameters of cerebrospinal fluid (CSF) and peripheral blood (PB) were analyzed.

RESULTS

A significant correlation was detected between CSF and PB parameters. The levels of CSF-adenosine dehydrogenase (ADA), CSF-protein, CSF-glucose, and CSF-chloride ions were significantly correlated with the levels of PB-aminotransferase, PB-bilirubin, PB-creatinine (Cr), PB-urea nitrogen, PB-electrolyte, PB-protein, and PB-lipid. Compared with NSDB, the levels of CSF-glucose were significantly decreased in the SDB group, while the levels of CSF-lactate dehydrogenase (LDH) and CSF-protein were significantly increased in the SDB group. In the SDB group, the levels of PB-potassium, PB-hemoglobin(Hb), and PB-albumin were significantly decreased in the patients with VM, while the level of PB-urea nitrogen was significantly increased in these patients.

CONCLUSION

Metabolic and structural alterations in the brain may be associated with peripheral metabolic changes.

Construction and validation of a nomogram model to predict the poor prognosis in patients with pulmonary cryptococcosis

Background

Patients with poor prognosis of pulmonary cryptococcosis (PC) are prone to other complications such as meningeal infection, recurrence or even death. Therefore, this study aims to analyze the influencing factors in the poor prognosis of patients with PC, so as to build a predictive nomograph model of poor prognosis of PC, and verify the predictive performance of the model.

Methods

This retrospective study included 410 patients (78.1%) with improved prognosis of PC and 115 patients (21.9%) with poor prognosis of PC. The 525 patients with PC were randomly divided into the training set and validation set according to the ratio of 7:3. The Least Absolute Shrinkage and Selection Operator (LASSO) algorithm was used to screen the demographic information, including clinical characteristics, laboratory test indicators, comorbidity and treatment methods of patients, and other independent factors that affect the prognosis of PC. These factors were included in the multivariable logistic regression model to build a predictive nomograph. The receiver operating characteristic curve (ROC), calibration curve and decision curve analysis (DCA) were used to verify the accuracy and application value of the model.

Results

It was finally confirmed that psychological symptoms, cytotoxic drugs, white blood cell count, hematocrit, platelet count, CRP, PCT, albumin, and CD4/CD8 were independent predictors of poor prognosis of PC patients. The area under the curve (AUC) of the predictive model for poor prognosis in the training set and validation set were 0.851 (95% CI: 0.818-0.881) and 0.949, respectively. At the same time, calibration curve and DCA results confirmed the excellent performance of the nomogram in predicting poor prognosis of PC.

Conclusion

The nomograph model for predicting the poor prognosis of PC constructed in this study has good prediction ability, which is helpful for improving the prognosis of PC and further optimizing the clinical management strategy.

Cerebrospinal Fluid Lactate as a Prognostic Marker of Disease Severity and Mortality in Cryptococcal Meningitis

BACKGROUND

Cerebrospinal fluid (CSF) lactate levels can be used to differentiate between bacterial and viral meningitis. We measured CSF lactate in individuals with cryptococcal meningitis to determine its clinical significance.

METHODS

We measured point-of-care CSF lactate at the bedside of 319 Ugandan adults living with human immunodeficiency virus at diagnosis of cryptococcal meningitis. We summarized demographic variables and clinical characteristics by CSF lactate tertiles. We evaluated the association of CSF lactate with clinical characteristics and survival.

RESULTS

Individuals with high CSF lactate >5 mmol/L at cryptococcal diagnosis more likely presented with altered mental status (P < .0001), seizures (P = .0005), elevated intracranial opening pressure (P = .03), higher CSF white cells (P = .007), and lower CSF glucose (P = .0003) compared with those with mid-range (3.1 to 5 mmol/L) or low (≤3 mmol/L) CSF lactate levels. Two-week mortality was higher among individuals with high baseline CSF lactate >5 mmol/L (35%; 38 of 109) compared with individuals with mid-range (22%; 25 of 112) or low CSF lactate (9%; 9 of 97; P =<.0001). After multivariate adjustment, CSF lactate >5 mmol/L remained independently associated with excess mortality (adjusted hazard ratio = 3.41; 95% confidence interval, 1.55-7.51; P = .002). We found no correlation between baseline CSF lactate levels and blood capillary lactate levels.

CONCLUSIONS

Baseline point-of-care CSF lactate levels are a prognostic marker of disease severity and mortality in cryptococcal meningitis. Individuals with an elevated baseline CSF lactate level are more likely to present with altered mental status, seizures, and elevated CSF opening pressure and are at a greater risk of death. Future studies are needed to determine targeted therapeutic management strategies in persons with high CSF lactate.

Cryptococcosis by Cryptococcus neoformans/Cryptococcus gattii Species Complexes in non-HIV-Infected Patients in Southeastern Brazil

INTRODUCTION:

The clinical manifestations of cryptococcosis are usually associated with the infecting agents Cryptococcus neoformans (CN) and C. gattii (CG) species complexes and the host. In this study, non-HIV-infected patients, at a university hospital in southeastern Brazil, had epidemiological and clinical data associated with cryptococcal disease and isolated Cryptococcus species: CN - 24 patients and CG - 12 patients.

METHODS:

The comparison was comprised of demographic data, predisposing factors, clinical and laboratory manifestations, and outcomes of cryptococcosis patients treated between 2000 and 2016. Immunocompetent and immunosuppressed patients were also compared, irrespective of the infecting species. Cryptococcus spp. were genotyped by PCR-RFLP analysis of the URA5 gene.

RESULTS:

Infections by the CN species complex (100% VNI genotype) were associated with drug immunosuppression and fungemia, and patients infected with the CG species complex (83% VG II and 17% VGI genotypes) had more evident environmental exposure and higher humoral response. CN and CG affected patients with or without comorbidities.

CONCLUSIONS:

Diabetes mellitus, other chronic non-infectious diseases, and alcoholism were likely predisposing factors for infection by both CN and CG species. Immunocompetent patients, independent of the infecting Cryptococcus species complexes, showed a higher occurrence of meningitis and a trend toward less fungal dissemination and longer survival than immunosuppressed hosts.

Establishment of a novel scoring model for mortality risk prediction in HIV-infected patients with cryptococcal meningitis

Background

Cryptococcal meningitis (CM) remains a leading cause of death in HIV-infected patients, despite advances in CM diagnostic and therapeutic strategies. This study was performed with the aim to develop and validate a novel scoring model to predict mortality risk in HIV-infected patients with CM (HIV/CM).

Methods

Data on HIV/CM inpatients were obtained from a Multicenter Cohort study in China. Independent risk factors associated with mortality were identified based on data from 2013 to 2017, and a novel scoring model for mortality risk prediction was established. The bootstrapping statistical method was used for internal validation. External validation was performed using data from 2018 to 2020.

Results

We found that six predictors, including age, stiff neck, impaired consciousness, intracranial pressure, CD4⁺ T-cell count, and urea levels, were associated with poor prognosis in HIV/CM patients. The novel scoring model could effectively identify HIV/CM patients at high risk of death on admission (area under curve 0.876; p<0.001). When the cut-off value of 5.5 points or more was applied, the sensitivity and specificity was 74.1 and 83.8%, respectively. Our scoring model showed a good discriminatory ability, with an area under the curve of 0.879 for internal validation via bootstrapping, and an area under the curve of 0.886 for external validation.

Conclusions

Our developed scoring model of six variables is simple, convenient, and accurate for screening high-risk patients with HIV/CM, which may be a useful tool for physicians to assess prognosis in HIV/CM inpatients.