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

Nomogram to Predict the Outcome of Ventriculoperitoneal Shunt Among Patients with Non-HIV Cryptococcal Meningitis

BACKGROUND

The ventriculoperitoneal (VP) shunt is widely acknowledged as a treatment option for managing intracranial hypertension resulting from non-human immunodeficiency virus (HIV) cryptococcal meningitis (CM). Nonetheless, there is currently no consensus on the appropriate surgical indications for this procedure. Therefore, it is crucial to conduct a preoperative evaluation of patient characteristics and predict the outcome of the VP shunt to guide clinical treatment effectively.

METHODS

A retrospective analysis was conducted on data from 85 patients with non-HIV CM who underwent VP shunt surgery at our hospital. The analysis involved studying demographic data, preoperative clinical manifestations, cerebrospinal fluid (CSF) characteristics, and surgical outcomes and comparisons between before and after surgery. A nomogram was developed and evaluated.

RESULTS

The therapy outcomes of 71 patients improved, whereas 14 cases had worse outcomes. Age, preoperative cryptococcus count, and preoperative CSF protein levels were found to influence the surgical outcome. The nomogram exhibited exceptional predictive performance (area under the curve = 0.896, 95% confidence interval: 0.8292-0.9635). Internal validation confirmed the nomogram's excellent predictive capabilities. Moreover, decision curve analysis demonstrated the nomogram's practical clinical utility.

CONCLUSIONS

The surgical outcome of VP shunt procedures patients with non-HIV CM was associated with age, preoperative cryptococcal count, and preoperative CSF protein levels. We developed a nomogram that can be used to predict surgical outcomes in patients with non-HIV CM.

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

BACKGROUND

Cryptococcal meningitis (CM) remains a major cause of death among people living with HIV in rural sub-Saharan Africa. We previously reported that a CM diagnosis and treatment program (CM-DTP) improved hospital survival for CM patients in rural, northern Uganda. This study aimed to evaluate the impact on long-term survival.

METHODS

We conducted a retrospective study at Lira Regional Referral Hospital in Uganda evaluating long-term survival (≥1 year) of CM patients diagnosed after CM-DTP initiation (February 2017-September 2021). We compared with a baseline historical group of CM patients before CM-DTP implementation (January 2015-February 2017). Using Cox proportional hazards models, we assessed time-to-death in these groups, adjusting for confounders.

RESULTS

We identified 318 CM patients, 105 in the Historical Group, and 213 in the CM-DTP Group. The Historical Group had a higher 30-day mortality of 78.5% compared to 42.2% in the CM-DTP Group. The overall survival rate for the CM-DTP group at three years was 25.6%. Attendance at follow-up visits (HR:0.13, 95% CI: [0.03-0.53], p <0.001), ART adherence (HR:0.27, 95% CI: [0.10-0.71], p = 0.008), and fluconazole adherence: (HR:0.03, 95% CI: [0.01-0.13], p <0.001), weight >50kg (HR:0.54, 95% CI: [0.35-0.84], p = 0.006), and performance of therapeutic lumbar punctures (HR:0.42, 95% CI: [0.24-0.71], p = 0.001), were associated with lower risk of death. Altered mentation was associated with increased death risk (HR: 1.63, 95% CI: 1.10-2.42, p = 0.016).

CONCLUSION

Long-term survival of CM patients improved after the initiation of the CM-DTP. Despite this improved survival, long-term outcomes remained sub-optimal, suggesting that further work is needed to enhance long-term survival.

Antifungal Resistance in Cryptococcal Infections

Antifungal therapy, especially with the azoles, could promote the incidence of less susceptible isolates of Cryptococcus neoformans and C. gattii species complexes (SC), mostly in developing countries. Given that these species affect mostly the immunocompromised host, the infections are severe and difficult to treat. This review encompasses the following topics: 1. infecting species and their virulence, 2. treatment, 3. antifungal susceptibility methods and available categorical endpoints, 4. genetic mechanisms of resistance, 5. clinical resistance, 6. fluconazole minimal inhibitory concentrations (MICs), clinical outcome, 7. environmental influences, and 8. the relevance of host factors, including pharmacokinetic/pharmacodynamic (PK/PD) parameters, in predicting the clinical outcome to therapy. As of now, epidemiologic cutoff endpoints (ECVs/ECOFFs) are the most reliable antifungal resistance detectors for these species, as only one clinical breakpoint (amphotericin B and C. neoformans VNI) is available.

Clinical characteristics, treatment, and outcome of low-risk non-HIV-associated cryptococcal meningitis: A retrospective cohort study

Although non-human immunodeficiency virus (HIV)-associated cryptococcal meningitis (CM) is a severe disease, there are still some non-HIV CM patients with a low risk of therapeutic failure. Recognizing clinical characteristics of low-risk non-HIV-associated CM may enable clinicians to treat non-HIV-associated CM more reasonably. According to the definition of low-risk non-HIV-associated CM in the 2010 Infectious Diseases Society of America guideline, a total of 220 non-HIV CM patients were divided into two groups (Group 1: 35 low-risk patients and Group 2: 185 non-low-risk patients). Clinical characteristics, treatment, and outcome were compared between the two groups. Compared with non-low-risk patients, low-risk patients had a lower rate of headache (82.9% vs. 95.7%, P = .012), cerebrospinal fluid (CSF) opening pressure (OP) at baseline (CSF OP < 250-mm H2O, 60.0% vs. 32.4%, P = .001), and baseline CSF cryptococcal count (median, 0 vs. 2376, P < .001), higher baseline CSF white blood cell (median, 130 vs. 90, P = .029) and CSF protein (median, 0.87 vs. 0.73, P = .011). Multivariate analysis showed that baseline CSF OP <250-mm H2O (OR: 2.545, 95% CI 1.168, 5.545, P = .019) was independently associated with low-risk for non-HIV-associated CM. The lengths of AMB-d-based induction therapy of low-risk patients (median, 20 days) were shorter (P < .001) than that of non-low-risk patients (median, 38 days). The successful outcome rate of low-risk patients was higher than non-low-risk patients (97.1% vs. 54.6%, P < .001). We demonstrated that non-HIV-associated CM patients with baseline CSF OP < 250-mm H2O were prone to the low-risk status.

Development and validation of a machine learning model to predict prognosis in HIV-negative cryptococcal meningitis patients: a multicenter study

PURPOSE

To predict prognosis in HIV-negative cryptococcal meningitis (CM) patients by developing and validating a machine learning (ML) model.

METHODS

This study involved 523 HIV-negative CM patients diagnosed between January 1, 1998, and August 31, 2022, by neurologists from 3 tertiary Chinese centers. Prognosis was evaluated at 10 weeks after the initiation of antifungal therapy.

RESULTS

The final prediction model for HIV-negative CM patients comprised 8 variables: Cerebrospinal fluid (CSF) cryptococcal count, CSF white blood cell (WBC), altered mental status, hearing impairment, CSF chloride levels, CSF opening pressure (OP), aspartate aminotransferase levels at admission, and decreased rate of CSF cryptococcal count within 2 weeks after admission. The areas under the curve (AUCs) in the internal, temporal, and external validation sets were 0.87 (95% CI 0.794-0.944), 0.92 (95% CI 0.795-1.000), and 0.86 (95% CI 0.744-0.975), respectively. An artificial intelligence (AI) model was trained to detect and count cryptococci, and the mean average precision (mAP) was 0.993.

CONCLUSION

A ML model for predicting prognosis in HIV-negative CM patients was built and validated, and the model might provide a reference for personalized treatment of HIV-negative CM patients. The change in the CSF cryptococcal count in the early phase of HIV-negative CM treatment can reflect the prognosis of the disease. In addition, utilizing AI to detect and count CSF cryptococci in HIV-negative CM patients can eliminate the interference of human factors in detecting cryptococci in CSF samples and reduce the workload of the examiner.

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

OBJECTIVE

Cryptococcal meningitis (CM) is a not rare condition in HIV-negative patients. Here, we describe the clinical characteristics, possible risk factors, and outcomes of HIV-negative patients with CM.

METHODS

Medical records from 99 HIV-negative patients with CM admitted to our hospital from 2010 to 2021 were reviewed systematically. We compared the clinical features and outcomes between patients with underlying diseases and otherwise healthy hosts.

RESULTS

The 99 HIV-negative CM patients had a mean age at presentation of 56.2 ± 16.2 years, and the female-to-male ratio was 77:22. A total of 52 (52.5%) CM patients had underlying conditions, and 47 patients (47.5%) had no underlying conditions. Kidney transplant represented the most frequent underlying condition (11.1%), followed by rheumatic disease (10.1%) and hematological diseases (9.1%). Compared to patients without underlying conditions, those with underlying conditions had significantly more fever, more steroid therapy, higher serum creatinine, and lower albumin, IgG, hemoglobin, and platelets (p < 0.05 for each). CM patients without underlying conditions had significantly more alcohol abuse than those with underlying conditions (31.9% vs. 9.6%, p = 0.011). By logistic regression analysis, male gender (OR = 3.16, p = 0.001), higher CSF WBC (OR = 2.88, p = 0.005), and protein (OR = 2.82, p = 0.002) were significantly associated with mortality.

CONCLUSION

Patients with underlying conditions had a similar mortality to patients without underlying conditions. Alcohol abuse was a probable risk factor for CM for previously healthy patients. Male gender, higher CSF WBC, and protein were significantly associated with mortality.