ArticleBMC infectious diseases2023
The clinic-based predictive modeling for prognosis of patients with cryptococcal meningitis.
Article in BMC infectious diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 6 citations in OpenAlex.
- Cryptococcal Meningitis: Comparison of Short- (≤ 1 Week) Versus Longer-duration (> 1 Week) Liposomal Amphotericin B Induction Therapy and Factors Associated With Clinical Outcomes in HIV and Non-HIV Patients.Open forum infectious diseases · 2026Trial
- Development and internal validation of a prognostic nomogram for poor outcomes in neonatal bacterial meningitis.Translational pediatrics · 2026Article
- Cerebrospinal Fluid Lactate Levels as a Prognostic Indicator in Patients With Cryptococcal Meningitis Who Are HIV Negative: A Retrospective Cohort Study.Open forum infectious diseases · 2024Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundCryptococcal meningitis (CM) is the most common fungal infection of the central nervous system that can cause significant morbidity and mortality. Although several prognostic factors have been identified, their clinical efficacy and use in combination to predict outcomes in immunocompetent patients with CM are not clear. Therefore, we aimed to determine the utility of those prognostic factors alone or in combination in predicting outcomes of immunocompetent patients with CM.
methodsThe demographic and clinical data of patients with CM were collected and analyzed. The clinical outcome was graded by the Glasgow outcome scale (GOS) at discharge, and patients were divided into good (score of 5) and unfavorable (score of 1-4) outcome groups. Prognostic model was created and receiver-operating characteristic curve analyses were conducted.
resultsA total of 156 patients were included in our study. Patients with higher age at onset (p = 0.021), ventriculoperitoneal shunt placement (p = 0.010), Glasgow Coma Scale (GCS) score of less than 15(p< 0.001), lower CSF glucose concentration (p = 0.037) and immunocompromised condition (p = 0.002) tended to have worse outcomes. Logistic regression analysis was used to create a combined score which had a higher AUC (0.815) than those factors used alone for predicting outcome.
conclusionsOur study shows that a prediction model based on clinical characteristics had satisfactory accuracy in prognostic prediction. Early recognition of CM patients at risk of poor prognosis using this model would be helpful in providing timely management and therapy to improve outcomes and to identify individuals who warrant early follow-up and intervention.
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