Retrospective cohort study analyzes clinical features and mortality risk in non-HIV elderly patients with cryptococcal meningitis, suggesting early identification of high-risk cases.
Background Cryptococcal meningitis (CM) is a life-threatening fungal infection with increasing incidence among non-HIV (human immunodeficiency virus) elderly populations. However, data on CM in non-HIV elderly patients are limited. This study aimed to analyze the clinical features, outcomes, and prognostic factors in non-HIV elderly CM patients using the largest dataset to date. Methods A retrospective cohort study was conducted using data from 667 non-HIV CM patients treated between 2013 and 2022. Patients were categorized into elderly (≥60 years) and non-elderly groups. Clinical features, laboratory findings, and neuroimaging results were analyzed. Least Absolute Shrinkage and Selection Operator regression identified prognostic factors, and multivariate logistic regression was used to construct a nomogram for predicting mortality. The model’s discrimination, calibration, and decision curve analysis (DCA) were evaluated. Results Elderly patients accounted for 23.5% of the study population, exhibited distinct clinical characteristics, and had a significantly higher one-year all-cause mortality rate (31.2% [95% confidence interval (CI) 23.61-38.71] vs . 13.8% [95% CI 10.77-16.81], P < 0.001). Four prognostic factors for elderly patients were identified, and a predictive nomogram was developed. The predictive model achieved an area under the curve (AUC) of 0.81 (95% CI 0.71-0.91), and the AUC was 0.79 (95% CI 0.70-0.87) in the internal validation. The model was well-calibrated, and DCA indicated a net benefit. Conclusion Non-HIV elderly CM patients present distinct clinical characteristics and have a higher mortality risk. The predictive model may facilitate the early identification of high-risk patients and guide timely interventions.
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Xu et al. (2025) studied this question.
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