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Stadelman-Behar, Anna M, Tiffin, Nicki, Ellis, Jayne, Creswall, Fiona V, Ssebambulidde, Kenneth, Nuwagira, Edwin, Richards, Lauren and Lutje, Vittoria (2024) 'Diagnostic Prediction Model for Tuberculous Meningitis: An Individual Participant Data Meta-Analysis'. The American Journal of Tropical Medicine and Hygiene, Vol 11, Issue 3, pp. 546-553.
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Abstract
No accurate and rapid diagnostic test exists for tuberculous meningitis (TBM), leading to delayed diagnosis. We leveraged data from multiple studies to improve the predictive performance of diagnostic models across different populations, settings, and subgroups to develop a new predictive tool for TBM diagnosis. We conducted a systematic review to analyze eligible datasets with individual-level participant data (IPD). We imputed missing data and explored three approaches: stepwise logistic regression, classification and regression tree (CART), and random forest regression. We evaluated performance using calibration plots and C-statistics via internal–external cross-validation. We included 3,761 individual participants from 14 studies and nine countries. A total of 1,240 (33%) participants had “definite” (30%) or “probable” (3%) TBM by case definition. Important predictive variables included cerebrospinal fluid (CSF) glucose, blood glucose, CSF white cell count, CSF differential, cryptococcal antigen, HIV status, and fever presence. Internal validation showed that performance varied considerably between IPD datasets with C-statistic values between 0.60 and 0.89. In external validation, CART performed the worst (C = 0.82), and logistic regression and random forest had the same accuracy (C = 0.91). We developed a mobile app for TBM clinical prediction that accounted for heterogeneity and improved diagnostic performance (https://tbmcalc.github.io/tbmcalc). Further external validation is needed.
| Item Type: | Article |
|---|---|
| Subjects: | WF Respiratory System > WF 20 Research (General) WF Respiratory System > Tuberculosis > WF 200 Tuberculosis (General) WL Nervous System > WL 200 Meninges. Blood-brain barrier |
| Faculty: Department: | Clinical Sciences & International Health > Clinical Sciences Department |
| Digital Object Identifer (DOI): | https://doi.org/10.4269/ajtmh.23-0789 |
| Depositing User: | Christianne Esparza |
| Date Deposited: | 15 Jan 2025 09:52 |
| Last Modified: | 15 Jan 2025 09:54 |
| URI: | https://archive.lstmed.ac.uk/id/eprint/25813 |
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