Central nervous system tuberculosis: characteristics, risks, and outcomes in California adults, 2010–2022
Bibliographic record
Abstract
Central nervous system (CNS) tuberculosis (TB) is rare and causes substantial morbidity and mortality. We quantified the frequency, characteristics, outcomes, and risks associated with CNS TB. We performed a retrospective analysis of culture-confirmed TB in adults reported to the California TB Registry during 2010–2022 to compare individuals with CNS TB vs. non-CNS TB. We used a causal diagram and modified Poisson model with robust variance to estimate the adjusted relative risk of CNS TB vs. non-CNS TB among people with TB caused by Mycobacterium bovis vs. non- M. bovis M. tuberculosis complex. We also identified risk factors for death with CNS TB. There were 21,117 TB cases reported; 382 (1.8 %) involved the CNS. Compared to those without CNS TB, those with CNS TB were more likely younger, of Hispanic ethnicity, born in Mexico, infected with M. bovis , co-infected with HIV, immunosuppressed, and to have had normal chest radiography. The adjusted relative risk of M. bovis (vs. non- M. bovis ) causing CNS TB was 2.86 (95 % CI 2.04–4.02). A large number of CNS TB patients died, 108 (28.3 %). Among people with CNS TB, death was associated with older age, end-stage renal disease, and immune suppression. More than one quarter of patients with CNS TB died. People with TB caused by M. bovis , were more likely to have CNS TB than people with TB caused by non- M. bovi s forms of the M. tuberculosis complex. Further efforts to prevent, rapidly diagnose, and effectively treat CNS TB is warranted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".