Neurocognitive Outcome Following Tuberculous Meningitis Treatment : A Systematic Review
Bibliographic record
Abstract
Background and objective: Tuberculous meningitis (TBM) is an infectious disease of the central nervous system that remains to be a global health challenge. Patients who survive after experiencing TBM have a risk of developing functional, cognitive and psychological disorders that can affect daily activities. The objective of this study is to present a comprehensive review of data on cognitive outcome after TBM infection. Method: We conducted a systematic literature search to identify studies addressing cognitive outcomes in adult TBM patients. Following a systematic literature search (PubMed, Scopus, EBSCO), studies were reviewed by independent reviewers to assess eligibility for inclusion. Three independent reviewers extracted data from included studies. Result: Among the articles identified, 6 studies met inclusion criteria, reporting cognitive outcomes for 330 patients with TBM. All studies followed the patients for 12 months or more. Three studies used Mini-Mental State Examinations (MMSE) to assess cognitive function, while other studies used a variety of tools: HIV-associated neurocognitive disorder (HAND), Montreal Cognitive Assessment (MoCA), neuropsychological (NEUROPSI), and Wechsler Adult Intelligence Scale (WAIS). All studies reported an improvement in cognitive function after completion of TB therapy. Two studies compared TBM with HIV, and showed TBM patients with HIV had worse cognitive outcomes than those without HIV. Conclusion: Cognitive function assessment tools in TBM patients are diverse and after approximately 12 months of follow-up following TB therapy, there was improvement in cognitive function. Standardized reporting of cognitive outcomes will be essential to improve data quality and data-sharing potential.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".