Meningitis as a Hidden Cause of Neurological Deterioration in Patients With Known Brain Metastases: A Report of Two Cases
Bibliographic record
Abstract
When a patient with known brain metastases presents to the emergency department with neurological deterioration, an overt diagnosis exists. However, alternative diagnoses should also be considered in the appropriate clinical context. A correct diagnosis is critical for the appropriate treatment, especially in cases, in which a reversible cause of illness exists. In this report, we describe two cases of cancer patients with known brain metastases in whom the neurological deterioration was due to carcinomatous meningitis and viral menigitis, respectively. A lumbar puncture was performed based on the fact that neurological deterioration was in contrast with the absence of new findings in brain CT scans. As it is emphasized by these two cases, patients with brain metastases, unchanged at CT imaging, and recent neurological deterioration must undergo lumbar puncture before their symptoms are considered a progression of their already existing brain metastases. In some cases, the deterioration might be due to a potentially reversible illness or due to an illness requiring specific treatment. J Med Cases. 2016;7(11):475-477 doi: http://dx.doi.org/10.14740/jmc2631w
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".