Severe Intracranial Hypertension Associated with Tetracycline Use in Non-Small Cell Lung Cancer
Bibliographic record
Abstract
Introduction : Erlotinib has become an established treatment for patients with non-small cell lung cancer harbouring an epidermal growth factor receptor (EGFR) mutation. Tetracycline antibiotics are commonly prescribed for erlotinib-induced acneiform rash. A rare but morbid complication of tetracycline use is intracranial hypertension, an association which has not been reported in the oncology literature. Presentation of Case : We report a case of severe intracranial hypertension in a patient with non-small cell lung cancer. Risk factors were prolonged tetracycline use and leptomeningeal carcinomatosis. Initial investigations were unhelpful, necessitating a high index of suspicion. Conclusion : Tetracycline antibiotics, which are commonly prescribed for erlotinib rash, are an important risk factor for intracranial hypertension. Our patient developed severe vision loss from papilloedema, despite normal neuroimaging and relatively low opening pressure on lumbar puncture. Continuous intracranial pressure monitoring can be a valuable investigation in such circumstances.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".