Lumbar Puncture and Brain Herniation in Acute Bacterial Meningitis: A Review
Bibliographic record
Abstract
There has been controversy regarding the risk of cerebral herniation caused by a lumbar puncture (LP) in acute bacterial meningitis (ABM). This review discusses in detail the issues involved in this controversy. Cerebral herniation occurs in about 5% of patients with ABM, accounting for about 30% of the mortality. In many reports, LP is temporally strongly associated with this event of herniation and is most likely causative based on pathophysiologic arguments. Although a computed tomography (CT) scan of the head is useful to find contraindications to an LP, a normal CT scan in ABM does not mean that an LP is safe. Clinical signs of “impending” herniation are the best predictors of when to delay an LP because of the risk of precipitating herniation, even with a normal CT scan. Some of these clinical signs to be considered are deteriorating level of consciousness (particularly to a Glasgow Coma Scale of ≤ 11), brainstem signs (including pupillary changes, posturing, or irregular respirations), and a very recent seizure. The risk of not doing an LP when it is contraindicated because of concern of the risk of herniation is extremely small. In those considered high risk for herniation, interventions to control intracranial pressure, such as attention to airway, breathing, and circulation, with a mannitol infusion and antibiotics started, should be the priorities, followed by an urgent CT scan and not an LP.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".