Acute neurosurgical management of traumatic brain injury and spinal cord injury
Bibliographic record
Abstract
Purpose of review This review discusses some of the recent advances and current controversies in the acute clinical management of traumatic brain injury (TBI) and spinal cord injury (SCI). Recent findings Several key risk factors for adverse prognosis in TBI have been identified, including female sex. In the management of intracranial hypertension antibiotic impregnated intraventricular catheters have been found to reduce the risk for infection, and new studies have examined the roles of mannitol, hyperventilation, and hypothermia. Moderate hypothermia has also been found to improve outcome. Hyperoxia is now being explored as a treatment option for improving brain metabolism in TBI. That acute SCI continues to be a challenging diagnosis is supported by a recent study that showed that 9.1% of SCIs are missed initially. The diagnosis and management of spinal instability has been studied in different patient groups. In SCI without radiographic abnormality, the presence of normal magnetic resonance imaging findings was associated with a good prognosis. New studies in the field of early decompression and the prevention of thromboembolism in SCI have also been published. Guidelines for the management of acute SCI recommend methylprednisolone and GM-1 ganglioside only as options. Summary In neurotrauma some established treatments have been re-examined and their efficacy proven, whereas others that were once considered the standard of care in SCI, such as methylprednisolone, have been questioned. Large multicenter trials are needed to assess treatments such as early decompression in SCI and decompressive craniectomy in TBI. A truly effective neuroprotective therapy in neurotrauma remains elusive.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".