Neurosurgery (Critical Care/Neuro Trauma)
Bibliographic record
Abstract
Background: There exists the role for novel agents in the management of refractory intracranial pressure (ICP) via targeting cerebral acidosis, hyperemia, and excitotoxicity. Objective: We performed 4 separate systematic reviews to determine the effect of tromethamine (THAM), indomethacin, and ketamine on ICP. Methods: All articles from MEDLINE, BIOSIS, EMBASE, Global Health, HealthStar, Scopus, Cochrane Library, the International Clinical Trials Registry Platform (inception to: February 2014 – THAM, July 2014 – Indomethacin, November 2013 - Ketamine), and gray literature were searched. The strength of evidence was adjudicated using both the Oxford and GRADE methodology. Results: Twelve articles were reviewed utilizing THAM while documenting ICP in neurosurgical patients. All but one study documented a decrease in ICP. Twelve original articles were reviewed utilizing indomethacin for ICP in neurological patients. All but one study documented a decrease in ICP. Seven articles were reviewed utilizing ketamine, documenting ICP in TBI patients, with 16 in non-trauma neurological patients. ICP did not increase in the studies during ketamine administration, and trended to decrease ICP. Conclusion: There exists Oxford level 2b, GRADE B evidence that THAM reduces ICP in the TBI and malignant ischemic infarct population. There exists Oxford level 2b, GRADE C evidence that indomethacin and ketamine reduce ICP in the adult severe TBI population.
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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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".