Acute management of acquired brain injury part I: An evidence-based review of non-pharmacological interventions
Bibliographic record
Abstract
PRIMARY OBJECTIVE: To review the literature on non-pharmacological interventions used in acute settings to manage elevated intracranial pressure (ICP) and minimize cerebral damage in patients with acquired brain injury (ABI). MAIN OUTCOMES: A literature search of multiple databases (CINAHL, EMBASE, MEDLINE and PSYCHINFO) and hand-searched articles covering the years 1980-2008 was performed. Peer reviewed articles were assessed for methodological quality using the PEDro scoring system for randomized controlled trials (RCTs) and the Downs and Black tool for RCTs and non-randomized trials. Levels of evidence were assigned and recommendations made. RESULTS: Five non-invasive interventions for acute ABI management were assessed: adjusting head posture, body rotation (continuous rotational therapy and prone positioning), hyperventilation, hypothermia and hyperbaric oxygen. Two invasive interventions were also reviewed: cerebrospinal fluid (CSF) drainage and decompressive craniectomy (DC). CONCLUSIONS: There is a paucity of information regarding non-pharmacological acute management of patients with ABI. Strong levels of evidence were found for only four of the seven interventions (decompressive craniectomy, cerebrospinal fluid drainage, hypothermia and hyperbaric oxygen) and only for specific components of their use. Further research into all interventions is warranted.
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".