Nursing management of intracranial hypertension in adults with severe brain injury in a neurosurgery intensive care unit: a best practice implementation project
Bibliographic record
Abstract
INTRODUCTION: The nursing management of intracranial hypertension in adult patients with severe brain injury is crucial for maintaining the stability of intracranial pressure, which ultimately improves patient outcomes. OBJECTIVES: This project aimed to implement evidence-based practices for the nursing management of intracranial hypertension in adult patients with severe brain injury. METHODS: This evidence implementation project was conducted in a neurosurgery intensive care unit in a large tertiary hospital in Guangzhou, China. The project was guided by the JBI Evidence Implementation Framework, which is an audit and feedback model with seven stages. The Ottawa Model of Research Use was used to identify barriers and facilitators to best practices and to develop improvement strategies. RESULTS: Thirty-three nurses and 50 patients with severe brain injury participated in the baseline and follow-up audits. After project implementation, follow-up audits revealed significantly improved compliance with best practices compared with baseline. Nurses' awareness of best practices increased (41% to 96%); nursing assessment, monitoring, and interventions related to intracranial hypertension rose significantly (from 82%, 75%, and 59% to 98%, 84%, and 87%, respectively); and patients' optic nerve sheath diameter was notably lower (6.002±0.677 mm to 5.698±0.730 mm). CONCLUSIONS: The systematic integration of consistent training and education, together with the refinement of care processes and the creation of relevant tools, led to a significant improvement in awareness and adherence to best practices. Further testing of this program in more hospitals is needed. SPANISH ABSTRACT: http://links.lww.com/IJEBH/A243.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".