The Role of Anesthesia in Sedation and Weaning From Mechanical Ventilation: A Systematic Review
Bibliographic record
Abstract
Mechanical ventilation is a critical component of care in ICUs, yet its prolonged use can result in significant complications. Effective sedation strategies play a pivotal role in facilitating the discontinuation of mechanical ventilation and minimizing associated adverse outcomes. This systematic review evaluates the impact of anesthetic-based sedation methods on optimizing the process of weaning adult patients from mechanical ventilation in intensive care settings. A comprehensive literature search was conducted across major databases, including PubMed, Web of Science, Scopus, the Virtual Health Library, and Cochrane CENTRAL, up to March 10, 2024, following established systematic review guidelines. Eligible studies included randomized controlled trials and observational research comparing anesthetic agents with conventional sedation techniques, with outcomes such as weaning duration, extubation success, length of stay in the ICU, incidence of delirium, sedation quality, adverse events, and mortality. Study quality was assessed using a validated methodological checklist. Out of 1,649 records screened, five studies met the inclusion criteria. Results indicated that dexmedetomidine was associated with shorter weaning times and reduced anxiety, agitation, and delirium compared to traditional sedation. Sequential sedation protocols, particularly transitions from midazolam to dexmedetomidine, yielded improved clinical outcomes, while enteral methadone significantly reduced weaning duration compared to fentanyl. Despite higher daily costs, anesthetic agents demonstrated favorable economic outcomes due to shorter intensive care stays. These findings suggest that targeted anesthetic sedation strategies may enhance the weaning process and improve overall patient outcomes, underscoring the need for further large-scale studies to validate and standardize these approaches.
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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 | 0.011 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".