Sedation in the Intensive Care Unit
Bibliographic record
Abstract
CONTEXT: Sedation has become an integral part of critical care practice in minimizing patient discomfort; however, sedatives have adverse effects and the potential to prolong mechanical ventilation, which may increase health care costs. OBJECTIVE: To determine which form of sedation is associated with optimal sedation, the shortest time to extubation, and length of intensive care unit (ICU) stay. DATA SOURCES: A key word search of MEDLINE, EMBASE, and the Cochrane Collaboration databases and hand searches of 6 anesthesiology journals from 1980 to June 1998. Experts and industry representatives were contacted, personal files were searched, and reference lists of relevant primary and review articles were reviewed. STUDY SELECTION: Studies included were randomized controlled trials enrolling adult patients receiving mechanical ventilation and requiring short-term or long-term sedation. At least 2 sedative agents had to be compared and the quality of sedation, time to extubation, or length of ICU stay analyzed. DATA EXTRACTION: Data on population, intervention, outcome, and methodological quality were extracted in duplicate by 2 of 3 investigators using 8 validity criteria. DATA SYNTHESIS: Of 49 identified randomized controlled trials, 32 met our selection criteria; 20 studied short-term sedation and 14, long-term sedation. Of these, 20 compared propofol with midazolam. Most trials were not double-blind and did not report or standardize important cointerventions. Propofol provides at least as effective sedation as midazolam and results in a faster time to extubation, with an increased risk of hypotension and higher cost. Insufficient data exist to determine effect on length of stay in the ICU. Isoflurane demonstrated some advantages over midazolam, and ketamine had a more favorable hemodynamic profile than fentanyl in patients with head injuries. CONCLUSION: Considering the widespread use of sedation for critically ill patients, more large, high-quality, randomized controlled trials of the effectiveness of different agents for short-term and long-term sedation are warranted.
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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 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".