Impact of Ketamine on Analgosedative Consumption in Critically Ill Patients: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Objective: The aim of this study was to synthesize evidence available on continuous infusion ketamine versus nonketamine regimens for analgosedation in critically ill patients. Data sources A search of MEDLINE, EMBASE, CINAHL, CDSR, and ClinicalTrials.gov was performed from database establishment to November 2021 using the following search terms: critical care, ICU, ketamine, sedation , and anesthesia . All studies included the primary outcome of interest: daily opioid and/or sedative consumption. Study selection and data extraction Relevant human studies were considered. Randomized controlled trials (RCT), quasi-experimental studies, and observational cohort studies were eligible. Two reviewers independently screened articles, extracted data, and appraised studies using the Cochrane RoB and ROBINS-I tools. Data synthesis A total of 13 RCTs, 5 retrospective, and 1 prospective cohort study were included (2255 participants). The primary analysis of six RCTs demonstrated reduced opioid consumption with ketamine regimens (n = 494 participants, −13.19 µg kg −1 h −1 morphine equivalents, 95% CI −22.10 to −4.28, P = 0.004). No significant difference was observed in sedative consumption, duration of mechanical ventilation (MV), ICU or hospital length of stay (LOS), intracranial pressure, and mortality. Small sample size of studies may have limited ability to detect true differences between groups. Relevance to patient care and clinical practice This meta-analysis examining ketamine use in critically ill patients is the first restricting analysis to RCTs and includes up-to-date publication of trials. Findings may guide clinicians in consideration and dosing of ketamine for multimodal analgosedation. Conclusion Results suggest ketamine as an adjunct analgosedative has the potential to reduce opioid exposure in postoperative and MV patients in the ICU. More RCTs are required before recommending routine use of ketamine in select populations.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".