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Record W7038841060

Ketamine Sedation in the Intensive Care Unit: A Survey, Systematic Review, Network Meta-analysis, and Pilot Study Protocol

2023· dissertation· en· W7038841060 on OpenAlexaboutno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2023
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicColeoptera Taxonomy and Distribution
Canadian institutionsnot available
Fundersnot available
KeywordsSedationSedativeKetamineIntensive careRandomized controlled trialProtocol (science)
DOInot available

Abstract

fetched live from OpenAlex

This thesis consists of two studies presented as two separate manuscripts (one has been published in a peer-reviewed journal and the other is in the process of being submitted to a peer-reviewed journal) and a protocol for a pilot randomized controlled trial. The overarching aim of this thesis was to explore the evidence examining the use of ketamine as a sedative for critically ill mechanically ventilated patients in the Intensive Care Unit (ICU). We conducted a national survey to understand the beliefs and practices of Canadian ICU physicians regarding the use of ketamine as a continuous intravenous sedative in critically ill patients and to gauge interest in participating in a randomized controlled trial (RCT). We surveyed 400 physician members of the Canadian Critical Care Society and found that most respondents rarely use ketamine as a continuous infusion for sedation or analgesia in the ICU. We found that there were a number of clinical circumstances that would make physicians more likely to use ketamine such as asthma exacerbation and established tolerance to opioids. Conversely, physicians were concerned about the potential side effects of ketamine, particularly psychotropic effects including delirium. Overall, the majority of physicians surveyed agreed that there is a need for a clinical trial to evaluate the effectiveness and safety of ketamine as a sedative infusion in the ICU. The results of this survey informed the second manuscript which is a systematic review examining the use of procedural sedation medications in acutely ill patients. Prospective data examining ketamine as a continuous sedative in critically ill patients is sparse and insufficient for pooled analysis. Therefore, we focused on an indirect source of evidence, the role of ketamine as a procedural sedation drug. In order to summarize this data, we performed a systematic review and network meta-analysis (NMA) comparing all peri-procedural sedative drugs in acutely ill patients. The NMA provides the ability to include indirect data into the pooled point estimates. We performed a search of multiple databases and found 82 RCTs (8,105 patients) that met eligibility criteria, 78 conducted in the Emergency Department and 4 in the ICU. Compared to alternative medications, we found that ketamine was associated with the fewest respiratory adverse events based on high certainty evidence. Furthermore, we found that combining ketamine with propofol resulted in the highest patient satisfaction (high certainty) and the fewest cardiac adverse events (low certainty). The final component of this thesis is a pilot RCT protocol examining the feasibility of a larger RCT assessing the efficacy and safety of an adjunctive ketamine continuous infusion in mechanically ventilated ICU patients. We plan to submit this protocol for peer-reviewed funding as a first step to address this clinically important question.

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 imitation

Not 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.

metaresearch head score (Codex)0.083
metaresearch head score (Gemma)0.111
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.083
Threshold uncertainty score0.441

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0830.111
Meta-epidemiology (narrow)0.0040.006
Meta-epidemiology (broad)0.0100.014
Bibliometrics0.0090.009
Science and technology studies0.0030.003
Scholarly communication0.0050.005
Open science0.0040.004
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0460.005

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.

Opus teacher head0.095
GPT teacher head0.278
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreProtocol

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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