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Record W4313552837 · doi:10.1101/2023.01.03.23284166

Non-steroidal anti-inflammatories for analgesia in critically ill patients: a systematic review and meta-analysis of randomized control trials

2023· review· en· W4313552837 on OpenAlexafffund
Chen-Hsiang Ma, Kimberly B. Tworek, Janice Y. Kung, Sebastian Kilcommons, Kathleen E. Wheeler, Arabesque Parker, Janek Senaratne, Erika MacIntyre, Wendy Sligl, Constantine Karvellas, Fernando G. Zampieri, Demetrios J. Kutsogiannis, John Basmaji, Kimberley Lewis, Dipayan Chaudhuri, Sameer Sharif, Oleksa Rewa, Bram Rochwerg, Sean M. Bagshaw, Vincent Lau

Bibliographic record

VenuemedRxiv · 2023
Typereview
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsAlberta HealthWestern UniversityAlberta Health ServicesMcMaster UniversityUniversity of AlbertaImpact
FundersLondon Health Sciences Centre
KeywordsMedicineCochrane LibraryMeta-analysisRandomized controlled trialMechanical ventilationIntensive care unitConfidence intervalRelative riskAdverse effectMEDLINEAnesthesiaOpioidIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Abstract Purpose While opioids are part of usual care for analgesia in the intensive care unit (ICU), there are concerns regarding excess use. This is a systematic review of non-steroidal anti-inflammatories (NSAIDs) use in critically ill adult patients. Methods We conducted a systematic search of MEDLINE, EMBASE, CINAHL, and Cochrane Library. We included randomized control trials (RCTs) comparing NSAIDs alone or as an adjunct to opioids for analgesia. The primary outcome was opioid utilization. We reported mean difference for continuous outcomes and relative risk for dichotomous outcomes with 95% confidence intervals (CIs). We evaluated study risk of bias using the Cochrane risk of bias tool and evidence certainty using GRADE. Results We included 15 RCTs (n=1621 patients). Adjunctive NSAID therapy to opioids reduced 24-hour oral morphine equivalent consumption by 21.4mg (95% CI: 11.8-31.0mg reduction, high certainty) and probably reduced pain scores (measured by visual analogue scale) by -6.1mm (95% CI: -12.2 to +0.1, moderate certainty). Adjunctive NSAIDs probably had no impact on duration of mechanical ventilation (-1.6 hours, 95% CI: -0.4 to -2.7 hours, moderate certainty) and may have no impact on ICU length of stay (-2.1 hours, 95% CI: -6.1 to +2.0 hours, low certainty). Variability in reporting of adverse outcomes (e.g. gastrointestinal bleeding, acute kidney injury) precluded their meta-analysis. Conclusion In critically ill adult patients, NSAIDs reduced opioid use, probably reduced pain scores, but were uncertain for duration of mechanical ventilation or ICU length of stay. Further research is required to characterize the prevalence of NSAID-related adverse outcomes. Take-Home Message In this systematic review and meta-analysis of 15 randomized control trials that included 1621 critically ill adult patients, the addition of non-steroidal anti-inflammatories to an opioid analgesic strategy reduced 24-hour opioid use and modestly reduced pain with no impact on duration of mechanical ventilation or ICU length of stay.

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)0.020
metaresearch head score (Gemma)0.054
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.028
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.054
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0280.031
Bibliometrics0.0080.008
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.077
GPT teacher head0.380
Teacher spread0.303 · 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 designMeta-analysis
Domainnot available
GenreReview

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 routes2
Has abstractyes

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