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Record W4405643850 · doi:10.1111/jan.16688

A Systematic Review of Multimodal Analgesic Effectiveness on Acute Postoperative Pain After Adult Cardiac Surgery

2024· review· en· W4405643850 on OpenAlexaff
Rochelle Wynne, Rebecca M. Jedwab, Kari Hanne Gjeilo, Suzanne Fredericks, Rosalie Magboo, Emily K. Hyde, Mohammad Goudarzi Rad, Sheila O’Keefe-McCarthy, Lisa Keeping‐Burke, Jo Murfin, Tieghan Killackey, Jill Bruneau, Stacey Matthews, Tracey Bowden, Julie Sanders, Irene Lie

Bibliographic record

VenueJournal of Advanced Nursing · 2024
Typereview
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsMemorial University of NewfoundlandUniversity of New BrunswickToronto Metropolitan UniversityUniversity Health NetworkUniversity of TorontoBrock UniversityUniversity of ManitobaWinnipeg Regional Health Authority
Fundersnot available
KeywordsMedicineAnalgesicAnesthesiaRandomized controlled trialClinical trialMultimodal therapyRegimenOpioidMeta-analysisCardiac surgeryPhysical therapySurgeryInternal medicine

Abstract

fetched live from OpenAlex

AIM: To synthesise the best available empirical evidence about the effectiveness of multimodal analgesics on pain after adult cardiac surgery. DESIGN: A systematic review with meta-analysis. METHODS: Indexed full-text papers or abstracts, in any language, of randomised controlled trials of adult patients undergoing cardiac surgery investigating multimodal postoperative analgesic regimen effect on mean level of patient-reported pain intensity at rest. DATA SOURCES: Eight databases, via two platforms and three trial registries were searched from 1 January 1995 to 1 June 2024 returning 3823 citations. RESULTS: Of the 123 full-text papers assessed, 29 were eligible for inclusion. Data were independently extracted by a minimum of two reviewers in Covidence. There were 2195 participants, aged 60.4 ± 6.6 (range 40-79) years, who were primarily male (n = 1522, 76.1%), randomised in the included studies. Risk of bias was high and reporting quality was poor. Patient-reported pain was measured at rest in 28 (96.6%) trials. Data were suitable for pooled analysis from 10 (34.5%) of these trials with an average rest pain intensity of 3.3 (SD 1.5) in the control and 2.7 (SD 1.9) in the intervention groups, respectively. No trials compared combinations of nonopioid, opioid-agonist-antagonist, partial opioid agonists or full opioid agonists. Most trials (n = 11, 37.9%) compared two different full opioid options for less than 72 h (n = 24, 82.7%). CONCLUSIONS: Robust trials are needed to determine which multimodal analgesic combination will optimise patient recovery after adult cardiac surgery. There is an urgent need to test and refine high-quality end-point measures. IMPLICATIONS FOR PATIENT CARE: Adequate assessment precedes ideal pain treatment. The findings from this review reveal neither are sufficient, and the impact of suboptimal pain management on postoperative recovery is grossly underinvestigated. IMPACT: The optimal combination of multimodal analgesics is unknown despite being recommended in best practice guidelines for enhanced recovery after cardiac surgery. Almost 30% of adults continue to experience ongoing pain up to a year after cardiac surgery, and findings from this review reveal a dearth of robust empirical evidence for optimal pain management, and heterogeneity in the way pain is assessed, measured and managed. This review provides a premise for robust trials focused on acute postoperative recovery in cardiac surgery and beyond. REPORTING METHOD: This review was conducted in accordance with the PRISMA-P statement. PATIENT OR PUBLIC CONTRIBUTION: There was no patient or public contribution. PROTOCOL REGISTRATION: PROSPERO: CRD42022355834.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.214
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0070.003
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.341
Teacher spread0.327 · 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 teacher head, not a consensus.

Study designSystematic review
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

Citations4
Published2024
Admission routes1
Has abstractyes

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