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Record W4213183298 · doi:10.1007/s12630-021-02183-z

Efficacy of regional anesthesia techniques for postoperative analgesia in patients undergoing major oncologic breast surgeries: a systematic review and network meta-analysis of randomized controlled trials

2022· review· en· W4213183298 on OpenAlexafffund
Narinder Pal Singh, Jeetinder Kaur Makkar, Aswini Kuberan, Ryan Guffey, Vishal Uppal

Bibliographic record

VenueCanadian Journal of Anesthesia/Journal canadien d anesthésie · 2022
Typereview
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsNova Scotia Health AuthorityIzaak Walton Killam Health CentreDalhousie University
FundersDalhousie University
KeywordsMedicineRandomized controlled trialLevobupivacaineAnesthesiaPlaceboMeta-analysisNerve blockNauseaBreast surgeryBreast cancerPostoperative nausea and vomitingCancer painSurgeryAnalgesicInternal medicineCancer

Abstract

fetched live from OpenAlex

BACKGROUND: The optimal regional technique to control pain after breast cancer surgery remains unclear. We sought to synthesize available data from randomized controlled trials comparing pain-related outcomes following various regional techniques for major oncologic breast surgery. METHODS: In a systematic review and network meta-analysis, we searched trials in PubMed, Embase Scopus, Medline, Cochrane Central and Google Scholar, from inception to 31 July 2020, for commonly used regional techniques. The primary outcome was the 24-hr resting pain score measured on a numerical rating score of 0-10. We used surface under the cumulative ranking curve (SUCRA) to establish the probability of an intervention ranking highest. The analysis was performed using the Bayesian random effects model, and effect sizes are reported as 95% credible interval (Crl). We conducted cluster-rank analysis by combining 24-hr pain ranking with 24-hr opioid use or incidence of postoperative nausea and vomiting. RESULTS: Seventy-nine randomized controlled trials containing 11 different interventions in 5,686 patients were included. The SUCRA values of the interventions for 24-hr resting pain score were continuous paravertebral block (0.83), serratus anterior plane block (0.76), continuous wound infusion (0.76), single-level paravertebral block (0.68), erector spinae plane block (0.59), modified pectoral block (0.49), intercostal block (0.45), multilevel paravertebral block (0.41), wound infiltration (0.33), no intervention (0.12), and placebo (0.08). When compared with placebo, the continuous paravertebral block (mean difference, 1.26; 95% Crl, 0.43 to 2.12) and serratus anterior plane block (mean difference, 1.12; 95% Crl, 0.32 to 1.9) had the highest estimated probability of decreasing 24-hr resting pain scores. Cluster ranking analysis combining 24-hr resting pain scores and opioid use showed that most regional analgesia techniques were more effective than no intervention or placebo. Nevertheless, wound infiltration and continuous wound infusion may be the least effective active interventions for reducing postoperative nausea and vomiting. CONCLUSION: Continuous paravertebral block and serratus anterior plane block had a high probability of reducing pain at 24 hr after major oncologic breast surgery. The certainty of evidence was moderate to very low. Future studies should compare different regional anesthesia techniques, including surgeon-administered techniques such as wound infiltration or catheters. Trials comparing active intervention with placebo are unlikely to change clinical practice. STUDY REGISTRATION: PROSPERO (CRD42020198244); registered 19 October 2020.

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)0.008
metaresearch head score (Gemma)0.024
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: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.024
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0150.028
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.061
GPT teacher head0.312
Teacher spread0.251 · 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

Citations49
Published2022
Admission routes2
Has abstractno

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