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Record W4295339279 · doi:10.1111/jocs.16882

Median sternotomy pain after cardiac surgery: To block, or not? A systematic review and meta‐analysis

2022· review· en· W4295339279 on OpenAlexaff
Morgan King, Thomas Stambulic, Syed M. Ali Hassan, Patrick A. Norman, Kendra Derry, Darrin Payne, Mohammad El‐Diasty

Bibliographic record

VenueJournal of Cardiac Surgery · 2022
Typereview
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsKingston Health Sciences CentreQueen's University
Fundersnot available
KeywordsMedicineMeta-analysisMedian sternotomyCardiac surgerySurgeryMEDLINEInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Inadequate pain control after median sternotomy leads to reduced mobilization, increased respiratory complications, and longer hospital stays. Typically, postoperative pain is controlled by opioid analgesics that may have several adverse effects. Parasternal intercostal block (PSB) has emerged as part of a multimodal strategy to control pain after median sternotomy. However, the effectiveness of this intervention on postoperative pain control and analgesic use has not been fully established. METHODS AND RESULTS: We conducted a meta-analysis to assess the effect of PSB on postoperative pain and analgesic use in adult cardiac surgery patients undergoing median sternotomy. PubMed, Embase, Google Scholar, and the Cochrane database were searched with the following search strategy: ([postoperative pain] or [pain relief] OR [analgesics] or [analgesia] or [nerve block] or [regional block] or [local block] or [regional anesthesia] or [local anesthetic] or [parasternal block] and [sternotomy]) and (humans [filter]). Inclusion criteria were: patients who underwent cardiac surgery via median sternotomy, age >18 and parasternal block (continuous and single dose). Exclusion criteria were: noncardiac surgery, nonparasternal nerve blocks, and the use of NSAIDS in parasternal block. Quality assessment was performed by three independent reviewers via the Cochrane risk of bias assessment tool. Of 1165 total citations, 18 were found to be relevant. Of these 18 citations, 7 citations (N = 2223 patients) reported postoperative pain scores in an extractable format and 11 citations (N = 2155 patients) reported postoperative opioid use in an extractable format. For postoperative opioid use, morphine equivalent doses were calculated for all studies and postoperative pain scores were standardized to a 10-point visual analog scale for comparison between studies; both these were reported as total opioid use or cumulative score ranging from 24 to 72 h postoperative. All data analyses were run using a random effects model, using a restricted maximum likelihood estimator, to obtain summary standardized mean differences with 95% confidence interval (CI's). For studies which only reported median and interquatile range (IQR), the median was standard deviation was estimated by IQR/1.35. Following median sternotomy both postoperative pain (SMD [95% CI] -0.49 [-0.92 to -0.06]) and postoperative morphine equivalent use (SMD [95% CI] -1.68 [-3.11 to -0.25]) were significantly less in the PSB group. CONCLUSION: Our meta-analysis suggests that parasternal nerve block significantly reduces postoperative pain and opioid use.

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)0.012
metaresearch head score (Gemma)0.033
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 score0.018
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.033
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0180.027
Bibliometrics0.0060.008
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
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 head0.071
GPT teacher head0.321
Teacher spread0.250 · 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

Citations33
Published2022
Admission routes1
Has abstractyes

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