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Record W4283359708 · doi:10.1101/2022.06.22.22276758

The Analgesic Efficacy of Different Techniques Surrounding Regional Anesthesia of the Lumbar Plexus and its Terminal Branches for Hip Fracture Surgeries

2022· preprint· en· W4283359708 on OpenAlexaff
Abnoos Mosleh-Shirazi, Brian D. OʼDonnell

Bibliographic record

VenuemedRxiv · 2022
Typepreprint
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineAnalgesicHip fractureAnesthesiaRandomized controlled trialCochrane LibraryContext (archaeology)LumbarNerve blockSurgeryInternal medicineOsteoporosis

Abstract

fetched live from OpenAlex

ABSTRACT Background Research is limited in comparing the analgesic efficacy of the various types of blocks with one another for hip fracture surgeries. Due to the rapid pace in the development of these new techniques in blocking the lumbar plexus and its terminal branches, uncertainty exists in literature and in practice regarding the definition and efficacy of one technique in comparison to another. Objectives (1) To write a narrative description of regional anesthesia approaches to the lumbar plexus and associated terminal branches; (2) To do a systematic review and meta-analysis of published articles regarding the analgesic efficacy of regional anesthesia in the context of hip fracture and hip fracture surgery. Questions (1) Does regional anesthesia of the lumbar plexus and its terminal branches enhance analgesic outcomes following hip fracture and hip fracture surgery? (2) Does the evidence point toward one techniques superiority over another? (3) Does evidence show a necessity for a nerve block over the use of opioid analgesics? Search methods Six databases: EMBASE, PUBMED, SCOPUS, EBSCO (CINAHL and MEDLINE), WEB OF SCIENCE, COCHRANE LIBRARY were searched on October 12th, 2020. Search criteria Studies were selected based on inclusion of: Study Design: Prospective Randomized Controlled Trials (RCT), Population: Adults (18+ years) undergoing hip fracture surgery, Intervention: FNB, FICB, PCB and/or PENG block, Comparison: Another intervention of interest, Placebo, Non-intervention, Systemic analgesics (Opioids, NSAIDs, Paracetamol), Outcome: Analgesic efficacy (Pain scores measured by Numeric Pain Rating Scale (NRS) or Visual Analogue Scale (VAS)). Studies were excluded if: Unavailable in full-text, non-human studies, Not RCT, Surgery unrelated to hip fracture. Data collection and analysis Two reviewers extracted all relevant data from the full text versions of eligible studies using a predefined data extraction form. Study characteristics included: author, publication year, study design, sample size, inclusion and exclusion criteria, type of intervention and control, statistical analysis, outcome data, and authors’ main conclusions. Risk of bias in individual studies assessed by two reviewers based on criteria adapted from the Cochrane ‘Risk of Bias’ assessment tool. High-risk studies were excluded. Main results 1. FICB vs Opioid: pain scores at rest at 24h were lower in the FICB group (-0.79 [-1.34, - 0.24], P= 0.005). Pain scores on movement at 12h were lower in the FICB group (-1.91 [-2.5, -1.3], P<0.00001). No difference between groups in other times. 2. FNB vs Opioid: Initial pain scores at rest were lower in FNB (-0.58 [-0.104, -0.12], P=0.01). 3. FICB vs FNB: No difference between groups at rest. Pain scores on movement: initial scores following block, and at 24 hours were lower in the FNB group (initial: 0.53 [0.21, 0.86], P=0.001, 24 h: 0.61 [0.29, 0.94], P=0.0002, results not estimable for 12h (not enough data)). Authors’ conclusions Both femoral nerve block and fascia iliaca compartment block enhance analgesic outcomes following hip fracture and hip fracture surgery, superior to the use of systemic analgesics such as opioids. FNB may be more efficacious at reducing pain following hip fracture surgery when compared to FICB.

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)0.009
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.034
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.006
Bibliometrics0.0050.005
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.032
GPT teacher head0.286
Teacher spread0.254 · 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 designObservational
Domainnot available
GenreEmpirical

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
Published2022
Admission routes1
Has abstractyes

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