The Analgesic Efficacy of Different Techniques Surrounding Regional Anesthesia of the Lumbar Plexus and its Terminal Branches for Hip Fracture Surgeries
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,009 | 0,034 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,006 | 0,006 |
| Bibliométrie | 0,005 | 0,005 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».