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Record W3048426041 · doi:10.4097/kja.20436

Managing rebound pain after regional anesthesia

2020· review· en· W3048426041 on OpenAlexaff
Felipe Muñoz-Leyva, Javier Cubillos, Ki Jinn Chin

Bibliographic record

VenueKorean journal of anesthesiology · 2020
Typereview
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsWestern UniversityToronto Western HospitalLondon Health Sciences CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineAnesthesiaAnalgesicPerioperativeLocal anestheticAnestheticRegimenBlockadeSurgery

Abstract

fetched live from OpenAlex

Rebound pain after regional anesthesia can be defined as transient acute postoperative pain that ensues following resolution of sensory blockade, and is clinically significant, either with regard to the intensity of pain or the impact on psychological well-being, quality of recovery, and activities of daily living. Current evidence suggests that it represents an unmasking of the expected nociceptive response in the absence of adequate systemic analgesia, rather than an exaggerated hyperalgesic phenomenon induced by local anesthetic neural blockade. In the majority of patients, it does not appear to significantly impact cumulative postoperative opioid consumption, quality of recovery, or patient satisfaction, and is not associated with longer-term sequelae such as persistent post-surgical pain. Nevertheless, it must be considered whenever regional anesthesia is incorporated into perioperative management. Strategies to mitigate the impact of rebound pain include routine prescribing of a systemic multimodal analgesic regimen, as well as patient education on appropriate expectations regarding block offset and expected surgical pain, and timely initiation of analgesic medication. Prolonging the duration of action of regional anesthesia with continuous catheter techniques or local anesthetic adjuncts may also help alleviate rebound pain, although further research is required to confirm this.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.905
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.039
GPT teacher head0.297
Teacher spread0.258 · 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 designNot applicable
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

Citations130
Published2020
Admission routes1
Has abstractyes

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