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Caudal analgesia and anesthesia techniques in children

2005· article· en· W1964956610 on OpenAlexaff
Ban C. H. Tsui, Charles B. Berde

Bibliographic record

VenueCurrent Opinion in Anaesthesiology · 2005
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsUniversity of Alberta HospitalAlberta Hospital Edmonton
Fundersnot available
KeywordsMedicineKetamineAnesthesiaLocal anestheticLevobupivacaineNeuraxial blockadeAnestheticBupivacaineUltrasoundNerve blockRegional anesthesiaSurgerySpinal anesthesiaRadiology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Caudal epidural blockade remains the cornerstone of pediatric regional anesthesia. In this article we provide a comprehensive review of the recent developments in caudal anesthesia in infants and children. RECENT FINDINGS: Research has focused on prolonging the duration of single-shot caudal blocks and accurately positioning continuous caudal catheters. New local anesthetics with similar potencies but less toxicity have been introduced. Opioids prolong the duration of analgesia of local anesthetic, but have also been associated with unacceptable side effects, particularly in pediatric outpatients. Various non-opioid adjuncts with more favorable side-effect profiles may increase the duration of analgesia. New ultrasound and nerve-stimulation techniques have been developed to accurately guide epidural catheters to a specific spinal level. SUMMARY: The addition of ketamine or clonidine to a caudal local anesthetic prolong the duration of the block. However, a preservative-free preparation of ketamine that is suitable for neuraxial use is not widely available. Ultrasound imaging and electrical stimulation are promising options to accurately position a caudal needle. However, because ultrasound imaging is more difficult in older children, nerve stimulation is a more-suitable technique to accurately guide caudal catheters in this patient population. Although complications associated with caudal block are rare, the risks and benefits must be carefully considered on an individual basis.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.315
Teacher spread0.290 · 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.

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

Citations152
Published2005
Admission routes1
Has abstractyes

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