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Record W4388947494 · doi:10.14740/jmc4161

Epidural-Like Effect of a Continuous Right-Sided Erector Spinae Plane Blockade for Complicated Pediatric Abdominal Surgery

2023· article· en· W4388947494 on OpenAlexvenueno aff
Vipin Bansal, Emmanuel Alalade

Bibliographic record

VenueJournal of Medical Cases · 2023
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCatheterAnesthesiaRopivacaineBupivacaineLocal anestheticSurgeryNeuraxial blockadeContraindicationAbdominal surgeryAnestheticSpinal anesthesia

Abstract

fetched live from OpenAlex

The erector spinae plane block (ESPB) is increasingly gaining popularity in pediatric anesthesiology as it provides an alternative to neuraxial anesthesia in those with relative and absolute contraindications. Recent studies show craniocaudal spread in cadavers and multi-level spread impacting neural structures in live subjects. We present a case report of a pediatric patient with a history of abdominal surgeries, contraindication to neuraxial anesthesia, and thoracic vertebrae fractures. Bilateral ESPB catheters were initially placed but the left catheter was accidentally dislodged. Each ESPB catheter was initially programmed to flow at rate of 2 cc/h of ropivacaine 0.1% for a max combined rate of 4 cc/h. Once the left ESPB catheter was dislodged, the right ESPB catheter was programmed to flow at 4 cc/h which surprisingly continued to provide adequate bilateral analgesia for the patient without the need for additional narcotics. In cases where a unilateral ESPB catheter is the only option due to catheter displacement or contamination, administering a higher volume of local anesthetic may still yield satisfactory pain relief for managing postoperative discomfort following abdominal surgery.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.312
Teacher spread0.282 · 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 designCase report
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
Published2023
Admission routes1
Has abstractyes

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