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Record W2133541258 · doi:10.1542/hpeds.2013-0014

Intravenous Acetaminophen: An Alternative to Opioids for Pain Management?

2013· article· en· W2133541258 on OpenAlexaff
Sarah Schwartz, Daniel A. Rauch

Bibliographic record

VenueHospital Pediatrics · 2013
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineAcetaminophenAdverse effectMorphineAnesthesiaOpioidVialAnalgesicRandomized controlled trialPain managementSurgeryInternal medicine

Abstract

fetched live from OpenAlex

> You are consulted to co-manage a 7-month-old girl after surgical reduction of intussusception. The surgery was uncomplicated, and the patient was extubated in the operating room. Pain management will consist of intravenous (IV) opioids, specifically morphine. IV acetaminophen has recently become available at your institution, and you wonder if it could reduce the need for morphine in this patient. Would this then minimize the potential for adverse effects? IV acetaminophen, under the brand name Ofirmev®, was approved in 2010 by the US Food and Drug Administration for the management of mild to moderate pain, the management of moderate to severe pain with adjunctive opioid analgesics, and the reduction of fever in patients aged ≥2 years at a dosage of 15 mg/kg every 6 hours to a maximum of 75 mg/kg per day.1 The cost for a single-use vial is about $10. Although there are 10 years of worldwide experience, the use of IV acetaminophen in North America has remained limited despite growing evidence supporting its benefits and relative safety. Use in infants has been particularly limited due to its off-label status. In the double-blind, randomized controlled trial recently published in JAMA ,2 Ceelie et al investigated the utility of IV acetaminophen in infants. More specifically, they sought to determine whether the routine use of IV acetaminophen would reduce postoperative morphine requirements in patients …

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.610
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.261
Teacher spread0.251 · 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 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

Citations1
Published2013
Admission routes1
Has abstractyes

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