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Record W2899997003 · doi:10.3389/fped.2018.00336

Safety of Patient-Controlled Analgesia After Surgery in Children And Adolescents: Concerns And Potential Solutions

2018· review· en· W2899997003 on OpenAlexaff
Don Daniel Ocay, Annik Otis, Alisson Roberto Teles, Catherine Ferland

Bibliographic record

VenueFrontiers in Pediatrics · 2018
Typereview
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsMcGill University Health CentreMontreal Children's HospitalMcGill UniversityShriners Hospitals for Children - Canada
Fundersnot available
KeywordsPatient-controlled analgesiaMedicineAdverse effectPain managementPatient safetyPaceIntensive care medicinePatient satisfactionAcute painHealth carePostoperative painMedical emergencyAnesthesiaSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Patient-controlled analgesia (PCA) is common practice for acute postoperative pain management. Postoperative PCA use decreases pain intensity and improves patient satisfaction when compared to non-PCA routes of medication administration. Although PCA has several advantages regarding efficacy and safety, adverse events remain a concern. Programming errors and protocols, patient monitoring, and PCA by proxy or with continuous infusion are recurring silent dangers of PCA use in children and adolescents. Innovative considerations need to be emphasized for future improvement of PCA devices for elective surgical patients. With technology within the healthcare setting advancing at a fast pace, smart pump technology is something to look forward to.

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: Observational
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.303
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
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 head0.010
GPT teacher head0.240
Teacher spread0.230 · 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
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

Citations16
Published2018
Admission routes1
Has abstractyes

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