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Record W2127060276 · doi:10.1177/0009922808316990

Analgesia and Sedation Practices for Incarcerated Inguinal Hernias in Children

2008· article· en· W2127060276 on OpenAlexaff
Khalid Alansari, Christopher Sulowski, Savithiri Ratnapalan

Bibliographic record

VenueClinical Pediatrics · 2008
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineSedationInguinal herniaEmergency departmentHerniaRetrospective cohort studySurgeryAnesthesiaGeneral surgeryPsychiatry

Abstract

fetched live from OpenAlex

In this study, the use of medications for analgesia and/or sedation for incarcerated inguinal hernia reductions in the emergency department was analyzed. A retrospective chart review was conducted for all patients presenting to a pediatric emergency department with incarcerated inguinal hernia from 2002 to 2005. A total of 99 children presented with incarcerated hernias during the study period. The median age was 11 months. Forty-four percent of children received medication for the procedure, of them 75% received parenteral and 25% oral or intranasal medications. Forty-five percent of children who received medication went through at least 1 hernia reduction attempt initially without medications. More than half the children with incarcerated inguinal hernias did not receive any medication for pain and/or sedation prior to hernia reduction. Guidelines for medication use for children with incarcerated inguinal hernias need to be developed.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.093
GPT teacher head0.415
Teacher spread0.322 · 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 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

Citations6
Published2008
Admission routes1
Has abstractyes

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