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Record W2995180868 · doi:10.1093/pch/pxz026

Managing pain and distress in children undergoing brief diagnostic and therapeutic procedures

2019· review· en· W2995180868 on OpenAlexafffund
Evelyne D Trottier, Marie‐Joëlle Doré‐Bergeron, Laurel Chauvin‐Kimoff, Krista Baerg, Samina Ali

Bibliographic record

VenuePaediatrics & Child Health · 2019
Typereview
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsCanadian Paediatric Society
FundersCanadian Association of Emergency Physicians
KeywordsDistressAuditMedicineHealth careMedical emergencyIntensive care medicineNursing

Abstract

fetched live from OpenAlex

Common medical procedures to assess and treat patients can cause significant pain and distress. Clinicians should have a basic approach for minimizing pain and distress in children, particularly for frequently used diagnostic and therapeutic procedures. This statement focuses on infants (excluding care provided in the NICU), children, and youth who are undergoing common, minor but painful medical procedures. Simple, evidence-based strategies for managing pain and distress are reviewed, with guidance for integrating them into clinical practice as an essential part of health care. Health professionals are encouraged to use minimally invasive approaches and, when painful procedures are unavoidable, to combine simple pain and distress-minimizing strategies to improve the patient, parent, and health care provider experience. Health administrators are encouraged to create institutional policies, improve education and access to guidelines, create child- and youth-friendly environments, ensure availability of appropriate staff, equipment and pharmacological agents, and perform quality audits to ensure pain management is optimal.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.020
GPT teacher head0.317
Teacher spread0.296 · 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 designNot applicable
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

Citations128
Published2019
Admission routes2
Has abstractyes

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