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Record W3016271100 · doi:10.1016/j.ejca.2020.02.039

Reducing pain and distress related to needle procedures in children with cancer: A clinical practice guideline

2020· review· en· W3016271100 on OpenAlexaff
Erik A. H. Loeffen, Renée L. Mulder, Anna Font‐Gonzalez, Piet Leroy, Bruce Dick, Anna Taddio, Gustaf Ljungman, Lindsay Jibb, Perri R. Tutelman, Christina Liossi, Alison Twycross, Karyn Positano, Rutger R. G. Knops, Marc H. W. A. Wijnen, Marianne D. van de Wetering, Leontien C.M. Kremer, L. Lee Dupuis, Fiona Campbell, Wim J. E. Tissing

Bibliographic record

VenueEuropean Journal of Cancer · 2020
Typereview
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsIzaak Walton Killam Health CentreUniversity of OttawaHospital for Sick ChildrenUniversity of TorontoUniversity of Alberta
Fundersnot available
KeywordsMedicineGuidelineDistressDistractionGrading (engineering)Quality of evidenceSedationHypnosisCancer painQuality of life (healthcare)Pain assessmentPhysical therapyIntensive care medicineCancerAlternative medicinePain managementRandomized controlled trialNursingClinical psychologySurgeryPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Children with cancer often undergo long treatment trajectories involving repeated needle procedures that potentially cause pain and distress. As part of a comprehensive effort to develop clinical practice guidelines (CPGs) to address pain prevention and management in children with cancer, we aimed to provide recommendations on the pharmacological and psychological management of procedure-related pain and distress. METHODS: Of the international inter-disciplinary CPG development panel (44 individuals), two working groups including 13 healthcare professionals focused on procedural pain and distress. Grading of Recommendations Assessment, Development and Evaluation methodology was used, including the use of systematic literature reviews to inform recommendations and the use of evidence to decision frameworks. At an in-person meeting in February 2018, the guideline panel discussed these frameworks and formulated recommendations which were then discussed with a patient-parent panel consisting of 4 survivors and 5 parents. RESULTS: The systematic reviews led to the inclusion of 48 randomised controlled trials (total number of participants = 2271). Quality of evidence supporting the recommendations ranged from very low to moderate. Strong recommendations were made for the use of topical anesthetics in all needle procedures, for offering deep sedation (DS)/general anesthesia (GA) to all children undergoing lumbar puncture, for the use of DS/ GA in major procedures in children of all ages, for the use of hypnosis in all needle procedures and for the use of active distraction in all needle procedures. CONCLUSION: In this CPG, an evidence-based approach to manage procedure-related pain and distress in children with cancer is presented. As children with cancer often undergo repeated needle procedures during treatment, prevention and alleviation of procedure-related pain and distress is of the utmost importance to increase quality of life in these children and their families.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.003
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 head0.032
GPT teacher head0.404
Teacher spread0.372 · 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

Citations91
Published2020
Admission routes1
Has abstractno

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