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Pharmacological interventions for chronic pain in children: an overview of systematic reviews

2019· review· en· W2946666458 on OpenAlexaff
Christopher Eccleston, Emma Fisher, Tess E Cooper, M.-C. Grégoire, Lauren C. Heathcote, Elliot J. Krane, Susan M. Lord, Navil F. Sethna, Anna-Karenia Anderson, Brian J. Anderson, Jacqueline Clinch, Jeffrey I. Gold, Richard F. Howard, Gustaf Ljungman, Andrew Moore, Neil L. Schechter, Philip J Wiffen, Nick Wilkinson, David G. Williams, Chantal Wood, Miranda A.L. van Tilburg, Boris Zernikow

Bibliographic record

VenuePain · 2019
Typereview
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsDalhousie University
FundersEvidence Synthesis ProgrammeNational Institute for Health and Care Research
KeywordsMedicineSystematic reviewMEDLINEPsychological interventionChronic painMeta-analysisRandomized controlled trialPhysical therapyAlternative medicineClinical trialPsychiatrySurgeryPathology

Abstract

fetched live from OpenAlex

We know little about the safety or efficacy of pharmacological medicines for children and adolescents with chronic pain, despite their common use. Our aim was to conduct an overview review of systematic reviews of pharmacological interventions that purport to reduce pain in children with chronic noncancer pain (CNCP) or chronic cancer-related pain (CCRP). We searched the Cochrane Database of Systematic Reviews, Medline, EMBASE, and DARE for systematic reviews from inception to March 2018. We conducted reference and citation searches of included reviews. We included children (0-18 years of age) with CNCP or CCRP. We extracted the review characteristics and primary outcomes of ≥30% participant-reported pain relief and patient global impression of change. We sifted 704 abstracts and included 23 systematic reviews investigating children with CNCP or CCRP. Seven of those 23 reviews included 6 trials that involved children with CNCP. There were no randomised controlled trials in reviews relating to reducing pain in CCRP. We were unable to combine data in a meta-analysis. Overall, the quality of evidence was very low, and we have very little confidence in the effect estimates. The state of evidence of randomized controlled trials in this field is poor; we have no evidence from randomised controlled trials for pharmacological interventions in children with cancer-related pain, yet cannot deny individual children access to potential pain relief. Prospero ID: CRD42018086900.

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)0.041
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.385
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0410.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.002
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)0.0000.000

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 head0.337
GPT teacher head0.497
Teacher spread0.160 · 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 designSystematic review
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

Citations106
Published2019
Admission routes1
Has abstractyes

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