MétaCan
Menu
Back to cohort
Record W4200304416 · doi:10.1080/10903127.2021.2018074

Evidence-Based Guidelines for Prehospital Pain Management: Literature and Methods

2021· article· en· W4200304416 on OpenAlexaff
Jonathan R. Powell, Lorin R. Browne, Kyle Guild, Manish I. Shah, Remle P. Crowe, George Lindbeck, Sabina Braithwaite, Eddy Lang, Ashish R. Panchal

Bibliographic record

VenuePrehospital Emergency Care · 2021
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsUniversity of Calgary
FundersMaternal and Child Health BureauNational Highway Traffic Safety AdministrationHealth Resources and Services Administration
KeywordsMedicineSystematic reviewGrading (engineering)Protocol (science)Evidence-based practiceMEDLINEMedical emergencyHealth careEvidence-based medicineAlternative medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Emergency Medical Services (EMS) clinicians commonly encounter patients with acute pain. A new set of evidence-based guidelines (EBG) was developed to assist in the prehospital management of pain. Our objective was to describe the methods used to develop these evidence-based guidelines for prehospital pain management. METHODS: The EBG development process was supported by a previous systematic review conducted by the Agency for Healthcare Research and Quality (AHRQ) covering nine different population, intervention, comparison, and outcome (PICO) questions. A technical expert panel (TEP) was formed and added an additional pediatric-specific PICO question. Identified evidence was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) framework and tabulated into Summary of Findings tables. The TEP then utilized a rigorous systematic method, including the PanelVoice function, for recommendation development which was applied to generate Evidence to Decision Tables (EtD). This process involved review of the Summary of Findings tables, asynchronous member judging, and facilitated panel discussion to generate final consensus-based recommendations. RESULTS: The work product described above was completed by the TEP panel from September 2020 to April 2021. For these recommendations, the overall certainty of evidence was very low or low, data for decisions on cost effectiveness and equity were lacking, and feasibility was rated well across all categories. Based on the evidence, one strong and seven conditional recommendations were made, with two PICO questions lacking sufficient evidence to generate a recommendation. CONCLUSION: We describe a protocol that leveraged established EBG development techniques, the GRADE framework in conjunction with a previous AHRQ systematic review to develop treatment recommendations for prehospital pain management. This process allowed for mitigation of many confounders due to the use of virtual and electronic communication. Our approach may inform future guideline development and increase transparency in the prehospital recommendations development processes.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.587
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.059
GPT teacher head0.401
Teacher spread0.342 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations10
Published2021
Admission routes1
Has abstractyes

Explore more

Same venuePrehospital Emergency CareSame topicPediatric Pain Management TechniquesFrench-language works237,207