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Record W3206423190 · doi:10.3390/healthcare9101360

Methoxyflurane in Non-Life-Threatening Traumatic Pain—A Retrospective Observational Study

2021· article· en· W3206423190 on OpenAlexaff
Florian Ozainne, Philippe Cottet, Carlos Lojo Rial, Stephan von Düring, Christophe A. Fehlmann

Bibliographic record

VenueHealthcare · 2021
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsUniversity of OttawaOttawa HospitalHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMethoxyfluraneObservational studyMedicineRetrospective cohort studyIntensive care medicineEmergency medicineAnesthesiaSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Pain management is a key issue in prehospital trauma. In Switzerland, paramedics have a large panel of analgesic options. Methoxyflurane was recently introduced into Switzerland, and the goal of this study was to describe both the effect of this medication and the satisfaction of its use. This was a retrospective cohort study, performed in one emergency ambulance service. It included adult patients with traumatic pain and a self-assessment of 3 or more on the visual analogue scale or verbal numerical rating scale. The primary outcome was the reduction in pain between the start of the care and the arrival at the hospital. Secondary outcomes included successful analgesia and staff satisfaction. From December 2018 to 4 June to October 2020, 263 patients were included in the study. Most patients had a low prehospital severity score. The median pain at arrival on site was 8 and the overall decrease in pain observed was 4.2 (95% CI 3.9-4.5). Regarding secondary outcomes, almost 60% had a successful analgesia, and over 70% of paramedics felt satisfied. This study shows a reduction in pain, following methoxyflurane, similar to outcomes in other countries, as well as the attainment of a satisfactory level of pain reduction, according to paramedics, with the advantage of including patients in their own care.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.008
Threshold uncertainty score0.690

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.149
GPT teacher head0.406
Teacher spread0.257 · 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.

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

Citations4
Published2021
Admission routes1
Has abstractyes

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