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Record W2033182961 · doi:10.1016/s0304-3959(03)00299-9

The effect of opioid analgesia on exercise test performance in chronic low back pain

2003· article· en· W2033182961 on OpenAlexafffund
Saifudin Rashiq, M Koller, Mark J. Haykowsky, Kathryn Jamieson

Bibliographic record

VenuePain · 2003
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of Alberta
FundersUniversity of Alberta
KeywordsFentanylMedicinePlaceboOpioidAnesthesiaCrossover studyLumbarRandomized controlled trialPhysical therapyInternal medicineSurgery

Abstract

fetched live from OpenAlex

The effect of opioid analgesia on tests of muscular function in chronic low back pain (CLBP) is unknown. Twenty-eight subjects with CLBP of at least moderate intensity performed the Sorensen isokinetic exercise test once after receiving 1 microg/kg fentanyl intravenously and once after placebo in a randomized-order double-blind crossover design. Naloxone 3 microg/kg was administered after the fentanyl phase. Fentanyl reduced mean+/-SD pain from 4.0+/-2.1 to 3.1+/-2.2 on a 0-10 verbal rating scale (P<0.05). Mean+/-SD Sorensen test performance was 77+/-49 s in the fentanyl arm and 60+/-42 s in the placebo arm. This represents an increased performance with fentanyl of 28% (P<0.001). We conclude that in addition to relieving pain in CLBP, the administration of 1 microg/kg fentanyl is associated with an improvement in lumbar exercise test performance. We presume that the pain relief resulted in increased test performance. Our result is at odds with those of randomized trials which have failed to demonstrate increased function following the treatment of pain with opioid analgesics. This highlights the complexity of the interaction between pain, analgesia and changes in function.

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)0.010
metaresearch head score (Gemma)0.004
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 score0.387
Threshold uncertainty score0.426

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.004
GPT teacher head0.238
Teacher spread0.234 · 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

Citations37
Published2003
Admission routes2
Has abstractyes

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