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Record W4387893278 · doi:10.1002/mus.27993

Provocative changes in nerve conductions: Fact or fiction?

2023· article· en· W4387893278 on OpenAlexaff
Lawrence R. Robinson

Bibliographic record

VenueMuscle & Nerve · 2023
Typearticle
Languageen
FieldMedicine
TopicPeripheral Nerve Disorders
Canadian institutionsToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsMedicineNerve conductionPathophysiologyWristIschemiaCarpal tunnel syndromeAxonCardiologyPhysical medicine and rehabilitationSurgeryAnatomyInternal medicine

Abstract

fetched live from OpenAlex

At times electrodiagnostic medical consultants (EMCs) are asked to perform studies in both a neutral position, and then again after the patient is in a provocative position that exacerbates symptoms, to assess for measurable electrophysiologic changes. While this approach might seem initially appealing, particularly when standard studies are not effective at diagnosis, empiric studies in several conditions have been unimpressive. Studies in median neuropathy at the wrist, thoracic outlet syndrome, piriformis syndrome, and radial tunnel syndrome have failed to demonstrate reproducible changes in nerve conduction studies in positions that exacerbate symptoms. Furthermore, there is lack of a plausible pathophysiologic mechanism for producing both measurable and rapidly reversible electrophysiologic changes after just a few minutes, or less, of compression. Axon loss and demyelination would not be rapidly reversible, and positional changes of 2 min or less (the durations generally studied) would be insufficient to produce measurable nerve ischemia. Last, we have gained a greater appreciation for how much nerves move within limbs with changes in joint position; this movement can lead to misleading changes in nerve conduction studies. It is thus appropriate to conclude that testing nerve conduction in provocative or symptomatic positions adds no value to electrodiagnostic testing.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.777
Threshold uncertainty score0.883

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.065
GPT teacher head0.336
Teacher spread0.271 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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