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Record W4310961157 · doi:10.1097/phm.0000000000002163

The Physiatrist’s Guide to Cyclist Palsy

2022· review· en· W4310961157 on OpenAlexaff
Jordan Farag, David Sherwood, Anne Kuwabara, Dinesh Kumbhare

Bibliographic record

VenueAmerican Journal of Physical Medicine & Rehabilitation · 2022
Typereview
Languageen
FieldMedicine
TopicPeripheral Nerve Disorders
Canadian institutionsToronto Rehabilitation InstituteUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsAccreditationMedicineWristPalsyPhysical medicine and rehabilitationPhysical therapySurgeryMedical educationAlternative medicinePathology

Abstract

fetched live from OpenAlex

Abstract: Ulnar neuropathy at the wrist is a common consequence of long-duration cycling, a condition termed “cyclist palsy.” Although cyclist palsy has been clinically well described in the literature, a gap exists regarding its electrodiagnostic evaluation and management. Patients with cyclist palsy present with a wide variety of sensory or motor impairments, depending on the location of the lesion. Electrodiagnostic studies are essential for accurate localization, with studies suggesting that pure motor lesions sparing the hypothenar muscles are most common among cyclists. This article aims to provide the electromyographer and physiatrist with a clinical approach to cyclist palsy and management strategies, including patient education, equipment changes, and alterations to bicycle fit. To Claim CME Credits Complete the self-assessment activity and evaluation online at http://www.physiatry.org/JournalCME CME Objectives At the conclusion of this educational module, participants will be able to: (1) Describe the possible clinical presentations of Cyclist Palsy based on Ulnar nerve anatomy in the wrist and hand; (2) State the cycling-related risk factors for Cyclist Palsy; and (3) Outline the principles in management for Cyclist Palsy. Level Advanced Accreditation The Association of Academic Physiatrists is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The Association of Academic Physiatrists designates this Journal-based CME activity for a maximum of 1.0 AMA PRA Category 1 Credit(s) ™. Physicians should only claim credit commensurate with the extent of their participation in the activity.

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)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.018
GPT teacher head0.397
Teacher spread0.379 · 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 designOther design
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

Citations4
Published2022
Admission routes1
Has abstractyes

Explore more

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