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Record W1985570596 · doi:10.1097/cnd.0b013e3181e943ed

Effect of Demyelinating Ulnar Nerve Injury on Strength and Fatigue

2011· article· en· W1985570596 on OpenAlexaff
Matti D. Allen, Timothy J. Doherty

Bibliographic record

VenueJournal of Clinical Neuromuscular Disease · 2011
Typearticle
Languageen
FieldMedicine
TopicPeripheral Nerve Disorders
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsMedicineWeaknessUlnar neuropathyUlnar nerveElbowDorsumPhysical medicine and rehabilitationHand musclesMuscle fatigueMuscle weaknessMotor nerveElectromyographyAnatomy

Abstract

fetched live from OpenAlex

OBJECTIVES: Conduction block (CB) from focal neuropathy is often associated with weakness and fatigue in affected muscles. Ulnar neuropathy at the elbow (UNE) provides an excellent model to examine the relationships between electrophysiologically defined CB and quantitative measurement of weakness and fatigue. METHODS: Eight healthy control subjects (47 ± 14 years) and nine patients (53 ± 3 years) with clinical and electrophysiological features of UNE with CB were studied. All underwent bilateral, ulnar motor nerve conduction studies recording from the first dorsal interosseous muscle as well as quantitative measurement of strength and fatigue of the first dorsal interosseous with a custom dynamometer. RESULTS: Strength and fatigue were similar in the dominant and nondominant hands of control subjects and unaffected limb in patients. Varying degrees of conduction block (14-62%, mean 36%) and conduction slowing (31 m/s ± 7) were observed in those with UNE. CB was associated with significant reductions in strength (42%) and fatigue (23%) on a timed fatigue task. The reductions in strength (r = 0.74) and fatigue (r = 0.60) were strongly correlated with the degree of CB. CONCLUSIONS: CB in UNE defined by electrophysiological criteria was strongly correlated with weakness and fatigue in the first dorsal interosseous. Fatigue may be simply related to the reduction in strength, but activity or frequency dependent CB may also contribute.

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)0.008
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 score0.191
Threshold uncertainty score0.937

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.061
GPT teacher head0.396
Teacher spread0.336 · 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
Published2011
Admission routes1
Has abstractyes

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