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Record W3120377478 · doi:10.1002/mus.27171

The complex association between pain and neuropathy

2021· article· en· W3120377478 on OpenAlexaff
Alon Abraham, Leif Erik Lovblom, Vera Bril

Bibliographic record

VenueMuscle & Nerve · 2021
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsUniversity Health NetworkSinai Health SystemUniversity of Toronto
FundersCSL BehringMyasthenia Gravis Foundation of America
KeywordsMedicinePolyneuropathyNeuropathic painWeaknessSural nerveProspective cohort studyInternal medicinePeripheral neuropathyPhysical therapySeverity of illnessSurgeryAnesthesiaDiabetes mellitus

Abstract

fetched live from OpenAlex

BACKGROUND: Several studies of patients with polyneuropathy failed to show differences between patients with and without pain. In the current study, we aimed to explore the association between neuropathic symptoms, mainly pain, and polyneuropathy characteristics. METHODS: A prospective cross-sectional study recruiting 151 patients with non-diabetic polyneuropathy was performed between November 2016 and May 2017. A total of 38 patients with chronic inflammatory demyelinating neuropathy were excluded. Patients underwent clinical, electrophysiological and functional assessments of their polyneuropathy. Polyneuropathy characteristics were compared depending on the presence and severity of neuropathic symptoms. RESULTS: The presence and the severity of weakness were associated with a more severe neuropathy as measured by clinical, electrophysiological and functional assessments, while the presence of pain was associated with higher sural amplitudes, and the severity of pain showed a curvilinear association with neuropathy severity. CONCLUSIONS: Our study shows a novel finding of a curvilinear association between pain and polyneuropathy severity.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.410
Threshold uncertainty score0.179

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.027
GPT teacher head0.262
Teacher spread0.235 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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