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Record W1999848546 · doi:10.1097/wco.0b013e32833c7a19

Sensory neuropathies, from symptoms to treatment

2010· review· en· W1999848546 on OpenAlexaff
Stéphan A. Botez, David N. Herrmann

Bibliographic record

VenueCurrent Opinion in Neurology · 2010
Typereview
Languageen
FieldNeuroscience
TopicHereditary Neurological Disorders
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineSensory systemDiseaseSensory neuropathyDermatologyPathologySurgeryNeurosciencePsychology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: The present review focuses on recent developments in diagnosis and treatment of sensory neuropathies. It does not seek to establish a comprehensive classification of sensory neuropathies, nor treatment guidelines per se. RECENT FINDINGS: Diagnostic criteria and guidelines have been developed for distal symmetric polyneuropathies, small fiber sensory neuropathies and sensory neuronopathies. Novel diagnostic tools such as skin biopsies now allow diagnosis of small fiber sensory neuropathies. Genetic testing has defined new subtypes of mitochondrial neuropathies and inherited neuropathies with sensory involvement. Intravenous immunoglobulin and tumor necrosis factor-alpha inhibitors show promise for some dysimmune sensory neuropathies or neuronopathies. Additional options for management of neuropathic pain are emerging. SUMMARY: Diagnostic methods for both acquired and hereditary sensory neuropathies have progressed in recent years, leading to earlier and more specific diagnoses and a better understanding of disease mechanisms. Much progress remains to be made regarding symptomatic and disease-modifying therapy for a range of sensory neuropathies, including those due to diabetes, HIV infection and from dysimmune or hereditary causes.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.997
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.002

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 head0.187
GPT teacher head0.400
Teacher spread0.212 · 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

Citations16
Published2010
Admission routes1
Has abstractyes

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