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Record W2135274328 · doi:10.1002/mus.21480

Clinical and electrophysiological parameters distinguishing acute‐onset chronic inflammatory demyelinating polyneuropathy from acute inflammatory demyelinating polyneuropathy

2009· article· en· W2135274328 on OpenAlexaff
Annie Dionne, Michael Nicolle, Angelika F. Hahn

Bibliographic record

VenueMuscle & Nerve · 2009
Typearticle
Languageen
FieldMedicine
TopicPeripheral Neuropathies and Disorders
Canadian institutionsWestern UniversityUniversité Laval
Fundersnot available
KeywordsChronic inflammatory demyelinating polyneuropathyMedicinePolyneuropathyPolyradiculoneuropathyWeaknessGuillain-Barre syndromeInternal medicineImmunologySurgeryAntibody

Abstract

fetched live from OpenAlex

Up to 16% of chronic inflammatory demyelinating polyneuropathy (CIDP) patients may present acutely. We performed a retrospective chart review on 30 acute inflammatory demyelinating polyneuropathy (AIDP) and 15 acute-onset CIDP (A-CIDP) patients looking for any clinical or electrophysiological parameters that might differentiate AIDP from acutely presenting CIDP. A-CIDP patients were significantly more likely to have prominent sensory signs. They were significantly less likely to have autonomic nervous system involvement, facial weakness, a preceding infectious illness, or need for mechanical ventilation. With regard to electrophysiological features, neither sural-sparing pattern, sensory ratio >1, nor the presence of A-waves was different between the two groups. This study suggests that patients presenting acutely with a demyelinating polyneuropathy and the aforementioned clinical features should be closely monitored as they may be more likely to have CIDP at follow-up.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.280
Teacher spread0.265 · 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 source (direct Gemma or distilled Codex), 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

Citations130
Published2009
Admission routes1
Has abstractyes

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