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Record W3216971470 · doi:10.1002/mus.27465

The long exercise test as a functional marker of periodic paralysis

2021· article· en· W3216971470 on OpenAlexfundno aff
Ana Freitas Ribeiro, Karen Suetterlin, Iwona Skorupinska, S. Veronica Tan, Jasper M. Morrow, Emma Matthews, Michael G. Hanna, Doreen Fialho

Bibliographic record

VenueMuscle & Nerve · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon channel regulation and function
Canadian institutionsnot available
FundersUniversity College London Hospitals Biomedical Research CentreMedical Research CouncilUniversity College London Hospitals NHS Foundation TrustNational Institute for Health and Care ResearchMedical Research Council CanadaWellcome Trust
KeywordsCohortContext (archaeology)MedicineInternal medicineMann–Whitney U testPediatricsPhysical therapyBiology

Abstract

fetched live from OpenAlex

AIMS: The aim of this study was to evaluate the sensitivity of the long exercise test (LET) in the diagnosis of periodic paralysis (PP) and assess correlations with clinical phenotypes and genotypes. METHODS: From an unselected cohort of 335 patients who had an LET we analyzed 67 patients with genetic confirmation of PP and/or a positive LET. RESULTS: 32/45 patients with genetically confirmed PP had a significant decrement after exercise (sensitivity of 71%). Performing the short exercise test before the LET in the same hand confounded results in four patients. Sensitivity was highest in patients with frequent (daily or weekly) attacks (8/8, 100%), intermediate with up to monthly attacks (15/21, 71%) and lowest in those with rare attacks (9/16, 56%) (p = .035, Mann-Whitney U-test). Patients with a positive LET without confirmed PP mutation comprised those with typical PP phenotype and a group with atypical features. DISCUSSION: In our cohort, the LET is strongly correlated with the frequency of paralytic attacks suggesting a role as a functional marker. A negative test in the context of frequent attacks makes a diagnosis of PP unlikely but it does not rule out the condition in less severely affected patients.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.563
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.011
GPT teacher head0.225
Teacher spread0.214 · 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 designBench or experimental
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

Citations17
Published2021
Admission routes1
Has abstractyes

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