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Record W4416257009 · doi:10.1212/wnl.0000000000214316

Multiple System Atrophy Without Dysautonomia

2025· article· en· W4416257009 on OpenAlexafffund
Ida Jensen, Sarah Bebermeier, Johanne Heine, Viktoria Ruf, Yaroslau Compta, Laura Molina‐Porcel, Claire Troakes, Albert Vamanu, S Downes, David J. Irwin, Jesse Cohen, Edward B. Lee, Christer Nilsson, Elisabet Englund, Mojtaba Nemati, Sabrina Katzdobler, Johannes Levin, Alexander Bernhardt, Alexander Pantelyat, Joseph Seemiller, S Berger, John C. van Swieten, Elise G.P. Dopper, Annemieke J.M. Rozemüller, Gábor G. Kovács, Nathaniel Bendahan, Anthony E. Lang, Jochen Herms, Günter U. Höglinger, Franziska Hopfner

Bibliographic record

VenueNeurology · 2025
Typearticle
Languageen
FieldNeuroscience
TopicHereditary Neurological Disorders
Canadian institutionsOntario Brain InstituteOccupational Cancer Research CentreToronto Western HospitalUniversity Health Network
FundersNational Institute on AgingParkinsonfondenNational Institutes of HealthCanadian Institutes of Health ResearchParkinson CanadaEdmond J. Safra Philanthropic FoundationPfizerDemensförbundetUniversity of PennsylvaniaLudwig-Maximilians-Universität MünchenBayer VitalFondation Brain CanadaTeva Pharmaceutical IndustriesBristol-Myers SquibbEli Lilly and CompanyBiogen
KeywordsDysautonomiaNatural historyAtrophyDiseaseRetrospective cohort studyScope (computer science)Central nervous system disease

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: Multiple system atrophy (MSA) is a neurodegenerative disorder characterized by 3 core symptom complexes: parkinsonism, cerebellar syndrome, and dysautonomia. Recent Movement Disorder Society (MDS) criteria allow for the clinical diagnosis of MSA based solely on motor symptoms, without requiring dysautonomia. This study aimed to evaluate the frequency and disease trajectory of MSA patients without dysautonomia compared with those with autonomic involvement. METHODS: < 0.05. RESULTS: < 0.05). DISCUSSION: The MDS-MSA criteria expand the diagnostic scope by identifying a motor-only subgroup with a distinct and potentially slower disease course. These findings underscore the importance of including motor-only patients in natural history and interventional studies. Limitations include retrospective data collection and potential variability in symptom documentation.

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)0.001
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 score0.595
Threshold uncertainty score0.768

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.017
GPT teacher head0.245
Teacher spread0.228 · 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

Citations4
Published2025
Admission routes2
Has abstractyes

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