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Record W4396731801 · doi:10.1016/j.heliyon.2024.e30875

Neurocognitive disorder in Myotonic dystrophy type 1

2024· article· en· W4396731801 on OpenAlexfundaboutno aff
Stefan Winblad, Ólöf Elíasdóttir, Sara Nordström, Christopher Lindberg

Bibliographic record

VenueHeliyon · 2024
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsnot available
FundersMontreal Neurological Institute and Hospital
KeywordsMyotonic dystrophyNeurocognitiveNeuroscienceMedicinePsychologyPhysical medicine and rehabilitationInternal medicineCognition

Abstract

fetched live from OpenAlex

Cognitive deficits and abnormal cognitive aging have been associated with Myotonic dystrophy type 1 (DM1), but the knowledge of the extent and progression of decline is limited. The aim of this study was to examine the prevalence of signs of neurocognitive disorder (mild cognitive impairment and dementia) in adult patients with DM1. A total of 128 patients with childhood, juvenile, adult, and late onset DM1 underwent a screening using the Montreal Cognitive Assessment (MoCA). Demographic and clinical information was collected. The results revealed that signs of neurocognitive disorder were relatively rare among the participants. However, 23.8 % of patients with late onset DM1 (aged over 60 years) scored below MoCA cut-off (=23), and this group also scored significantly worse compared to patients with adult onset. Age at examination were negatively correlated with MoCA scores, although it only explained a small portion of the variation in test results. Other demographic and clinical factors showed no association with MoCA scores. In conclusion, our findings indicate a low prevalence of signs of neurocognitive disorder in adult patients with DM1, suggesting that cognitive deficits rarely progress to severe disorders over time. However, the performance of patients with late onset DM1 suggests that this phenotype warrants further exploration in future studies, including longitudinal and larger sample analyses.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.024
GPT teacher head0.283
Teacher spread0.259 · 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 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
Published2024
Admission routes2
Has abstractyes

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