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Record W2884038518 · doi:10.3233/jnd-170277

Prenatal, Neonatal, and Early Childhood Features in Congenital Myotonic Dystrophy

2018· article· en· W2884038518 on OpenAlexaffabout
Eugenio Zapata‐Aldana, Delia Ceballos‐Sáenz, Rhiannon Hicks, Craig Campbell

Bibliographic record

VenueJournal of Neuromuscular Diseases · 2018
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsWestern UniversityLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineMyotonic dystrophyPediatricsInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Congenital myotonic dystrophy (CDM) is the neonatal onset and most severe presentation of Myotonic Dystrophy type 1. Since it first description, perinatal complications have been detailed including prolonged hospital stay, respiratory and feeding therapy during the neonatal period, although long-term complications are less documented. OBJECTIVE: Present a prospective cohort of CDM and compare it to the literature of other CDM case series, to adequately describe and contrast the prenatal, neonatal and infancy features of CDM. METHODS: A 5-year cohort of CDM eligible cases was conducted via the Canadian Pediatric Surveillance Program. 38 patients met the inclusion criteria. Comparison to other CDM case series published in the literature between 1992 and 2016 about perinatal and infancy morbidity. RESULT: From a total of 118 cases, the most frequent features were Polyhydramnios (58%), feeding therapy (77%), intubation and ventilation (58%); neonatal death was reported in 16% of the cases; the most frequent long-term morbidity were respiratory tract infections. CONCLUSIONS: We performed a detailed description of the main perinatal features of CDM and precise documentation of the mortality and morbidity during the first five years of life. This is an essential step in the knowledge of the natural history of CDM.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.651
Threshold uncertainty score0.959

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 science0.0000.000
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 head0.009
GPT teacher head0.237
Teacher spread0.227 · 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 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

Citations28
Published2018
Admission routes2
Has abstractyes

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