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Record W3045495336 · doi:10.1002/ppul.24988

Sleep disordered breathing: Assessment and therapy in the age of emerging neuromuscular therapies

2020· article· en· W3045495336 on OpenAlexaff
Neepa Gurbani, John E. Pascoe, Sherri L. Katz, Hemant Sawnani

Bibliographic record

VenuePediatric Pulmonology · 2020
Typearticle
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of Ottawa
Fundersnot available
KeywordsMedicineSpinal muscular atrophyDuchenne muscular dystrophyNeuromuscular diseaseAmyotrophic lateral sclerosisPolysomnographyMyopathyPhysical medicine and rehabilitationIntensive care medicineMuscular dystrophySMA*Respiratory failureSleep and breathingBreathingPediatricsPhysical therapyDiseasePathologyInternal medicineAnesthesiaApnea

Abstract

fetched live from OpenAlex

The term neuromuscular disease (NMD) encompasses a large variety of disorders that result in abnormal muscle function. Although it may be conventional to relate the use of this term to the most common muscular diseases (Duchenne muscular dystrophy [DMD], spinal muscular atrophy [SMA], and amyotrophic lateral sclerosis, etc), it is important to extend the term to pathologies manifested by severe neurologic (brain and spinal cord) malformations and injuries. In many of these scenarios, there are common mechanisms that contribute to sleep disordered breathing (SDB) and respiratory insufficiency although comorbidities may be somewhat different. Advances in the understanding of these diseases and their natural history, and increasing availability of mechanical ventilation to these patients have improved survival. The development of novel genetic and molecular therapies (as in the cases of DMD, SMA, and X-linked myotubular myopathy) provides an opportunity to use SDB as a reasonable outcome measure while also allowing the use of polysomnography as a validation tool in the assessments of effectiveness of therapies. We seek to provide an understanding of SDB in NMDs, and in the same light, would like to begin the conversation of thinking about weaning respiratory support when possible.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.094
Threshold uncertainty score0.355

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 head0.035
GPT teacher head0.318
Teacher spread0.283 · 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

Citations19
Published2020
Admission routes1
Has abstractyes

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