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Record W2128336437 · doi:10.1513/pats.201103-024sd

Update of Respiratory Tract Disease in Children with Primary Ciliary Dyskinesia

2011· review· en· W2128336437 on OpenAlexaff
Scott D. Sagel, S.D. Davis, Paolo Campisi, Sharon Dell

Bibliographic record

VenueProceedings of the American Thoracic Society · 2011
Typereview
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersNational Center for Advancing Translational SciencesNational Heart, Lung, and Blood InstituteNational Institutes of Health
KeywordsPrimary ciliary dyskinesiaMedicineDiseaseRespiratory tractDyskinesiaIntensive care medicineLung diseasePediatricsLungBronchiectasisRespiratory systemInternal medicineParkinson's disease

Abstract

fetched live from OpenAlex

Primary ciliary dyskinesia (PCD) is a rare genetic disease characterized by abnormal ciliary structure and function leading to impaired mucociliary clearance and chronic progressive sinopulmonary disease. Upper and lower respiratory tract manifestations are cardinal features of PCD. This review summarizes the current state of knowledge of respiratory tract disease in individuals with PCD and highlights the challenges in identifying and quantifying lung disease in very young children with PCD. No specific therapies are available to correct ciliary dysfunction in PCD. Treatment is not evidence based, and recommendations are largely extrapolated from cystic fibrosis and other conditions with impaired mucociliary clearance. There is a pressing need to develop and validate outcome measures, including patient-reported outcomes, that could be used to evaluate potential therapies in PCD. This review concludes with recommendations for clinical endpoints and outcome measures and a prioritized list of treatments to study in PCD clinical trials.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.355
Teacher spread0.320 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations59
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the American Thoracic SocietySame topicCystic Fibrosis Research AdvancesFrench-language works237,207