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Record W3118622101 · doi:10.1002/ppul.25248

Epidemiologic Study of Cystic Fibrosis: 25 years of observational research

2021· review· en· W3118622101 on OpenAlexaboutno aff
Michael W. Konstan, David J. Pasta, Donald R. VanDevanter, Jeffrey S. Wagener, Wayne J. Morgan

Bibliographic record

VenuePediatric Pulmonology · 2021
Typereview
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsnot available
FundersNational Center for Advancing Translational Sciences
KeywordsMedicineCystic fibrosisObservational studyNatural historyFamily medicinePharmacovigilanceIntensive care medicinePediatricsAdverse effectInternal medicine

Abstract

fetched live from OpenAlex

The Epidemiologic Study of Cystic Fibrosis (ESCF) was a prospective observational study of over 32,000 people with cystic fibrosis (CF) from 250 clinical care sites in North America from 1994 to 2005. Begun as a pharmacovigilance study in connection with the approval of dornase alfa in 1993, ESCF was open to all people with CF treated at any participating site in the United States or Canada. In addition to obtaining safety and effectiveness data on dornase alfa, ESCF collected encounter-based data to characterize the natural history and management of CF with a special focus on lung disease. During the study, 32,178 patients reported at least one encounter, contributing 869,136 encounters, 622,592 pulmonary function tests, 432,896 cultures, and 118,563 pulmonary exacerbations treated with intravenous antibiotics. Although ESCF data collection concluded in 2005, through a collaboration with the U.S. Cystic Fibrosis Foundation Patient Registry, additional follow-up data through 2017 was available for two-thirds of patients. This allowed for updating of CF genotype and survival information. Fifty-six peer-reviewed publications (cited over 3600 times) resulted from this study. In this manuscript we summarize the published ESCF manuscripts in thematic groups with key study findings and brief comments, and speculate on how ESCF findings will inform future data registries and patient care practices.

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)0.003
metaresearch head score (Gemma)0.023
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.920
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.279
GPT teacher head0.492
Teacher spread0.213 · 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 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

Citations15
Published2021
Admission routes1
Has abstractyes

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Same venuePediatric PulmonologySame topicCystic Fibrosis Research AdvancesFrench-language works237,207