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Record W3030820866 · doi:10.1186/s12931-020-01406-z

Short-term effects of Lumacaftor/Ivacaftor (Orkambi™) on exertional symptoms, exercise performance, and ventilatory responses in adults with cystic fibrosis

2020· letter· en· W3030820866 on OpenAlexafffund
Bradley S. Quon, Andrew H. Ramsook, Satvir S. Dhillon, Reid Mitchell, Kyle G. Boyle, Pearce Wilcox, Jordan A. Guenette

Bibliographic record

VenueRespiratory Research · 2020
Typeletter
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsUniversity of British ColumbiaProvidence Health CareSt. Paul's HospitalUniversity of British Columbia Hospital
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchMichael Smith Health Research BC
KeywordsMedicineIvacaftorPhysical therapyExertional dyspneaCystic fibrosisPhysical medicine and rehabilitationInternal medicine

Abstract

fetched live from OpenAlex

RATIONALE: Lumacaftor/ivacaftor (LUM/IVA) modestly improves lung function following 1 month of treatment but it is unknown if this translates into improvements in exercise endurance and exertional symptoms. METHODS: Adult CF participants completed a symptom-limited constant load cycling test with simultaneous assessments of dyspnea and leg discomfort ratings pre- and 1 month post-initiation of LUM/IVA. RESULTS: Endurance time, exertional dyspnea and leg discomfort ratings at submaximal exercise did not change significantly. There was a significant inverse correlation between changes in leg discomfort and endurance time (r = - 0.88; p = 0.009) following 1-month of LUM/IVA. CONCLUSIONS: Overall, 1-month of LUM/IVA did not increase endurance time or modify exertional dyspnea or leg discomfort ratings. However, individuals who experienced a reduction in leg discomfort following LUM/IVA had an improvement in endurance time. Future studies with a larger sample size are needed to verify these findings and to assess the long-term effects of LUM/IVA on exercise outcomes. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02821130. Registered July 1, 2016.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.456
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.005
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 head0.031
GPT teacher head0.329
Teacher spread0.298 · 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 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

Citations16
Published2020
Admission routes2
Has abstractyes

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