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Clinimetric Properties of Outcome Measures in Bronchiectasis

2022· article· en· W1930392224 on OpenAlexfundno aff
Judy Bradley, Kathryn M. Ferguson, Andrew Bailey, Katherine O’Neill, Rebecca H. McLeese, Adam T. Hill, Michael R. Loebinger, Mary Carroll, James D. Chalmers, Timothy Gatheral, Christopher Johnson, Anthony De Soyza, John R. Hurst, D.G. Downey, J.S. Elborn

Bibliographic record

VenueAnnals of the American Thoracic Society · 2022
Typearticle
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsnot available
FundersMedical Research CouncilQueen's University BelfastInnovative Medicines InitiativeImperial College LondonEuropean CommissionSanofiEuropean Federation of Pharmaceutical Industries and AssociationsInsmedGilead SciencesGlaxoSmithKlineQueen's UniversityPfizer
KeywordsMedicineBronchiectasisSpirometryExacerbationQuality of life (healthcare)Physical therapyPulmonary function testingProspective cohort studyInternal medicineLungAsthma

Abstract

fetched live from OpenAlex

Abstract Rationale There is a lack of outcome measures with robust clinimetric properties in bronchiectasis. Objectives To determine the clinimetric properties (reliability over 1 year during clinical stability and responsiveness over the course of antibiotics for pulmonary exacerbation) of objective and patient-reported outcome measures. Methods This multicenter cohort study included adults with bronchiectasis from seven hospitals in the United Kingdom. Participants attended four visits, 4 months apart over 1 year while clinically stable and at the beginning and end of exacerbation and completed lung function (spirometry and multiple breath washout), provided a blood sample for C-reactive protein (CRP) measurement, and completed health-related quality of life (HRQoL) questionnaires (Quality of Life-Bronchiectasis, St. George’s Respiratory Questionnaire, and EuroQoL 5-Dimensions 5-Levels). Results Participants (n = 132) had a mean (standard deviation) age of 66 (11) years, and 64% were female. Lung function parameters (forced expiratory volume in one second [FEV1], standard lung clearance index [LCI2.5]) were reliable over time [coefficient of variation (CV): <10%]). Regarding responsiveness, FEV1 demonstrated better properties than LCI2.5; therefore, a clear justification for the use of LCI2.5 in future trials is needed. CRP was less reliable (CV > 20%) over time than FEV1 and LCI2.5, and whereas CRP had a large mean change between the start and end of an exacerbation, this may have been driven by a small number of patients having a large change in CRP. Reliability of HRQoL questionnaires and questionnaire domains ranged from acceptable (CV: 20–30%) to good (CV: 10–20%), and HRQoL were responsive to treatment of exacerbations. Considering the specific questionnaire domain relevant to the intervention and its associated clinimetric properties is important. Additional statistics will support future power and/or sample size analysis. Conclusions This information on the clinimetric properties of lung function parameters, CRP, and HRQoL parameters should be used to inform the choice of outcome measures used in future bronchiectasis 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)0.147
metaresearch head score (Gemma)0.237
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.147
Threshold uncertainty score0.776

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1470.237
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.004
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.227
GPT teacher head0.456
Teacher spread0.229 · 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 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".

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Citations7
Published2022
Admission routes1
Has abstractyes

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