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Record W4403097972 · doi:10.1183/13993003.01565-2024

The McMaster Cough Severity Questionnaire (MCSQ): a cough severity instrument for patients with refractory chronic cough

2024· article· en· W4403097972 on OpenAlexafffund
Elena Kum, Gordon H. Guyatt, Rayid Abdulqawi, Peter V. Dicpinigaitis, Lieven Dupont, Stephen K. Field, Cynthia French, Peter G. Gibson, Richard S. Irwin, Faye Johnston, Lorcan McGarvey, Robert A. Newman, Nada Popović, John A. Smith, Woo‐Jung Song, Paul M. O’Byrne, Imran Satia

Bibliographic record

VenueEuropean Respiratory Journal · 2024
Typearticle
Languageen
FieldMedicine
TopicRespiratory and Cough-Related Research
Canadian institutionsSt. Joseph’s Healthcare HamiltonUniversity of CalgaryChevron (Canada)McMaster UniversityImpact
FundersMcMaster University
KeywordsMedicineChronic coughRefractory (planetary science)Physical therapyInternal medicineAsthma

Abstract

fetched live from OpenAlex

BACKGROUND: Cough severity represents an important end-point to assess the impact of therapies for patients with refractory chronic cough (RCC). Our objective was to develop a new patient-reported outcome measure addressing cough severity in patients with RCC. METHODS: Phase 1 (item generation): a systematic survey, focus groups and expert consultation generated 51 items. Phase 2 (item reduction): from a list of 51 items, 100 patients identified those they had experienced in the previous year and rated their importance on a 5-point scale. The McMaster Cough Severity Questionnaire (MCSQ) included items reported to occur most frequently and that had the highest importance scores. Patient feedback on the MCSQ led to elimination of redundant items. Another 100 patients completed the MCSQ, from which we performed an exploratory factor analysis and a Rasch analysis to further refine items on the MCSQ. RESULTS: Previous publications report on the details of Phase 1. Phase 2 led to selection of 15 items from the initial 51. Patient feedback on the 15 items led to elimination of five redundant items. An exploratory factor analysis of the 10-item MCSQ led to the selection of two domains, and the elimination of one item that demonstrated cross-loading and another that had high inter-item correlations. A Rasch analysis of the 8-item MCSQ confirmed that the response options functioned in a logically progressive manner and that no items exhibited differential item functioning. The final 8-item MCSQ has a 1-week recall period and includes two domains (intensity and frequency). The 8-item MCSQ had high internal consistency (Cronbach's α=0.89), proved able to distinguish different levels of cough severity (person separation index 0.89) and demonstrated high cross-sectional convergent validity (Pearson's correlation 0.76, 95% CI 0.66-0.83) with the 100-mm cough severity visual analogue scale. CONCLUSIONS: Initial evidence supports the validity of the MCSQ, an 8-item instrument measuring cough severity in patients with RCC. Future studies should evaluate its properties in measuring change over time.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.788
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.022
GPT teacher head0.283
Teacher spread0.261 · 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
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

Citations12
Published2024
Admission routes2
Has abstractyes

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