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Record W2516448544 · doi:10.1186/s12931-016-0421-9

The impact of comorbidities on productivity loss in asthma patients

2016· article· en· W2516448544 on OpenAlexaffabout
Solmaz Ehteshami‐Afshar, J. Mark FitzGerald, Christopher Carlsten, Hamid Tavakoli, Roxanne Rousseau, Wan C. Tan, Julia Rolf, Mohsen Sadatsafavi

Bibliographic record

VenueRespiratory Research · 2016
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsCentre for Advancing Health OutcomesOccupational Cancer Research CentreKelowna General HospitalUniversity of British Columbia
FundersGlaxoSmithKline
KeywordsComorbidityAbsenteeismMedicinePresenteeismAsthmaProductivityConfoundingPhysical therapyInternal medicinePsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Health-related productivity loss is an important, yet overlooked, component of the economic burden of disease in asthma patients of a working age. We aimed at evaluating the effect of comorbidities on productivity loss among adult asthma patients. METHODS: In a random sample of employed adults with asthma, we measured comorbidities using a validated self-administered comorbidity questionnaire (SCQ), as well as productivity loss, including absenteeism and presenteeism, using validated instruments. Productivity loss was measured in 2010 Canadian dollars ($). We used a two-part regression model to estimate the adjusted difference of productivity loss across levels of comorbidity, controlling for potential confounding variables. RESULTS: 284 adults with the mean age of 47.8 (SD 11.8) were included (68 % women). The mean SCQ score was 2.47 (SD 2.97, range 0-15) and the average productivity loss was $317.5 per week (SD $858.8). One-unit increase in the SCQ score was associated with 14 % (95 % CI 1.02-1.28) increase in the odds of reporting productivity loss, and 9.0 % (95 % CI 1.01-1.18) increase in productivity loss among those reported any loss of productivity. A person with a SCQ score of 15 had almost $1000 per week more productivity loss than a patient with a SCQ of zero. CONCLUSIONS: Our study deepens the evidence-base on the burden of asthma, by demonstrating that comorbidities substantially decrease productivity in working asthma patients. Asthma management strategies must be cognizant of the role of comorbidities to properly incorporate the effect of comorbidity and productivity loss in estimating the benefit of disease management strategies.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.067
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.078
GPT teacher head0.412
Teacher spread0.334 · 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.

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".

Quick stats

Citations21
Published2016
Admission routes2
Has abstractyes

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