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Record W73662042 · doi:10.1155/2012/723049

Integrated Approach to Diagnosis of Associated Occupational Asthma and Rhinitis

2012· article· en· W73662042 on OpenAlexaff
Sébastien Nguyen, Roberto Castaño, Manon Labrecque

Bibliographic record

VenueCanadian Respiratory Journal · 2012
Typearticle
Languageen
FieldMedicine
TopicOccupational exposure and asthma
Canadian institutionsUniversité de MontréalHôpital du Sacré-Cœur de Montréal
Fundersnot available
KeywordsMedicineOccupational asthmaAsthmaAcoustic rhinometryTechnicianInhalationDermatologyNasal provocation testSputumAllergenNoseAllergyInternal medicineSurgeryAnesthesiaImmunologyPathologyTuberculosis

Abstract

fetched live from OpenAlex

Patients with coexisting work-related rhinitis and asthma would benefit from an adequate and simultaneous recognition of both diseases. The present case illustrates the advantages and importance of using an integrated approach to confirm a diagnosis of occupational rhinitis (OR) and occupational asthma (OA). A 38-year-old woman, who worked as an animal laboratory technician since 2004, first noticed the appearance of rhinitis and conjunctivitis symptoms in 2007 when she was exposed to rats. A skin-prick test with rat extract was strongly positive. A specific inhalation challenge with parallel assessment of nasal and bronchial responses was conducted. After 10 min of exposure, she developed rhinitis and conjunctivitis symptoms, her forced expiratory volume in 1 s dropped by 27.5% and her nasal volume, measured by acoustic rhinometry, decreased by 80% from baseline values. After allergen exposure, induced sputum and nasal lavage examination demonstrated an increase in eosinophils (11% and 20%, respectively). A diagnosis of associated allergic OA and OR was confirmed and she was advised to stop working with rats. A systematic and parallel diagnostic approach enables confirmation of a diagnosis of OA and OR in patients complaining of work-related rhinitis and asthma symptoms.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.436

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.039
GPT teacher head0.280
Teacher spread0.241 · 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

Citations7
Published2012
Admission routes1
Has abstractyes

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