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Enregistrement W2097799213 · doi:10.1093/occmed/kqi181

Pre-employment assessment and health surveillance for employees exposed to occupational asthmagens: overview

2005· article· en· W2097799213 sur OpenAlexaboutno aff
P F Gannon

Notice bibliographique

RevueOccupational Medicine · 2005
Typearticle
Langueen
DomaineMedicine
ThématiqueOccupational exposure and asthma
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésOccupational asthmaMedicineAsthmaOccupational safety and healthOccupational hygieneIntervention (counseling)Occupational medicineEnvironmental healthOccupational exposureNursingPathology

Résumé

récupéré en direct d'OpenAlex

The recent publication of an evidence-based review of occupational asthma [1] has highlighted the areas for which there is little evidence to guide the practising occupational physician dealing with workers exposed to occupational asthmagens. In particular, there is little or no evidence for effective management of prospective employees with a pre-existing or current history of asthma. There are few studies of efficacy of health surveillance programmes and an absence of guidance regarding important components and recommended frequency of assessment. This in-depth review sets out to review these important practical subjects for occupational physicians and where there is little evidence gives example of good practice from major employers in a number of different industries. The final paper looks to the future and the emerging areas of knowledge. The paper by Tarlo and Liss [2] sets out areas where good evidence exists for prevention of occupational asthma now thought to account for 10% of adult-onset asthma. Early diagnosis and early removal from exposure are essential to minimize the impact of occupational asthma once it has developed. Following diagnosis, the management of choice is complete removal from exposure, but even with early intervention there will be socio-economic consequences. The evidence for health surveillance is less certain, but one of the major studies [3] in Ontario is discussed in detail. Although there was some evidence of benefit, improvements in incidence were temporarily related to other hygiene changes in the workplace, which may have impacted on the development of occupational asthma. Areas which still need to be addressed include the important components and the optimum frequency of health surveillance assessments. In the paper by Linnet [4] the practice of a major platinum refiner is described. Platinum is a potent sensitizer with between 25–90% of employee populations becoming sensitized. Its refining also involves exposure to a number of irritants. The current practice is to exclude smokers and current active asthmatics on treatment. A previous history of asthma would exclude an employee if he/she were young and had not been tested in an industrial environment. Skin-prick testing with platinum salts is the mainstay of health surveillance and is conducted on a 3-monthly basis in areas of high exposure. The platinum industry does not exclude atopics because it is now recognized that exclusion of this group, prevalent in the general population, would exclude a large proportion of potential employees who would never go on to develop occupational asthma. The paper by Gannon [5] describes a global integrated programme for the prevention, early detection and mitigation of occupational asthma in an industry where employees work with isocyanates. The reason isocyanates cannot often be substituted are discussed. The practical issues of a global company policy which has to integrate with local legal and accepted professional practice are described. The authors suggest that this approach could be a model for other industries.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,205
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,102
Tête enseignante GPT0,436
Écart entre enseignants0,335 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2005
Routes d'admission1
Résumé présentoui

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