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Enregistrement W2281916877 · doi:10.1155/2005/974678

Use of Spirometry and Respiratory Drugs in Manitobans Over 35 Years of Age with Obstructive Lung Diseases

2005· article· en· W2281916877 sur OpenAlexaffabout
NR Anthonisen, K Woodlrage, Jure Manfreda

Notice bibliographique

RevueCanadian Respiratory Journal · 2005
Typearticle
Langueen
DomaineMedicine
ThématiqueChronic Obstructive Pulmonary Disease (COPD) Research
Établissements canadiensUniversity of ManitobaHealth Sciences Centre
Organismes subventionnairesnon disponible
Mots-clésMedicineSpirometryCOPDAsthmaMedical prescriptionPharmacyInternal medicinePhysical therapyIntensive care medicineFamily medicinePharmacology

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Previous data indicated that spirometry was underused in people with obstructive disease, especially those with chronic obstructive pulmonary disease (COPD). OBJECTIVE: To examine the use of respiratory drugs in patients with COPD and asthma, and to relate drug use to spirometry. METHODS: Manitoba Health maintains a database of physician services remunerated by fees that includes spirometry. The database contains the diagnosis and patient identifiers, as well as sex, date of birth and residential postal code. Similar identifiers are used in the provincial pharmacare program that records prescriptions dispensed at retail pharmacies. These databases were examined for the time period between 1996 to 2000, and people over 35 years of age diagnosed with asthma, COPD or both were identified. The frequency of spirometry in these patients and their use of respiratory drugs was determined. RESULTS: Spirometry and drug prescription frequencies increased with the number of physician visits (including those for bronchitis), but their patterns differed. Patients with asthma or asthma plus COPD had considerably higher rates of drug prescription and slightly higher spirometry rates than did those with COPD. Patients with asthma and asthma plus COPD who underwent spirometry were slightly more likely to receive drugs than those who did not undergo spirometry; this trend was more striking in patients with COPD. However, approximately 30% of patients with COPD who had five physician visits and who underwent spirometry did not receive drugs; this was true for approximately 10% of similar patients with asthma. Patients with asthma generally received beta-agonists and inhaled steroids; these agents were less commonly given to patients with COPD, who instead were given anticholinergics much more often than were asthmatics. Patients who were diagnosed with asthma plus COPD had beta-agonist and inhaled corticosteroid prescription rates similar to asthmatics, and anticholinergic prescription rates similar to patients with COPD. Theophylline and antileukotriene drugs were used less often than were inhaled agents. In patients with asthma, drugs were frequently discontinued, and during drug use, prescription refills were consistent with an intake of 30.9% of the prescribed doses. In patients with COPD, discontinuing drugs early was uncommon, and refills were consistent with the use of 54% of the prescribed amounts. The same was true of patients with both COPD and asthma. DISCUSSION: Drug prescription was considerably more common in patients labelled with asthma or COPD plus asthma than in patients with COPD. Spirometry was also less common in patients with COPD but had a distinct influence on the frequency of drug prescription. Patterns of drug prescription were predictable, and patterns of drug use indicated poor compliance, in agreement with other data. The results suggest that COPD symptoms may be discounted and patients systematically undertreated or the diagnosis could frequently be applied to people with trivial disease or both.

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)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
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 enseignants0,027
Score d'incertitude au seuil0,998

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
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 Opus0,022
Tête enseignante GPT0,275
Écart entre enseignants0,253 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
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

Citations21
Publié2005
Routes d'admission2
Résumé présentoui

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