Under- and over-diagnosis of COPD: a global perspective
Notice bibliographique
Résumé
Globally, chronic obstructive pulmonary disease (COPD) is the fourth major cause of mortality and morbidity and projected to rise to third within a decade as our efforts to prevent, identify, diagnose and treat patients at a global population level have been insufficient. The European Respiratory Society and American Thoracic Society, along with the Global Initiative for Chronic Obstructive Lung Disease (GOLD) strategy document, have highlighted key pathological risk factors and suggested clinical treatment strategies in order to reduce the mortality and morbidity associated with COPD. This review focuses solely on issues related to the under- and over-diagnosis of COPD across the main geographical regions of the world and highlights some of the associated risk factors. Prevalence of COPD obtained mainly from epidemiological studies varies greatly depending on the clinical and spirometric criteria used to diagnose COPD, i.e. forced expiratory volume in 1 s to forced vital capacity ratio <0.7 or 5% below the lower limit of normal, and this subsequently affects the rates of under- and over-diagnosis. Although under-utilisation of spirometry is the major reason, additional factors such as exposure to airborne pollutants, educational level, age of patients and language barriers have been widely identified as other potential risk factors. Co-existent diseases, such as asthma, bronchiectasis, heart failure and previously treated tuberculosis, are reported to be the other determinants of under- and over-diagnosis of COPD. Key points Globally, there is large variation in the prevalence of COPD, with 10–95% under-diagnosis and 5–60% over-diagnosis (table 1) due to differences in the definition of diagnosis used, and the unavailability of spirometry in rural areas of low- and middle-income countries where the prevalence of COPD is likely to be high. In order to be diagnosed with COPD, patients must have a combination of symptoms with irreversible airflow obstruction defined by a post-bronchodilator FEV 1 /FVC ratio of <0.7 or below the fifth centile of the lower limit of normal (LLN), and with a history of significant exposure to a risk factor. Repeat spirometry is recommended if the ratio is between 0.6 and 0.8. Not performing spirometry is the strongest predictor for an incorrect diagnosis of COPD; however, additional factors, such as age, gender, ethnicity, self-perception of symptoms, co-existent asthma, and educational awareness of risk factor by patients and their physician, are also important. COPD can be associated with inhalation of noxious particles other than smoking tobacco. Educational aims To summarise the global prevalence of over- and under-diagnosis of COPD. To highlight the risk factors associated with the under- and over-diagnosis of COPD. To update readers on the key changes in the recent progress made regarding the correct diagnosis of COPD.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».