Prevalence of chronic respiratory disease using case-finding tools in adults living with noncommunicable disease in low- and middle-income countries: a systematic review
Notice bibliographique
Résumé
BACKGROUND: Chronic respiratory diseases (CRD) often coexist with other non-communicable diseases (NCD) and are responsible for nearly three-quarters of all deaths in low- and middle-income countries (LMIC). People living with NCD are considered at higher risk of having CRD, but the prevalence of CRD in those with other NCD in LMIC is not well described. This study aimed to identify the prevalence of CRD and/or abnormal spirometry identified through case-finding tools in adults living with NCD in LMIC. METHODS: This systematic review followed the PRISMA guidelines and included Lilacs, PubMed, Scielo, Embase and Web of Science databases. Two reviewers independently examined the titles and abstracts of studies identified from the search to determine eligibility for inclusion. Searching was carried out until May 16, 2024, and was updated in February 2025. Cross-sectional studies that used case finding tools to identify CRD in adults living with other NCD in LMIC were eligible. The studies were exported to Rayyan software, and duplicates were manually removed. Data were extracted including study characteristics, and quality was assessed using the modified Newcastle-Ottawa Scale risk of bias tool. A descriptive analysis of the prevalence of respiratory diseases and spirometric abnormalities was reported considering 95% confidence intervals. RESULTS: A total of 8,939 citations were screened based on titles and abstracts. Thirteen full-text articles were assessed for eligibility. Five studies were excluded for not providing sufficient data, two for inadequate outcome ascertainment, two for being conducted in developed countries, and one for only including patients with a previous COPD diagnosis. Three cross-sectional studies met the inclusion criteria, one conducted in India, and two in Brazil. Considering studies with a low risk of bias, the prevalence of CRD was between 1% and 5.2% in patients with hypertension. The prevalence of abnormal spirometry was between 11% and 17% in patients with coronary artery disease. CONCLUSION: The prevalence of CRD identified through case-finding tools in adults with NCD in LMIC varies according to the NCD in which it was investigated. These findings highlight the opportunity to case-find CRD by assessing people accessing care for other NCD. REGISTRATION: PROSPERO 2024 CRD42024534734.
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 | 0,003 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,006 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».