Prevalence and Risk Factors of Cognitive Impairment in COPD: A Systematic Review and Meta‐Analysis
Notice bibliographique
Résumé
ABSTRACT Aim The aim of this systematic review is to present the pooled estimated prevalence and risk factors for cognitive impairment (CI) in patients with chronic obstructive pulmonary disease (COPD). Background Patients with COPD suffer from progressive and irreversible airflow limitation, resulting in continuous impairment of lung function, which in addition to causing lesions in the lungs, often accrues to other organs as well. In recent years, a growing number of cross‐sectional and longitudinal studies have shown that hypoxia is an important factor in causing CI and that there is an important link between them, but the assessment of co‐morbid neurocognitive impairment and dysfunction is often overlooked. Some studies suggest that the diagnosis of mild cognitive impairment (MCI) is considered a precursor to dementia symptoms, with an annual conversion rate of 5%–10%, and it has been suggested that MCI is a potentially reversible state that can be used as a window for intervention. There is a lack of evidence on the prevalence and influencing factors of CI and its MCI. Design A systematic review and meta‐analysis. Methods PubMed, Web of Science, the Cochrane Library, Ovid, Wiley, and Scopus were searched for cohort, case‐control, and cross‐sectional studies investigating the prevalence and risk factors of CI and MCI in COPD to June 2023 from building. Meta‐analyses were performed to identify CI and MCI prevalence and risk factors using a random‐effects model. The methodological quality assessment was conducted by the modified Newcastle‐Ottawa Scale (NOS) and Agency for Healthcare Research and Quality (AHRQ). This study was registered on PROSPERO (CRD42021254124). Results In total, 41 studies (21 cohort studies, 7 case‐control studies, and 13 cross‐sectional studies) involving 138,030 participants were eligible for inclusion. Current evidence suggests that the average prevalence of CI and MCI in COPD was 20%–30% (95% CI, 0.17–0.28) and 24% (95% CI, 0.17–0.32), respectively. Significant heterogeneity existed both in CI and MCI ( I 2 = 99.76%, 91.40%, p < 0.001). Mata‐regression analysis showed that different region could be the source of heterogeneity in the pooled results. Cough, FEV1, PaO 2, age, education, depression, and BODE index are influential factors in the development of CI in COPD. Conclusion Integrated epidemiological evidence supports the hypothesis that the prevalence of CI in the COPD population has shown an increasing trend, with differences by region and by instrument. Cough, FEV1, PaO 2 , age, education, depression, and BODE index are influential factors in the development of cognitive impairment in COPD patients. We should promote early screening and management of COPD patients and take targeted measures to prevent and reduce the incidence of CI. Implications for Practice This systematic evaluation and meta‐analysis identifies seven important risk factors for the development of CI among COPD patients and exposes their current epidemiological findings to provide a theoretical basis for public health administrators and healthcare professionals to effectively increase the screening rate of cognitive impairment in patients with COPD as well as to carry out early intervention. Trial Registration PROSPERO).crd. york.ac.uk
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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,009 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| 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 | 0,001 |
| 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 ».