Rural–urban disparities in mortality of patients with acute myocardial infarction and heart failure: a systematic review and meta-analysis
Notice bibliographique
Résumé
AIMS: Patients with cardiac disease living in rural areas may face significant challenges in accessing care, and studies suggest that living in rural areas may be associated with worse outcomes. However, it is unclear whether rural-urban disparities have an impact on mortality in patients presenting with acute myocardial infarction (AMI) and heart failure (HF). This meta-analysis aimed to assess differences in mortality between rural and urban patients presenting with AMI and HF. METHODS AND RESULTS: A systematic search of the literature was performed using PubMed, Embase, MEDLINE, and CENTRAL for all studies published until 16 January 2024. A grey literature search was also performed using a manual web search. The following inclusion criteria were applied: (i) studies must compare rural patients to urban patients presenting to hospital with AMI or HF, and (ii) studies must report on mortality. The primary outcome was all-cause mortality. Comprehensive data were extracted including study design, patient characteristics (sex, age, and comorbidities), sample size, follow-up period, and outcomes. Odds ratios (ORs) were pooled with fixed-effects model. A subgroup analysis was performed to investigate causes for heterogeneity in which studies were separated based on in-hospital mortality, post-discharge mortality, and region of origin including North America, Europe, Asia, and Australia. In total, 37 studies were included (29 retrospective studies, 4 cross-sectional studies, and 4 prospective cohort studies) in our meta-analysis: 24 studies for AMI, 11 studies for HF, and 2 studies for both AMI and HF. This included a total of 21 107 886 patients with AMI (2 230 264 of which were in rural regions) and 18 434 270 patients with HF (2 655 469 of which were in rural regions). Rural patients with AMI had similar age (mean age 69.8 ± 5.7; vs. 67.5 ± 5.1) and were more likely to be female (43.2% vs. 38.5%) compared to urban patients. Rural patients with HF had similar age (mean age 77.1 ± 4.4 vs. 76.5 ± 4.2) and were more likely to be female (56.4% vs. 49.5%) compared to urban patients. The range of follow-up for the AMI cohort was 0 days to 24 months, and the range of follow-up for the HF cohort was 0 days to 24 months. Compared with urban patients, rural patients with AMI had higher mortality rate at follow-up [15.5% vs. 13.4%; OR 1.18, 95% confidence interval (CI), 1.13-1.24; I2 = 97%]. Compared with urban patients, rural patients with HF had higher mortality rate at follow-up (12.3% vs. 11.6%; OR 1.11, 95% CI, 1.11-1.12; I2 = 98%). CONCLUSION: To our knowledge, this is the first systematic review and meta-analysis assessing mortality differences between rural and urban patients presenting with AMI and HF. We found that patients living in rural areas had an increased risk of mortality when compared to patients in urban areas. Clinical and policy efforts are required to reduce these disparities. LAY SUMMARY: A total of 37 studies were included in our meta-analysis, involving over 39.5 million patients, and found higher mortality rates in rural patients with AMI and HF compared to those in urban areas. Clinical and policy efforts should focus on improving access to care and outcomes to reduce disparities between rural and urban areas.
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 | 0,004 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,012 | 0,003 |
| Bibliométrie | 0,001 | 0,001 |
| 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 ».