Geographic disparities in perioperative and mid-term outcomes after elective infrarenal endovascular aneurysm repair
Notice bibliographique
Résumé
Objective This study aimed to assess the impact of geographic location on mid-term postoperative outcomes after EVAR across 4 Canadian tertiary care institutions. We hypothesized that patients from rural or non-local areas may experience worse perioperative outcomes because of loss to follow-up, care transfers, and suboptimal surveillance. These factors could contribute to increased non-index readmissions and higher mortality rates following elective endovascular aneurysm repair (EVAR). Methods Elective infrarenal EVAR patients from four Canadian tertiary care institutions were assessed through a retrospective analysis of the Vascular Quality Initiative (VQI) database, stratified by rural versus urban postal codes. A subgroup analysis was also conducted using a 10-year retrospective dataset from Toronto General Hospital (TGH) and the VQI to evaluate EVAR outcomes based on patient geography. Primary outcomes included differences in loss to follow-up, overall survival, and reintervention-free survival. Secondary outcomes included differences in baseline characteristics, perioperative outcomes, and imaging surveillance. Statistical analyses consisted of t-tests for continuous variables, chi-square tests for categorical variables, and Kaplan-Meier survival analysis with log-rank tests. Results Elective EVAR outcomes from four Canadian hospitals (n=1,342 patients) were analyzed by rural versus urban status. Rural patients demonstrated higher postoperative imaging rates but were more likely to be lost to follow-up. Aggregate data revealed a survival advantage for urban patients at 12 months postoperatively. A subgroup analysis from a single tertiary care institution included 491 patients who underwent elective infrarenal EVAR. Patients were categorized by postal code as local versus non-local (80.9% and 19.1%, respectively) and urban versus rural (94.9% and 5.1%, respectively). The median follow-up duration was 32 months (IQR 51). Local and urban patients had significantly higher rates of follow-up within the first two months (local: 84.6% vs. non-local: 57.4%, p<0.001; urban: 80.2% vs. rural: 64.0%, p=0.050) and more frequent imaging between 6 and 12 months (local: 69.5% vs. non-local: 43.6%, p<0.001; urban: 65.9% vs. rural: 40.0%, p=0.008). However, survival analysis did not demonstrate significant differences in estimated mean postoperative survival between groups (urban: 9.19 years vs. rural: 9.87 years, p=0.162; local: 9.15 years vs. non-local: 9.72 years, p=0.219). Conclusions At the national level, four Canadian VQI centres demonstrated higher rates of loss to follow-up and decreased one-year survival among patients from rural communities. In contrast, a subgroup analysis from our institution revealed that rural and non-local patients received fewer follow-up appointments and underwent less postoperative imaging; however, no significant differences in mortality or reintervention were observed. The influence of geographic distance and rurality status on follow-up and imaging highlights a potential vulnerability to aneurysm-related mortality, warranting further investigation.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| 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 source (Gemma direct ou Codex distillé), 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 ».