Impact of Patient Demographics, Surgeon Volume, and Hospital Type on Distal Radius Fracture Surgery Outcomes: A Population-Based Study
Notice bibliographique
Résumé
Abstract This study aimed to evaluate the impact of patient demographics, surgeon volume, and hospital type on composite outcomes, infection, and revision following surgery for acute, isolated distal radius fractures (DRFs). This population-based study examined Ontario administrative health data from 2010 to 2020, identifying 13,389 adults who underwent surgical fixation for acute, isolated DRFs. Patients with open fractures, other associated injuries, neurovascular injuries, prior surgery on the same limb, or any other factors that could worsen prognosis were excluded. Covariates included were time to surgery, patient demographics (age, biological sex, comorbidities, rural residence, income quintile), surgeon factors (volume, fixation type), fracture type (intra-articular vs. extra-articular), and hospital type (teaching vs. non-teaching). The primary outcome was a composite measure of complications, including infection, revision surgery, and hardware removal. Secondary outcomes included postoperative infection and revision procedures. Time-to-event Cox proportional multivariable models were applied to estimate hazard ratios (HRs) with 95% confidence intervals (CIs), adjusting for covariates. A total of 13,389 patients were included in the analysis. Higher surgeon volume was associated with improved outcomes: Every additional five DRF surgeries performed in the prior year reduced the risk of composite complications by 4% (HR 0.96, 95% CI 0.94–0.98; p < 0.001) and the risk of revision surgery by 10% (HR 0.90, 95% CI 0.86–0.93; p < 0.001). Rural residence was associated with a 44% higher risk of postoperative infection (HR 1.43, 95% CI 1.08–1.89; p = 0.01). Increased comorbidity burden, measured by the Johns Hopkins score, was consistently associated with worse outcomes: Each one-point increase corresponded to a 6.4% higher likelihood of composite complications (HR 1.06, 95% CI 1.05–1.08; p < 0.001). Female sex was protective across outcomes, reducing the risk of infection by 25% (HR 0.75, 95% CI 0.59–0.96; p = 0.02) and revision surgery by 19% (HR 0.81, 95% CI 0.68–0.98; p = 0.02). Older age was associated with a modest but consistent protective effect, reducing the risk of composite complications by 1% per year of age (HR 0.99, 95% CI 0.98–0.99; p < 0.001). Surgeon volume independently reduced complications and revisions after DRF surgery, while rural residence and higher comorbidity burden markedly increased infection risk. The protective effects of female sex and older age highlight the importance of nuanced risk assessment. Strategies to expand access to high-volume surgeons and targeted perioperative care may improve outcomes and reduce disparities in fracture management. Level III.
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| 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 | 0,000 |
| 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 ».