1315 DISPARITIES IN ACCESS TO HIGH-VOLUME SURGEONS AND HOSPITALS AMONGST NON-METASTATIC KIDNEY CANCER PATIENTS TREATED WITH PARTIAL OR RADICAL NEPHRECTOMY
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You have accessJournal of UrologyKidney Cancer: Localized (II)1 Apr 20131315 DISPARITIES IN ACCESS TO HIGH-VOLUME SURGEONS AND HOSPITALS AMONGST NON-METASTATIC KIDNEY CANCER PATIENTS TREATED WITH PARTIAL OR RADICAL NEPHRECTOMY Andreas Becker, Hugo Lavigueur-Blouin, Florian Roghmann, Zhe Tian, Al'a Abdo, Malek Meskawi, Markus Graefen, Pierre I. Karakiewicz, Quoc-Dien Trinh, and Maxine Sun Andreas BeckerAndreas Becker Hamburg, Germany More articles by this author , Hugo Lavigueur-BlouinHugo Lavigueur-Blouin Montreal, Canada More articles by this author , Florian RoghmannFlorian Roghmann Herne, Germany More articles by this author , Zhe TianZhe Tian Montreal, Canada More articles by this author , Al'a AbdoAl'a Abdo Montreal, Canada More articles by this author , Malek MeskawiMalek Meskawi Montreal, Canada More articles by this author , Markus GraefenMarkus Graefen Hamburg, Germany More articles by this author , Pierre I. KarakiewiczPierre I. Karakiewicz Montreal, Canada More articles by this author , Quoc-Dien TrinhQuoc-Dien Trinh Montreal, Canada More articles by this author , and Maxine SunMaxine Sun Montreal, Canada More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2013.02.2669AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Previous literature has indicated a relationship between surgical and hospital volume and postoperative complications in several procedures. We sought to examine and compare access to high volume surgeons and hospitals amongst non-metastatic kidney cancer patients treated with either partial (PN) or radical nephrectomy (RN). METHODS Relying on the Florida Inpatient Database, 16634 non-metastatic renal cell carcinoma patients treated with PN or RN were identified between years 1998 and 2008. Distribution of patients according to age, comorbidities, race, gender, and insurance status was examined according to high-volume surgeons and hospitals (top 75th percentile). Generalized estimating equations for prediction of access to high-volume surgeons and hospitals were performed. Sub-analyses comprised of open PN, laparoscopic PN, open RN, and laparoscopic RN. RESULTS The majority of patients underwent open RN (76%) followed by open PN (15%). Laparoscopic RN and PN were given to respectively 8.3 and 1.0%. High surgical and hospital volume was defined as ≥10 and ≥33 nephrectomies per year, respectively. After accounting for all covariates, Medicare beneficiaries were 23% less likely to be treated by high-volume surgeons (P<0.001), while Medicaid recipients were 39% more likely to be treated by high-volume surgeons (P=0.001). Sicker individuals were less likely to be operated by high-volume surgeons (odds ratio: 0.97, P=0.01). Laparoscopy was more likely to be offered by high-volume surgeons (OR: 3.85, P<0.001). No statistically significant difference was recorded with respect to gender, race, and age. When access to high-volume hospitals was examined, Medicare patients were 24% less likely to be treated at a high-volume hospital, whereas Medicaid patients were 40% more likely to be treated at a high-volume hospital (both P≤0.001). Black race was associated with 13% lower odds of high-volume hospital access. Advancing age (OR: 0.95, P<0.001) and increasing baseline conditions (OR: 0.99, P=0.008) were both inversely related to high-volume hospitals. Similarly disparities were recorded after stratification according to open vs. laparoscopic PN/RN. CONCLUSIONS In the context that high surgical and hospital volume has been linked to better postoperative outcomes following nephrectomy, our results indicate that not all segments of the population will benefit from such quality of care. Some sociodemographic characteristics are consistently linked with lower use of high-volume surgeon or hospital. © 2013 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 189 Issue 4S April 2013 Page: e537 Advertisement Copyright & Permissions© 2013 by American Urological Association Education and Research, Inc.Metrics Author Information Andreas Becker Hamburg, Germany More articles by this author Hugo Lavigueur-Blouin Montreal, Canada More articles by this author Florian Roghmann Herne, Germany More articles by this author Zhe Tian Montreal, Canada More articles by this author Al'a Abdo Montreal, Canada More articles by this author Malek Meskawi Montreal, Canada More articles by this author Markus Graefen Hamburg, Germany More articles by this author Pierre I. Karakiewicz Montreal, Canada More articles by this author Quoc-Dien Trinh Montreal, Canada More articles by this author Maxine Sun Montreal, Canada More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...
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 | 0,000 | 0,002 |
| 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 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,023 | 0,001 |
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 ».