502 THE IMPACT OF SURGEON VOLUME AND SURGICAL APPROACH ON POST-RADICAL PROSTATECTOMY MORBIDITY IN MARYLAND HOSPITALS
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Résumé
You have accessJournal of UrologyProstate Cancer: Localized II1 Apr 2012502 THE IMPACT OF SURGEON VOLUME AND SURGICAL APPROACH ON POST-RADICAL PROSTATECTOMY MORBIDITY IN MARYLAND HOSPITALS Jeffrey Mullins, Elias Hyams, Phillip Pierorazio, Zhaoyong Feng, Bruce Trock, Mohamad Allaf, and Brian Matlaga Jeffrey MullinsJeffrey Mullins Baltimore, MD More articles by this author , Elias HyamsElias Hyams Baltimore, MD More articles by this author , Phillip PierorazioPhillip Pierorazio Baltimore, MD More articles by this author , Zhaoyong FengZhaoyong Feng Baltimore, MD More articles by this author , Bruce TrockBruce Trock Baltimore, MD More articles by this author , Mohamad AllafMohamad Allaf Baltimore, MD More articles by this author , and Brian MatlagaBrian Matlaga Baltimore, MD More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2012.02.573AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Nationwide data have suggested a link between surgeon volume and post-operative outcomes for men undergoing radical prostatectomy (RP). Furthermore, single surgeon series have suggested improved patient outcomes using robotic technology. However, the interaction of surgeon volume and surgical approach on post-operative morbidity has been less well characterized. The objective of this study is to assess the impact of surgeon volume and surgical approach on post-RP morbidity. METHODS The Maryland Health Service Cost Review Commission (HSCRC) database was queried for men undergoing RRP or RALRP from the fourth calendar quarter of 2008 to the first calendar quarter of 2011 using discharge ICD-9 codes. Patient demographic and immediate post-operative outcomes including length of hospital stay (LOS), hospital re-admission within 30 days, and need for intensive care unit admission were compared between patients undergoing surgery by high volume (>40 cases/year) and low volume surgeons (< 40 cases/year). Multivariable logistic regression analyses were performed to test the association between operative approach and surgeon volume with post-operative outcomes. RESULTS The study cohort consisted of 4,064 men undergoing radical prostatectomy of whom 76.6% had their surgery performed by a high volume surgeon. Patients undergoing RP by a low volume surgeon were more likely to have a robotic operation, be of non-Caucasian ethnicity, have a longer LOS (2.1 vs. 1.7 days, p <0.001), and were more likely to be readmitted to the hospital within 30 days (1.8% vs. 0.13%, p < 0.001). Multivariable logistic regression analyses demonstrated that high surgeon volume was significantly associated with lower risk of LOS > 2 days (OR 0.3, 95% CI: 0.2 - 0.4). Furthermore, open RP was significantly associated with LOS > 2 days (OR 2.3, 95% CI: 1.8 - 3.0) and 30-day readmission (OR 20.6, 95% CI: 2.7 - 154.5). After controlling for surgical approach, high surgeon volume was significantly associated with LOS > 2 days for both robotic and open RP, but the impact of surgeon volume on LOS was significantly greater for open RP. CONCLUSIONS Patients undergoing Robotic RP experienced shorter hospital stays and decreased rates of 30 day re-admission compared to those undergoing open RP. However, surgeon volume decreases post-operative LOS regardless of approach. When considering state-wide data, high surgeon volume and a robotic surgery improve post-operative morbidity. © 2012 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 187Issue 4SApril 2012Page: e206 Advertisement Copyright & Permissions© 2012 by American Urological Association Education and Research, Inc.MetricsAuthor Information Jeffrey Mullins Baltimore, MD More articles by this author Elias Hyams Baltimore, MD More articles by this author Phillip Pierorazio Baltimore, MD More articles by this author Zhaoyong Feng Baltimore, MD More articles by this author Bruce Trock Baltimore, MD More articles by this author Mohamad Allaf Baltimore, MD More articles by this author Brian Matlaga Baltimore, MD 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 | 0,007 |
| 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 | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,018 | 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 ».