79 THE TRUE RISK OF BLOOD TRANSFUSION AFTER NEPHRECTOMY FOR RENAL MASSES
Notice bibliographique
Résumé
You have accessJournal of UrologyGeneral & Epidemiological Trends & Socioeconomics: Evidence-based Medicine & Outcomes II1 Apr 201279 THE TRUE RISK OF BLOOD TRANSFUSION AFTER NEPHRECTOMY FOR RENAL MASSES Gino Vricella, Antonio Finelli, Shabbir Alibhai, Lee Ponsky, Rabii Madi, and Robert Abouassaly Gino VricellaGino Vricella Cleveland, OH More articles by this author , Antonio FinelliAntonio Finelli Toronto, Canada More articles by this author , Shabbir AlibhaiShabbir Alibhai Toronto, Canada More articles by this author , Lee PonskyLee Ponsky Cleveland, OH More articles by this author , Rabii MadiRabii Madi Cleveland, OH More articles by this author , and Robert AbouassalyRobert Abouassaly Cleveland, OH More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2012.02.125AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Perioperative blood transfusions are costly and have attendant risks and safety concerns. Reported blood transfusion rates after nephrectomy (radical and partial) demonstrate considerable variability, likely due to the referral patterns and selection biases that influence reports from tertiary academic centers. To our knowledge, the transfusion rate in general practice has not been previously reported. The aim of our study was to examine the actual transfusion rate and risk factors for blood transfusion after nephrectomy for renal masses on a population-level. METHODS We performed a population-based, retrospective observational study using a national discharge abstract database. Our cohort consisted of 10,902 patients treated by radical (RN) or partial nephrectomy (PN) for a renal mass between April 1, 2003 and March 31, 2008. Patient demographics and treatment approach (i.e. open vs. laparoscopic) were available for all patients. Surgeon and institution volume quartiles for kidney surgery were created. Adjustment for comorbidity was performed using the Charlson-Deyo Index. The association between blood transfusion and various explanatory variables was examined using the Chi-square test, as well as with multivariable logistic regression. RESULTS The overall blood transfusion rate for patients in our study was 18.1%. Transfusions occurred after 28.2%, 12.7%, 9.2% and 8.6% of open RN, open PN, laparoscopic RN and laparoscopic PN, respectively (p<.0001). Transfusion rate was found to be strongly associated with age and comorbidity, such that patients <50 years old and having Charlson scores of 0 were transfused 11.2% and 14.5% of the time, compared with 28.2% and 40.7% in patients ≥80 years old and with Charlson scores of ≥3, respectively (p<.0001). On multivariable logistic regression, age (p<.0001), Charlson score (p<.0001), procedure type (p<.0001), surgeon (p<.0001) and hospital volume quartile (p<.0001) were found to be associated with the rate of blood transfusions, whereas year of surgery, gender and income quintile were not. CONCLUSIONS The transfusion rate after nephrectomy in general clinical practice is higher than that reported in the urologic literature. Patient and provider factors appear to contribute to the considerable variability that exists in the observed transfusion rate. A more detailed understanding of these factors may help in preoperative patient counseling and informed consent. © 2012 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 187Issue 4SApril 2012Page: e33-e34 Peer Review Report Advertisement Copyright & Permissions© 2012 by American Urological Association Education and Research, Inc.MetricsAuthor Information Gino Vricella Cleveland, OH More articles by this author Antonio Finelli Toronto, Canada More articles by this author Shabbir Alibhai Toronto, Canada More articles by this author Lee Ponsky Cleveland, OH More articles by this author Rabii Madi Cleveland, OH More articles by this author Robert Abouassaly Cleveland, OH 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 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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 ».