1290 DOES SURGEON AND HOSPITAL VOLUME AFFECT OUTCOMES FOR SURGERY FOR RENAL CELL CARCINOMA WITH INFERIOR VENA CAVA INVOLVEMENT? – RESULTS OF A NATIONAL POPULATION BASED STUDY
Bibliographic record
Abstract
You have accessJournal of UrologyKidney Cancer: Localized II1 Apr 20121290 DOES SURGEON AND HOSPITAL VOLUME AFFECT OUTCOMES FOR SURGERY FOR RENAL CELL CARCINOMA WITH INFERIOR VENA CAVA INVOLVEMENT? – RESULTS OF A NATIONAL POPULATION BASED STUDY Paul Toren, Robert Abouassaly, Narhari Timilshina, Girish Kulkarni, and Antonio Finelli Paul TorenPaul Toren Toronto, Canada More articles by this author , Robert AbouassalyRobert Abouassaly Cleveland, OH More articles by this author , Narhari TimilshinaNarhari Timilshina Toronto, Canada More articles by this author , Girish KulkarniGirish Kulkarni Toronto, Canada More articles by this author , and Antonio FinelliAntonio Finelli Toronto, Canada More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2012.02.1624AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES In several major surgical procedures, an association with provider volume and outcomes has been seen, justifying a centralization of these procedures. Radical nephrectomy with removal of inferior vena cava (IVC) thrombus is a relatively rare, but large and complex operation in urology. Using Canada-wide population based data, we determined to assess whether surgeon or hospital volume had an effect on in-hospital mortality and complications. METHODS The Canadian Institute for Health Information(CIHI) Canadian Classification of Health Intervention(CCI) codes and Canadian Classification of Diagnostic, Therapeutic, and Surgical Procedures (CCP) codes were used to identify all nephrectomies associated with IVC thrombus performed in 9/10 Canadian provinces from 1998-2007. The CIHI Discharge Abstract Database (DAD) was used to assess in-hospital mortality and surgical complication rates for each procedure. The Charlson Co-morbidity Index (CCI) for each patient was calculated from ICD-9 and ICD-10 codes. Patients were excluded who underwent a partial nephrectomy, laparoscopic nephrectomy or had incomplete data. RESULTS During the study period, 816 nephrectomies associated with venous thrombus were performed on 521 men and 295 women. The in-hospital mortality rate was 7% (59 patients); surgical complications were noted in 122 (15%) of patients. Age and co-morbidity were the strongest predictors of in hospital mortality on multivariate logistic analysis. Multivariate logistic regression analysis showed a trend to lower in-hospital mortality with higher surgeon volume which was significant at the highest quartile (OR for highest vs lowest quartile 0.42(0.0.18-0.98; P=0.05)). This relationship was not seen with hospital volume (P= 0.34). Over time, more surgeries were performed by the higher quartile surgeons. Most (65%) surgical complications were split between the highest and lowest quartiles of surgeon volume. With increasing hospital volume, there was a trend for increased complications on multivariate analysis (OR 2.1 (2.1-4.1; P=0.03). CONCLUSIONS For radical nephrectomies associated with IVC thrombus, increasing surgeon volume, but not hospital volume, corresponded to lower in-hospital mortality rates. Age and co-morbidity remain the strongest predictors of in-hospital mortality. Higher hospital volume quartile was associated with higher surgical complications. © 2012 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 187Issue 4SApril 2012Page: e523 Advertisement Copyright & Permissions© 2012 by American Urological Association Education and Research, Inc.MetricsAuthor Information Paul Toren Toronto, Canada More articles by this author Robert Abouassaly Cleveland, OH More articles by this author Narhari Timilshina Toronto, Canada More articles by this author Girish Kulkarni Toronto, Canada More articles by this author Antonio Finelli Toronto, Canada More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".