709 OLDER AND SICKER RENAL CELL CARCINOMA PATIENTS ARE OPERATED AT LOW VOLUME HOSPITALS
Bibliographic record
Abstract
You have accessJournal of UrologyKidney Cancer: Evaluation and Staging II1 Apr 2012709 OLDER AND SICKER RENAL CELL CARCINOMA PATIENTS ARE OPERATED AT LOW VOLUME HOSPITALS Maxine Sun, Quoc-Dien Trinh, Marco Bianchi, Jens Hansen, Nawar Hanna, Zhe Tian, Shahrokh Shariat, Paul Perrotte, and Pierre Karakiewicz Maxine SunMaxine Sun Montreal, Canada , Quoc-Dien TrinhQuoc-Dien Trinh Detroit, MI , Marco BianchiMarco Bianchi Milan, Italy , Jens HansenJens Hansen Hamburg, Germany , Nawar HannaNawar Hanna Montreal, Canada , Zhe TianZhe Tian Montreal, Canada , Shahrokh ShariatShahrokh Shariat New York, NY , Paul PerrottePaul Perrotte Montreal, Canada , and Pierre KarakiewiczPierre Karakiewicz Montreal, Canada View All Author Informationhttps://doi.org/10.1016/j.juro.2012.02.793AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Hospital volume represents an established determinant of outcomes. We sought to examine the patient selection for surgical candidates according to hospital volume, using patient age and baseline comorbidities as proxies. METHODS Overall, 48172 non-metastatic renal cell carcinoma (RCC) patients were identified amongst 2084 hospitals originating from the Nationwide Inpatient Sample, between years 1998 and 2007. We examined patient age, baseline Charlson comorbidity index (CCI), gender, race, nephrectomy type, hospital teaching status, hospital region, and surgical approach (open vs. laparoscopic) according to hospital volume, which was modeled in a continuously coded fashion. Finally, we examined the effect of hospital volume on patient age and CCI, using linear regression analyses. Adjustment was made for all the aforementioned covariates. RESULTS The overall mean hospital volume was 16 nephrectomies per year (median 9, interquartile range [IQR]: 4–20). First, hospital volume decreased with increasing patient age (≤59 years mean: 17 (median 9) vs. ≥80 years: 13 (median 8), P<0.001) and increasing CCI (0 mean: 16 (median 9) vs. ≥3: 13 (median 8), P<0.001). The effect of hospital volume also differed according to gender, nephrectomy type, hospital teaching status, hospital region, and surgical approach. Specifically, females, patients of Hispanic race, radical nephrectomies, non-teaching hospitals, hospitals located in the West, and cases performed via the open approach were more likely to be of low hospital volume. In univariable linear regression analyses, decreasing age (beta: -0.044, P<0.001) and decreasing CCI (beta: -0.027, P<0.001) was inversely associated with increasing hospital volume. These findings were confirmed in multivariable analyses, where patients with increasing age (beta: -3.512, P<0.001) and higher CCI (beta: -3.896, P<0.001) were more likely to be operated at hospitals with a low hospital volume. CONCLUSIONS Individuals of more advanced age and those with multiple comorbidities tend to be treated at low hospital volume institutions. Such practice may lead to less favorable outcomes in those individuals. © 2012 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 187Issue 4SApril 2012Page: e290-e291 Advertisement Copyright & Permissions© 2012 by American Urological Association Education and Research, Inc.MetricsAuthor Information Maxine Sun Montreal, Canada More articles by this author Quoc-Dien Trinh Detroit, MI More articles by this author Marco Bianchi Milan, Italy More articles by this author Jens Hansen Hamburg, Germany More articles by this author Nawar Hanna Montreal, Canada More articles by this author Zhe Tian Montreal, Canada More articles by this author Shahrokh Shariat New York, NY More articles by this author Paul Perrotte Montreal, Canada More articles by this author Pierre Karakiewicz Montreal, 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".