Impact of hospital and surgeon volumes on short-term and long-term outcomes of radical cystectomy
Bibliographic record
Abstract
PURPOSE OF REVIEW: There is heightened awareness and trends towards centralizing high-risk, complex surgeries such as radical cystectomy to minimize complications and improve survival. However, after nearly a decade of mandated and/or passive centralization of care, debate regarding its benefits and harms continues. RECENT FINDINGS: During the past decade, mandated and passive centralization has led to an increase in radical cystectomies performed in high-volume hospitals (HVHs) and, perhaps by high-volume surgeons (HVS), in addition to efforts to increase the uptake of multidisciplinary strategies in the management of radical cystectomy patients. Consequently, 30 and 90-day mortality rates and overall survival have improved, and major complications and transfusion rates have decreased. Factors impacting surgical quality, such as negative surgical margin(s), pelvic lymphadenectomy and/or lymph node yield rates have increased. However, current studies have not demonstrated a coadditive impact of centralization on oncological outcomes (i.e. cancer-specific and recurrence-free survival). The benefits of centralization on oncologic survival of radical cystectomy remain unclear given the varied definitions of HVHs and HVSs across studies. In fact, centralization of radical cystectomy could lead to an increase in patient load in HVHs and for HVSs, thereby leading to longer surgery waiting times, a factor that is important in the management of muscle-invasive bladder cancer. SUMMARY: The benefits of centralization of radical cystectomy with multidisciplinary management are shown increasingly and convincingly. More studies are necessary to prospectively test the benefits, risks and harms of centralization.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Review of hospital and surgeon volume effects on cystectomy outcomes; health services question about clinical outcomes.
This clinical review concerns surgical centralization and patient outcomes, not research evaluation.
Health-services review of surgical volume–outcome relationships for cystectomy; clinical quality, not research evaluation.
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 | 0.003 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".