Postoperative Mortality Rate after Radical Cystectomy: A Systematic Review of Epidemiologic Series
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: Mortality after radical cystectomy (RC) varies widely in the literature. In cohort studies, mortality rates can vary from as low as 0.5% in large-volume academic centers (2) to as high as 25% in developing countries series. This study aims to perform a systematic review of population-based studies reporting mortality after RC. METHODS: A Systematic search was performed in Medline (PubMed®), Embase, and Cochrane for epidemiologic studies reporting mortality after RC. Institutional cohorts and those reporting mortality for specific groups within populations were excluded. Case series and non-epidemiologic series were also excluded. The aim of this review is to evaluate in-hospital mortality (IHM), 30-day mortality (30M), and 90-day mortality (90M). RESULTS: Systematic search resulted in 42 papers comprising 449,661 patients who underwent RC from 1984 to 2017. Mean age was 66.1. Overall IHM, 30M, and 90M were 2.6%, 2.7%, and 4.9%, respectively, with 90M being 2.6 times higher than IHM on average. Lowest IHM was found in Canada and Australia (0.2% and 0.6%, respectively), while the highest IHM was 7.8% (Brazil). Canada and Spain showed the highest 90M (6.5%). 159,584 urinary diversions were analyzed, being mostly ileal conduits (76.8%). CONCLUSIONS: The majority of the studies available are from major developed economies with paucity of data in the developing world. 90M after RC tends to be at least twice as high as IHM. The knowledge of such epidemiologic data is vital to guide public policies, such as centralization, in order to reduce mortality.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it