Comparative Analysis of Long-Term Renal Outcomes in Upper Tract Urothelial Carcinoma: Local Ablation Versus Radical Nephroureterectomy
Bibliographic record
Abstract
(1) Background: Upper tract urothelial carcinoma (UTUC) is typically managed through radical nephroureterectomy (RNU) or local ablation (LA). Compared to RNU, LA offers nephron-sparing benefit for select patients but may present increased recurrence risk. This study primarily compares long-term differences between LA and RNU in chronic kidney disease (CKD) progression, estimated glomerular filtration rate (eGFR) decline, all-cause mortality, and need for dialysis. (2) Methods: A retrospective cohort study was conducted using the TriNetX database, examining patients with UTUC treated with RNU (n = 2007) or LA (n = 4172). Propensity score matching balanced both cohorts (n = 1965 per group). Risk ratios and hazard ratios with 95% confidence intervals were calculated over 10 years. (3) Results: At 10 years, LA preserved higher mean eGFR (53.49 vs. 46.72; p < 0.001) and lower mean creatinine (1.56 vs. 1.66; p = 0.017). However, LA held a higher incidence of end-stage renal disease (ESRD) (3.6% vs. 2.2%, p = 0.008) and all-cause mortality (26.7% vs. 23.5%, p = 0.016). There was no significant difference in rates of dialysis (p = 0.79). (4) Conclusions: RNU did not carry an increased risk of ESRD, advanced stages of CKD, need for renal dialysis, or overall mortality compared with LA. LA may delay but not totally prevent renal dysfunction when compared to RNU, and exhibits a more gradual timeline.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".