Survival outcomes for patients with surgically induced end-stage renal disease
Bibliographic record
Abstract
INTRODUCTION: While medically induced end-stage renal disease (m-ESRD) has been well-studied, outcomes in patients with surgically induced ESRD (s-ESRD) are unknown. We sought to quantitatively compare the non-oncological outcomes for s-ESRD and m-ESRD in a large, population-based cohort. METHODS: Medicare patients >65 years old initiating hemodialysis were identified using the U.S. Renal Data System database (2000-2012). Metastatic cancer, prior transplant history, and nephrectomy for polycystic kidney disease were exclusion criteria. Patients were classified as having s-ESRD or m-ESRD based on hospital and physician claims for nephrectomy within a year preceding the onset of maintenance hemodialysis. Outcomes included non-cancer mortality (NCM), overall survival (OS), cardiovascular event (CVE), and renal transplantation. Time-to-event analyses were performed using Kaplan-Meier and cumulative incidence curves, and multivariable Cox and Fine-and-Grey regression models. RESULTS: The cohort included 312 612 patients, of whom 1648 (0.53%) had s-ESRD. Compared to m-ESRD patients, s-ESRD patients had a significantly lower five-year cumulative incidence of NCM (68% vs. 80%; p<0.001) and CVE (62% vs. 68%; p<0.001), with a correspondingly higher probability of OS (22% vs. 17%; p<0.001) and rate of renal transplantation (3.6% vs. 2.0%; p<0.001). On multivariable analyses, s-ESRD remained associated with lower risks of NCM (p<0.001) and CVE (p<0.001), improved OS (p<0.001), and higher chance of renal transplantation (p<0.001). CONCLUSIONS: While outcomes for s-ESRD appear more favorable than m-ESRD, s-ESRD is still associated with a substantial risk of NCM and CVE, and a low incidence of renal transplantation in Medicare patients >65 years old. These non-oncological outcomes are worth considering in patients potentially facing postoperative ESRD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".