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Higher perioperative morbidity and in‐hospital mortality in patients with end‐stage renal disease undergoing nephrectomy for non‐metastatic kidney cancer: a population‐based analysis

2012· article· en· W1606568926 on OpenAlexaff
Jan Schmitges, Quoc‐Dien Trinh, Maxine Sun, Jens Hansen, Marco Bianchi, Claudio Jeldres, Paul Perrotte, Roland Dahlem, Shahrokh F. Shariat, Felix K.‐H. Chun, Francesco Montorsi, Mani Menon, Margit Fisch, Markus Graefen, Pierre I. Karakiewicz

Bibliographic record

VenueBritish Journal of Urology · 2012
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineNephrectomyPerioperativePopulationEnd stage renal diseaseKidney diseaseCohortRenal replacement therapyDiseaseSurgeryRenal functionInternal medicineKidney

Abstract

fetched live from OpenAlex

UNLABELLED: What's known on the subject? and What does the study add? Patients with renal failure more frequently harbour RCC due to predisposing factors such as cystic disease of the kidney. The benefit of nephrectomy might be outweighed by adverse perioperative events, however, which may be more prevalent in patients with end-stage renal disease (ESRD). In a population-based study focusing on patients after non-elective colorectal surgery, patients with ESRD had an increased risk of mortality and complications. To date, small-scale studies have reported complication rates in patients with ESRD after nephrectomy for RCC with conflicting results. However, no formal contemporary analysis has been compiled within a nephrectomy cohort of adequate size. The present population-based case-control study showed that patients with ESRD are at substantially higher risk of in-hospital mortality and in-hospital complications. Specifically, we demonstrated higher cardiac-related complications, transfusion and haemorrhage/haematoma rates in patients with ESRD than in others. Moreover, patients with ESRD are more likely to have prolonged length of stay in hospital, and incur higher hospital charges. Based on the findings of the present study, use of biopsy and active surveillance for small, carefully selected renal masses might be considered in patients with ESRD at high risk of morbidity and mortality after surgery. OBJECTIVE: To examine the effect of end-stage renal disease (ESRD) on six short-term nephrectomy outcomes. PATIENTS AND METHODS: The Nationwide Inpatient Sample was used to assess the rates of blood transfusions, intra-operative and postoperative complications, length of hospital stay (LOS) within the highest quartile (>5 days), total hospital charges within the highest quartile (>$33 391) and in-hospital mortality. Propensity-based matching was performed to adjust for potential baseline differences between patients with ESRD and others. Multivariable logistic regression analyses further adjusted for confounding variables. RESULTS: Overall, 46 225 patients underwent open radical, open partial, laparoscopic radical or laparoscopic partial nephrectomy for non-metastatic kidney cancer between 1998 and 2007. Of those, 941 patients with ESRD were identified (2.0%). For patients with ESRD and others, the following rates were recorded, respectively: blood transfusions, 17.4 vs 9.1% (P < 0.001); intra-operative complications, 3.5 vs 3.3% (P = 0.81); postoperative complications, 19.2 vs 15.6% (P = 0.007); length of stay within the highest quartile, 55.4 vs 30.1% (P < 0.001); total hospital charges within the highest quartile, 50.4 vs 26.3% (P < 0.001); in-hospital mortality, 2.4 vs 0.5% (P < 0.001). In multivariable logistic regression analyses, patients with ESRD were more likely to receive a blood transfusion (odds ratio [OR] = 2.05, P < 0.001), to experience any postoperative complication (OR = 1.25, P = 0.019), to have a LOS within the highest quartile (OR = 3.06, P < 0.001), to have hospital charges within the highest quartile (OR = 3.10, P < 0.001), and to die during hospitalization (OR = 4.85, P < 0.001). CONCLUSIONS: Patients with ESRD are at substantially higher risk of adverse outcomes after nephrectomy. Most importantly, the in-hospital mortality rate is fivefold higher.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.018
GPT teacher head0.279
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations27
Published2012
Admission routes1
Has abstractyes

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