| Autor: |
Fabio Crocerossa, Cristian Fiori, Umberto Capitanio, Andrea Minervini, Umberto Carbonara, Savio D. Pandolfo, Davide Loizzo, Daniel D. Eun, Alessandro Larcher, Andrea Mari, Antonio Andrea Grosso, Fabrizio Di Maida, Lance J. Hampton, Francesco Cantiello, Rocco Damiano, Francesco Porpiglia, Riccardo Autorino |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
European Urology Open Science, Vol 38, Iss , Pp 52-59 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2666-1683 |
| DOI: |
10.1016/j.euros.2022.02.005 |
| Popis: |
Background: Long-term renal function after partial nephrectomy (PN) is difficult to predict as it is influenced by several modifiable and nonmodifiable variables, often intertwined in complex relations. Objective: To identify variables influencing long-term renal function after PN and to assess their relative weight. Design, setting, and participants: A total of 457 patients who underwent either robotic (n = 412) or laparoscopic PN (n = 45) were identified from a multicenter international database. Outcome measurements and statistical analysis: The 1-yr estimated glomerular filtration rate (eGFR) percentage loss (1YPL), defined as the eGFR percentage change from baseline at 1 yr after surgery, was the outcome endpoint. Predictors evaluated included demographic data, tumor features, and operative and postoperative variables. Bayesian multimodel analysis of covariance was used to build all possible models and compare the fit of each model to the data via model Bayes factors. Bayesian model averaging was used to quantify the support for each predictor via the inclusion Bayes factor (BFincl). High-dimensional undirected graph estimation was used for network analysis of conditional independence between predictors. Results and limitations: Several models were found to be plausible for estimation of 1YPL. The best model, comprising postoperative eGFR percentage loss (PPL), sex, ischemia technique, and preoperative eGFR, was 207 times more likely than all the other models regarding relative predictive performance. Its components were part of the top 44 models and were the predictors with the highest BFincl. The role of cold ischemia, solitary kidney status, surgeon experience, and type of renorraphy was not assessed. Conclusions: Preoperative eGFR, sex, ischemia technique, and PPL are the best predictors of eGFR percentage loss at 1 yr after minimally invasive PN. Other predictors seem to be irrelevant, as their influence is insignificant or already nested in the effect of these four parameters. Patient summary: Kidney function at 1 year after partial removal of a kidney depends on sex, the technique used to halt blood flow to the kidney during surgery, and kidney function at baseline and in the early postoperative period. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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