Literature DB >> 29759510

Predicting morbidity after robotic partial nephrectomy: The effect of tumor, environment, and patient-related factors.

Zine-Eddine Khene1, Benoit Peyronnet2, Neil J Kocher3, Haley Robyak3, Corentin Robert4, Benjamin Pradere2, Emmanuel Oger5, Solène-Florence Kammerer-Jacquet6, Grégory Verhoest2, Nathalie Rioux-Leclercq6, Romain Mathieu2, Jay D Raman3, Karim Bensalah2.   

Abstract

PURPOSE: To investigate the effect of tumor and nontumor related parameters on perioperative outcomes of robotic partial nephrectomy (RPN). PATIENTS AND METHODS: Patients who underwent RPN for a localized renal tumor at 2 institutions between June 2010 and November 2016 were reviewed. RENAL and Mayo adhesive probability (MAP) scores were calculated and information on comorbid conditions including ASA score, performance status, Charlson's comorbidity index (CCI), and history of cardiovascular disease was collected. Correlations between each variable and warm ischemia time, estimated blood loss (EBL), operative time, change in estimated glomerular filtration rate, and length of hospital stay were assessed. Logistic regression analyses were performed to identify the best predictors of overall complications, major complications, risk of conversion, and Trifecta achievement.
RESULTS: A total of 500 patients were included. RENAL score was found to have a statistically significant (P<0.05) correlation with warm ischemia time, EBL, and change in estimated glomerular filtration rate. MAP score showed significant association (P<0.05) with operative time and EBL. CCI had a significant correlation (P<0.05) with length of hospital stay and postoperative complications. In multivariable analyses, MAP score as a continuous variable (OR = 7.66; P<0.001) and MAP risk group stratification (OR = 3.29; P = 0.005) were independent predictors of the risk of conversion. Major complications were significantly associated with the cardiovascular disease in both univariable (OR = 2.35; P = 0.01) and multivariable analysis (OR = 4.52, P = 0.01). Finally, the MAP score as a continuous variable was an independent factor of Trifecta achievement (OR = 0.56; P = 0.04).
CONCLUSION: Patients related factors were the most important determinants of postoperative complications after RPN. RENAL and MAP scores had some influence on intraoperative parameters.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Comorbidities; Complication; Nephrometry scores; Partial nephrectomy; Robotic surgical procedures

Mesh:

Year:  2018        PMID: 29759510     DOI: 10.1016/j.urolonc.2018.04.005

Source DB:  PubMed          Journal:  Urol Oncol        ISSN: 1078-1439            Impact factor:   3.498


  4 in total

1.  Development of a simple nomogram to estimate risk for intraoperative complications before partial nephrectomy based on the Mayo Adhesive Probability score combined with the RENAL nephrometry score.

Authors:  Xiaojun Tan; Dachun Jin; Jian Hu; Weili Zhang; Yu Zhou; Yunxiang Li; Yuanfeng Zhang; Ji Wu
Journal:  Investig Clin Urol       Date:  2021-07

2.  A novel nephrometry scoring system for predicting peri-operative outcomes of retroperitoneal laparoscopic partial nephrectomy.

Authors:  Bin Yang; Lu-Lin Ma; Min Qiu; Hai-Zhui Xia; Wei He; Tian-Yu Meng; Min Lu; Jian Lu
Journal:  Chin Med J (Engl)       Date:  2020-03-05       Impact factor: 2.628

3.  External validation of the Simplified PADUA REnal (SPARE) nephrometry system in predicting surgical outcomes after partial nephrectomy.

Authors:  Chi-Ping Huang; Chao-Hsiang Chang; Hsi-Chin Wu; Che-Rei Yang; Po-Fan Hsieh; Guang-Heng Chen; Po-Jen Hsiao; Yi-Huei Chang; Yu-Ping Wang; Yu-De Wang
Journal:  BMC Urol       Date:  2020-09-11       Impact factor: 2.264

Review 4.  Trifecta achievement in patients undergoing partial nephrectomy: a systematic review and meta-analysis of predictive factors.

Authors:  Nigemutu Bai; Muge Qi; Dan Shan; Suo Liu; Ta Na; Liang Chen
Journal:  Int Braz J Urol       Date:  2022 Jul-Aug       Impact factor: 3.050

  4 in total

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