Unsupervised Machine Learning to Identify Risk Factors of Pyeloplasty Failure in Ureteropelvic Junction Obstruction

被引:1
|
作者
Song, Jonathan J. [1 ]
Kielhofner, Jane [2 ]
Qian, Zhiyu [2 ]
Gu, Catherine [2 ]
Boysen, William [2 ]
Chang, Steven [2 ]
Dahl, Douglas [3 ]
Eswara, Jairam [2 ]
Haleblian, George [2 ]
Wintner, Anton [3 ]
Wollin, Daniel A. [2 ]
机构
[1] Boston Univ, Chobanian & Avedisian Sch Med, Boston, MA USA
[2] Brigham & Womens Hosp, Dept Urol, Boston, MA USA
[3] Massachusetts Gen Hosp, Dept Urol, Boston, MA USA
关键词
ureteropelvic junction obstruction; pyeloplasty; outcomes; risk factors; unsupervised machine learning; RENAL-FUNCTION; LAPAROSCOPIC MANAGEMENT; IMPACT; CRITERIA; CHILDREN; SURGERY; SUCCESS;
D O I
10.1089/end.2024.0264
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Introduction: In adult patients with ureteropelvic junction obstruction (UPJO), little data exist on predicting pyeloplasty outcome, and there is no unified definition of pyeloplasty success. As such, defining pyeloplasty success retrospectively is particularly vulnerable to bias, allowing researchers to choose significant outcomes with the benefit of hindsight. To mitigate these biases, we performed an unsupervised machine learning cluster analysis on a dataset of 216 pyeloplasty patients between 2015 and 2023 from a multihospital system to identify the defining risk factors of patients that experience worse outcomes.Methods: A KPrototypes model was fitted with pre- and perioperative data and blinded to postoperative outcomes. T-test and chi-square tests were performed to look at significant differences of characteristics between clusters. SHapley Additive exPlanation values were calculated from a random forest classifier to determine the most predictive features of cluster membership. A logistic regression model identified which of the most predictive variables remained significant after adjusting for confounding effects.Results: Two distinct clusters were identified. One cluster (denoted as "high-risk") contained 111 (51.4%) patients and was identified by having more comorbidities, such as old age (62.7 vs 35.7), high body mass index (BMI) (26.9 vs 23.8), hypertension (66.7% vs 17.1%), and previous abdominal surgery (72.1% vs 37.1%) and was found to have worse outcomes, such as more frequent severe postoperative complications (7.2% vs 1.0%). After adjusting for confounding effects, the most predictive features of high-risk cluster membership were old age, low preoperative estimated glomerular filtration rate (eGFR), hypertension, greater BMI, previous abdominal surgery, and left-sided UPJO.Conclusions: Adult UPJO patients with older age, lower eGFR, hypertension, greater BMI, previous abdominal surgery, and left-sided UPJO naturally cluster into to a group that more commonly suffers from perioperative complications and worse outcomes. Preoperative counseling and perioperative management for patients with these risk factors may need to be thought of or approached differently.
引用
收藏
页码:1164 / 1171
页数:8
相关论文
共 50 条
  • [31] Renal Cortical Thickness After Pyeloplasty in Pediatric Ureteropelvic Junction Obstruction
    Chalieopanyarwong, Virote
    Attawettayanon, Worapat
    RESEARCH AND REPORTS IN UROLOGY, 2021, 13 : 699 - 704
  • [32] Early pyeloplasty versus conservative management of severe ureteropelvic junction obstruction in asymptomatic infants
    Tabari, Ahmad Khaleghnejad
    Atqiaee, Khashayar
    Mohajerzadeh, Leily
    Rouzrokh, Mohsen
    Ghoroubi, Javad
    Alam, Alireza
    Lotfollahzadeh, Saran
    Tabatabaey, Ali
    Bakaeean, Behnaz
    JOURNAL OF PEDIATRIC SURGERY, 2020, 55 (09) : 1936 - 1940
  • [33] Robot-assisted laparoscopic Anderson-Hynes pyeloplasty for ureteropelvic junction obstruction
    Bersang, Ann Kortbaek
    Rashu, Badal Sheikho
    Niebuhr, Malene Hartwig
    Fode, Mikkel
    Thomsen, Frederik Ferlov
    JOURNAL OF ROBOTIC SURGERY, 2024, 18 (01)
  • [34] Dismembered and non-dismembered retroperitoneoscopic pyeloplasty for the treatment of ureteropelvic junction obstruction in children
    Subotic, Svetozar
    Weiss, Hagen
    Wyler, Stephen
    Rentsch, Cyrill A.
    Rassweiler, Jens
    Bachmann, Alexander
    Teber, Dogu
    WORLD JOURNAL OF UROLOGY, 2013, 31 (03) : 689 - 695
  • [35] Outcome analysis of immediate and delayed laparoscopic pyeloplasty in infants with severe ureteropelvic junction obstruction
    Bao, Qiao
    Ma, Weijun
    Zhang, Xiewu
    Chen, Shuhan
    Luo, Jiayao
    Zhang, Gang
    Lao, Weihua
    Chen, Yueqing
    FRONTIERS IN PEDIATRICS, 2022, 10
  • [36] Kidney duplication with ureteropelvic junction obstruction in childhood. Retroperitoneoscopic pyeloplasty
    Subotic, S.
    Reichenbach-Klinke, E.
    UROLOGE, 2010, 49 (11): : 1393 - +
  • [37] From Laparoscopic Pyeloplasty to Robot-Assisted Laparoscopic Pyeloplasty in Primary and Reoperative Repairs for Ureteropelvic Junction Obstruction in Children
    Tam, Yuk Him
    Pang, Kristine Kit Yi
    Wong, Yuen Shan
    Chan, Kin Wai
    Lee, Kim Hung
    JOURNAL OF LAPAROENDOSCOPIC & ADVANCED SURGICAL TECHNIQUES, 2018, 28 (08): : 1012 - 1018
  • [38] Head-to-Head Comparison of Modified Laparoscopic Pyeloplasty and Robot-Assisted Pyeloplasty for Ureteropelvic Junction Obstruction in China
    Hong, Peng
    Ding, Guangpu
    Zhu, Dongdong
    Yang, Kunlin
    Pan, Jinhong
    Li, Xuesong
    Chen, Zhipeng
    Zhang, Lei
    Tang, Qi
    Hao, Han
    Zhou, Zhansong
    Zhou, Liqun
    UROLOGIA INTERNATIONALIS, 2018, 101 (03) : 337 - 344
  • [39] Transumbilical Single-Site Multiport Laparoscopic Pyeloplasty for Children with Ureteropelvic Junction Obstruction in China: A Multicenter Study
    Liu, Dehong
    Zhou, Huixia
    Chao, Min
    Qi, Jinchun
    Wei, Huayu
    An, Nini
    Chen, Haitao
    Li, Long
    JOURNAL OF LAPAROENDOSCOPIC & ADVANCED SURGICAL TECHNIQUES, 2017, 27 (06): : 655 - 659
  • [40] Prediction of surgical necessity in children with ureteropelvic junction obstruction using machine learning
    Alici, cigdem Arslan
    Tokar, Baran
    IRISH JOURNAL OF MEDICAL SCIENCE, 2025, : 583 - 590