Literature DB >> 33466610

Prediction of Postoperative Complications for Patients of End Stage Renal Disease.

Young-Seob Jeong1, Juhyun Kim2, Dahye Kim1, Jiyoung Woo1, Mun Gyu Kim3, Hun Woo Choi3, Ah Reum Kang4, Sun Young Park3.   

Abstract

End stage renal disease (ESRD) is the last stage of chronic kidney disease that requires dialysis or a kidney transplant to survive. Many studies reported a higher risk of mortality in ESRD patients compared with patients without ESRD. In this paper, we develop a model to predict postoperative complications, major cardiac event, for patients who underwent any type of surgery. We compare several widely-used machine learning models through experiments with our collected data yellow of size 3220, and achieved F1 score of 0.797 with the random forest model. Based on experimental results, we found that features related to operation (e.g., anesthesia time, operation time, crystal, and colloid) have the biggest impact on model performance, and also found the best combination of features. We believe that this study will allow physicians to provide more appropriate therapy to the ESRD patients by providing information on potential postoperative complications.

Entities:  

Keywords:  end stage renal disease; feature selection; machine learning model; postoperative complication; postoperative complications

Mesh:

Year:  2021        PMID: 33466610      PMCID: PMC7828737          DOI: 10.3390/s21020544

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  29 in total

1.  Significance of coronary vasospasm in the perioperative management of non-cardiac surgery.

Authors:  Yasuhiro Nagayoshi; Hiroaki Kawano; Sunao Kojima; Hirofumi Soejima; Koichi Kaikita; Masafumi Nakayama; Hitoshi Sumida; Seigo Sugiyama; Hisao Ogawa
Journal:  Circ J       Date:  2012-05-16       Impact factor: 2.993

2.  Surgery for diverticulitis is associated with high risk of in-hospital mortality and morbidity in older patients with end-stage renal disease.

Authors:  Erin Moran-Atkin; Miloslawa Stem; Anne O Lidor
Journal:  Surgery       Date:  2014-06-21       Impact factor: 3.982

3.  The risk of major elective vascular surgical procedures in patients with end-stage renal disease.

Authors:  Csaba Gajdos; Mary T Hawn; Deidre Kile; William G Henderson; Thomas Robinson; Martin McCarter; Mark Nehler
Journal:  Ann Surg       Date:  2013-04       Impact factor: 12.969

4.  Predicting Surgical Complications in Patients Undergoing Elective Adult Spinal Deformity Procedures Using Machine Learning.

Authors:  Jun S Kim; Varun Arvind; Eric K Oermann; Deepak Kaji; Will Ranson; Chierika Ukogu; Awais K Hussain; John Caridi; Samuel K Cho
Journal:  Spine Deform       Date:  2018 Nov - Dec

5.  Use of Machine Learning for Prediction of Patient Risk of Postoperative Complications After Liver, Pancreatic, and Colorectal Surgery.

Authors:  Katiuscha Merath; J Madison Hyer; Rittal Mehta; Ayesha Farooq; Fabio Bagante; Kota Sahara; Diamantis I Tsilimigras; Eliza Beal; Anghela Z Paredes; Lu Wu; Aslam Ejaz; Timothy M Pawlik
Journal:  J Gastrointest Surg       Date:  2019-08-05       Impact factor: 3.452

6.  Can We Improve Prediction of Adverse Surgical Outcomes? Development of a Surgical Complexity Score Using a Novel Machine Learning Technique.

Authors:  J Madison Hyer; Susan White; Jordan Cloyd; Mary Dillhoff; Allan Tsung; Timothy M Pawlik; Aslam Ejaz
Journal:  J Am Coll Surg       Date:  2019-10-28       Impact factor: 6.113

7.  A Clinical Risk Prediction Tool for 6-Month Mortality After Dialysis Initiation Among Older Adults.

Authors:  James P Wick; Tanvir C Turin; Peter D Faris; Jennifer M MacRae; Robert G Weaver; Marcello Tonelli; Braden J Manns; Brenda R Hemmelgarn
Journal:  Am J Kidney Dis       Date:  2016-11-14       Impact factor: 8.860

8.  Predicting postoperative complications of head and neck squamous cell carcinoma in elderly patients using random forest algorithm model.

Authors:  YiMing Chen; Wei Cao; XianChao Gao; HuiShan Ong; Tong Ji
Journal:  BMC Med Inform Decis Mak       Date:  2015-06-09       Impact factor: 2.796

Review 9.  Using Artificial Intelligence Resources in Dialysis and Kidney Transplant Patients: A Literature Review.

Authors:  Alexandru Burlacu; Adrian Iftene; Daniel Jugrin; Iolanda Valentina Popa; Paula Madalina Lupu; Cristiana Vlad; Adrian Covic
Journal:  Biomed Res Int       Date:  2020-06-10       Impact factor: 3.411

10.  Using machine learning techniques to develop forecasting algorithms for postoperative complications: protocol for a retrospective study.

Authors:  Bradley A Fritz; Yixin Chen; Teresa M Murray-Torres; Stephen Gregory; Arbi Ben Abdallah; Alex Kronzer; Sherry Lynn McKinnon; Thaddeus Budelier; Daniel L Helsten; Troy S Wildes; Anshuman Sharma; Michael Simon Avidan
Journal:  BMJ Open       Date:  2018-04-10       Impact factor: 2.692

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  5 in total

1.  Prediction of blood pressure changes associated with abdominal pressure changes during robotic laparoscopic low abdominal surgery using deep learning.

Authors:  Yang-Hoon Chung; Young-Seob Jeong; Gati Lother Martin; Min Seo Choi; You Jin Kang; Misoon Lee; Ana Cho; Bon Sung Koo; Sung Hwan Cho; Sang Hyun Kim
Journal:  PLoS One       Date:  2022-06-06       Impact factor: 3.752

2.  Intraoperative Hypotension Prediction Model Based on Systematic Feature Engineering and Machine Learning.

Authors:  Subin Lee; Misoon Lee; Sang-Hyun Kim; Jiyoung Woo
Journal:  Sensors (Basel)       Date:  2022-04-19       Impact factor: 3.847

Review 3.  Artificial intelligence and anesthesia: a narrative review.

Authors:  Valentina Bellini; Emanuele Rafano Carnà; Michele Russo; Fabiola Di Vincenzo; Matteo Berghenti; Marco Baciarello; Elena Bignami
Journal:  Ann Transl Med       Date:  2022-05

4.  Clinical and financial impact of chronic kidney disease in emergency general surgery operations.

Authors:  Vishal Dobaria; Joseph Hadaya; Shannon Richardson; Cory Lee; Zachary Tran; Arjun Verma; Yas Sanaiha; Peyman Benharash
Journal:  Surg Open Sci       Date:  2022-06-07

Review 5.  Computational Models Used to Predict Cardiovascular Complications in Chronic Kidney Disease Patients: A Systematic Review.

Authors:  Alexandru Burlacu; Adrian Iftene; Iolanda Valentina Popa; Radu Crisan-Dabija; Crischentian Brinza; Adrian Covic
Journal:  Medicina (Kaunas)       Date:  2021-05-27       Impact factor: 2.430

  5 in total

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