ArticleSensors (Basel, Switzerland)2021
Prediction of Postoperative Complications for Patients of End Stage Renal Disease.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 4 of them syntheses that pooled it.
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Who cites it
13 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Machine learning-augmented interventions in perioperative care: a systematic review and meta-analysis.British journal of anaesthesia · 2024Pooled it
- Prediction of Complications and Prognostication in Perioperative Medicine: A Systematic Review and PROBAST Assessment of Machine Learning Tools.Anesthesiology · 2024Pooled it
- Predict, diagnose, and treat chronic kidney disease with machine learning: a systematic literature review.Journal of nephrology · 2023Pooled it
- Computational Models Used to Predict Cardiovascular Complications in Chronic Kidney Disease Patients: A Systematic Review.Medicina (Kaunas, Lithuania) · 2021Pooled it
- Artificial intelligence for electrocardiographic diagnosis of perioperative myocardial ischaemia: a scoping review.British journal of anaesthesia · 2025Article
- Variational quantum classifier-based early identification and classification of chronic kidney disease using sparse autoencoder and LASSO shrinkage.PeerJ. Computer science · 2025Article
- No difference in oncological outcomes and perioperative complications between patients with ESRD with unilateral and bilateral UTUC receiving radical nephroureterectomy.Scientific reports · 2024Article
- Prediction of multiclass surgical outcomes in glaucoma using multimodal deep learning based on free-text operative notes and structured EHR data.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Clinical and financial impact of chronic kidney disease in emergency general surgery operations.Surgery open science · 2022Article
- Artificial intelligence and anesthesia: a narrative review.Annals of translational medicine · 2022Review
- Intraoperative Hypotension Prediction Model Based on Systematic Feature Engineering and Machine Learning.Sensors (Basel, Switzerland) · 2022Article
- Machine learning in perioperative medicine: a systematic review.Journal of anesthesia, analgesia and critical care · 2022Review
- Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.