| Autor: |
Syed S; Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, USA., Syed M; Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, USA., Prior F; Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, USA.; Department of Radiology, University of Arkansas for Medical Sciences, Little Rock, AR, USA., Zozus M; Department of Population Health Sciences, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA., Syeda HB; Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, USA., Greer ML; Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, USA., Bhattacharyya S; Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, USA.; Department of Biological Sciences and Arkansas Biosciences Institute, Arkansas State University, Jonesboro., Garg S; Division of Gastroenterology and Hepatology, University of Arkansas for Medical Sciences, Little Rock, AR, USA. |
| Abstrakt: |
Endoscopy procedures are often performed with either moderate or deep sedation. While deep sedation is costly, procedures with moderate sedation are not always well tolerated resulting in patient discomfort, and are often aborted. Due to lack of clear guidelines, the decision to utilize moderate sedation or anesthesia for a procedure is made by the providers, leading to high variability in clinical practice. The objective of this study was to build a Machine Learning (ML) model that predicts if a colonoscopy can be successfully completed with moderate sedation based on patients' demographics, comorbidities, and prescribed medications. XGBoost model was trained and tested on 10,025 colonoscopies (70% - 30%) performed at University of Arkansas for Medical Sciences (UAMS). XGBoost achieved average area under receiver operating characteristic curve (AUC) of 0.762, F1-score to predict procedures that need moderate sedation was 0.85, and precision and recall were 0.81 and 0.89 respectively. The proposed model can be employed as a decision support tool for physicians to bolster their confidence while choosing between moderate sedation and anesthesia for a colonoscopy procedure. |
