Mohamed Hany, Mohamed El Shafei, Mohamed Ibrahim, Ann Samy Shafiq Agayby, Anwar Ashraf Abouelnasr, Moustafa R Aboelsoud, Ehab Elmongui, Bart Torensma
{"title":"术前腹部超声检查在初级代谢和减肥手术患者术前准备中的作用:基于4418份患者记录的机器学习算法","authors":"Mohamed Hany, Mohamed El Shafei, Mohamed Ibrahim, Ann Samy Shafiq Agayby, Anwar Ashraf Abouelnasr, Moustafa R Aboelsoud, Ehab Elmongui, Bart Torensma","doi":"10.1007/s11695-024-07433-9","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The utility of preoperative abdominal ultrasonography (US) in evaluating patients with obesity before metabolic bariatric surgery (MBS) remains ambiguously defined.</p><p><strong>Method: </strong>Retrospective analysis whereby patients were classified into four groups based on ultrasound results. Group 1 had normal findings. Group 2 had non-significant findings that did not affect the planned procedure. Group 3 required additional or follow-up surgeries without changing the surgical plan. Group 4, impacting the procedure, needed further investigations and was subdivided into 4A, delaying surgery for more assessments, and 4B, altering or canceling the procedure due to critical findings. Machine learning techniques were utilized to identify variables.</p><p><strong>Results: </strong>Four thousand four hundred eighteen patients' records were analyzed. Group 1 was 45.7%. Group 2, 35.7%; Group 3, 17.0%; Group 4, 1.5%, Group 4A, 0.8%; and Group 4B, 0.7%, where surgeries were either canceled (0.3%) or postponed (0.4%). The hyperparameter tuning process identified a Decision Tree classifier with a maximum tree depth of 7 as the most effective model. The model demonstrated high effectiveness in identifying patients who would benefit from preoperative ultrasound before MBS, with training and testing accuracies of 0.983 and 0.985. It also showed high precision (0.954), recall (0.962), F1 score (0.958), and an AUC of 0.976.</p><p><strong>Conclusion: </strong>Our study found that preoperative ultrasound demonstrated clinical utility for a subset of patients undergoing metabolic bariatric surgery. Specifically, 15.9% of the cohort benefited from the identification of chronic calculous cholecystitis, leading to concomitant cholecystectomy. Additionally, surgery was postponed in 1.4% of the cases due to other findings. While these findings indicate a potential benefit in certain cases, further research, including a cost-benefit analysis, is necessary to fully evaluate routine preoperative ultrasound's overall utility and economic impact in this patient population.</p>","PeriodicalId":19460,"journal":{"name":"Obesity Surgery","volume":null,"pages":null},"PeriodicalIF":2.9000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11349839/pdf/","citationCount":"0","resultStr":"{\"title\":\"The Role of Preoperative Abdominal Ultrasound in the Preparation of Patients Undergoing Primary Metabolic and Bariatric Surgery: A Machine Learning Algorithm on 4418 Patients' Records.\",\"authors\":\"Mohamed Hany, Mohamed El Shafei, Mohamed Ibrahim, Ann Samy Shafiq Agayby, Anwar Ashraf Abouelnasr, Moustafa R Aboelsoud, Ehab Elmongui, Bart Torensma\",\"doi\":\"10.1007/s11695-024-07433-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The utility of preoperative abdominal ultrasonography (US) in evaluating patients with obesity before metabolic bariatric surgery (MBS) remains ambiguously defined.</p><p><strong>Method: </strong>Retrospective analysis whereby patients were classified into four groups based on ultrasound results. Group 1 had normal findings. Group 2 had non-significant findings that did not affect the planned procedure. Group 3 required additional or follow-up surgeries without changing the surgical plan. Group 4, impacting the procedure, needed further investigations and was subdivided into 4A, delaying surgery for more assessments, and 4B, altering or canceling the procedure due to critical findings. Machine learning techniques were utilized to identify variables.</p><p><strong>Results: </strong>Four thousand four hundred eighteen patients' records were analyzed. Group 1 was 45.7%. Group 2, 35.7%; Group 3, 17.0%; Group 4, 1.5%, Group 4A, 0.8%; and Group 4B, 0.7%, where surgeries were either canceled (0.3%) or postponed (0.4%). The hyperparameter tuning process identified a Decision Tree classifier with a maximum tree depth of 7 as the most effective model. The model demonstrated high effectiveness in identifying patients who would benefit from preoperative ultrasound before MBS, with training and testing accuracies of 0.983 and 0.985. It also showed high precision (0.954), recall (0.962), F1 score (0.958), and an AUC of 0.976.</p><p><strong>Conclusion: </strong>Our study found that preoperative ultrasound demonstrated clinical utility for a subset of patients undergoing metabolic bariatric surgery. Specifically, 15.9% of the cohort benefited from the identification of chronic calculous cholecystitis, leading to concomitant cholecystectomy. Additionally, surgery was postponed in 1.4% of the cases due to other findings. While these findings indicate a potential benefit in certain cases, further research, including a cost-benefit analysis, is necessary to fully evaluate routine preoperative ultrasound's overall utility and economic impact in this patient population.</p>\",\"PeriodicalId\":19460,\"journal\":{\"name\":\"Obesity Surgery\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2024-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11349839/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Obesity Surgery\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s11695-024-07433-9\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/8/8 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"SURGERY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Obesity Surgery","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s11695-024-07433-9","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/8/8 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"SURGERY","Score":null,"Total":0}
The Role of Preoperative Abdominal Ultrasound in the Preparation of Patients Undergoing Primary Metabolic and Bariatric Surgery: A Machine Learning Algorithm on 4418 Patients' Records.
Background: The utility of preoperative abdominal ultrasonography (US) in evaluating patients with obesity before metabolic bariatric surgery (MBS) remains ambiguously defined.
Method: Retrospective analysis whereby patients were classified into four groups based on ultrasound results. Group 1 had normal findings. Group 2 had non-significant findings that did not affect the planned procedure. Group 3 required additional or follow-up surgeries without changing the surgical plan. Group 4, impacting the procedure, needed further investigations and was subdivided into 4A, delaying surgery for more assessments, and 4B, altering or canceling the procedure due to critical findings. Machine learning techniques were utilized to identify variables.
Results: Four thousand four hundred eighteen patients' records were analyzed. Group 1 was 45.7%. Group 2, 35.7%; Group 3, 17.0%; Group 4, 1.5%, Group 4A, 0.8%; and Group 4B, 0.7%, where surgeries were either canceled (0.3%) or postponed (0.4%). The hyperparameter tuning process identified a Decision Tree classifier with a maximum tree depth of 7 as the most effective model. The model demonstrated high effectiveness in identifying patients who would benefit from preoperative ultrasound before MBS, with training and testing accuracies of 0.983 and 0.985. It also showed high precision (0.954), recall (0.962), F1 score (0.958), and an AUC of 0.976.
Conclusion: Our study found that preoperative ultrasound demonstrated clinical utility for a subset of patients undergoing metabolic bariatric surgery. Specifically, 15.9% of the cohort benefited from the identification of chronic calculous cholecystitis, leading to concomitant cholecystectomy. Additionally, surgery was postponed in 1.4% of the cases due to other findings. While these findings indicate a potential benefit in certain cases, further research, including a cost-benefit analysis, is necessary to fully evaluate routine preoperative ultrasound's overall utility and economic impact in this patient population.
期刊介绍:
Obesity Surgery is the official journal of the International Federation for the Surgery of Obesity and metabolic disorders (IFSO). A journal for bariatric/metabolic surgeons, Obesity Surgery provides an international, interdisciplinary forum for communicating the latest research, surgical and laparoscopic techniques, for treatment of massive obesity and metabolic disorders. Topics covered include original research, clinical reports, current status, guidelines, historical notes, invited commentaries, letters to the editor, medicolegal issues, meeting abstracts, modern surgery/technical innovations, new concepts, reviews, scholarly presentations and opinions.
Obesity Surgery benefits surgeons performing obesity/metabolic surgery, general surgeons and surgical residents, endoscopists, anesthetists, support staff, nurses, dietitians, psychiatrists, psychologists, plastic surgeons, internists including endocrinologists and diabetologists, nutritional scientists, and those dealing with eating disorders.