ArticleSurgical endoscopy2022
A machine learning analysis of difficulty scoring systems for laparoscopic liver surgery.
Article in Surgical endoscopy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The "Textbook Outcome" Isn't Textbook: Significant Variation in "Textbook Outcome" Definitions following a Systematic Review of the Surgical Oncology Literature.Annals of surgical oncology · 2026Pooled it
- Towards standardized assessment of surgical difficulty in robotic hepatobiliary surgery: a comparative validation study.Journal of robotic surgery · 2026Article
- Article
- A comparative study of argon plasma coagulation and electrosurgical knife on postoperative complications after curative resection for hepatocellular carcinoma.Langenbeck's archives of surgery · 2025Article
- Robotic vs laparoscopic resection for hepatocellular carcinoma: multicentric propensity-score matched analysis of surgical and oncologic outcomes in 647 patients.Updates in surgery · 2025Article
- Utility of a novel scoring system for difficulty of pure laparoscopic hepatectomy for intrahepatic cholangiocarcinoma.Scientific reports · 2024Article
- Explainable artificial intelligence prediction-based model in laparoscopic liver surgery for segments 7 and 8: an international multicenter study.Surgical endoscopy · 2024Article
- Application value of laparoscopic surgery in elderly patients (≥ 75 years) with colorectal cancer and prognostic factors influencing 5-year overall survival.American journal of translational research · 2024Article
- Utility of Machine Learning in the Prediction of Post-Hepatectomy Liver Failure in Liver Cancer.Journal of hepatocellular carcinoma · 2024Article
- Sub-classification of laparoscopic left hepatectomy based on hierarchic interaction of tumor location and size with perioperative outcomes.Journal of hepato-biliary-pancreatic sciences · 2023Article
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Abstract
introductionIn the last decade, several difficulty scoring systems (DSS) have been proposed to predict technical difficulty in laparoscopic liver resections (LLR). The present study aimed to investigate the ability of four DSS for LLR to predict operative, short-term, and textbook outcomes.
methodsPatients who underwent LLR at a single tertiary referral center from January 2014 to June 2020 were included in the present study. Four DSS for LLR (Halls, Hasegawa, Kawaguchi, and Iwate) were investigated to test their ability to predict operative and postoperative complications. Machine learning algorithms were used to identify the most important DSS associated with operative and short-term outcomes.
resultsA total of 346 patients were included in the analysis, 28 (8.1%) patients were converted to open surgery. A total of 13 patients (3.7%) had severe (Clavien-Dindo ≥ 3) complications; the incidence of prolonged length of stay (> 5 days) was 39.3% (n = 136). No patients died within 90 days after the surgery. According to Halls, Hasegawa, Kawaguchi, and Iwate scores, 65 (18.8%), 59 (17.1%), 57 (16.5%), and 112 (32.4%) patients underwent high difficulty LLR, respectively. In accordance with a random forest algorithm, the Kawaguchi DSS predicted prolonged length of stay, high blood loss, and conversions and was the best performing DSS in predicting postoperative outcomes. Iwate DSS was the most important variable associated with operative time, while Halls score was the most important DSS predicting textbook outcomes. No one of the DSS investigated was associated with the occurrence of complication.
conclusionsAccording to our results DDS are significantly related to surgical complexity and short-term outcomes, Kawaguchi and Iwate DSS showed the best performance in predicting operative outcomes, while Halls score was the most important variable in predicting textbook outcome. Interestingly, none of the DSS showed any correlation with or importance in predicting overall and severe postoperative complications.
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