Clinical Department of Abdominal and General Surgery, University Medical Centre Maribor, Maribor, Slovenia.
Department of Surgery, Faculty of Medicine, University of Maribor, Maribor, Slovenia.
Radiol Oncol. 2021 Sep 6;56(1):111-118. doi: 10.2478/raon-2021-0035.
This study aimed to quantitatively evaluate the learning curve of laparoscopic liver resection (LLR) of a single surgeon.
A retrospective review of a prospectively maintained database of liver resections was conducted. 171 patients undergoing pure LLRs between April 2008 and April 2021 were analysed. The Halls difficulty score (HDS) for theoretical predictions of intraoperative complications (IOC) during LLR was applied. IOC was defined as blood loss over 775 mL, unintentional damage to the surrounding structures, and conversion to an open approach. Theoretical association between HDS and the predicted probability of IOC was utilised to objectify the shape of the learning curve.
The obtained learning curve has resulted from thirteen years of surgical effort of a single surgeon. It consists of an absolute and a relative part in the mathematical description of the additive function described by the logarithmic function (absolute complexity) and fifth-degree regression curve (relative complexity). The obtained learning curve determines the functional dependency of the learning outcome versus time and indicates several local extreme values (peaks and valleys) in the learning process until proficiency is achieved.
This learning curve indicates an ongoing learning process for LLR. The proposed mathematical model can be applied for any surgical procedure with an existing difficulty score and a known theoretically predicted association between the difficulty score and given outcome (for example, IOC).
本研究旨在定量评估单个外科医生行腹腔镜肝切除术（LLR）的学习曲线。
对 2008 年 4 月至 2021 年 4 月期间前瞻性维护的肝切除术数据库进行回顾性分析。共分析了 171 例接受纯腹腔镜肝切除术的患者。应用 Halls 难度评分（HDS）对 LLR 术中并发症（IOC）的理论预测进行评估。IOC 定义为出血量超过 775ml、意外损伤周围结构以及转为开放手术。理论上 HDS 与预测的 IOC 概率之间的关联用于客观地描述学习曲线的形状。
该学习曲线是由一位外科医生经过 13 年的手术努力获得的。它由对数函数（绝对复杂度）和五次回归曲线（相对复杂度）描述的加法函数的绝对和相对部分组成。获得的学习曲线确定了学习成果与时间的功能依赖性，并表明在熟练程度达到之前，学习过程中存在几个局部极值（峰和谷）。
该学习曲线表明 LLR 是一个持续的学习过程。所提出的数学模型可应用于任何具有现有难度评分且已知难度评分与给定结果（例如 IOC）之间存在理论预测关联的手术。
