The external validation of a difficulty scoring system for predicting the risk of intraoperative complications during laparoscopic liver resection

Abstract

BackgroundThis study aimed to externally validate and upgrade the recent difficulty scoring system (DSS) proposed by Halls et al. to predict intraoperative complications (IOC) during laparoscopic liver resection (LLR).MethodsThe DSS was validated in a cohort of 128 consecutive patients undergoing pure LLRs between 2008 and 2019 at a single tertiary referral center. The validated DSS includes four difficulty levels based on five risk factors (neoadjuvant chemotherapy, previous open liver resection, lesion type, lesion size and classification of resection). As established by the validated DSS, IOC was defined as excessive blood loss (> 775 mL), conversion to an open approach and unintentional damage to surrounding structures. Additionally, intra- and postoperative outcomes were compared according to the difficulty levels with usual statistic methods. The same five risk factors were used for validation done by linear and advanced nonlinear (artificial neural network) models. The study was supported by mathematical computations to obtain a mean risk curve predicting the probability of IOC for every difficulty score.ResultsThe difficulty level of LLR was rated as low, moderate, high and extremely high in 36 (28.1%), 63 (49.2%), 27 (21.1%) and 2 (1.6%) patients, respectively. IOC was present in 23 (17.9%) patients. Blood loss of >775 mL occurred in 8 (6.2%) patients. Conversion to open approach was required in 18 (14.0%) patients. No patients suffered from unintentional damage to surrounding structures. Rates of IOC (0, 9.5, 55.5 and 100%) increased gradually with statistically significant value among difficulty levels (P < 0.001). The relations between the difficulty level, need for transfusion, operative time, hepatic pedicle clamping, and major postoperative morbidity were statistically significant (P < 0.05). Linear and nonlinear validation models showed a strong correlation (correlation coefficients 0.914 and 0.948, respectively) with the validated DSS. The Weibull cumulative distribution function was used for predicting the mean risk probability curve of IOC.ConclusionThis external validation proved this DSS based on patient’s, tumor and surgical factors enables us to estimate the risk of intra- and postoperative complications. A surgeon should be aware of an increased risk of complications before starting with more complex procedures.

Comparing practice and outcome of laparoscopic liver resection between high-volume expert centres and nationwide low-to-medium volume centres

“…Recently, an external validation 28 has been performed showing the accuracy of the Southampton difficulty score to estimate the risk of intra-and postoperative complications. The latter may confirm that the Southampton difficulty score is a valid difficulty scoring system to use within our daily clinical practice.…”

The learning curve of laparoscopic liver resection utilising a difficulty score

“…Perioperative definitions were provided elsewhere. 11 The surgical technique for LLR has been extensively described by others 17 and performed as reported previously. [18][19][20] At the time of the operation all patients had given their written consent that anonymous data can be used for research purposes.…”

“…10 The conversion was defined as the requirement for laparotomy at any time of the procedure, except for the extraction of the resected specimen. 10 In 11 , the authors searched for functorial dependence between IOC and HDS using the first 128 patients of the observed cohort. The best-fit-dependency was found to be the Weibull cumulative distribution function 21 of the form with and .…”

“…[6][7][8][9] Halls et al 10 developed and internally validated a difficulty score estimating the risk of intraoperative complications (IOC) during LLR, which was externally validated by the authors of the present study. 11 Along with the evolution of LLR, its learning curves (LCs) have received increased attention. [12][13][14] The idealised model of the LC has been described, demonstrating continuous result improvement along with experience.…”

“…FIGURE 1. The continuous mean risk curve of intraoperative complication (IOC) as a function of the Halls difficulty score: the theoretical probability of intraoperative complication 11. …”