scholarly journals The learning curve of laparoscopic liver resection utilising a difficulty score

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Arpad Ivanecz ◽  
Irena Plahuta ◽  
Matej Mencinger ◽  
Iztok Perus ◽  
Tomislav Magdalenic ◽  
...  

Abstract Background This study aimed to quantitatively evaluate the learning curve of laparoscopic liver resection (LLR) of a single surgeon. Patients and methods 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. Results 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. Conclusions 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).

2018 ◽  
Vol 105 (9) ◽  
pp. 1182-1191 ◽  
Author(s):  
M. C. Halls ◽  
G. Berardi ◽  
F. Cipriani ◽  
L. Barkhatov ◽  
P. Lainas ◽  
...  

HPB ◽  
2020 ◽  
Vol 22 ◽  
pp. S208-S209
Author(s):  
A. Ivanecz ◽  
I. Plahuta ◽  
T. Magdalenic ◽  
L. Oblak ◽  
B. Krebs ◽  
...  

BMC Surgery ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Arpad Ivanecz ◽  
Irena Plahuta ◽  
Tomislav Magdalenić ◽  
Matej Mencinger ◽  
Iztok Peruš ◽  
...  

Abstract Background This 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). Methods The 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. Results The 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. Conclusion This 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.


2018 ◽  
Vol 3 ◽  
pp. 45-45 ◽  
Author(s):  
Yu Saito ◽  
Shinichiro Yamada ◽  
Satoru Imura ◽  
Yuji Morine ◽  
Tetsuya Ikemoto ◽  
...  

HPB ◽  
2018 ◽  
Vol 20 ◽  
pp. S416-S417
Author(s):  
A. Ivanecz ◽  
B. Krebs ◽  
B. Ilijevec ◽  
A. Stožer ◽  
S. Potrč

Medicine ◽  
2016 ◽  
Vol 95 (43) ◽  
pp. e5138 ◽  
Author(s):  
Federico Tomassini ◽  
Vincenzo Scuderi ◽  
Roos Colman ◽  
Marco Vivarelli ◽  
Roberto Montalti ◽  
...  

HPB ◽  
2017 ◽  
Vol 19 (9) ◽  
pp. 818-824 ◽  
Author(s):  
Mikhail Efanov ◽  
Ruslan Alikhanov ◽  
Victor Tsvirkun ◽  
Ivan Kazakov ◽  
Olga Melekhina ◽  
...  

HPB ◽  
2016 ◽  
Vol 18 ◽  
pp. e241
Author(s):  
M. van der Poel ◽  
F. Huisman ◽  
M. Besselink ◽  
P. Tanis ◽  
T. van Gulik ◽  
...  

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