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. Author manuscript; available in PMC: 2024 Sep 1.
Published in final edited form as: Surgery. 2023 Jun 9;174(3):581–592. doi: 10.1016/j.surg.2023.04.057

Impact of liver cirrhosis, severity of cirrhosis and portal hypertension on the outcomes of minimally-invasive left lateral sectionectomies for primary liver malignancies

Fabricio Ferreira Coelho 1, Paulo Herman 1, Jaime A P Kruger 1, Andrew G R Wu 2, Ken-Min Chin 3, Kiyoshi Hasegawa 4, Wanguang Zhang 5, Mohammed Alzoubi 6, Davit L Aghayan 7, Tiing-Foong Siow 8, Olivier Scatton 9, T Peter Kingham 10, Marco V Marino 11, Vincenzo Mazzaferro 12, Adrian K H Chiow 13, Iswanto Sucandy 14, Arpad Ivanecz 15, Sung-Hoon Choi 16, Jae Hoon Lee 17, Mikel Gastaca 18, Marco Vivarelli 19, Felice Giuliante 20, Andrea Ruzzenente 21, Chee-Chien Yong 22, Safi Dokmak 23, Constantino Fondevila 24, Mikhail Efanov 25, Zenichi Morise 26, Fabrizio Di Benedetto 27, Raffaele Brustia 28, Raffaele Dalla Valle 29, Ugo Boggi 30, David Geller 31, Andrea Belli 32, Riccardo Memeo 33, Salvatore Gruttadauria 34, Alejandro Mejia 35, James O Park 36, Fernando Rotellar 37, Gi-Hong Choi 38, Ricardo Robles-Campos 39, Xiaoying Wang 40, Robert P Sutcliffe 41, Johann Pratschke 42, Eric C H Lai 43, Charing C N Chong 44, Mathieu D’Hondt 45, Kazuteru Monden 46, Santiago Lopez-Ben 47, Rong Liu 48, Alessandro Ferrero 49, Giuseppe Maria Ettorre 50, Federica Cipriani 51, Daniel Cherqui 52, Xiao Liang 53, Olivier Soubrane 54, Go Wakabayashi 55, Roberto I Troisi 56, Mengqiu Yin 57, Tan-To Cheung 58, Atsushi Sugioka 59, Ho-Seong Han 60, Tran Cong duy Long 61, David Fuks 54, Mohammad Abu Hilal 6,62, Kuo-Hsin Chen 8, Luca Aldrighetti 51, Bjørn Edwin 7, Brian K P Goh 3,63; International robotic and laparoscopic liver resection study group investigators are coauthors of this study
PMCID: PMC10986843  NIHMSID: NIHMS1901039  PMID: 37301612

Abstract

Introduction:

The impact of cirrhosis and portal hypertension (PHT) on peri-operative outcomes of minimally-invasive left lateral sectionectomies (MI-LLS) remains unclear. We aimed to compare the peri-operative outcomes between patients with preserved and compromised liver function (non-cirrhotics vs. Child-Pugh A) when undergoing MI-LLS. In addition, we aimed to determine if the extent of cirrhosis (Child-Pugh A vs. B) and presence of PHT had significant impact on peri-operative outcomes.

Methods:

This was an international multicentre retrospective analysis of 1526 patients who underwent MI-LLS for primary liver malignancies at 60 centres worldwide between 2004–2021. 1370 patients met the inclusion criteria and formed the final study group. Baseline clinicopathological characteristics and peri-operative outcomes of these patients were compared. To minimize confounding factors, a 1:1 propensity score matching (PSM) and coarsened exact matching (CEM) was performed.

Results:

The study group comprised 559, 753 and 58 patients who were non-cirrhotics, Child-Pugh A and Child-Pugh B cirrhotics respectively. Six-hundred and thirty cirrhotic patients had PHT while 170 did not. After PSM and CEM, Child-Pugh A cirrhotic patients undergoing MI-LLS had longer operative time, higher intraoperative blood loss, higher transfusion rate, and longer hospital stay when compared to non-cirrhotic patients. The extent of cirrhosis did not have significant impact on perioperative outcomes except for a longer duration of hospital stay.

Conclusion:

Liver cirrhosis adversely affected both the intraoperative technical difficulty and perioperative outcomes of MI-LLS.

This study aimed to compare the peri-operative outcomes between patients with preserved and compromised liver function (non-cirrhotics vs. Child-Pugh A cirrhosis) when undergoing minimally-invasive left lateral sectionectomies (MI-LLS). Liver cirrhosis adversely affected both the intraoperative technical difficulty and perioperative outcomes of MI-LLS.

Keywords: laparoscopic liver, laparoscopic hepatectomy, minimally-invasive liver, minimally-invasive hepatectomy, left lateral sectionectomy, liver cirrhosis, portal hypertension

Introduction

Minimally invasive liver resections (MILRs) have been increasingly performed over the last 2 decades (1–3). With the advent of surgical technology, improved anaesthetic knowledge of the physiological effects of MILR and accumulating laparoscopic expertise amongst hepatobiliary surgeons, several robust studies have shown improved peri-operative outcomes in MILR as compared to open liver resections (OLR) with regards to the peri- and early post-operative periods (decreased blood loss, shorter operative time, lower complication rates, and shorter hospital stay) (4–9). Some of these advantages of MILR are also seen in patients with cirrhosis (10).

Left lateral sectionectomy (LLS) has been proposed as the ideal procedure for MILR due to its unique anatomical characteristics such as its midline position in the abdominal cavity, small parenchymal volume, predictable vascular anatomy and straight transection line (11, 12). These contribute to a shorter learning curve and amenability to standardization of surgical technique for minimally-invasive LLS (MI-LLS). (13,14). This stand was supported in the 2014 Morioka consensus where the laparoscopic approach was deemed to be the standard of care for LLS (15). Today, MI-LLS is accepted to be the gold standard for treatment of primary hepatic tumors in patients treated at tertiary institutions with a specialized hepatobiliary service (12,16,17). This procedure has, over time, become so commonplace in the armamentarium of hepatobiliary surgeons; however, the impact of cirrhosis and portal hypertension (PHT) on the difficulty and peri-operative outcomes of MI-LLS remains unclear and poorly studied (18).

Several difficulty scoring systems have been formulated over the years in an attempt to grade the complexity of MILR (19). None of these have, however, taken into account the presence of cirrhosis or PHT (19–23). While the Iwate scoring system recognized and took into account the impact of Child-Turcotte-Pugh (CTP) B cirrhosis on the difficulty of MILR, the presence of CTP A cirrhosis or portal hypertension was not included in the system (20). Contrary to these scoring systems, a recent survey of expert MILR surgeons revealed that most surgeons regarded the presence of cirrhosis as having a major impact on the difficulty of MILR (24). Furthermore, studies have suggested that the impact of cirrhosis would differ according to the extent and complexity of the liver resection (18).

Hence with this controversy in mind, we performed this study to determine the impact and severity of cirrhosis on the difficulty and postoperative outcomes of MI-LLS. In order to reduce the effect of potential confounding factors, we utilized 2 matching techniques. Furthermore, the study population was only limited to patients who underwent MI-LLS for primary liver malignancies and excluded resections for other pathologies.

Methods

This was a retrospective review comprising 3426 patients from 60 centers worldwide who underwent MI-LLS (laparoscopic and robotic) between 2004–2021. Thirty-nine were Western and 21 were Eastern centers. All centers performed a minimum annual volume of over 10 MLR per annum and 55 had a volume of over 20 MILR per annum. The centers provided unselected consecutive data of patients over a fixed time period. Of these, 1,526 MI-LLS were performed for primary liver malignancies (hepatocellular carcinoma, cholangiohepatoma, intrahepatic cholangiocarcinoma). All institutions obtained their respective approvals according to their local center’s requirements. This study was approved by the Singapore General Hospital Institution Review Board and the need for patient consent was waived. The de-identified data were collected in the individual centers. These were collated and analyzed centrally at the Singapore General Hospital.

Only patients who underwent totally laparoscopic or robotic liver resections were included. Hand-assisted or laparoscopic-assisted cases were excluded. Patients who underwent concomitant major operations such as bilio-enteric anastomoses, colectomies, stoma reversal, gastrectomies, splenectomies and vascular resections were excluded. Notably, patients who underwent concomitant minor operations such as hernia repair, local ablation and hilar lymph node dissection were included. Patients who had history of previous liver resection or underwent MILR with concomitant other liver resections were also excluded. 1370 cases were included in the final study group.

A list of pre-operative clinicopathological data for which patients were matched for can be found in Tables 1 to 5. Of note, baseline difficulty of MI-LLS was matched across study groups based on the Iwate scoring system. Important peri- and post-operative parameters compared include operative time, estimated blood loss, transfusion requirement, use of Pringle maneuver, conversion rate, length of hospital stay, Clavien-Dindo complications, re-operation rate and peri-operative mortality.

Table 1.

Comparison between baseline characteristics of MI-LLS in Child-Pugh A cirrhosis vs non-cirrhosis

Entire unmatched cohort 1:1 PSM (nearest neighbor matching)
 1:1 CE M
All (N = 1312) Childs A Cirrhosis (N = 753) Non-cirrhosis (N = 559) P-value Childs A Cirrhosis (N = 396) Non-cirrhosis (N = 396) P-value (paired) Childs A Cirrhosis (N = 128) Non-cirrhosis (N = 128) P-value (paired)
Median age, yrs [IQR] 63.76 [55.00, 71.91] 63.00 [55.00, 70.00] 65.00 [55.00, 73.00] 0.033 62.95 [55.00, 70.00] 64.00 [54.00, 72.00] 0.788 63.00 [55.75, 68.00] 61.65 [55.75, 68.00] 0.294
Male sex, n (%) 984 (75.0) 577 (76.6) 407 (72.8) 0.130 301 (76.0) 306 (77.3) 0.731 116 (90.6) 116 (90.6) NA
BMI 24.32 [22.00, 27.20] 24.30 [21.98, 27.50] 24.39 [22.19, 26.90] 0.619 24.30 [22.00, 27.69] 24.12 [22.12, 26.87] 0.175 23.88 [21.72, 26.72] 24.01 [22.18, 27.02] 0.415
Robotic, n (%)
Laparoscopic, n (%)		 177 (13.5)
1135 (86.5)		 96 (12.7)
657 (87.3)		 81 (14.5)
478 (85.5)		 0.406 54 (13.6)
342 (86.4)		 57 (14.4)
339 (85.6)		 0.841 9 (7.0)
119 (93.0)		 9 (7.0)
119 (93.0)		 NA
Previous abdominal surgery, n (%) 204 (16.1) 105 (14.7) 99 (17.8) 0.157 67 (16.9) 63 (15.9) 0.775 6 (4.7) 6 (4.7) NA
Year of surgery, n (%)
2004–2009
2010–2015
2016–2021		 86 (6.6)
416
(31.7) 810
(61.7)		 49 (6.5)
260 (34.5)
444 (59.0)		 37 (6.6)
156 (27.9)
366 (65.5)		 0.036 28 (7.1)
120 (30.3)
248 (62.6)		 26 (6.6)
118 (29.8)
252 (63.6)		 0.957 3 (2.3)
35 (27.3)
90 (70.3)		 3 (2.3)
35
(27.3) 90
(70.3)		 NA
ASA score, n (%)
 1/2
 3/4		 937 (71.5) 374
(28.5)		 542 (72.1)
210 (27.9)		 395 (70.7)
164 (29.3)		 0.618 281 (71.0)
115 (29.0)		 279 (70.5)
117 (29.5)		 0.938 106 (82.8)
22 (17.2)		 106 (82.8)
22 (17.2)		 NA
Tumor type, n (%)
 HCC
 ICC/ cholangiohepatoma		 1121 (85.8) 685 (91.0)
68 (9.0)		 436 (78.8)
117 (21.2)		 <0.001 355 (89.6)
41 (10.4)		 352 (88.9)
44 (11.1)		 0.770 127 (99.2)
1 (0.8)		 127 (99.2)
1 (0.8)		 NA
185 (14.2)
Median tumor size, mm [IQR] 35.00 [24.00, 52.75] 30.00 [22.00, 47.00] 40.00 [28.00, 60.00] <0.001 34.50 [25.00, 53.25] 35.00 [24.75, 50.00] 0.324 30.00 [21.00, 40.00] 30.00 [25.00, 40.75] 0.099
Multiple tumors, n (%) 168 (12.8) 108 (14.3) 60 (10.8) 0.066 36 (9.1) 42 (10.6) 0.556 1 (0.8) 1 (0.8) NA
Concomitant minor surgery excluding cholecystectomy, n (%) 26 (2.0) 15 (2.0) 11 (2.0) 1.000 8 (2.0) 9 (2.3) 1.000 1 (0.8) 1 (0.8) NA
Hilar lymph node dissection, n (%) 35 (2.7) 13 (1.7) 22 (3.9) 0.022 10 (2.5) 13 (3.3) 0.677 0 (0.0) 0 (0.0) NA
Median Iwate difficulty score, [IQR](range) 5.00 [4.00, 5.00] (2,8) 5.00 [4.00, 5.00] (2,8) 5.00 [4.00, 5.00] (3,8) <0.001 5.00 [4.00, 5.00] (3,8) 5.00 [4.00, 5.00] (3,8) 0.235 5.00 [4.00, 5.00] (3,6) 5.00 [4.00, 5.00] (3,6) NA
Iwate difficulty, n (%)
 Intermediate
 High
 Expert		 107 (8.2)
1191 (90.8)
14 (1.1)		 73 (9.7)
673 (89.4)
7 (0.9)		 34 (6.1)
518 (92.7)
7 (1.3)		 0.054 27 (6.8)
365 (92.2)
4 (1.0)		 32 (8.1)
361 (91.2)
3 (0.8)		 0.718 10 (7.8)
118 (92.2)
0 (0.0)		 10 (7.8)
118 (92.2)
0 (0.0)		 NA
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MI-LLS: minimally invasive left lateral sectionectomy; PSM: propensity score matching; CEM: coarsened exact matching; BMI: body mass index; ASA score: American Society of Anesthesiologists score; HCC: hepatocellular carcinoma; ICC: intrahepatic cholangiocarcinoma; IQR, interquartile range; NA, not applicable

Bold p-value: P<0.05

Table 5.

Comparison between baseline characteristics of MI-LLS in cirrhosis patients with and without PHT

Entire unmatched cohort 1:1 PSM (nearest neighbor matching) 1:1 CEM
All (N = 800) Cirrhosis PHT (N = 630) Cirrhosis No PHT (N = 170) Pvalue Cirrhosis PHT (N = 130) Cirrhosis No PHT (N = 130) Pvalue Cirrhosis PHT (N = 73) Cirrhosis No PHT (N = 73) P-value (paired)
Mean age, yrs [IQR] 62.65 [54.00, 70.00] 63.00 [55.25, 70.00] 62.00 [54.00, 70.00] 0.692 62.45 [55.00, 69.75] 61.00 [54.00, 67.75] 0.463 62.90 [55.00, 70.00] 61.00 [55.00, 67.00] 0.341
Male sex, n (%) 606 (75.8) 130 (76.5) 476 (75.6) 0.884 100 (76.9) 103 (79.2) 0.755 64 (87.7) 64 (87.7) NA
BMI 24.27 [21.95, 27.30] 24.42 [21.84, 27.70] 24.22 [21.97, 27.20] 0.864 24.11 [21.51, 27.42] 24.24 [21.45, 27.10] 0.686 24.76 (4.39) 24.28 (3.56) 0.448
Robotic, n (%) Laparoscopic, n (%) 107 (13.4) 693 (86.6) 23 (13.5) 147 (86.5) 84 (13.3) 546 (86.7) 1 19 (14.6) 111 (85.4) 16 (12.3) 114 (87.7) 0.710 4 (5.5) 69 (94.5) 4 (5.5) 69 (94.5) NA
Previous abdominal surgery, n (%) 108 (14.2) 25 (14.7) 83 (14.0) 0.926 20 (15.4) 14 (10.8) 0.391 5 (6.8) 5 (6.8) NA
Childs A, n (%) Childs B, n (%) 742 (92.8) 58 (7.2) 142 (83.5) 28 (16.5) 600 (95.2) 30 (4.8) 0.926 118 (90.8) 12 (9.2) 113 (86.9) 17 (13.1) 0.383 73 (100.0) 0 (0.0) 73 (100.0) 0 (0.0) NA
Year of surgery, n (%)
2004–2009
2010–2015
2016–2021		 49 (6.1)
269 (33.6)
482 (60.2)		 10 (5.9)
59 (34.7)
101 (59.4)		 39 (6.2)
210 (33.3)
381 (60.5)		 0.941 8 (6.2)
46 (35.4)
76 (58.5)		 9 (6.9)
47 (36.2)
74 (56.9)		 0.909 4 (5.5)
25 (34.2)
44 (60.3)		 4 (5.5)
25 (34.2)
44 (60.3)		 NA
ASA score, n (%)
 1/2
 3/4		 575 (72.0) 104 (61.2)
66 (38.8)		 471 (74.9)
158 (25.1)		 0.001 90 (69.2)
40 (30.8)		 81 (62.3)
49 (37.7)		 0.298 51 (69.9)
22 (30.1)		 51 (69.9)
22 (30.1)		 NA
224 (28.0)
Tumor type, n (%)
HCC
ICC/ cholangiohepatoma		 729 (91.1)
71 (8.9)		 160 (94.1)
10 (5.9)		 569 (90.3)
61 (9.7)		 0.163 122 (93.8)
8 (6.2)		 120 (92.3)
10 (7.7)		 0.814 73 (100.0)
0 (0.0)		 73 (100.0)
0 (0.0)		 NA
Median tumor size, mm [IQR] 30.00 [22.00, 49.00] 30.00 [22.00, 50.00] 30.00 [22.00, 48.00] 0.887 30.00 [21.00, 43.75] 30.00 [20.00, 45.00] 0.638 30.00 [20.00, 39.00] 30.00 [20.00, 38.00] 0.825
Multiple tumors, n (%) 115 (14.4) 24 (14.1) 91 (14.4) 1 19 (14.6) 19 (14.6) 1.000 5 (6.8) 5 (6.8) NA
Concomitant minor surgery excluding cholecystectomy, n (%) 15 (1.9) 1 (0.6) 14 (2.2) 0.214 1 (0.8) 1 (0.8) 1.000 0 (0.0) 0 (0.0) NA
Hilar lymph node dissection, n (%) 13 (1.6) 3 (1.8) 10 (1.6) 0.744 1 (0.8) 3 (2.3) 0.617 0 (0.0) 0 (0.0) NA
Median Iwate difficulty score, [IQR] (range) 5.00 [4.00, 5.00](2,8) 5.00 [4.00, 5.00] (2,8) 5.00 [4.00, 5.00] (3,7) 0.877 5.00 [4.00, 5.00] (3,7) 5.00 [4.00, 5.00] (3,7) 0.715 5.00 [4.00, 5.00] (3,6) 5.00 [4.00, 5.00] (3,6) NA
Iwate difficulty, n (%)
 Intermediate
 High
 Expert		 72 (9.0)
714 (89.2)
14 (1.8)		 17 (10.0)
149 (87.6)
4 (2.4)		 55 (8.7)
565 (89.7)
10 (1.6)		 0.687 14 (10.8)
114 (87.7)
2 (1.5)		 12 (9.2)
115 (88.5)
3 (2.3)		 NA 6 (8.2)
67 (91.8)
0 (0.0)		 6 (8.2)
67 (91.8)
0 (0.0)		 NA
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MI-LLS: minimally invasive left lateral sectionectomy; PHT: portal hypertension; PSM: propensity score matching; CEM: coarsened exact matching; IPTW: inverse probability of treatment weighting; BMI: body mass index; ASA score: American Society of Anesthesiologists score; HCC: hepatocellular carcinoma; ICC: intrahepatic cholangiocarcinoma; IQR, interquartile range; NA, not applicable

Bold p-value: P<0.05

Definitions

LLS was defined according to the 2000 Brisbane classification as anatomic resection of segments 2 and 3 (25). Diameter of the largest lesion was used in the cases of multiple tumors. Difficulty of LLS resections were graded according to the Iwate score. Clinically significant PHT was defined based on radiological and clinical criteria such as the presence of ascites, esophageal varices or splenomegaly with a platelet count of less than 100,000/μL (portal venous pressure/hepatic venous pressure gradient was not routinely measured in most centers). Post-operative complications were stratified according to the Clavien-Dindo classification and recorded for up to 30 days or during the same hospitalization including 30-day readmissions (26).

Statistical analyses

Propensity score matching (PSM) and Coarsened Exact Matching (CEM) were used to estimate the effect of varying degrees of liver cirrhosis on MI-LLS. For PSM, the propensity score was estimated with logistic regression with a mixed effect model. The factors used in calculating the propensity score are the baseline variables stated in Tables 1, 3 and 5, respectively. A random effects parameter was also included in the model to account for between-center variation. For PSM comparison of CTP A cirrhotic against non-cirrhotic liver in Tables 1 and 2, patients of one stratum were matched 1:1, using nearest neighbor matching without replacement or discard, utilizing logit link, to patients of the other strata. To improve matching, a small caliper was used to achieve good balance of < 0.1 across all variables after matching. During matching, any patient with missing data in any of the variables used for matching was discarded. Similar methodology was employed for PSM comparison in Tables 3 to 6, comparing CTP A to B, and cirrhosis with and without PHT.

Table 3.

Comparison between baseline characteristics of MI-LLS in Child-Pugh A vs Child-Pugh B cirrhosis

Entire unmatched cohort 1:1 PSM (nearest neighbor matching) 1:1 CEM
All (N = 811) Child A (N = 753) Child B (N = 58) P-value Child A (N = 49) Child B (N = 49) P-value (paired) Child A (N = 46) Child B (N = 46) P-value (paired)
Mean age, yrs [IQR] 62.80 [54.00, 70.00] 63.00 [55.00, 70.00] 53.50 [47.00, 66.75] <0.001 58.00 [49.00, 65.00] 54.00 [47.00, 67.00] 0.719 64.00 [56.50, 71.00] 53.00 [47.00, 64.50] 0.003
Male sex, n (%) 615 (75.8) 577 (76.6) 38 (65.5) 0.081 39 (79.6) 35 (71.4) 0.289 33 (71.7) 33 (71.7) NA
BMI 24.28 [21.93, 27.34] 24.30 [21.98, 27.50] 23.90 [20.98, 26.60] 0.180 23.11 [20.90, 25.61] 23.95 [21.19, 26.98] 0.230 23.80 [21.89, 26.34] 23.73 [21.26, 26.20] 0.898
Robotic, n (%) Laparoscopic, n (%) 107 (13.2) 704 (86.8) 96 (12.7) 657 (87.3) 11 (19.0) 47 (81.0) 0.252 10 (20.4) 39 (79.6) 10 (20.4) 39 (79.6) 1.000 5 (10.9) 41 (89.1) 5 (10.9) 41 (89.1) NA
Previous abdominal surgery, n (%) 112 (14.5) 105 (14.7) 7 (12.1) 0.723 3 (6.1) 6 (12.2) 0.450 3 (6.5) 3 (6.5) NA
Year of surgery, n (%)
2004–2009
2010–2015
2016–2021		 49 (6.0)
275 (33.9)
487 (60.0)		 49 (6.5)
260 (34.5)
444 (59.0)		 0 (0.0)
15 (25.9)
43 (74.1)		 0.023 0 (0.0)
8 (16.3)
41 (83.7)		 0 (0.0)
9 (18.4)
40 (81.6)		 1.000 0 (0.0)
13 (28.3)
33 (71.7)		 0 (0.0)
13 (28.3)
33 (71.7)		 NA
ASA score, n (%)
 1/2
 3/4		 579 (71.5)
231 (28.5)		 542 (72.1)
210 (27.9)		 37 (63.8)
21 (36.2)		 0.232 36 (73.5)
13 (26.5)		 32 (65.3)
17 (34.7)		 0.343 32 (69.6)
14 (30.4)		 32 (69.6)
14 (30.4)		 NA
Tumor type, n (%)
 HCC
 ICC/ cholangiohepatoma		 739 (91.1)
72 (8.9)		 685 (91.0)
68 (9.0)		 54 (93.1)
4 (6.9)		 0.810 46 (93.9)
3 (6.1)		 46 (93.9)
3 (6.1)		 1.000 45 (97.8)
1 (2.2)		 45 (97.8)
1 (2.2)		 NA
Median tumor size, mm [IQR) 30.00 [22.00, 50.00] 30.00 [22.00, 47.00] 35.00 [30.00, 53.75] 0.06 35.00 [30.00, 50.00] 31.00 [28.00, 55.00] 0.623 30.50 [24.00, 44.00] 32.00 [30.00, 50.00] 0.422
Multiple tumors, n (%) 117 (14.4) 108 (14.3) 9 (15.5) 0.959 9 (18.4) 8 (16.3) 1.000 5 (10.9) 5 (10.9) NA
Concomitant minor surgery excluding cholecystectomy, n (%) 15 (1.8) 15 (2.0) 0 (0.0) 0.617 0 (0.0) 0 (0.0) NA 0 (0.0) 0 (0.0) NA
Hilar lymph node dissection, n (%) 14 (1.7) 13 (1.7) 1 (1.7) 1.000 0 (0.0) 1 (2.0) 1.000 0 (0.0) 0 (0.0) NA
Median Iwate difficulty score excluding Childs score, [IQR] (range) 5.00 [4.00, 5.00] (2,8) 5.00 [4.00, 5.00] (2,8) 5.00 [4.00, 5.00] (3,7) 0.134 5.00 [4.00, 5.00] (3,7) 5.00 [4.00, 5.00] (3,7) 0.903 5.00 [4.00, 5.00] (3,8) 5.00 [5.00, 5.00] (3,7) 0.260
Iwate difficulty exclude Childs score, n (%)
 Intermediate
 High
 Expert		 77 (9.5)
726 (89.5)
8 (1.0)		 73 (9.7)
673 (89.4)
7 (0.9)		 4 (6.9)
53 (91.4)
1 (1.7)		 0.464 3 (6.1)
45 (91.8)
1 (2.0)		 4 (8.2)
44 (89.8)
1 (2.0)		 NA 1 (2.2)
44 (95.7)
1 (2.2)		 1 (2.2)
44 (95.7)
1 (2.2)		 NA
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MI-LLS: minimally invasive left lateral sectionectomy; PSM: propensity score matching; CEM: coarsened exact matching; IPTW: inverse probability of treatment weighting; BMI: body mass index; ASA score: American Society of Anesthesiologists score; HCC: hepatocellular carcinoma; ICC: intrahepatic cholangiocarcinoma; IQR, interquartile range; NA, not applicable

Table 2.

Comparison between perioperative outcomes of MI-LLS in Child-Pugh A cirrhosis vs non-cirrhosis

Entire unmatched cohort 1:1 PSM (nearest neighbor matching) 1:1 CEM
All (N = 1312) Childs A Cirrhosis (N = 753) Non-cirrhosis (N = 559) P-value Childs A Cirrhosis (N = 396) Non-cirrhosis (N = 396) P-value (paired) Childs A Cirrhosis (N = 128) Non-cirrhosis (N = 128) P-value (paired)
Open conversion, n (%) 43 (3.3) 27 (3.6) 16 (2.9) 0.568 14 (3.5) 8 (2.0) 0.286 6 (4.7) 2 (1.6) 0.289
Median operating time, min [IQR] 170.00 [120.00, 230.00] 180.00 [120.00, 240.00] 158.50 [105.00, 210.00] <0.001 179.50 [120.00, 240.00] 156.00 [100.00, 210.00] 0.004 174.50 [110.00, 230.00] 155.00 [90.00, 210.00] 0.421
Median blood loss, ml [IQR] 100.00 [50.00, 200.00] 100.00 [50.00, 200.00] 100.00 [50.00, 200.00] 0.139 100.00 [50.00, 200.00] 100.00 [40.00, 159.50] 0.003 100.00 [50.00, 200.00] 50.00 [20.00, 145.00] 0.041
Blood loss > 500 mls, n (%) 69 (5.5) 40 (5.6) 29 (5.5) 1.000 21 (5.5) 15 (4.0) 0.186 11 (8.7) 5 (4.1) 0.267
Intraoperative blood transfusion, n (%) 49 (3.7) 31 (4.1) 18 (3.2) 0.484 13 (3.3) 9 (2.3) 0.522 8 (6.2) 0 (0.0) 0.013
Pringle maneuver applied, n (%) 245 (18.9) 134 (18.0) 111 (20.1) 0.369 85 (21.7) 67 (17.1) 0.093 26 (20.3) 21 (16.8) 0.532
Median postoperative stay, d [IQR], 5.00 [4.00, 7.00] 5.00 [4.00, 7.00] 5.00 [4.00, 7.00] 0.003 5.00 [4.00, 7.00] 5.00 [4.00, 7.00] 0.026 5.00 [4.00, 7.00] 5.00 [4.00, 7.00] 0.651
Postoperative morbidity, n (%) 176 (13.4) 105 (13.9) 71 (12.7) 0.568 54 (13.6) 43 (10.9) 0.284 11 (8.6) 9 (7.0) 0.823
Major morbidity (Clavien-Dindo grade> 2), n (%) 32 (2.4) 18 (2.4) 14 (2.5) 1.000 9 (2.3) 9 (2.3) 1.000 0 (0.0) 1 (0.8) 1.000
Reoperation, n (%) 11 (0.8) 4 (0.5) 7 (1.3) 0.221 3 (0.8) 5 (1.3) 0.724 0 (0.0) 0 (0.0) NA
30-day readmission, n (%) 27 (2.1) 14 (1.9) 13 (2.3) 0.704 9 (2.3) 6 (1.5) 0.606 3 (2.4) 0 (0.0) 0.248
30-day mortality, n (%) 3 (0.2) 0 (0.0) 3 (0.5) 0.077 0 (0.0) 3 (0.8) 0.248 0 (0.0) 0 (0.0) NA
In-hospital mortality, n (%) 4 (0.3) 0 (0.0) 4 (0.7) 0.033 0 (0.0) 3 (0.8) 0.248 0 (0.0) 0 (0.0) NA
90-day mortality, n (%) 9 (0.7) 3 (0.4) 6 (1.1) 0.182 1 (0.3) 4 (1.0) 0.371 0 (0.0) 0 (0.0) NA
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MI-LLS: minimally invasive left lateral sectionectomy; PSM: propensity score matching; CEM: coarsened exact matching; IQR, interquartile rangeBold p-value: P<0.05

Table 6.

Comparison between perioperative outcomes of MI-LLS in cirrhosis patients with and without PHT

Entire unmatched cohort 1:1 PSM (nearest neighbor matching) 1:1 CEM
All (N = 800) Cirrhosis PHT (N = 630) Cirrhosis NPHT (N = 170) P-value Cirrhosis PHT (N = 130) Cirrhosis NPHT (N = 130) P-value Cirrhosis PHT (N = 73) Cirrhosis NPHT (N = 73) P-value (paired)
Open conversion, n (%) 28 (3.5) 10 (5.9) 18 (2.9) 0.095 7 (5.4) 1 (0.8) 0.077 2 (2.7) 2 (2.7) 1.000
Median operating time, min [IQR] 180.00 [120.00, 239.00] 177.00 [120.00, 240.00] 180.00 [120.00, 239.00] 0.624 180.00 [120.00, 240.00] 168.00 [125.00, 210.00] 0.386 165.00 [119.00, 210.00] 170.00 [133.00, 219.00] 0.752
Median blood loss, ml [IQR] 100.00 [50.00, 200.00] 100.00 [50.00, 300.00] 100.00 [50.00, 200.00] 0.002 100.00 [50.00, 300.00] 100.00 [50.00, 200.00] 0.194 100.00 [50.00, 200.00] 50.00 [45.00, 150.00] 0.276
Blood loss > 500 mls, n (%) 42 (5.5) 17 (10.4) 25 (4.2) 0.003 12 (9.4) 8 (6.3) 0.646 5 (7.1) 3 (4.5) 0.724
Intraoperative blood transfusion, n (%) 36 (4.5) 14 (8.2) 22 (3.5) 0.015 9 (6.9) 3 (2.3) 0.149 6 (8.2) 1 (1.4) 0.074
Pringle maneuver applied, n (%) 151 (19.1) 47 (27.8) 104 (16.7) 0.002 30 (23.1) 22 (17.2) 0.349 12 (16.7) 10 (13.9) 0.823
Median postoperative stay, d [IQR] 5.85 [4.00, 8.00] 5.00 [4.00, 8.00] 6.00 [4.00, 8.00] 0.911 5.00 [4.00, 8.00] 5.00 [4.00, 8.00] 0.558 5.00 [4.00, 6.00] 5.00 [4.00, 7.00] 0.356
Postoperative morbidity, n (%) 113 (14.1) 31 (18.2) 82 (13.0) 0.107 21 (16.2) 15 (11.5) 0.405 9 (12.3) 7 (9.6) 0.789
Major morbidity (Clavien-Dindo grade> 2), n (%) 19 (2.4) 3 (1.8) 16 (2.5) 0.778 2 (1.5) 3 (2.3) 1.000 1 (1.4) 2 (2.7) 1.000
Reoperation, n (%) 5 (0.6) 2 (1.2) 3 (0.5) 0.288 1 (0.8) 0 (0.0) 1.000 1 (1.4) 1 (1.4) 1.000
30-day readmission, n (%) 16 (2.0) 4 (2.4) 12 (1.9) 0.757 3 (2.3) 3 (2.3) 1.000 2 (2.8) 2 (2.8) 1.000
30-day mortality, n (%) 1 (0.1) 1 (0.6) 0 (0.0) 0.213 0 (0.0) 0 (0.0) NA 0 (0.0) 0 (0.0) NA
In-hospital mortality, n (%) 1 (0.1) 1 (0.6) 0 (0.0) 0.213 0 (0.0) 0 (0.0) NA 0 (0.0) 0 (0.0) NA
90-day mortality, n (%) 4 (0.5) 2 (1.2) 2 (0.3) 0.2 1 (0.8) 0 (0.0) 1.000 1 (1.4) 0 (0.0) 1.000
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IQR, interquartile range; NA, not applicable

Bold p-value: P<0.05

For CEM, continuous variables were coarsened using an automatic binning algorithm based on Sturge’s rule into bins. Patients were 1:1 matched using with nearest neighbor matching without replacement within each stratum, any unmatched units in the stratum were dropped. This methodology was applied to all 3 CEM models. After matching, balance was checked via standardized mean difference across the covariates, with a threshold of 0.1 being indicative of tight match. Love plot of each match’s covariate balance was plotted and presented below (Supplementary data S1–S6).

For unpaired comparisons of frequencies of categorical variables, Chi square test was used. For the unpaired comparisons of median values and interquartile ranges, Mann-Whitney U test, and for the comparisons of mean values and standard deviations, one-way test were used. For paired sample tests, McNemar’s test was employed for categorical variables and Wilcoxon Signed-Rank test for continuous variables. The statistical analyses were performed with RStudio version 1.4.1717, R version 4.1.0.

Results

A total of 1370 patients who underwent MI-LLS for primary liver malignances were included in the study. Eight-hundred and fifty-two cases (62.2%) were performed in Eastern and 518 (37.8%) were performed in Western centers. Of these, 559 (40.8%) patients had no cirrhosis and 811 (59.2%) patients had cirrhosis (753 CTP A; 58 CTP B). There was no significant difference in the proportion of cirrhotics amongst patients in Eastern [511/852 (60.0%)] compared to Western centers [299/518 (57.7%)] (P=0.410). Of the cirrhotic patients, 800 were evaluated for the presence of PHT and divided in 2 subgroups: with PHT (N=630) and without PHT (N=170). Eleven patients had missing information on PHT. A total of 2.4% (n=33) and 0.9% (n=12) of patients presented with major post-operative morbidity and mortality, respectively. 3.3% (n=45) of MI-LLS required conversion to open surgery, and the overall mortality rate was 0.7% (n=10).

Non-cirrhotic vs. CTP A cirrhotic patients

This study group comprised a total of 1312 patients with 753 in the CTP A group and 559 in the non-cirrhotic group. In the entire unmatched cohort, cirrhosis was associated with a lower median age (63.0 years [55.0–70.0] vs 65 years [55.0–73.0], P=0.033), a higher proportion of patients with hepatocellular carcinoma (91% vs. 78.8%, P<0.001), smaller tumors (30 mm [22–47] vs. 40 mm [28–60], P<0.001), lower frequency of hilar lymph node dissection (1.7% vs 3.9%, P=0.022), and higher median Iwate score (P<0.001) (Table 1). In the unmatched comparison, patients with CTP A cirrhosis had longer operative times (180.0 min [120.0–240.0] vs 158.5 min [105.0–210.0], P<0.001), postoperative stay (5.0 days [4.0–7.0] vs. 5.0 [4.0–7.0], P=0.003), and higher in-hospital mortality (0% vs. 0.7%, P=0.033) (Table 2).

PSM and CEM with 1:1 ratio resulted in 396 and 128 matched pairs, respectively. Both groups were well balanced in all baseline characteristics in both matched cohorts (Table 1). Cirrhotic patients presented with longer operative time after PSM (179.5 min [120.0–240.0] vs 156.0 min [100.0–210.0], P=0.004), but not in the CEM (174.5 min [110.0–230.0] vs 155.0 min [90.0–210.0], P=0.421) analysis. Cirrhosis was consistently associated with higher intraoperative blood loss (PSM: 100.0 ml [50.0–200.0] vs 100.0 ml [40.0–159.5], P=0.003; CEM: 100.0 ml [50.0–200.0] vs. 50.0 ml [20.0–145.0], P=0.041), and higher transfusion rates (CEM: 6.2% vs. 0%, P=0.013). Length of hospital stay was significantly longer in PSM analysis (5.0 days [4.0–7.0] vs. 5.0 days [4.0–7.0], P=0.026), but not in CEM analysis (5.0 days [4.0–7.0] vs 5.0 [4.0–7.0], P=0.651) (Table 2).

CTP A vs. CTP B patients

This study group comprised a total of 811 cirrhotic patients, with 753 in the CTP A group and 58 in the CTP B group. In the unmatched cohort, Child-Pugh B patients had a lower median age (53.50 [47.0–66.8] vs 63 years [55.0–70.0]; P<0.001) and a higher proportion of patients operated in the last 5 years (Table 3). In this unmatched comparison, patients in the CTP B group had the Pringle maneuver more frequently employed (31% vs 18%, P=0.024) and recorded longer durations of hospital stay (9.0 days [4.6–12.0] vs 5.0 days [4.0–7.0], P<0.001) (Table 4).

Table 4.

Comparison between perioperative outcomes of MI-LLS in Child-Pugh A vs Child-Pugh B cirrhosis

Entire unmatched cohort 1:1 PSM (nearest neighbor matching) 1:1 CEM
All (N = 811) Childs A (N = 753) Childs B (N = 58) P-value Childs A (N = 49) Childs B (N = 49) P-value (paired) Childs A (N = 46) Childs B (N = 46) P-value (paired)
Open conversion, n (%) 29 (3.6) 27 (3.6) 2 (3.4) 1.000 1 (2.0) 2 (4.1) 1.000 1 (2.2) 2 (4.3) 1.000
Median operating time, min [IQR] 180.00 [120.00, 238.25] 180.00 [120.00, 240.00] 177.50 [115.00, 210.00] 0.183 173.00 [120.00, 208.00] 170.00 [100.00, 210.00] 0.550 180.00 [144.50, 221.50] 180.00 [116.25, 210.00] 0.085
Median blood loss, ml [IQR] 100.00 [50.00, 200.00] 100.00 [50.00, 200.00] 100.00 [50.00, 300.00] 0.214 100.00 [50.00, 300.00] 100.00 [50.00, 300.00] 0.736 100.00 [21.25, 200.00] 100.00 [50.00, 300.00] 0.110
Blood loss > 500 mls, n (%) 43 (5.5) 40 (5.6) 3 (5.3) 1.000 7 (14.3) 3 (6.2) 0.289 1 (2.4) 3 (6.7) 0.617
Intraoperative blood transfusion, n (%) 36 (4.4) 31 (4.1) 5 (8.6) 0.172 5 (10.2) 4 (8.2) 1.000 0 (0.0) 5 (10.9) 0.074
Pringle maneuver applied, n (%) 152 (19.0) 134 (18.0) 18 (31.0) 0.024 9 (18.4) 17 (34.7) 0.136 13 (28.9) 15 (32.6) 0.814
Median postoperative stay, d (SD) 5.05 [4.00, 8.00] 5.00 [4.00, 7.00] 9.00 [4.60, 12.00] <0.001 7.00 [5.00, 10.00] 8.00 [4.00, 11.00] 0.210 5.00 [4.00, 7.00] 9.00 [6.00, 13.50] <0.001
Postoperative morbidity, n (%) 115 (14.2) 105 (13.9) 10 (17.2) 0.618 6 (12.2) 9 (18.4) 0.579 4 (8.7) 8 (17.4) 0.343
Major morbidity (Clavien- Dindo grade> 2), n (%) 19 (2.3) 18 (2.4) 1 (1.7) 1.000 0 (0.0) 1 (2.0) 1.000 0 (0.0) 1 (2.2) 1.000
Reoperation, n (%) 5 (0.6) 4 (0.5) 1 (1.7) 0.311 0 (0.0) 1 (2.0) 1.000 0 (0.0) 1 (2.2) 1.000
30-day readmission, n (%) 16 (2.0) 14 (1.9) 2 (3.4) 0.323 0 (0.0) 2 (4.1) 0.480 0 (0.0) 1 (2.2) 1.000
30-day mortality, n (%) 1 (0.1) 0 (0.0) 1 (1.7) 0.072 0 (0.0) 1 (2.0) 1.000 0 (0.0) 1 (2.2) 1.000
In-hospital mortality, n (%) 1 (0.1) 0 (0.0) 1 (1.7) 0.072 0 (0.0) 1 (2.0) 1.000 0 (0.0) 1 (2.2) 1.000
90-day mortality, n (%) 4 (0.5) 3 (0.4) 1 (1.7) 0.257 0 (0.0) 1 (2.0) 1.000 0 (0.0) 1 (2.2) 1.000
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MI-LLS: minimally invasive left lateral sectionectomy; PSM: propensity score matching; CEM: coarsened exact matching; IPTW: inverse probability of treatment weighting; IQR, interquartile range

Bold p-value: P<0.05

In the matched cohorts, PSM and CEM with 1:1 ratio resulted in 49 and 46 matched pairs, respectively. Both groups were well balanced in all baseline characteristics in the PSM matched cohort (Table 3). In CEM, only median age was different between the groups (Child-Pugh B: 53.0 years [47.0–64.5] vs Child-Pugh A: 64.0 years [56.5–71.0], P=0.003) (Table 3). All perioperative outcomes were similar between the groups, with the exception of a longer hospital stay in Child-Pugh B patients after CEM analysis (9.0 days [6.0–13.5] vs 5.0 days [4.0–7.0], P<0.001) (Table 4).

Cirrhotic patients with vs. without PHT

This study group comprised a total of 800 cirrhotic patients with 670 in the PHT group and 130 in the non-PHT group (Table 5). In the unmatched comparison, patients with PHT presented with higher estimated blood loss (100.0 ml [50.0–300.0] vs 100.0 ml [50.0–200.0], P=0.002), higher frequency of blood loss > 500 ml (10.4% vs 4.2%, P=0.003), and a higher transfusion rate (8.2% vs 3.5%, P=0.015). Additionally, Pringle maneuver was more frequently applied in patients with PHT (27.8% vs. 16.7%, P=0.002) (Table 6). PSM and CEM with 1:1 ratio resulted in 130 and 73 matched pairs, respectively. Both groups were well balanced in all baseline characteristics in the matched cohorts (Table 5). There were no differences in all the peri-operative outcomes analyzed (Table 6).

Discussion

To the best of our knowledge, this represents the first study specifically evaluating the impact of liver cirrhosis, severity of cirrhosis and PHT on the difficulty and perioperative outcomes of patients undergoing MI-LLS. Based on our data, the presence of liver cirrhosis (CTP A) did not increase the risk of conversion, but significantly increased operative time, blood loss and transfusion requirements in the matched cohorts. Additionally, the presence of cirrhosis was associated with longer duration of hospital stay. Notably, there was no significant difference between postoperative morbidity and major morbidity rates despite the poorer perioperative outcomes. This minimal impact on postoperative outcomes is likely due to the large future liver remnant after LLS.

LLS was the first minimally invasive anatomical liver resection performed and simultaneously reported by Azagra et al. (27) and Kaneko et al. (28) in 1996. Subsequently, multiple studies have demonstrated the advantages of MILR over open surgery in terms of decreased perioperative morbidity, blood loss, and length of stay (29,30). With its favourable anatomical location and predictable anatomy, MI-LLS has been proven to be a highly standardizable operation with a gentler-than-average learning curve (as opposed to other types of hepatectomies) (13, 31–34). For these reasons, MI-LLS is now considered as the gold-standard approach in most specialized liver surgery centers. (16, 35)

A plethora of well-powered studies have confirmed the safety and feasibility of MI-LLS over the past decade (7, 11, 36). Recent population-based studies and two randomized controlled trials have been published supporting the use of MI-LLS (37–40). In a recent meta-analysis, Macacari et al. (12) demonstrated that laparoscopic LLS was associated with less blood loss, lower transfusion rates and shorter hospital stay when compared to those undergoing open surgery in a study that included 3415 patients over 23 different studies. Subsequent studies that specifically comparing robotic and laparoscopic approaches to LLS found similar perioperative outcomes (41). Today, MI-LLS is categorized as a low to intermediate difficulty procedure according to most difficulty scoring systems for MILR (20–23, 42).

However, the impact of cirrhosis and its severity on the difficulty and outcomes of MILRs is controversial. Physiologic changes such as hardened parenchymal texture, raised portal pressure, hypoalbuminemia, ascites, coagulopathy, and thrombocytopenia commonly make liver resection more challeging in cirrhotic patients (43, 44). Notably, however, studies with small sample sizes did not show significant differences in outcomes comparing patients who underwent MILRs with and without cirrhosis (45, 46).

In contrast, a large recent multicenter PSM study reported worse outcomes in a cirrhotic cohort undergoing MILR (47), while Tong et al. (48) found a two-fold increase in risk of open conversion and post-operative complications in patients with cirrhosis undergoing MILR. Similarly, Goh et al.(18) found that MILRs in cirrhotic patients were associated with an increased open conversion rate, prolonged operative time, increased blood loss, increased transfusion rate, prolonged hospital stay and an overall increase in postoperative morbidity. Additionally, it was observed in this study that the differences in outcomes between MILR in cirrhotics vs. non-cirrhotics were more pronounced in patients undergoing more difficult resections. However, several of these studies were limited as these included MILR for various pathologies such as benign disease and metastases which are important confounding factors as these pathologies occurred much more frequently in the non-cirrhotic cohort compared to the cirrhotic cohort.

To date, there has been a woeful lack of high-quality evidence studying the effects of cirrhosis and PHT on the peri-operative outcomes of MI-LLS. The largest study to date comes as a recent multicentre study reporting on 2245 patients undergoing MI-LLS. Wang et. al. reports an overall open conversion rate of 2.8% with male gender, larger tumor size and clinically significant PHT identified as independently significant predictive factors on multivariate analysis. This study reported that the presence of cirrhosis had no significant association with risk of requiring open conversion (49). This data suggests that only advanced cirrhosis with PHT impacts the conversion risk of MI-LLS. Of note, this study failed to analyze other noteworthy peri-operative variables commonly associated with MILR including operative time, blood loss, use of Pringles maneuver, duration of hospital stay, morbidity and mortality.

Benefits of the minimally invasive approach for hepatectomy in patients with higher grades of cirrhosis (CTP B) were recently demonstrated in a multicentre study that showed lower blood loss, less morbidity and fewer major complications in the MILR cohort when compared to their open liver resection counterparts (50). Notably, this study found MILR to be associated with a significantly shorter median duration of post-operative hospital stay as compared to the open liver resection group (7.5 days vs. 18 days), with no differences in overall or disease-free survival. This study however, reported that patients with more advanced cirrhosis (CTP B9) or PHT presented with a significantly higher rate of post-operative morbidity. This study, unfortunately, failed to present subgroup analyses with regards to the type of hepatectomy performed (minor vs. technical major vs. traditional major) (50). While CTP B cirrhosis was associated with an increased difficulty in the Iwate score (20), other studies failed to report similar findings. Cipriani et al. (45) compared CTP A (n=100) and B (n=25) patients who underwent MILR due to hepatocellular carcinoma and found no differences in the perioperative outcomes. Our results showed that MI-LLS in CTP B patients is not associated with significant differences in peri-operative outcomes, except for a longer duration of hospital stay over CTP patients. This suggests that upon identification of cirrhotic patients at increased risk of undergoing liver resection, MI-LLS may be performed safely with similar outcomes in both CTP A and B patients in properly selected patients at experienced centers. With improved collaboration between surgeons and gastroenterologists, anaesthetic knowledge on intraoperative physiology in cirrhotics and the advent of sub-specialized nursing care, our study suggests that the intuitively increased morbidity associated with increasing levels of hepatic dysfunction can be effectively mitigated once these patients with compensated cirrhosis are identified pre-operatively.

PHT has been previously reported to be associated with increased intra-operative difficulty and poorer perioperative outcomes in patients undergoing MILR (45, 50). This is reflected in the abovementioned study by Wang et. al. that reported on the significantly increased risk of open conversion in patients with PHT undergoing MI-LLS (49). In our study PHT was not associated to higher conversion rate or poorer post-operative outcomes. Possible explanations for this could be the relatively low technical difficulty of LLS and the experience of the centers included in this study. Furthermore, the relatively large future liver remnant (FLR) associated with this procedure, likely resulted in minimal impact on the post-operative portal pressure and hepatic function. Moreover, improved patient selection and pre-operative screening allows surgeons to now be more cognizant of high-risk patients with limited physiological reserves who should be treated with a lower threshold for open conversion before the onset of clinically significant intra-operative deterioration that may affect the recovery course.

Our study presents with several limitations including its retrospective nature resulting in a higher likelihood for selection bias and confounding factors. Furthermore, as an international multicenter study, heterogeneity in surgical technique, perioperative management and healthcare systems between centers affords an additional layer of bias. Nonetheless, this represented “real world” data and increased the generalizability of our findings. Additionally, the long study period also raises concern regarding confounding factors of advancing surgical technology, anaesthetic knowledge and expertise and surgeon experience. Unsurprisingly, surgical training, equipment and protocol has evolved over the 17-year study period. Despite a large number of patients being included in this study, subgroups like CTP B cirrhosis had a small sample size after matching, which increase the risk of type 1 and type 2 errors. Despite the aforementioned limitations, the restriction of our study group to a highly focused subset of hepatectomies (LLS) only in patients with primary liver malignancies allows our study to analyze the impact of liver cirrhosis on perioperative outcomes of MILR more precisely and reduce the impact of confounding factors. This is unlike previous studies which included patients undergoing various types of MILR with different pathologies. PSM and CEM also allowed us to reduce the reduce the impact of confounding biases. Lastly, it must be added that there is no internationally recognized standard method for measuring blood loss and its scientific validity is limited. However, the transfusion rate was found to be significantly higher in cirrhotics after 1:1 CEM supporting the clinical significance of these findings.

Conclusion

The increased technical difficulties associated with MI-LLS in patients with cirrhosis is evidenced by their significantly increased blood loss, higher transfusion rate and longer post-operative stay compared to patients without cirrhosis. Hence, the presence of cirrhosis should be included in future difficulty scoring systems. This information would also be important for new surgeons embarking on MILR and for future auditing and benchmarking of MILR.

Supplementary Material

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Funding/Support:

Dr T. P. Kingham was partially supported by the US National Cancer Institute MSKCC Core Grant number P30 CA008747 for this study

Dr M. Yin was partially funded by the Research Project of Zhejiang Provincial Public Welfare Fund project in the Field of Social development (LGF20H160028)

Dr Brian Goh was partially supported by a grant from Intuitive Foundation for this study. All research findings, conclusions or recommendations expressed in this work are those of the authors and not of the Intuitive Foundation.

Conflict of Interest/Disclosure:

We confirm all the authors are accountable for all aspects of the work and we report the following disclosures:

i) Goh BK has received travel grants and honorarium from Johnson and Johnson, Olympus and Transmedic the local distributor for the Da Vinci Robot.

ii) Marino MV is a consultant for CAVA robotics LLC.

iii) Fretland A reports receiving speaker fees from Bayer.

iv) Pratschke J reports a research grant from Intuitive Surgical Deutschland GmbH and personal fees or non-financial support from Johnson & Johnson, Medtronic, AFS Medical, Astellas, CHG Meridian, Chiesi, Falk Foundation, La Fource Group, Merck, Neovii, NOGGO, pharma-consult Peterson, and Promedicis.

v) Rotellar F reports speaker fees and support outside the submitted work from Integra, Medtronic, Olympus, Corza, Sirtex and Johnson & Johnson.

vi) Schmelzle M reports personal fees or other support outside of the submitted work from Merck, Bayer, ERBE, Amgen, Johnson & Johnson, Takeda, Olympus, Medtronic, Intuitive.

vii) Troisi RI reports speaker fees and support outside the submitted work from Integra, Stryker, Medtronic, Medistim, MSD.

International robotic and laparoscopic liver resection study group investigators

  1. Nicholas L. Syn (Yong Loo Lin School of Medicine, National University of Singapore and Ministry of Health Holdings Singapore)

  2. Mikel Prieto (Hepatobiliary Surgery and Liver Transplantation Unit, Biocruces Bizkaia Health Research Institute, Cruces University Hospital, University of the Basque Country, Bilbao, Spain)

  3. Juul Meurs (Department of Digestive and Hepatobiliary/Pancreatic Surgery, Groeninge Hospital, Kortrijk, Belgium)

  4. Celine De Meyere (Department of Digestive and Hepatobiliary/Pancreatic Surgery, Groeninge Hospital, Kortrijk, Belgium)

  5. Kit-Fai Lee (Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Prince of Wales Hospital, The Chinese University of Hong Kong, New Territories, Hong Kong SAR, China)

  6. Diana Salimgereeva (Department of Hepato-Pancreato-Biliary Surgery, Moscow Clinical Scientific Center, Moscow, Russia)

  7. Ruslan Alikhanov (Department of Hepato-Pancreato-Biliary Surgery, Moscow Clinical Scientific Center, Moscow, Russia)

  8. Nita Thiruchelvam (Hepatopancreatobiliary Unit, Department of Surgery, Changi General Hospital, Singapore)

  9. Jae-Young Jang (Department of General Surgery, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Korea)

  10. Yutaro Kato (Department of Surgery, Fujita Health University School of Medicine, Aichi, Japan)

  11. Masayuki Kojima (Department of Surgery, Fujita Health University School of Medicine, Aichi, Japan)

  12. Victor Lopez-Lopez (Department of General, Visceral and Transplantation Surgery, Clinic and University Hospital Virgen de la Arrixaca, IMIB-ARRIXACA, El Palmar, Murcia, Spain)

  13. Margarida Casellas I Robert (Hepatobiliary and Pancreatic Surgery Unit, Department of Surgery, Dr. Josep Trueta Hospital, IdIBGi, Girona, Spain)

  14. Roberto Montalti (Department of Clinical Medicine and Surgery, Division of HPB, Minimally Invasive and Robotic Surgery, Federico II University Hospital Naples, Naples, Italy)

  15. Mariano Giglio (Department of Clinical Medicine and Surgery, Division of HPB, Minimally Invasive and Robotic Surgery, Federico II University Hospital Naples, Naples, Italy)

  16. Boram Lee (Department of Surgery, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seoul, Korea)

  17. Mizelle D’Silva (Department of Surgery, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seoul, Korea)

  18. Hao-Ping Wang Department of Surgery, Chang Gung Memorial Hospital, Kaohsiung

  19. Mansour Saleh (Department of Hepatobiliary Surgery, Assistance Publique Hopitaux de Paris, Centre Hepato-Biliaire, Paul-Brousse Hospital, Villejuif, France)

  20. Franco Pascual (Department of Hepatobiliary Surgery, Assistance Publique Hopitaux de Paris, Centre Hepato-Biliaire, Paul-Brousse Hospital, Villejuif, France)

  21. Simone Vani (Hepatobiliary Surgery Unit, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Catholic University of the Sacred Heart, Rome, Italy)

  22. Francesco Ardito, (Hepatobiliary Surgery Unit, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Catholic University of the Sacred Heart, Rome, Italy)

  23. Ugo Giustizieri (HPB Surgery, Hepatology and Liver Transplantation, Fondazione IRCCS Istituto Nazionale Tumori di Milano, Milan, Italy)

  24. Davide Citterio (HPB Surgery, Hepatology and Liver Transplantation, Fondazione IRCCS Istituto Nazionale Tumori di Milano, Milan, Italy)

  25. Federico Mocchegiani (HPB Surgery and Transplantation Unit, United Hospital of Ancona, Department of Experimental and Clinical Medicine Polytechnic University of Marche)

  26. Giammauro Berardi (Division of General Surgery and Liver Transplantation, S. Camillo Forlanini Hospital, Rome, Italy)

  27. Marco Colasanti (Division of General Surgery and Liver Transplantation, S. Camillo Forlanini Hospital, Rome, Italy)

  28. Yoelimar Guzmán (General & Digestive Surgery, Hospital Clínic, Barcelona, Spain)

  29. Kevin P. Labadie (Department of Surgery, University of Washington Medical Center. Seattle, USA)

  30. Maria Conticchio (Unit of Hepato-Pancreatc-Biliary Surgery, “F. Miulli” General Regional Hospital, Acquaviva delle Fonti, Bari, Italy)

  31. Epameinondas Dogeas (Department of Surgery, Division of Hepatobiliary and Pancreatic Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA, USA)

  32. Emanuele F. Kauffmann (Division of General and Transplant Surgery, University of Pisa, Pisa, Italy)

  33. Mario Giuffrida (Hepatobiliary Surgery Unit, Department of Medicine and Surgery, University of Parma, Parma, Italy)

  34. Daniele Sommacale (Department of Digestive and Hepatobiliary and Pancreatic Surgery, AP-HP, Henri-Mondor Hospital, Creteil, France)

  35. Alexis Laurent, (Department of Digestive and Hepatobiliary and Pancreatic Surgery, AP-HP, Henri-Mondor Hospital, Creteil, France)

  36. Paolo Magistri (HPB Surgery and Liver Transplant Unit, University of Modena and Reggio Emilia, Modena, Italy)

  37. Kohei Mishima (Center for Advanced Treatment of Hepatobiliary and Pancreatic Diseases, Ageo Central General Hospital, Saitama, Japan)

  38. Moritz Schmelzle (Department of Surgery, Campus Charité Mitte and Campus Virchow-Klinikum, Charité-Universitätsmedizin, Corporate Member of Freie Universität Berlin, and Berlin Institute of Health, Berlin, Germany)

  39. Felix Krenzien (Department of Surgery, Campus Charité Mitte and Campus Virchow-Klinikum, Charité-Universitätsmedizin, Corporate Member of Freie Universität Berlin, and Berlin Institute of Health, Berlin, Germany)

  40. Prashant Kadam (Department of Hepatopancreatobiliary and Liver Transplant Surgery, University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom)

  41. Eric C. Lai (Department of Surgery, Pamela Youde Nethersole Eastern Hospital, Hong Kong SAR, China)

  42. Jacob Ghotbi (The Intervention Centre and Department of HPB Surgery, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway)

  43. Åsmund Avdem Fretland (The Intervention Centre and Department of HPB Surgery, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway)

  44. Fabio Forchino (Department of General and Oncological Surgery. Mauriziano Hospital, Turin, Italy)

  45. Alessandro Mazzotta (Department of Digestive, Oncologic and Metabolic Surgery, Institute Mutualiste Montsouris, Universite Paris Descartes, Paris, France)

  46. Francois Cauchy (Department of HPB Surgery and Liver Transplantation, Beaujon Hospital, Clichy, France)

  47. Yoshikuni Kawaguchi (Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo. Japan)

  48. Chetana Lim (Department of Digestive, HBP and Liver Transplantation, Hopital Pitie-Salpetriere, Sorbonne Universite, Paris, France)

  49. Bernardo Dalla Valle (General and Hepatobiliary Surgery, Department of Surgery, Dentistry, Gynecology and Pediatrics University of Verona, GB Rossi Hospital, Verona, Italy)

  50. Qu Liu, (Faculty of Hepatopancreatobiliary Surgery, the First Medical Center of Chinese People’s Liberation Army (PLA) General Hospital, Beijing, China)

  51. Junhao Zheng (Department of General Surgery, Sir Run-Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China)

  52. Phan Phuoc Nghia, (Department of Hepatopancreatobiliary Surgery, University Medical Center, University of Medicine and Pharmacy, Ho Chi Minh City, Vietnam)

  53. Zewei Chen (Department of Hepatobiliary Surgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, China)

  54. Shian Yu (Department of Hepatobiliary Surgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, China)

Footnotes

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