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The predictive value of a subjective difficulty scale (DS) after surgical procedures is unknown. The objective of this study was to evaluate the prognostic value of a DS after liver transplantation (LT) and to identify predictors of difficulty. Surgeons prospectively evaluated the difficulty of 441 consecutive liver transplantations from donation after brain death at the end of the surgery by using a DS from 0 to 10 (“the easiest to the hardest you can imagine”). DS was associated with severe morbidity. The risk of graft loss at 1 year remained unchanged from 0 to 6 but increased beyond 6. Graft survival and patient survival of group with DS 7–10 was significantly impaired compared to groups with DS: 0–3 or DS: 4–6 but were significantly impaired for the group with DS: 7–10. Independent predictors of difficult LT (DS ≥ 7) were annular segment 1, transjugular intrahepatic portosystemic shunt, retransplantation beyond 30 days, portal vein thrombosis, and ascites. Of them, ascites was a borderline non-significant covariate (
The difficulty in achieving a surgical procedure dramatically varies from one patient to another, independently of its intrinsic complexity (
This study focused on the technical difficulty of liver transplantation (LT) and proposed a different approach for assessing difficulty. Surgeons prospectively evaluated the difficulty by using a scale ranging from 0 to 10, according to their feeling at the end of the LT.
The prognostic value of such a subjective difficulty scale (DS) is unknown. Balance of Risk (BAR) and Survival Outcomes following Liver Transplantation (SOFT) scores are two validated tools that predict early survival after LT (
The objectives of this study were to test the impact of DS on outcomes and its added value with regard to validated prognostic models. Lastly, we aimed at identifying preoperative variables that predict difficult LT.
This study included all consecutive patients who underwent LT with a full liver graft from donation after brain death from January 2015 to March 2019 at the Paul Brousse Hospital, Villejuif, France. Every LT involved a fellow, defined here as a “junior” surgeon, and an attending defined as a “senior” surgeon. At the end of each LT, junior surgeons were in charge of entering intraoperative data into a dedicated online questionnaire, including a DS item. Junior surgeons were to give a number ranging from 0 to 10 (0 being the “easiest LT that you can imagine” and 10 being the “most difficult LT you can imagine”).
From October 2018 until the end of the study period, both senior and junior surgeons were asked to evaluate the DS, blinded for the evaluation of each other.
LTs without DS were not included. Donor variables were retrieved from the Cristal database of the Agence de la Biomédecine, the French national agency in charge of organ allocation. The design of this study was discussed and approved at our weekly institutional research meeting. This study was achieved in accordance with French legal requirements and the Declaration of Helsinki. Before surgery, patients provided their written consent according to which they permit that data obtained during standard health care can be used for scientific purposes.
Pretransplant CT scans were reviewed by YK, blinded for outcomes and DS value. The presence of the following items was assessed: - annular segment I, defined as a complete inferior vena cava encirclement by hypertrophic caudal lobe. - significant spontaneous portosystemic shunt (SPSS) ≥ 7 mm in diameter.
Total hepatectomy was achieved with caval preservation and transient porto-caval anastomosis in most recipients. The caval anastomosis was done according to the three vein-piggy back technique (
Initial immunosuppression comprised a triple-drug regimen of tacrolimus, mycophenolate mofetil, and corticosteroid. Steroid boluses were used to treat moderate to severe acute rejection episodes after histological documentation. In selected cases, everolimus was introduced to enable early withdrawal of tacrolimus (
All statistical analyses were performed using R version 3.5.1.
Our analysis followed 6 steps: Step 1: We tested the relationship between DS and severe morbidity and 1-year patient survival. Step 2: We evaluated the additional predictive value of DS by comparing the performance of BAR and SOFT scores before and after adding the DS. Step 3: We compared survival according to three levels of difficulty: “easy” (0–3), “intermediate” (4–6), and “difficult” (7–10). Cutoff values to define these categories were arbitrarily chosen. Step 4: We performed a univariate and multivariate analysis for predicting difficult transplantation. Step 5: We compared the type of complications according to difficult transplantation. Step 6: We tested the senior-junior agreement of DS during hepatectomy and implantation.
In step 1, the relationship between DS and severe morbidity and 1-year patient survival was explored by using regression and Cox models, respectively.
DS was treated not as an ordinal variable but as a continuous variable for simplicity. Severe morbidity was defined by at least one grade IIIa event according to the Dindo-Clavien classification (
In step 2, we evaluated the performance of the models without and with DS by using the Area Under Curve (AUC) and Akaike Information Criterion (AIC).
In step 3, graft survival was calculated from the date of LT. Data were censored at the time of last follow-up. The event of interest for graft survival was death or retransplantation, whereas death was the only event of interest used for patient survival calculation. Of note, for 1-year patient survival calculation, patients who died after 1 year from LT were censored. Survival curves were plotted according to Kaplan-Meier method. Survival probabilities were compared by using the log-rank test (
In univariate analysis (step 4 and 5), continuous variables were expressed as median (range) and compared with the non-parametric Mann-Whitney test. Categorical variables were evaluated using chi-squared or Fisher exact tests, as appropriate. Variables associated with difficult transplant (
In step 6, we used the Lin concordance correlation coefficient (
Of the 631 LT performed during the study period, 525 LT met the inclusion criteria, i.e., a whole liver graft from donation after brain death. After excluding LT without available DS (
For our study population, the 3-month and 1-year graft survival were 93% and 87%, respectively. One-year patient survival was 91%. Severe morbidity occurred in 166 (37.6%) LTs. A primary non-function was observed in 16 cases (3.6%).
The DS was evaluated by twelve junior surgeons. The median value of DS was 6, ranging from 1 to 10. DS was comprised between 0–3, 4-6, and 7–10 in 66 (15%), 204 (46.3%), and 171 (38.8%) LTs, respectively. The distribution of DS values is shown in
Distribution of DS value across the study population.
As shown in
Risk for severe morbidity
The predictive value of BAR and SOFT models are given in
Performance of SOFT and BAR models with and without DS for severe morbidity, 3-month graft survival, and 1-year patient survival.
Severe morbidity | |||||||
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Model | Variables | OR | 95% CI |
|
AUC | AIC |
|
One-variable model | SOFT | 1.06 | 1.03–1.09 | <.001 | .63 | 545 | |
Two-variable model | SOFT | 1.06 | 1.03–1.08 | <.001 | .721 | 510 | |
DS | 1.40 | 1.26–1.57 | <.001 | <.001 | |||
One-variable model | BAR | 1.08 | 1.04–1.12 | <.001 | .619 | 549 | |
Two-variable model | BAR | 1.07 | 1.05–1.13 | <.001 | .727 | 510 | |
DS | 1.48 | 1.30–1.64 | <.001 | ||||
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One-variable model | SOFT | 1.02 | 1.02–1.38 | .227 | .632 | 226 | |
Two-variable model | SOFT + DS | 1.02 | 1.02–1.38 | .441 | .715 | 216 | <.001 |
1.38 | 1.14–1.70 | .001 | |||||
One-variable model | BAR | 1.03 | .96–1.10 | .304 | .619 | 227 | |
Two-variable model | BAR | 1.04 | .97–1.11 | .25 | .720 | 217 | <.001 |
DS | 1.40 | 1.16–1.72 | <.001 | ||||
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One-variable model | SOFT | 1.07 | 1.03–1.11 | <.001 | .664 | 407 | |
Two-variable model | SOFT | 1.07 | 1.03–1.11 | .001 | .709 | 397 | <.001 |
DS | 1.34 | 1.12–1.59 | .001 | ||||
One-variable model | BAR | 1.08 | 1.2–1.14 | .007 | .626 | 412 | |
Two-variable model | BAR | 1.08 | 1.2–1.14 | .008 | .701 | 399 | <.001 |
DS | 1.39 | 1.17–1.66 | <.001 |
Comparisons of AUC, with the roc. test function (pROC, package).
BAR; balance of risk; DS, difficulty scale; SOFT, survival outcomes after liver transplantation; OR, odds ratio.
Graft survival and patient survival are reported in
Kaplan-Meier curves for graft survival
Univariate analysis is shown in
Risk factors for difficult LT (DS ≥ 7): Univariable and multivariable logistic regression analysis.
Variables | DS < 7 | DS ≥ 7 |
|
Multivariate analysis | ||
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OR | 95% CI |
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Recipient | ||||||
Male Sex | 184 (68.1) | 128 (74.9) | .161 | |||
Age, years | 55.0 (15.0–71.0) | 53.0 (12.0–71.0) | .300 | |||
BMI, kg/m2 | 25.2 (15.4–45.7) | 25.1 (11.4–46.1) | .741 | |||
MELD score at transplant | 19.0 (6.0–40.0) | 19.0 (6.0–40.0) | .516 | |||
ICU at the time of transplant | 53 (19.6) | 29 (17.0) | .564 | |||
Pretransplant dialysis | 12 (4.44) | 10 (5.85) | .663 | |||
ReLT beyond 30 days | 17 (6.30) | 32 (18.8) | <.001 | 4.11 | 2.18–7.99 | <.001 |
TIPS in place | 8 (2.96) | 16 (9.41) | .007 | 2.68 | 1.06–7.12 | .02 |
Combined Kidney transplant | 16 (5.93) | 12 (7.02) | .797 | |||
Explant weight, g | 1,295 (400–6,290) | 1,315 (435–3,665) | .532 | |||
Pretransplant TACE | 53 (19.6) | 31 (18.2) | .812 | |||
Night time (10 pm–6 am) | 43 (15.9) | 28 (16.4) | >.99 | |||
Donor | ||||||
Male sex | 142 (52.6) | 100 (58.5) | .266 | |||
Age, years | 60.0 (6.00–91.0) | 57.0 (14.0–93.0) | .318 | |||
BMI, kg/m2 | 24.7 (13.8–51.3) | 24.2 (14.6–41.0) | .595 | |||
Weight of the graft, g | 1,332 (700–2,425) | 1,400 (685–2,795) | .168 | |||
GW/recipient BW ratio | 1.8 (.7–4.3) | 1.8 (.8–5.9) | .601 | |||
Explant weight/recipient BW ratio | 1.7 (.7–10.5) | 1.7 (.6–6.9) | .965 | |||
Pretransplant CT scan | ||||||
Ascites |
103 (39.0) | 95 (56.2) | .001 | 1.64 | 1.07–2.51 | .04 |
Annular segment 1 | 6 (2.27) | 25 (14.9) | <.001 | 6.58 | 2.71–18.49 | <.001 |
Annular segment 1 and Piggy Back caval anastomosis | 3 (1.1) | 17 (10.1) | <.001 | |||
Portosystemic shunt | 120 (45.5) | 116 (69) | <.001 | |||
Portal vein thrombosis | 25 (9.5) | 38 (22.6) | <.001 | 2.17 | 1.20–3.95 | .01 |
PVT Yerdel 1–2 |
25 (9.5) | 30 (17.5) | <.001 | |||
PVT Yerdel 3 | 0 (0) | 8 (4.8) | ||||
Scoring systems | ||||||
BAR | 8 (1–22) | 8 (1–22) | .571 | |||
D-MELD | 1,050 (162–5,312) | 1,064 (153–3,400) | .387 | |||
SOFT | 9 (3–36) | 12 (0–45) | .004 | |||
ET-DRI | 1.47 (.95–2.86) | 1.44 (.97–2.71) | .938 |
BAR; balance of risk; BMI, body mass index; BW, body weight; D-MELD, Donor age X MELD, score; ET-DRI, European Transplant—Donor Risk Index; GW, graft weight; ICU, intensve care unit; MELD, Model for end-stage liver Disease; PVT, portal vein thrombosis; RBC, red blood cell; SOFT, survival outcomes following liver transplantation; TACE, transarterial chemoembolization; TIPS, transjugular intrahepatic portosystemic shunt.
Ascites was defined regardless of its volume, according to intraoperative finding at laparotomy.
Yerdel classification (
() indicates range for continuous variables and % for categorical variables.
Oberved probabilities for difficult LT (DS ≥ 7) according to the number of risk factors (Annular segment 1, ReLT after 30 days, Ascites, Portal vein thrombosis, TIPS).
Observed probability of DS ≥ 7 | |
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No. Factor | No. DS ≥ 7/overall number |
0 | 46/177 (26%) |
1 | 59/169 (35%) |
2 | 45/65 (69%) |
3+ | 18/21 (86%) |
Observed proportions of difficult transplant according to the number of factors are given in
The type of surgical complications, according to LT difficulty DS < 7 vs. DS ≥ 7, is shown in
Complications according to DS.
Type of complications | DS < 7 | DS ≥ 7 |
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Early allograft dysfunction |
57 (21.1%) | 49 (28.7%) | .091 |
Vascular complications |
16 (5.9%) | 35 (20.5%) | <.001 |
Biliary complications |
9 (3.3%) | 5 (2.9%) | >.99 |
Hemorrhage |
31 (11.5%) | 24 (14.0%) | .520 |
Infection | 71 (26.3%) | 56 (32.7%) | .177 |
Renal failure |
18 (6.7%) | 21 (12.3%) | .064 |
According to Olthoff et al.
Thrombosis or stenosis of the hepatic artery, the portal vein or caval anastomosis diagnosed on imaging regardless of the management.
Stenosis or biliary fistula.
Hemorrhage requiring laparotomy or hematoma on imaging requiring transfusion.
Stage III acute kidney injury (KDIGO Classification).
The DS values given by the junior and senior are given in
Agreement of DS between junior and senior surgeons for hepatectomy
The technical difficulty is inherently subjective. In previous studies, the technical difficulty in surgery was assessed by using various surrogates. The originality of our study was to prospectively evaluate the difficulty according to the surgeon’s subjective feeling at the end of the transplantation.
We observed that DS correlates with morbidity and even 1-year survival. The importance of intraoperative factors to improve the predictive ability of pretransplant models has been recognized (
As expected, the DS was associated with some objective variables like duration of surgery or transfusion volume, already known to impact outcomes (
The risk of death within the first year started to sharply increase beyond 6, suggesting that this cutoff value of seven carries a relevant clinical meaning. Five independent factors of “difficult” transplant were identified. Of them, late retransplantation is not a surprising finding. Adhesions, sometimes filled by portal hypertension, and modified anatomical landmark makes ReLT more challenging than primary transplantation (
Identifying “difficult” transplants with pretransplant variables yields some logistics advantages. Recipient laparotomy should begin as early as possible to limit cold ischemia time. DS highlights some technical difficulties such as annular segment 1 or portal vein thrombosis and may serve to better define the surgical strategy before LT. Complex transplantation may also require a team of two experienced surgeons. It may also guide the graft choice and avoid the combination of a marginal graft and complex transplantation associated with poor results (
The DS may also be of interest in the early post-transplant period. Some patients after “technically easy” LT are likely good candidates for enhanced recovery protocol, whereas recipients with high DS may potentially benefit from tailored monitoring, including daily Doppler and systematic CT scan. However, the possibility to tailor monitoring according to DS remains a hypothesis, and a more refined difficulty scale (evaluating each step, for example) might be a more efficient approach to anticipate outcomes.
The DS proposed here is prone to biases. An important variation in the evaluation according to experience, surgical skills, and timing of surgery could be expected. A surgeon’s “feeling at the end of LT” can be affected by innumerable variables, including the type of procedure, time of day, surgeon or assistant exhaustion or mood, issues with anesthesia, instruments, staff personnel, and many other factors, some even unrelated to surgical or medical aspects. As a result, the same case, potentially with the same outcome, could be subjectively evaluated by the surgeon differently in contrasting circumstances. In addition, the agreement across centers may not be warranted, depending on recruitment, number of cases, and type of disease treated. We also observed acceptable agreement between the senior and junior surgeon evaluations, suggesting that DS keeps a reasonable degree of reproducibility, despite its subjectivity. Discordant values in the DS were mainly observed in the intermediate range of difficulty, whereas “difficult” and “easy” were less subject to disagreement. The present study carries some limitations, in addition to its monocentric nature. The DS has not been evaluated in 16% of LT. We decided not to use multiple imputations because DS is the primary variable of interest. The comparisons of the study population with the group of LTs without DS showed significant differences for junior surgeons but neither for recipient characteristics nor intraoperative data.
The DS did not evaluate specifically for total hepatectomy and graft implantation in the whole cohort. A pretransplant DS would also have been helpful to test predictive variables and study the discrepancy between pre- and post-transplant DS. Validation of the DS prognostic value and the risk factors for complex transplant on an independent cohort is necessary to test the reproducibility and the relevancy of the DS in routine.
In conclusion, end-transplant DS predicts morbidity and 1-year survival after liver transplantation. Its value may be helpful to adapt monitoring and facilitate the early diagnosis of complications.
The raw data supporting the conclusion of this article will be made available by the authors, under reasonable request.
The design of this study was discussed and approved at our weekly institutional research meeting. This study was achieved in accordance with French legal requirements and the Declaration of Helsinki. Before surgery, patients have given a written consent according to which they permit that data obtained during standard health care can be used for scientific purposes.
YK and M-AA designed the study. YK, DP, EF-S, and M-AA performed the research. YK and M-AA wrote the manuscript. DC, DA, EV, RA, AC, HB, and NG contributed important reagents.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
BAR, balance-of-risk; DS, difficulty scale; ET-DRI, Eurotransplant Donor Risk Index; ICU, intensive care unit; LT, liver transplantation; MELD, Model for End-stage Liver Disease; PV, Portal vein; ReLT, Retransplantation; RBC, red blood cells; TACE, transarterial chemoembolization; TIPS, transjugular intrahepatic portosystemic shunt; SOFT, survival outcomes following liver transplantation.