This multicenter study evaluated end-of-surgery serum lactate concentration as a predictor of postoperative outcomes in patients undergoing liver resection. Using data from 519 patients, the study identified lactate concentration cut-offs that predicted high clinical risk scores, 90-day mortality, and severe morbidity. Models including lactate concentration showed improved accuracy over those without. Validation in 466 additional patients confirmed lactate concentration as an important predictor, especially for clinical risk and mortality. Pre- and intraoperative factors like diabetes, major hepatectomy, and transfusion predicted elevated lactate concentrations. The study concluded lactate is a reliable early indicator of postoperative outcomes after liver resection.

1. End-of-Surgery Serum Lactate concentration
as a major predictor of postoperative
outcome. A multicentre prospective study.
Eric Vibert, Emmanuel Boleslawski, Cyril Cosse, Rene Adam,
Denis Castaing, Daniel Cherqui, Salima Naili, Jean-Marc
Régimbeau, Antonio Sa Cunha, Stéphanie Truant, Maher Fleyfel,
François René Pruvot, Catherine Paugam, Olivier Farges
ACHBT Hepatectomy Registry

2. PST-AST = 450 UI/L
PST-ALT = 420 UI/L
AUROC = 0.61 AUROC = 0.57
French Multicentric Study : 651 pts in 9 HPB Centers
Postoperative Peak of Transaminase is not a relevant endpoint to predict outcome
2014

3. Objectives of the study
After an elective liver resection:
1. Is Arterial Lactate Concentration at the end
of surgery (LCT-EOS) predictive of outcome ?
2. If yes, is there pre- or intraoperative
predictors of an increase in LCT-EOS ?

4. Study endpoints
• End of surgery arterial Lactate Concentration
– Between 1 and 4 hours after end of liver transection
• Postoperative outcome (90-day outcome)
– High Clinical Comprehensive Index (> 3rd quartile)
– Mortality
– Severe morbidity (Clavien’s grade III-V)

5. ACHBT Web Prospective Registry

6. 1342 Consecutive Hepatectomies in 4 Hospitals
Training Cohort
June 2012 – December 2014
In Paul Brousse Hosp.
Validation Cohort
June 2012 – December 2014
In Beaujon, Lille, Amiens Hosp.
565 Patients 777 Patients
519 Patients 466 Patients
Dosage of Art. LCT routinely at
the end of sugery (92%)
Dosage of Art. LCT according
to surgical complexity (60%)

7. 519 Patients in the Training Cohort
Patients
Age (yr), median (IQR) 62 (18-87)
Gender, male 298 (57%)
BMI (kg/m²), mean ± DS 25.1 ± 4.8
Diabetes 100 (19%)
Cirrhosis 62 (12%)
Preoperative Portal Vein Occlusion 67 (13%)
Major Hepatectomy 236 (45.5%)
Laparoscopy 59 (12%)
Synchronous Major Procedure 81 (16%)
Inflow Occlusion 348 (67%)
Blood Loss > 500 cc 176 (34%)
Diagnosis
Metastatic disease 259 (50%)
Primary malignancy 199 (38%)
Benign and Living Donor 51 (10%)
Parasitosis 10 (2%)

8. Postoperative Outcome in the 2 cohorts
Training cohort
n = 519
Validation cohort
n = 466
P value
Grade of Clavien N(%) N(%)
0.0001
Grade 0 212 (40.8) 121 (30.0)
Grade I 36 (6.9) 41 (8.8)
Grade II 164 (31.6) 164 (35.2)
Grade III 88 (16.9) 69 (14.8)
Grade IV 9 (1.7) 41 (8.8)
Grade V 10 (1.9) 30 (6.4)
CCI , median (95%CI) 20.92 (18.91-22.93) 24.24 (22.42-26.06) <0.0001
CCI > 3rd Quartile 124 (23.9) 192 (41.2) 0.0001

9. 3 steps to evaluate LCT-EOS prognostic impact
1. Building models of outcome in the training cohort
- LCT-EOS cut-off was determined by ROC-curves for the 3 endpoints
(High CCI, Mortality, Severe Morb)
- Uni- and Multivariate analyses of pre- and intraoperative factors,
including LCT-EOS, were performed for the 3 endpoints.
- AUROC of each model (which included or not LCT-EOS) were
compared to evaluate the additive value of LCT-EOS
2. Testing the models in the validation cohort (Real Life)
– AUROC of each model with / without LCT-OES
– Calibration : Prediction vs Observation ?
3. Calculate Se, Sp, Accuracy of models in the entire cohort

10. Firt Step : Building Models

11. Training Cohort : LCT-EOS cut-offs
End Point LCT-EOS cut-off AUROC
High CCI (>3rd quartile) 3.0 mmol/L 0.86 (95%CI 0.82 – 0.89)
90-day Mortality 3.0 mmol/L 0.87 (95%CI 0.83 – 0.91)
90-day Severe Morbidity 2.8 mmol/L 0.76 (95%CI 0.72 – 0.80)
High CCI > 3rd Q.
Mortality.
Severe Morbidity
2012-2014 : 519 Patients with
systematic dosage of Lactate
at the end of surgery

12. Variables Hazard ratio 95% CI
For high CCI (> 3rd quartile)
Major hepatectomy 2.0 1.1 - 4.6
Associated procedure 3.6 1.3 – 10
Transection > 90 min 1.8 1.0 - 3.4
Blood Loss > 500 cc 2.3 1.2 - 4.4
LCT-EOS > 3 mmol/L 2.2 1.1 - 4.2
For 90-day Mortality
Diabetes 7.34 2.1 – 25
Cirrhosis 4.34 1.9 – 28
Associated procedure 4.31 1.5 – 28
Length of Surgery > 300 min 2.6 1.1 - 5.4
LCT-EOS > 3 mmol/L 3.4 2.5 - 5.2
For 90-day Severe Morbidity
BMI > 28 2.5 1.2 – 5.2
Associated procedure 2.9 1.4 – 6.2
Ischemia duration > 30 min 2.2 1.2 – 4.2
Transection > 90 min 1.9 1.0 – 3.4
Blodd Loss > 500 cc 2.7 1.4 – 5.1
LCT – EOS > 2.8 mmol/L 2.0 1.1-3.9

13. Predictive Models for the 3 endpoints
0.75 (0.68-0.82)
0.77 (0.71-0.83)
0.69 (0.64-0.73)
0.74 (0.70-0.78)
0.68 (0.65-0.71)
0.72 (0.65-0.71)

14. Second Step : Validate Models in
the « real-life » Cohort…

15. Impact of LCT-EOS in validation cohort
The role of LCT-EOS was more important for predicting High-CCI
and Mortality than severe morbidity
0.73 (0.70-0.76)
0.85 (0.78-0.92)
0.69 (0.65-0.73)
0.72 (0.69-0.75)
0.71 (0.68-0.74)
0.76 (0.68-0.74)
High CCI Mortality Severe Morb.

16. Model Calibration in the Validation cohort
predicted (%) real (%) predicted (%) real (%) predicted (%) real (%)
0 17 17,1 1,08 1,25 20,6 20,8
1 17,95 18,1 2,5 2,09 21,5 21,5
2 18,74 19,5 3,7 3,05 22,3 22,9
3 19,53 20,3 5,16 4,22 23,15 24,5
4 20,32 20,8 6,36 5,06 24,75 25,8
5 21,26 22,4 7,78 6,4 26,5 28,3
High CCI score 90-day mortality Severe morbidity
N. of risk factors
Result of model (Prediction) VS Real Outcome in Validation cohort according to the N. of risk factors
High CCI Mortality Severe Morb.

17. Third Step : Use all patients to
calculated Se, Sp and Accuracy

18. End point
Models
without LCT
Models
with LCT
Increased
Accuracy with
LCT
High CCI
Score
DOR 4.69 5.46
Sensitivity 71% 74% 16%
Specificity 66% 66%
Mortality
DOR 2.35 3.16
Sensitivity 69% 74% 34%
Specificity 51% 52%
Severe
Morbidity
DOR 2.55 2.99
Sensitivity 71% 74% 17%
Specificity 65% 65%
“Diagnostic accuracy is defined as the proportion of all tests that give a correct
result (Scott et al. 2008)”

19. Objectives of the study
After an elective liver resection:
1. Is Arterial Lactate Concentration at the end
of surgery (LCT-EOS) predictive of outcome ?
2. If yes, is there pre- or intraoperative
predictors of an increase in LCT-EOS ?

20. Variables Hazard ratio 95% CI
Diabetes 2.2 1.1 - 4.6
Major Hepatectomy 3.7 2.1 – 6.5
Repeat Hepatectomy 2.7 1.2 – 6.0
Synchronous Major Procedure 2.4 1.1 - 5.0
Inflow occlusion 2.0 1.0 – 3.8
Transfusion 2.3 1.1 - 4.5
Pre- and Intraoperative factors
predictive of LCT-EOS > 3 mmol/L
Results of Multivariate analyis in the Training Cohort

21. Conclusions
• This multicentric study including a training cohort of 519
patients and validation cohort of 466 patients over a 24
months with a prospective outcome evaluation period
demonstrated that
Arterial Lactate concentration at the End of Surgery is an
early, convenient and reliable endpoint for postop. outcomes
LCT-EOS must be used to explore the impact of pre- and/or
intraoperatives factors on the outcome of liver resection
• LCT-EOS > 3 mmol/L is a surrogate endpoint that
determine the need for critical care after hepatectomy