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Balci, Deniz

0000-0002-6246-1123

Mayo Clinic

Bahçeşehir University

Citations 5

Portal Vein Thrombosis in Pediatric Liver Transplantation With Technical Variant Grafts: An International Multicenter Analysis of Risk and Prognostic Factors
Raptis, Dimitri A., Gunasekaran, Vasanthakumar , Rammohan, Ashwin, Sakamoto, Seisuke, Uchida, Hajime, Beekum, Cornelius J. van, Krendl, F. J., Chen, Itsuko Chih-Yi, Domenick, Bryanna , Kow, Alfred, Soejima, Yuji, Furuya, Katryn N. , Mazariegos, George V., Dunn, Stephen, Olthoff, Kim, Rand, Elizabeth B. , Chen, C L, Balci, Deniz, Nadalin, Silvio, Schneeberger, Stefan, Sudan, Debra L., Schmelzle, Moritz, Herden, Uta , Fischer, L, Sayed, Blayne A., Ng, Vicky L, Kasahara, Mureo, Rela, Mohamed, Broering, Dieter C., Xia, Qiang, Clavien, P A, Li, Zhihao, Sudan, Debra L. , Li, Zhihao , Sayed, Blayne A , Sudan, Debra L , Li, Zhihao , Wang, Kaihang , Madadi‐Sanjani, Omid , Y, Liu , Raptis, Dimitri , Rammohan, Ashwin , Sakamoto, Seisuko , Uchida, Hajime , Kaliciński, Piotr , Goldaracena, Nicolás , Beekum, Cornelius J. van , Krendl, Felix Julius , Chen, Itsuko Chih-Yi, Kow, Alfred Wei Chieh , Soejima, Yuji , Mazariegos, George , Mali, Vidyadhar Padmakar , Leipnitz, Ian , Balci, Deniz , Kirimker, Elvan Onur , Nadalin, Silvio , Schneeberger, Stefan , Schmelzle, Moritz , Sayed, Blayne A. , Kowalewski, Grzegorz , Kasahara, Mureo , Rela, Mohamed , Bröering, Dieter C. , Xia, Qiang

Transplantation | June 9, 2026 | Volume: 110 | Issue: 8 | Pages: e1695-e1704

10.1097/tp.0000000000005777 Get It

Background. The adoption of technical variant grafts has expanded the donor pool for pediatric liver transplantation, but it also poses a risk of portal vein thrombosis (PVT). This study evaluated risk and prognostic factors of PVT in children undergoing liver transplantation with technical variant grafts. Methods. A total of 3137 pediatric patients from 19 centers were included: 470 received split/reduced deceased donor grafts and 2667 received living donor grafts. Multivariable logistic regression was used to identify risk factors, whereas time-dependent Cox models were used to assess the impact on survival. Results. PVT occurred in 102 patients (3.3%) and was associated with increased mortality (adjusted hazard ratio, 2.86; 95% confidence interval [CI], 1.13-7.25; P = 0.027) and graft loss (adjusted hazard ratio, 9.97; 95% CI, 4.90-20.3; P < 0.001). Risk factors included younger age, lower weight, higher Pediatric End-Stage Liver Disease score, longer cold ischemia and operation times, higher graft-to-recipient weight ratio, increased red blood cell transfusions, and biliary atresia. After adjusting for center, lower weight (odds ratio, 0.84 per kg; 95% CI, 0.71-1.00; P = 0.047) and biliary atresia (odds ratio, 2.34; 95% CI, 1.10-5.00; P = 0.027) remained predictors. Five-year patient (88.4% versus 93.1%) and graft survival (82.7% versus 96.3%) were significantly inferior in patients with PVT. Conclusions. Low-weight children with biliary atresia constituted a high-risk group, highlighting the necessity for early detection and management.
Early graft failure after adult living donor liver transplantation: A multicenter risk analysis and development of the early allograft failure in living donor liver transplantation (EAGLE-LDLT) model
Li, Zhihao, Centonze, Leonardo , Raptis, Dimitri , Marquez, Kris Ann Hervera , Rammohan, Ashwin, Gunasekaran, Vasanthakumar , Hong, Suyoung , Chen, I Lun, KIM, Jongman , Hsu, Shih-Chao , Akamatsu, Nobuhisa, Shaked, Oren, Genedy, Lara, Dutkowski, Philipp , Nadalin, Silvio, Boehnert, Markus U, Mathur, Abhishek, Emond, J., Testa, Giuliano, Olthoff, Kim, Taner, Timucin, Wong, Tiffany CL, Hasegawa, Kiyoshi, Balci, D., Cattral, Mark, Sapisochin, G., Selzner, Nazia, Jeng, Long-Bin, Chen, Chao-Long, Suh, Kyung-Suk, Rela, Mohamed, Broering, Dieter, Clavien, Pierre-Alain, Kim, Jong Man , Raptis, Dimitri Aristotle , Li, Zhihao , Hong, Su young , Chen, I. , Centonze, Leonardo , Li, Zhihao , Rammohan, Ashwin , Chen, Itsuko Chih-Yi , Kirimker, Elvan Onur , Akamatsu, Nobuhisa , Shaked, Oren , Finotti, Michele , Yeow, Marcus , Nadalin, Silvio , Boehnert, Markus U , Polak, Wojciech G , Bonney, Glenn K , Samstein, Benjamin , Emond, Jean C , Testa, Giuliano , Olthoff, Kim M , Heimbach, Julie K , Taner, Timucin , Wong, Tiffany C L , Balci, Deniz , Cattral, Mark , Sapisochin, Gonzalo , Selzner, Nazia , Jeng, Long-Bin , Joh, Jae-Won , Chen, Chao-Long , Suh, Kyung-Suk , Di Sandro, Stefano , Rela, Mohamed , Broering, Dieter , Clavien, Pierre-Alain , Akamatsu, Nobuhisa , Shaked, Oren , Boehnert, Markus , Polak, Wojciech G. , Mathur, Abhishek , Samstein, Benjamin , Emond, Jean C. , Testa, Giuliano , Heimbach, Julie K. , Taner, Timuçin , Wong, Tiffany , Hasegawa, Kiyoshi , Cattral, Mark S. , Sapisochín, Gonzalo , Selzner, Nazia , Joh, Jae‐Won , Rela, Mohamed , Bröering, Dieter C. , Clavien, Pierre‐Alain

Liver Transplantation | January 21, 2026 | Volume: 32 | Issue: 7 | Pages: 1027-1039

10.1097/lvt.0000000000000816 Get It

Early allograft failure (EAF) after living donor liver transplantation (LDLT) remains a clinical challenge. Existing prediction models developed for deceased donor transplantation poorly apply to LDLT due to distinct surgical and physiological factors. This study identifies clinical determinants of EAF and develops an LDLT-specific prediction model. We conducted a multicenter retrospective cohort study from 17 high-volume LDLT centers (January 2016–December 2020) with external validation at a tertiary center in Saudi Arabia (January 2015–December 2022). The primary outcome was EAF (graft loss or patient death ≤90 d). Multivariable mixed-effects logistic regression identified preoperative/intraoperative risk factors. The EAGLE-LDLT model was constructed using postoperative laboratory values. Performance was compared against established models (EAD, MEAF, A2ALL) using ROC analysis and decision curve analysis. The development cohort included 2944 adult LDLT recipients (67.7% male; median age 55 y; median MELD 14) with a 5.5% EAF rate. External validation included 1020 recipients (median MELD 21, 6.7% EAF). Independent risk factors for EAF were MELD (OR 1.06, 95% CI 1.04–1.08), donor BMI (OR 1.05, 95% CI 1.00–1.10), portal vein thrombosis (OR 1.73, 95% CI 1.13–2.63), and hepaticojejunostomy (OR 1.58, 95% CI 1.06–2.36). The EAGLE-LDLT model incorporating peak ALT (>468 U/L), peak INR (>1.9), and bilirubin (>3.5 mg/dL) and INR (>1.3) at POD7, demonstrated superior discrimination (AUC=0.81) compared with MEAF (AUC=0.77, p =0.004), EAD (AUC=0.67, p <0.001), and A2ALL (AUC=0.65, p <0.001). EAGLE-LDLT achieved balanced sensitivity (75.0%) and specificity (73.7%), effectively stratifying patients into high-risk (15% of patients; 40.4% EAF incidence) and low-risk groups. Preoperative and intraoperative clinical factors predict EAF in LDLT. The EAGLE-LDLT model accurately identifies LDLT recipients at the highest risk for EAF postoperatively.
Living liver donor safety: Intraoperative considerations in living liver donation—Guidelines from the ILTS–iLDLT group consensus conference 2025
Bhangui, Prashant , Hakeem, Abdul Rahman , Maira, Tommaso Di , Rammohan, Ashwin, Sayed, Blayne A. , Soejima, Yuji , Shingina, Alexandra , Cheah, Yee Lee , McCluskey, Stuart, Spiro, Michael , Ganesh, Swaytha , Rajalingam, Rajesh , Gupta, Subash , Findlay, James Y. , Chieh, Alfred Kow Wei, Sakamoto, Seisuko, Xia, Qiang, Kim, Ki-Hun , Polak, W., Soin, A G, Pomposelli, James J. , Vyas, Mary, Wiggins, Chantal, Mas, Valeria, Taner, Timucin, Broering, Dieter, Chen, Chao-Leng, Burra, Patrizia, Ascher, N. L., Lerut, Jan, Rela, Mohamed, Selzner, Nazia, Balci, Deniz, Olthoff, Kim M. , Polak, Wojciech G. , Hakeem, Abdul , Rammohan, Ashwin , Sayed, Blayne A , McCluskey, Stuart , Findlay, James, Sakamoto, Seisuko , Xia, Qiang , Polak, Wojciech G , Sapisochin, Gonzalo , Pomposelli, James , Selzner, Nazia , Balci, Deniz , Bhangui, Prashant , Di Maira, Tommaso , Gupta, Amar C. , Xia, Qiang , Sapisochín, Gonzalo , Soin, Arvinder S., Taner, Timuçin , Bröering, Dieter C. , Terrault, Norah A. , Burra, Patrizia , Hirschfield, Gideon M. , Lerut, Jan , Rela, Mohamed , Heimbach, Julie K. , Selzner, Nazia

Liver Transplantation | January 5, 2026 | Volume: 32 | Issue: 4 | Pages: 592-608

10.1097/lvt.0000000000000800 Get It

The success of living donor liver transplantation (LDLT) has bridged the growing gap between organ demand and availability in patients with liver failure or liver cancer. Safety of the living liver donor (LLD) is paramount, and astute intraoperative management plays a critical role in ensuring optimal outcomes for them. Given that intraoperative surgical and anesthesia practices vary widely across centers, the International Liver Transplantation Society (ILTS) and the International Living Donor Liver Transplantation Group (iLDLT Group) convened a global consensus conference in Toronto in March 2025 to develop guidelines for intraoperative management of the LLD. This manuscript details the recommendations on intraoperative considerations for the safety of LLD developed by Working Group II of the Consensus Scientific Committee, using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system for assessment of recommendations, and the Danish model of consensus. Working Group II focused on intraoperative monitoring, fluid and ventilation strategies, surgical techniques for vascular and biliary division, surgeon and center-specific experience, and intraoperative crises planning. These guidelines aim to support both established and emerging LDLT teams to ensure high-quality and safe intraoperative care for the LLD.
Validation of a Pretransplant Risk Prediction Model for Early Allograft Dysfunction After Living-donor Liver Transplantation
Gunasekaran, Vasanthakumar , Chen, I. , Marquez, Kris Ann Hervera , Hsu, Shih-Chao, Akamatsu, Nobuhisa , Shaked, Oren , Genedy, Lara, Yebyo, Henock G. , Dutkowski, Philipp , Boehnert, Markus , Mathur, Abhishek , Emond, Jean C. , Testa, Giuliano , Olthoff, Kim M. , Rosen, Charles B. , Taner, Timuçin , Wong, Tiffany , Lo, Chung‐Mau, Cattral, Mark S. , Sapisochin, Gonzalo, Jeng, Long‐Bin , Chen, Chao‐Long , Rela, Mohamed , Bröering, Dieter C. , Clavien, Pierre‐Alain , Li, Zhihao , Yeow, Marcus, Hsu, Shih-Chao , Li, Zhihao , Akamatsu, Nobuhisa , Wong, Tiffany C L , Li, Zhihao, Raptis, Dimitri , Rammohan, Ashwin , Hong, Su young , Kim, Jong Man , Kirimker, Elvan Onur , Finotti, Michele , Yeow, Marcus , Braun, Julia , Nadalin, Silvio , Polak, Wojciech G. , Bonney, Glenn Kunnath , Samstein, Benjamin , Heimbach, Julie K. , Hasegawa, Kiyoshi , Balci, Deniz , Sapisochín, Gonzalo , Selzner, Nazia , Joh, Jae-Won , Suh, Kyung-Suk

Transplantation | January 28, 2025 | Volume: 109 | Issue: 8 | Pages: 1383-1392

10.1097/tp.0000000000005331 Get It

Background. Early allograft dysfunction (EAD) affects outcomes in liver transplantation (LT). Existing risk models developed for deceased-donor LT depend on posttransplant factors and fall short in living-donor LT (LDLT), where pretransplant evaluations are crucial for preventing EAD and justifying the donor’s risks. Methods. This retrospective study analyzed data from 2944 adult patients who underwent LDLT at 17 centers between 2016 and 2020. We developed a logistic regression model to predict EAD based on this development cohort. We used data from 1020 patients at the King Faisal Transplant Center for external validation. Results. In the development cohort, 321 patients (10.9%) experienced EAD. These patients had poorer health status, more liver decompensation, and higher requirements of hospitalization than those without EAD. Multivariable logistic regression identified independent pretransplant predictors of EAD: laboratory Model for End-Stage Liver Disease score (odds ratio [OR], 1.08; 95% confidence interval [CI], 1.06-1.09), the necessity for hospitalization at the time of transplant (OR, 2.58; 95% CI, 2.00-3.30), and graft weight in kilogram (OR, 0.27; 95% CI, 0.17-0.45). Using these predictors, we developed the model for EAD after LDLT, which demonstrated strong discriminative ability in the development cohort with an area under the curve (AUC) of 0.71 (95% CI, 0.68-0.74). The model maintained high discrimination during internal validation (AUC, 0.70; 95% CI, 0.67-0.73) and showed a modest reduction in discriminative power in external validation (AUC, 0.65; 95% CI, 0.61-0.68). Conclusions. EAD post-LDLT is influenced by the recipient’s pretransplant health condition and the graft weight. Integrating the model for EAD after LDLT into the pretransplant process of pairing donors and recipients can enhance the safety and efficacy of LDLT.
Novel Benchmark for Adult-to-Adult Living-donor Liver Transplantation
Li, Zhihao , Gunasekaran, Vasanthakumar , Chen, Itsuko Chih-Yi, Marquez, Kris Ann Hervera , Hsu, Shih Chao, Kirimker, Elvan Onur, Akamatsu, Nobuhisa , Shaked, Oren , Genedy, Lara, Dutkowski, Philipp , Boehnert, Markus , Mathur, Abhisek, Emond, Jean C. , Testa, Giuliano , Olthoff, Kim M. , Rosen, Charles B. , Taner, Timuçin , Lo, Chung Mau , Cattral, Mark S. , Jeng, Long Bin, Bröering, Dieter C. , Chen, Chao‐Long, Suk, Kyung-Suh, Rela, Mohamed , Clavien, Pierre‐Alain , Hsu, Shih-Chao , Li, Zhihao , Akamatsu, Nobuhisa , Rammohan, Ashwin , Hong, Su young , Chen, Itsuko Chih-Yi, Kim, Jong Man , Kirimker, Elvan Onur, Finotti, Michele , Yeow, Marcus , Nadalin, Silvio , Polak, Wojciech G. , Bonney, Glenn Kunnath , Mathur, Abhishek , Samstein, Benjamin , Heimbach, Julie K. , Wong, Tiffany , Hasegawa, Kiyoshi , Balci, Deniz , Sapisochín, Gonzalo , Selzner, Nazia , Jeng, Long-Bin , Joh, Jae-Won , Suk, Kyung-Suh

Annals of Surgery | July 21, 2023 | Volume: 278 | Issue: 5 | Pages: 798-806

10.1097/sla.0000000000006038 Get It

Objective: To define benchmark values for adult-to-adult living-donor liver transplantation (LDLT). Background: LDLT utilizes living-donor hemiliver grafts to expand the donor pool and reduce waitlist mortality. Although references have been established for donor hepatectomy, no such information exists for recipients to enable conclusive quality and comparative assessments. Methods: Patients undergoing LDLT were analyzed in 15 high-volume centers (≥10 cases/year) from 3 continents over 5 years (2016–2020), with a minimum follow-up of 1 year. Benchmark criteria included a Model for End-stage Liver Disease ≤20, no portal vein thrombosis, no previous major abdominal surgery, no renal replacement therapy, no acute liver failure, and no intensive care unit admission. Benchmark cutoffs were derived from the 75th percentile of all centers’ medians. Results: Of 3636 patients, 1864 (51%) qualified as benchmark cases. Benchmark cutoffs, including posttransplant dialysis (≤4%), primary nonfunction (≤0.9%), nonanastomotic strictures (≤0.2%), graft loss (≤7.7%), and redo-liver transplantation (LT) (≤3.6%), at 1-year were below the deceased donor LT benchmarks. Bile leak (≤12.4%), hepatic artery thrombosis (≤5.1%), and Comprehensive Complication Index (CCI ® ) (≤56) were above the deceased donor LT benchmarks, whereas mortality (≤9.1%) was comparable. The right hemiliver graft, compared with the left, was associated with a lower CCI ® score (34 vs 21, P < 0.001). Preservation of the middle hepatic vein with the right hemiliver graft had no impact neither on the recipient nor on the donor outcome. Asian centers outperformed other centers with CCI ® score (21 vs 47, P < 0.001), graft loss (3.0% vs 6.5%, P = 0.002), and redo-LT rates (1.0% vs 2.5%, P = 0.029). In contrast, non-benchmark low-volume centers displayed inferior outcomes, such as bile leak (15.2%), hepatic artery thrombosis (15.2%), or redo-LT (6.5%). Conclusions: Benchmark LDLT offers a valuable alternative to reduce waitlist mortality. Exchange of expertise, public awareness, and centralization policy are, however, mandatory to achieve benchmark outcomes worldwide.