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- Bui, Anh T., et al.
(författare)
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Reduced metabolic flexibility is a predictor of weight gain among liver transplant recipients
- 2023
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Ingår i: Liver transplantation. - : LIPPINCOTT WILLIAMS & WILKINS. - 1527-6465 .- 1527-6473.
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Tidskriftsartikel (refereegranskat)abstract
- Metabolic flexibility is the ability to match biofuel availability to utilization and is inversely associated with increased metabolic burden among liver transplant (LT) recipients. The present study evaluated the impact of metabolic flexibility on weight gain following LT. LT recipients were enrolled prospectively (n = 47) and followed for 6 months. Metabolic flexibility was measured using whole-room calorimetry and is expressed as a respiratory quotient (RQ). Peak RQ represents maximal carbohydrate metabolism and occurs in the post-prandial state, while trough RQ represents maximal fatty acid metabolism occurring in the fasted state. The clinical, metabolic, and laboratory characteristics of the study cohort of lost weight (n = 14) and gained weight (n = 33) were similar at baseline. Patients who lost weight were more likely to reach maximal RQ (maximal carbohydrate oxidation) early and rapidly transitioned to trough RQ (maximal fatty acid oxidation). In contrast, patients who gained weight had delayed time to peak RQ and trough RQ. In multivariate modeling, time to peak RQ (& beta;-coefficient 0.509, p = 0.01), time from peak RQ to trough RQ (& beta;-coefficient 0.634, p = 0.006), and interaction between time to peak RQ to trough RQ and fasting RQ (& beta;-coefficient 0.447, p = 0.02) directly correlated with the severity of weight gain. No statistically significant relationship between peak RQ, trough RQ, and weight change was demonstrated. Inefficient transition between biofuels (carbohydrates and fatty acids) is associated with weight gain in LT recipients that is independent of clinical metabolic risk. These data offer novel insight into the physiology of obesity after LT with the potential to develop new diagnostics and therapeutics.
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| 2. |
- Goto, Toru, et al.
(författare)
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Superior long‐term outcome of Adult Living Donor Liver Transplantation : A cumulative single‐center cohort study with 20 years follow‐up
- 2022
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Ingår i: Liver transplantation. - : John Wiley & Sons. - 1527-6465 .- 1527-6473. ; 28:5, s. 834-842
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Tidskriftsartikel (refereegranskat)abstract
- Living donor liver transplantation (LDLT) is an attractive alternative to deceased donor liver transplantation (DDLT). Although both modalities have similar short-term outcomes, long-term outcomes are not well studied. We compared the 20-year outcomes of 668 adults who received LDLT with1596 DDLTs at the largest liver transplantation (LT) program in Canada. Recipients of LDLT were significantly younger and more often male than DDLT recipients (P < 0.001). Autoimmune diseases were more frequent in LDLT, whereas viral hepatitis and alcohol-related liver disease were more frequent in DDLT. LDLT recipients had lower Model for End-Stage Liver Disease scores (P = 0.008), spent less time on the waiting list (P < 0.001), and were less often inpatients at the time of LT (P < 0.001). In a nonadjusted analysis, 1-year, 10-year, and 20-year patient survival rates were significantly higher in LDLT (93%, 74%, and 56%, respectively) versus DDLT (91%, 67%, and 46%, respectively; log-rank P = 0.02) as were graft survival rates LDLT (91%, 67%, and 50%, respectively) versus (90%, 65%, and 44.3%, respectively, for DDLT; log-rank P = 0.31). After multivariable adjustment, LDLT and DDLT were associated with a similar hazard of patient and graft survival. Our data of 20 years of follow-up of LDLT from a single, large Western center demonstrates excellent long-term outcomes for recipients of LDLT.
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| 3. |
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| 4. |
- Ivanics, Tommy, et al.
(författare)
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The Toronto Postliver Transplantation Hepatocellular Carcinoma Recurrence Calculator : A Machine Learning Approach
- 2022
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Ingår i: Liver transplantation. - : John Wiley & Sons. - 1527-6465 .- 1527-6473. ; 28:4, s. 593-602
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Tidskriftsartikel (refereegranskat)abstract
- Liver transplantation (LT) listing criteria for hepatocellular carcinoma (HCC) remain controversial. To optimize the utility of limited donor organs, this study aims to leverage machine learning to develop an accurate posttransplantation HCC recurrence prediction calculator. Patients with HCC listed for LT from 2000 to 2016 were identified, with 739 patients who underwent LT used for modeling. Data included serial imaging, alpha-fetoprotein (AFP), locoregional therapies, treatment response, and posttransplantation outcomes. We compared the CoxNet (regularized Cox regression), survival random forest, survival support vector machine, and DeepSurv machine learning algorithms via the mean cross-validated concordance index. We validated the selected CoxNet model by comparing it with other currently available recurrence risk algorithms on a held-out test set (AFP, Model of Recurrence After Liver Transplant [MORAL], and Hazard Associated with liver Transplantation for Hepatocellular Carcinoma [HALT-HCC score]). The developed CoxNet-based recurrence prediction model showed a satisfying overall concordance score of 0.75 (95% confidence interval [CI], 0.64-0.84). In comparison, the recalibrated risk algorithms' concordance scores were as follows: AFP score 0.64 (outperformed by the CoxNet model, 1-sided 95% CI, >0.01; P = 0.04) and MORAL score 0.64 (outperformed by the CoxNet model 1-sided 95% CI, >0.02; P = 0.03). The recalibrated HALT-HCC score performed well with a concordance of 0.72 (95% CI, 0.63-0.81) and was not significantly outperformed (1-sided 95% CI, >= 0.05; P = 0.29). Developing a comprehensive posttransplantation HCC recurrence risk calculator using machine learning is feasible and can yield higher accuracy than other available risk scores. Further research is needed to confirm the utility of machine learning in this setting.
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| 5. |
- Lissing, M, et al.
(författare)
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Liver Transplantation for Acute Intermittent Porphyria
- 2021
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Ingår i: Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society. - : Ovid Technologies (Wolters Kluwer Health). - 1527-6473. ; 27:4, s. 491-501
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Tidskriftsartikel (refereegranskat)
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| 6. |
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| 7. |
- Siddiqui, Mohammad Shadab, et al.
(författare)
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Saroglitazar improves nonalcoholic fatty liver disease and metabolic health in liver transplant recipients
- 2023
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Ingår i: Liver transplantation. - : LIPPINCOTT WILLIAMS & WILKINS. - 1527-6465 .- 1527-6473. ; 29:9, s. 979-986
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Tidskriftsartikel (refereegranskat)abstract
- NAFLD is common after liver transplantation (LT) and is associated with an increased metabolic burden. Currently, there is a paucity of investigations into the treatment of post-LT NAFLD. In the present study, we evaluated the safety and efficacy of saroglitazar, a novel dual peroxisome proliferator-associated receptor & alpha;/& gamma; agonist, on the treatment of post-LT NAFLD and metabolic burden. This is a phase 2A, single-center, open-label, single-arm study in which patients with post-LT NAFLD received saroglitazar magnesium 4 mg daily for 24 weeks. NAFLD was defined by a controlled attenuation parameter & GE;264 dB/m. The primary endpoint was the reduction in liver fat as measured by MRI proton density fat fraction (MRI-PDFF). Secondary MRI-based metabolic endpoints included visceral adipose tissue, abdominal subcutaneous adipose tissue volumes, muscle fat infiltration, and fat-free muscle volume. Saroglitazar treatment led to a reduction in MRI-PDFF from 10.3 & PLUSMN;10.5% at baseline to 8.1 & PLUSMN;7.6%. A relative 30% reduction from baseline MRI-PDFF value was noted in 47% of all patients and 63% of patients with baseline MRI-PDFF >5%. Reduction in serum alkaline phosphatase was an independent predictor of MRI-PDFF response. Saroglitazar did not decrease fat-free muscle volume nor increase muscle fat infiltration, but did lead to a mild increase in visceral adipose tissue and abdominal subcutaneous adipose tissue. The study drug was well tolerated and a mild nonsignificant increase in serum creatinine was noted. Saroglitazar did not affect the weight. The study provides preliminary data demonstrating the safety and metabolic benefits of saroglitazar in LT recipients and underscores the importance of future studies to establish its efficacy after LT.
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