Abstract
Background
Sarcopenia after liver transplantation is poorly characterized in recipients with metabolic dysfunction-associated steatotic liver disease (MASLD) and severe obesity. We evaluated longitudinal changes in psoas muscle index (PMI) after transplantation and examined whether PMI trajectory was associated with post-transplant survival.
Methods
We performed a retrospective single-center study of adults with MASLD and body mass index ≥ 35 kg/m2 who underwent orthotopic liver transplantation between January 2015 and June 2023. PMI was measured on computed tomography at the L3 level before transplantation and at 6 months, 1 year, 3 years, and 5 years when available. Longitudinal change was assessed using linear mixed-effects models adjusted for survival status. Survival analyses included Kaplan–Meier estimation and univariate logistic regression.
Results
Seventy-three recipients were included; mean age was 59.3 years, 50.7% were women, median body mass index was 38.1 kg/m2, and mean Model for End-Stage Liver Disease score was 23.6. PMI declined significantly from baseline to 6 months (β = − 0.60, 95% confidence interval [CI] − 0.98 to − 0.22; p = 0.002) and 1 year (β = − 0.46, 95% CI − 0.83 to − 0.09; p = 0.015), with persistent reduction at 3 years. Survivors showed modest early decline followed by relative stabilization, whereas non-survivors demonstrated steeper decline. However, pre-transplant PMI, 6-month PMI, and early PMI change were not significantly associated with mortality.
Conclusions
In liver transplant recipients with MASLD and severe obesity, muscle loss worsens during the first post-transplant year and may persist thereafter. These findings raise questions regarding optimal timing of nutritional and physical rehabilitation and justify larger studies to determine the prognostic significance of post-transplant muscle trajectories.
Keywords: Muscle wasting, Body composition, Computed tomography, Transplant recipient, Frailty, Myosteatosis, Rehabilitation, Metabolic syndrome, Graft outcomes, Mortality risk
Introduction
Patients with obesity are known to have increased risks for both postoperative complications and the development of fatty liver. As this population grows, more patients with obesity will be eligible for liver transplantation. Reduction of muscle mass, or sarcopenia, is a significant complication both pre- and post-liver transplantation. There is robust data regarding the mortality risk of sarcopenia in non-transplant cirrhosis patients [1, 2].
Data around post-transplant mortality risk and sarcopenia are mixed [3], with some studies showing that pre-transplant sarcopenia increases post-transplant mortality [4], but others find no significant mortality differences [5]. One prospective study of 53 patients examined the effect of worsening sarcopenia post-transplant and found that pre-transplant sarcopenia was associated with increased post-transplant mortality, with a trend toward increased mortality in patients with worsening post-transplant sarcopenia [6].
Data around post-transplant sarcopenia have mostly examined the initial months after transplant. One study found that liver transplant did not significantly reverse sarcopenia for the majority of patients during follow-up of 19 months, and in fact, some patients developed new-onset sarcopenia after transplant [6].
Since liver transplant patients often live many years after transplant, longer-term follow-up could help shed light on whether these post-transplant changes persist [7]. Herein, we aimed to study post-transplant sarcopenia and its effect on mortality in liver transplant patients with class 2 or higher obesity.
Methods
Study Design
This was a retrospective analysis of adult patients (> 18 years old) with pre-transplant class 2 or higher obesity who underwent liver transplant for metabolic associated steatotic liver disease (MASLD) from 01/01/2015 to 06/30/2023 (n = 73) at the Cleveland Clinic. Functional assessment of strength was determined by physical therapy evaluation, but no formal frailty index was used. Recipients of liver transplants for other indications were excluded (e.g., alcohol-related liver disease as defined by committee assessment, primary biliary cholangitis, primary sclerosing cholangitis, hepatocellular carcinoma). Cleveland Clinic’s institutional review board approved the study protocol.
Outcomes
Outcomes were changes in pre- and post-transplant psoas muscle index (PMI) between patients who survived and died post-transplant, and associations between time and post-transplant PMI. To calculate PMI, computed tomography (CT) scans were retrieved from the immediate preoperative period and at the 6-month, 1-year, 3-year, and 5-year postoperative periods as available. Axial CT images were obtained through the level of L3. Psoas muscle area was measured at this level using a volumetric software which differentiated tissue types based on Hounsfield unit attenuation (HU 0–100 was used). The total area of the psoas muscles was obtained at this level and divided by the patient’s height2 to obtain a PMI.
Variables
Other variables that were extracted during the manual chart review were demographic (e.g., age, sex, and race) and clinical characteristics (smoking history, metabolic syndrome characteristics as defined by the presence of a diabetes diagnosis in the electronic medical record, a diagnosis of hypertension in the electronic medical record, obesity as defined by BMI > 30 regardless of ethnicity, high triglycerides, over 150 mg/dL, and low HDL under 40 mg/dL for men and under 50 mg/dL for women, history of hepatocellular carcinoma, body mass index [BMI], albumin, model for end-stage liver disease [MELD], transplant donor type, immunosuppression type, complications, and length of stay).
Statistical Analysis
Continuous variables were summarized as mean ± standard deviation (SD) if normally distributed, and as median with interquartile range (IQR) if not. Normality was assessed using the Shapiro–Wilk test. Categorical variables were summarized as frequency and percentage. Group comparisons for categorical variables were conducted using Pearson’s Chi-square test or Fisher’s exact test, as appropriate. Continuous variables were compared using the two-sample t‑test and Wilcoxon rank-sum test. The linear mixed-effects model was used to assess the association between time and PMI, adjusting for patient status. Pairwise comparisons were used to compare PMI at different time points and p-values were adjusted using the Benjamini–Hochberg (BH) method. A Kaplan–Meier survival curve was generated to visualize overall survival probability after transplant and a log-rank test was used to compare by quartiles of pre-transplant PMI. Analyses were performed using R software and a significance level of 0.05 was used for all tests.
Results
Pre-transplant Demographic and Clinical Characteristics
A total of 73 patients underwent liver transplantation (Table 1). At transplant, the mean (SD) age was 59.3 (7.9) years, 49% were male, and 96% were Caucasian/White. The majority of patients had diabetes (70%), hypertension (84%), low HDL (55%), and obesity (99%). The median BMI was 38.1 [36.0–43.0], the mean MELD was 23.6 (8.8), and the mean PMI was 6.4 (1.9).
Table 1.
Comparison of pre- and post-transplantation characteristics between patients who survived and those who died after liver transplantation
| Characteristic | All (n = 73) | Alive (n = 57) | Died (n = 16) | p value |
|---|---|---|---|---|
| Pre-transplantation characteristics | ||||
| Age at transplant, mean (SD) | 59.3 (7.94) | 59.1 (8.09) | 59.9 (7.60) | 0.702 |
| Male Sex, n (%) | 36 (49.3%) | 29 (50.9%) | 7 (43.8%) | 0.825 |
| Race, n (%) | 0.586 | |||
| Black/African American | 3 (4.11%) | 3 (5.26%) | 0 (0.00%) | |
| Caucasian/White | 70 (95.9%) | 54 (94.7%) | 16 (100%) | |
| Smoking, n (%) | 0.343 | |||
| Never/Former | 67 (93.1%) | 51 (91.1%) | 16 (100%) | |
| Current | 5 (6.94%) | 5 (8.93%) | 0 (0.00%) | |
| Metabolic syndrome characteristics | ||||
| Diabetes, n (%) | 51 (69.9%) | 42 (73.7%) | 9 (56.2%) | 0.214 |
| Hypertension, n (%) | 61 (83.6%) | 48 (84.2%) | 13 (81.2%) | > 0.999 |
| Low HDL, n (%) | 40 (54.8%) | 33 (57.9%) | 7 (43.8%) | 0.471 |
| High triglycerides, n (%) | 32 (43.8%) | 29 (50.9%) | 3 (18.8%) | 0.045 |
| Obesity, n (%) | 72 (98.6%) | 56 (98.2%) | 16 (100%) | > 0.999 |
| History of HCC in year before transplant, n (%) | 10 (13.7%) | 7 (12.3%) | 3 (18.8%) | 0.681 |
| BMI at transplant, median [IQR] | 38.1 [36.0–43.0] | 38.0 [36.0–42.2] | 38.9 [35.8–44.0] | 0.575 |
| Albumin at transplant (g/dL), Mean (SD) | 3.34 (0.56) | 3.40 (0.53) | 3.12 (0.61) | 0.122 |
| MELD, mean (SD) | 23.6 (8.87) | 22.9 (9.02) | 25.8 (8.14) | 0.228 |
| Time on transplant waiting list, Median [IQR] | 109 [29, 269] | 112 [41, 363] | 59.0 [7.00, 180] | 0.183 |
| Type of transplant, n (%) | > 0.999 | |||
| Deceased donor | 63 (86.3%) | 49 (86.0%) | 14 (87.5%) | |
| Live donor | 10 (13.7%) | 8 (14.0%) | 2 (12.5%) | |
| Pre-transplant PMI, mean (SD) | 6.40 (1.87) | 6.35 (1.66) | 6.57 (2.47) | 0.739 |
| PMI Categories, n (%) | 0.026 | |||
| PMI ≤ 25% (≤ 4.83) | 17 (26.2%) | 13 (26.5%) | 4 (25.0%) | |
| PMI > 25%–50% (> 4.83–6.32) | 16 (24.6%) | 15 (30.6%) | 1 (6.25%) | |
| PMI > 50%–75% (> 6.32–7.29) | 16 (24.6%) | 8 (16.3%) | 8 (50.0%) | |
| PMI > 75% (> 7.29) | 16 (24.6%) | 13 (26.5%) | 3 (18.8%) | |
| Post-transplantation characteristics | ||||
| Immunosuppression type | ||||
| Tacrolimus, n (%) | 70 (95.9%) | 57 (100%) | 13 (81.2%) | 0.008 |
| Sirolimus, n (%) | 7 (9.59%) | 6 (10.5%) | 1 (6.25%) | 0.664 |
| Everolimus, n (%) | 11 (15.1%) | 8 (14.0%) | 3 (18.8%) | 0.679 |
| MMF/CellCept, n (%) | 63 (86.3%) | 51 (89.5%) | 12 (75.0%) | 0.211 |
| Prednisone, n (%) | 2 (2.74%) | 2 (3.51%) | 0 (0.00%) | > 0.999 |
| Postoperative Complications | ||||
| Infections, n (%) | 27 (37.0%) | 20 (35.1%) | 7 (43.8%) | 0.733 |
| Pneumonia, n (%) | 4 (5.48%) | 3 (5.26%) | 1 (6.25%) | > 0.999 |
| Biliary stricture, n (%) | 4 (5.48%) | 4 (7.02%) | 0 (0.00%) | 0.591 |
| Vascular complications, n (%) | 26 (35.6%) | 18 (31.6%) | 8 (50.0%) | 0.287 |
| Cardiovascular events, n (%) | 9 (12.3%) | 7 (12.3%) | 2 (12.5%) | > 0.999 |
| Graft failure, n (%) | 3 (4.11%) | 1 (1.75%) | 2 (12.5%) | 0.132 |
| Number of postoperative complications, Median [IQR] | 1.00 [0.00–2.00] | 1.00 [0.00–2.00] | 2.00 [1.00–2.00] | 0.095 |
| Post-Transplant Outcomes | ||||
| Post-transplant Albumin at 6 months (g/dL), Median [IQR] | 3.80 [3.50–4.00] | 3.80 [3.60–4.05] | 3.30 [3.10–3.95] | 0.043 |
| Post-transplant BMI, Median [IQR] | 38.1 [36.0–43.0] | 38.0 [36.0–42.2] | 38.9 [35.8–44.0] | 0.575 |
| Length of ICU stay (days), Median [IQR] | 3.00 [2.00–7.00] | 3.00 [2.00–5.00] | 5.50 [3.00–24.5] | 0.064 |
| Length of hospital stay (days), Median [IQR] | 12.0 [9.00–18.0] | 12.0 [9.00–16.0] | 17.5 [8.75–38.8] | 0.171 |
HDL high-density lipoprotein, HCC hepatocellular carcinoma, BMI body mass index, MELD model for end-stage liver disease, PMI psoas muscle index, MMF mycophenolate mofetil, ICU intensive care unit, IQR interquartile range, SD standard deviation
Of those transplanted, 78% survived and 22% died post-transplant, respectively. Compared to those who died, a higher proportion of those who survived had high triglycerides at transplantation (19% vs. 51%, p = 0.045) and were in the 25%–50% PMI quartile (> 4.83–6.32) (6.3% vs. 31%, overall p = 0.026). The two patient groups did not differ in other characteristics.
Post-transplant Clinical Characteristics
Tacrolimus (96%) and MMF/CellCept (86%) were the most frequently used immunosuppressants, and infections (37%) followed by vascular complications (36%) were the most frequent postoperative complications. Compared to patients who died post-transplant, patients who lived had a higher proportion prescribed tacrolimus (100% vs. 81%, p = 0.008) and a higher median 6-month post-transplant albumin (3.80 [3.60–4.05] vs. 3.30 [3.10–3.95], p = 0.043). The two patient groups did not differ in other immunosuppressants, postoperative complications, post-transplant BMI, or length of intensive care unit stay or hospital stay.
Psoas Muscle Index (PMI) Over Time
A linear mixed-effects model demonstrated a significant decrease in PMI from pre-transplant to 6 months (β = − 0.60; p = 0.002) and to 1 year (β = − 0.46; p = 0.015) (Table 2). While PMI remained lower at 3 years, this change did not reach statistical significance, likely due to a smaller sample size at year 3.
Table 2.
Linear mixed-effects model for PMI change over time
| Characteristic | Beta | 95% CI | p value |
|---|---|---|---|
| Pre-transplant | – | – | |
| Post 6-month | − 0.60 | − 0.98, − 0.22 | 0.002 |
| Post 1-year | − 0.46 | − 0.83, − 0.09 | 0.015 |
| Post 3-year | − 0.52 | − 1.1, 0.04 | 0.070 |
Pre-transplant was used as the reference level. The model was adjusted for patient status. A beta coefficient < 0 indicates PMI lower than baseline. PMI: psoas muscle index, CI confidence interval
PMI and Mortality
PMI trajectories by survival status showed that patients who survived had a slight decline in PMI followed by relative stabilization (Fig. 1), whereas those who died exhibited more pronounced declines in PMI.
Fig.1.
PMI Change over time by post-transplant Status. PMI: psoas muscle index
Among patients who survived, there were no statistically significant changes between pre-transplant PMI and post-transplant PMI at 1 year, and pre-transplant PMI and post-transplant PMI at 3 years (all p values > 0.05) (Table 3). Similarly, there were no statistically significant changes in PMI (all p values > 0.05) among patients who died, although median PMI remained numerically lower at 3 years in this group.
Table 3.
Comparisons between pre- and post-transplant PMI time points (6 Months, 1 Year, and 3 Years) among patients who survived and died
| Time point A vs Time point B | Time Point A | Time point B | p value | p value (Adjusted) | N | |
|---|---|---|---|---|---|---|
| Patients Who Survived | ||||||
| Pre-transplant vs. Post 6-month | 6.88 (1.85) | 6.29 (2.05) | 0.082 | 0.25 | 17 | |
| Pre-transplant vs. Post 1-year | 6.48 (1.66) | 6.10 (2.24) | 0.19 | 0.29 | 21 | |
| Pre-transplant vs. Post 3-year | 5.41 [4.96, 6.63] | 4.83 [4.26, 6.49] | 0.29 | 0.29 | 7 | |
| Patients Who Died | ||||||
| Pre-transplant vs. Post 6-month | 6.29 [4.20, 7.13] | 4.61 [3.95, 6.33] | 0.15 | 0.15 | 8 | |
| Pre-transplant vs. Post 1-year | 5.50 [3.94, 6.92] | 5.10 [3.49, 6.04] | 0.063 | 0.13 | 6 |
Statistics presented as Mean (SD) or Median [25th, 75th]. The paired t-test or the Wilcoxon signed-rank test was used. P-value was adjusted using the Benjamini–Hochberg method. There were too few observations to compare pre-transplant vs. Post 3-year among patients who died
PMI psoas muscle index
Univariate logistic regression (Table 4) revealed no statistically significant associations between pre-transplant PMI, post-transplant PMI, or post–pre-PMI difference in mortality (all p values > 0.05). Demographic and clinical characteristics stratified by pre-transplant PMI quartiles are presented in Table 5; sex and diabetes differed significantly across PMI quartiles.
Table 4.
Univariate logistic regression: mortality
| Characteristic | N | OR | 95% CI | p value |
|---|---|---|---|---|
| Psoas muscle mass pre-transplant | 25 | 0.78 | 0.48, 1.19 | 0.26 |
| Psoas muscle mass post-transplant 6-month | 25 | 0.79 | 0.49, 1.19 | 0.29 |
| Post 6-month—Pre PMI differences | 25 | 1.00 | 0.48, 2.13 | > 0.99 |
OR odds ratio, CI confidence interval
Table 5.
Demographic and clinical characteristics by quartiles of pre-transplant PMI
| [ALL] | < = 25% (< = 4.83) | < 25–50% (< 4.83–6.32) | < 50–75% (< 6.32–7.29) | > 75% (> 7.29) | p value | N | |
|---|---|---|---|---|---|---|---|
| N = 65 | N = 17 | N = 16 | N = 16 | N = 16 | |||
| Age at transplant, Mean (SD) | 59.3 (8.11) | 59.9 (8.95) | 57.2 (7.04) | 62.5 (6.95) | 57.5 (8.83) | 0.220 | 65 |
| Sex, N (%): | 0.012 | 65 | |||||
| Male | 31 (47.7%) | 3 (17.6%) | 8 (50.0%) | 8 (50.0%) | 12 (75.0%) | ||
| Female | 34 (52.3%) | 14 (82.4%) | 8 (50.0%) | 8 (50.0%) | 4 (25.0%) | ||
| Race, N (%): | 1.000 | 65 | |||||
| Black/African American | 3 (4.62%) | 1 (5.88%) | 1 (6.25%) | 1 (6.25%) | 0 (0.00%) | ||
| Caucasian/white | 62 (95.4%) | 16 (94.1%) | 15 (93.8%) | 15 (93.8%) | 16 (100%) | ||
| BMI at time of transplant, Median [25th;75th] | 38.0 [36.0;42.0] | 36.5 [35.0;44.5] | 36.6 [35.1;43.1] | 39.2 [37.6;41.3] | 38.0 [36.2;38.8] | 0.640 | 65 |
| Smoking history, N (%): | 0.462 | 64 | |||||
| Never or former | 59 (92.2%) | 17 (100%) | 15 (93.8%) | 14 (87.5%) | 13 (86.7%) | ||
| Current | 5 (7.81%) | 0 (0.00%) | 1 (6.25%) | 2 (12.5%) | 2 (13.3%) | ||
| History of HCC in the year before transplant, N (%): | 0.380 | 65 | |||||
| No | 57 (87.7%) | 15 (88.2%) | 16 (100%) | 13 (81.2%) | 13 (81.2%) | ||
| Yes | 8 (12.3%) | 2 (11.8%) | 0 (0.00%) | 3 (18.8%) | 3 (18.8%) | ||
| Diabetes, N (%): | 0.003 | 65 | |||||
| No | 20 (30.8%) | 8 (47.1%) | 4 (25.0%) | 8 (50.0%) | 0 (0.00%) | ||
| Yes | 45 (69.2%) | 9 (52.9%) | 12 (75.0%) | 8 (50.0%) | 16 (100%) | ||
| Hypertension, N (%): | 0.825 | 65 | |||||
| No | 11 (16.9%) | 3 (17.6%) | 4 (25.0%) | 2 (12.5%) | 2 (12.5%) | ||
| Yes | 54 (83.1%) | 14 (82.4%) | 12 (75.0%) | 14 (87.5%) | 14 (87.5%) | ||
| Obesity, N (%): | 1.000 | 65 | |||||
| No | 1 (1.54%) | 1 (5.88%) | 0 (0.00%) | 0 (0.00%) | 0 (0.00%) | ||
| Yes | 64 (98.5%) | 16 (94.1%) | 16 (100%) | 16 (100%) | 16 (100%) | ||
| HDL < 40 mg/dL for men and < 50 mg/dL for women, N (%): | 0.071 | 65 | |||||
| No | 30 (46.2%) | 12 (70.6%) | 7 (43.8%) | 7 (43.8%) | 4 (25.0%) | ||
| Yes | 35 (53.8%) | 5 (29.4%) | 9 (56.2%) | 9 (56.2%) | 12 (75.0%) | ||
| Triglyceride > 150, N (%): | 0.226 | 65 | |||||
| No | 39 (60.0%) | 10 (58.8%) | 8 (50.0%) | 13 (81.2%) | 8 (50.0%) | ||
| Yes | 26 (40.0%) | 7 (41.2%) | 8 (50.0%) | 3 (18.8%) | 8 (50.0%) | ||
| Number of metabolic syndrome risks (continuous), Median [25th;75th] | 3.00 [3.00;4.00] | 3.00 [2.00;4.00] | 3.00 [3.00;4.25] | 3.00 [2.75;4.00] | 4.00 [3.75;5.00] | 0.010 | 65 |
| Number of metabolic syndrome risks (categorical), N (%): | 0.128 | 65 | |||||
| 1 | 2 (3.08%) | 1 (5.88%) | 0 (0.00%) | 1 (6.25%) | 0 (0.00%) | ||
| 2 | 9 (13.8%) | 4 (23.5%) | 2 (12.5%) | 3 (18.8%) | 0 (0.00%) | ||
| 3 | 23 (35.4%) | 7 (41.2%) | 7 (43.8%) | 5 (31.2%) | 4 (25.0%) | ||
| 4 | 20 (30.8%) | 4 (23.5%) | 3 (18.8%) | 7 (43.8%) | 6 (37.5%) | ||
| 5 | 11 (16.9%) | 1 (5.88%) | 4 (25.0%) | 0 (0.00%) | 6 (37.5%) | ||
| metabolic syndrome (cutoff > = 1), N (%): Yes | 65 (100%) | 17 (100%) | 16 (100%) | 16 (100%) | 16 (100%) | 65 | |
| metabolic syndrome (cutoff > = 2), N (%): | 1.000 | 65 | |||||
| 1 | 2 (3.08%) | 1 (5.88%) | 0 (0.00%) | 1 (6.25%) | 0 (0.00%) | ||
| > = 2 | 63 (96.9%) | 16 (94.1%) | 16 (100%) | 15 (93.8%) | 16 (100%) | ||
| HCV status, N (%): | 0.321 | 65 | |||||
| never | 62 (95.4%) | 17 (100%) | 15 (93.8%) | 14 (87.5%) | 16 (100%) | ||
| resolved | 3 (4.62%) | 0 (0.00%) | 1 (6.25%) | 2 (12.5%) | 0 (0.00%) | ||
| HBV status, N (%): | 0.035 | 65 | |||||
| Vaccinated | 60 (92.3%) | 17 (100%) | 15 (93.8%) | 12 (75.0%) | 16 (100%) | ||
| Chronic | 1 (1.54%) | 0 (0.00%) | 0 (0.00%) | 1 (6.25%) | 0 (0.00%) | ||
| Resolved | 4 (6.15%) | 0 (0.00%) | 1 (6.25%) | 3 (18.8%) | 0 (0.00%) | ||
| Time on the transplant waiting list (days), Median [25th;75th] | 109 [27.0;269] | 93.5 [17.2;218] | 154 [78.0;429] | 53.5 [5.25;117] | 151 [74.8;560] | 0.063 | 64 |
| Type of transplant, N (%): | 0.411 | 65 | |||||
| Deceased donor | 57 (87.7%) | 15 (88.2%) | 13 (81.2%) | 16 (100%) | 13 (81.2%) | ||
| Live donor | 8 (12.3%) | 2 (11.8%) | 3 (18.8%) | 0 (0.00%) | 3 (18.8%) | ||
| MELD score at time of transplant, Mean (SD) | 24.0 (8.86) | 27.8 (8.41) | 22.9 (8.19) | 26.3 (9.57) | 18.7 (6.89) | 0.013 | 65 |
| Albumin level at time of transplant, Mean (SD) | 3.32 (0.53) | 3.20 (0.52) | 3.42 (0.47) | 3.22 (0.60) | 3.42 (0.54) | 0.479 | 65 |
| Albumin 6 months, Median [25th;75th] | 3.80 [3.50;4.00] | 3.70 [3.40;4.10] | 3.85 [3.60;4.03] | 4.00 [3.55;4.15] | 3.80 [3.52;4.00] | 0.802 | 58 |
| Albumin 1 year, Mean (SD) | 3.83 (0.44) | 3.73 (0.55) | 3.86 (0.43) | 3.89 (0.37) | 3.88 (0.37) | 0.754 | 54 |
| Albumin 3 years, Mean (SD) | 3.88 (0.38) | 3.88 (0.54) | 3.81 (0.26) | 3.78 (0.35) | 4.07 (0.24) | 0.583 | 28 |
| Albumin 5 years, Mean (SD) | 3.85 (0.40) | 3.74 (0.40) | 3.83 (0.49) | 4.10 (.) | 4.20 (.) | 0.741 | 11 |
| Psoas muscle mass pre-transplant, Mean (SD) | 6.40 (1.87) | 4.22 (0.65) | 5.80 (0.46) | 6.87 (0.36) | 8.86 (1.28) | < 0.001 | 65 |
| Psoas muscle index post-transplant 6 months, Mean (SD) | 5.97 (2.17) | 3.84 (0.90) | 5.08 (1.42) | 6.08 (1.48) | 8.21 (1.52) | < 0.001 | 25 |
| Psoas muscle index post-transplant 1 year, Mean (SD) | 5.88 (2.27) | 3.70 (0.82) | 5.30 (2.01) | 5.78 (1.19) | 8.37 (1.42) | < 0.001 | 27 |
| Psoas muscle index post-transplant 3 year, Mean (SD) | 5.38 (1.50) | 4.41 (0.59) | 5.84 (1.76) | 5.61 (2.57) | 6.40 (.) | 0.659 | 9 |
| Length of ICU stay after transplant (days), Median [25th;75th] | 3.00 [2.00;6.00] | 3.00 [3.00;15.0] | 4.50 [3.00;6.00] | 3.00 [2.00;5.50] | 3.00 [2.00;5.00] | 0.355 | 65 |
| Length of hospital stay after transplant (days), Median [25th;75th] | 12.0 [9.00;18.0] | 15.0 [9.00;28.0] | 10.5 [8.00;13.5] | 11.5 [9.75;22.8] | 11.5 [8.75;15.0] | 0.444 | 65 |
| Immunosuppression type: Tacrolimus, N (%): | 0.037 | 65 | |||||
| No | 3 (4.62%) | 0 (0.00%) | 0 (0.00%) | 3 (18.8%) | 0 (0.00%) | ||
| Yes | 62 (95.4%) | 17 (100%) | 16 (100%) | 13 (81.2%) | 16 (100%) | ||
| Immunosuppression type: Sirolimus, N (%): | 0.380 | 65 | |||||
| No | 60 (92.3%) | 14 (82.4%) | 15 (93.8%) | 15 (93.8%) | 16 (100%) | ||
| Yes | 5 (7.69%) | 3 (17.6%) | 1 (6.25%) | 1 (6.25%) | 0 (0.00%) | ||
| Immunosuppression type: Everolimus, N (%): | 0.746 | 65 | |||||
| No | 55 (84.6%) | 15 (88.2%) | 14 (87.5%) | 14 (87.5%) | 12 (75.0%) | ||
| Yes | 10 (15.4%) | 2 (11.8%) | 2 (12.5%) | 2 (12.5%) | 4 (25.0%) | ||
| Immunosuppression type: mycophenolate mofotil), N (%): | 0.237 | 65 | |||||
| No | 10 (15.4%) | 1 (5.88%) | 2 (12.5%) | 5 (31.2%) | 2 (12.5%) | ||
| Yes | 55 (84.6%) | 16 (94.1%) | 14 (87.5%) | 11 (68.8%) | 14 (87.5%) | ||
| Immunosuppression type: prednisone, N (%): | 1.000 | 65 | |||||
| No | 63 (96.9%) | 16 (94.1%) | 16 (100%) | 16 (100%) | 15 (93.8%) | ||
| Yes | 2 (3.08%) | 1 (5.88%) | 0 (0.00%) | 0 (0.00%) | 1 (6.25%) | ||
| Number of Immunosuppression type (continuous), Median [25th;75th] | 2.00 [2.00;2.00] | 2.00 [2.00;2.00] | 2.00 [2.00;2.00] | 2.00 [1.75;2.00] | 2.00 [2.00;2.00] | 0.349 | 65 |
| Number of Immunosuppression type (categorical), N (%): | 0.319 | 65 | |||||
| 0 | 3 (4.62%) | 0 (0.00%) | 0 (0.00%) | 3 (18.8%) | 0 (0.00%) | ||
| 1 | 5 (7.69%) | 1 (5.88%) | 2 (12.5%) | 1 (6.25%) | 1 (6.25%) | ||
| 2 | 45 (69.2%) | 12 (70.6%) | 11 (68.8%) | 10 (62.5%) | 12 (75.0%) | ||
| 3 | 9 (13.8%) | 2 (11.8%) | 3 (18.8%) | 2 (12.5%) | 2 (12.5%) | ||
| 4 | 3 (4.62%) | 2 (11.8%) | 0 (0.00%) | 0 (0.00%) | 1 (6.25%) | ||
| Immunosuppression type (cutoff > = 1), N (%): | 0.042 | 65 | |||||
| No | 3 (4.62%) | 0 (0.00%) | 0 (0.00%) | 3 (18.8%) | 0 (0.00%) | ||
| Yes | 62 (95.4%) | 17 (100%) | 16 (100%) | 13 (81.2%) | 16 (100%) | ||
| Postoperative complications: Infections, N (%) | 0.905 | 65 | |||||
| No | 41 (63.1%) | 11 (64.7%) | 9 (56.2%) | 10 (62.5%) | 11 (68.8%) | ||
| Yes | 24 (36.9%) | 6 (35.3%) | 7 (43.8%) | 6 (37.5%) | 5 (31.2%) | ||
| Postoperative complications: pneumonia, N (%): | 0.310 | 65 | |||||
| No | 62 (95.4%) | 17 (100%) | 16 (100%) | 15 (93.8%) | 14 (87.5%) | ||
| Yes | 3 (4.62%) | 0 (0.00%) | 0 (0.00%) | 1 (6.25%) | 2 (12.5%) | ||
| Postoperative complications: biliary stricture, N (%): | 0.176 | 65 | |||||
| No | 61 (93.8%) | 14 (82.4%) | 15 (93.8%) | 16 (100%) | 16 (100%) | ||
| Yes | 4 (6.15%) | 3 (17.6%) | 1 (6.25%) | 0 (0.00%) | 0 (0.00%) | ||
| Postoperative complications: vascular complications, N (%): | 0.613 | 65 | |||||
| No | 41 (63.1%) | 12 (70.6%) | 10 (62.5%) | 8 (50.0%) | 11 (68.8%) | ||
| Yes | 24 (36.9%) | 5 (29.4%) | 6 (37.5%) | 8 (50.0%) | 5 (31.2%) | ||
| Postoperative complications: cardiovascular events, N (%): | 0.627 | 65 | |||||
| No | 57 (87.7%) | 14 (82.4%) | 15 (93.8%) | 13 (81.2%) | 15 (93.8%) | ||
| Yes | 8 (12.3%) | 3 (17.6%) | 1 (6.25%) | 3 (18.8%) | 1 (6.25%) | ||
| Postoperative complications: graft failure, N (%): | 0.715 | 65 | |||||
| No | 62 (95.4%) | 17 (100%) | 15 (93.8%) | 15 (93.8%) | 15 (93.8%) | ||
| Yes | 3 (4.62%) | 0 (0.00%) | 1 (6.25%) | 1 (6.25%) | 1 (6.25%) | ||
| Postoperative complications: other, N (%): | 0.559 | 65 | |||||
| No | 47 (72.3%) | 10 (58.8%) | 12 (75.0%) | 12 (75.0%) | 13 (81.2%) | ||
| Yes | 18 (27.7%) | 7 (41.2%) | 4 (25.0%) | 4 (25.0%) | 3 (18.8%) | ||
| Number of postoperative complications (continuous), Median [25th;75th] | 1.00 [0.00;2.00] | 2.00 [1.00;2.00] | 1.00 [0.75;2.00] | 1.00 [1.00;2.00] | 1.00 [0.00;2.00] | 0.645 | 65 |
| Number of postoperative complications (categorical), N (%): | 0.296 | 65 | |||||
| 0 | 17 (26.2%) | 4 (23.5%) | 4 (25.0%) | 2 (12.5%) | 7 (43.8%) | ||
| 1 | 20 (30.8%) | 4 (23.5%) | 5 (31.2%) | 7 (43.8%) | 4 (25.0%) | ||
| 2 | 21 (32.3%) | 8 (47.1%) | 6 (37.5%) | 5 (31.2%) | 2 (12.5%) | ||
| 3 | 6 (9.23%) | 0 (0.00%) | 1 (6.25%) | 2 (12.5%) | 3 (18.8%) | ||
| 4 | 1 (1.54%) | 1 (5.88%) | 0 (0.00%) | 0 (0.00%) | 0 (0.00%) | ||
| postoperative complications (cutoff > = 1), N (%): | 0.297 | 65 | |||||
| No | 17 (26.2%) | 4 (23.5%) | 4 (25.0%) | 2 (12.5%) | 7 (43.8%) | ||
| Yes | 48 (73.8%) | 13 (76.5%) | 12 (75.0%) | 14 (87.5%) | 9 (56.2%) | ||
| Death, N (%): | 0.039 | 65 | |||||
| No | 49 (75.4%) | 13 (76.5%) | 15 (93.8%) | 8 (50.0%) | 13 (81.2%) | ||
| Yes | 16 (24.6%) | 4 (23.5%) | 1 (6.25%) | 8 (50.0%) | 3 (18.8%) | ||
| Cause of death: infection, N (%): | 0.467 | 65 | |||||
| No | 62 (95.4%) | 16 (94.1%) | 16 (100%) | 14 (87.5%) | 16 (100%) | ||
| Yes | 3 (4.62%) | 1 (5.88%) | 0 (0.00%) | 2 (12.5%) | 0 (0.00%) | ||
| Cause of death: rejection, N (%): No | 65 (100%) | 17 (100%) | 16 (100%) | 16 (100%) | 16 (100%) | 65 | |
| Cause of death: bleeding, N (%): | 0.175 | 65 | |||||
| No | 63 (96.9%) | 17 (100%) | 16 (100%) | 14 (87.5%) | 16 (100%) | ||
| Yes | 2 (3.08%) | 0 (0.00%) | 0 (0.00%) | 2 (12.5%) | 0 (0.00%) | ||
| Cause of death: cardiovascular, N (%): | 0.101 | 65 | |||||
| No | 58 (89.2%) | 16 (94.1%) | 16 (100%) | 12 (75.0%) | 14 (87.5%) | ||
| Yes | 7 (10.8%) | 1 (5.88%) | 0 (0.00%) | 4 (25.0%) | 2 (12.5%) | ||
| Cause of death: cancer, N (%): | 0.164 | 65 | |||||
| No | 63 (96.9%) | 17 (100%) | 16 (100%) | 14 (87.5%) | 16 (100%) | ||
| Yes | 2 (3.08%) | 0 (0.00%) | 0 (0.00%) | 2 (12.5%) | 0 (0.00%) | ||
| Number of Cause of death (continuous), Median [25th;75th] | 0.00 [0.00;0.00] | 0.00 [0.00;0.00] | 0.00 [0.00;0.00] | 0.50 [0.00;1.00] | 0.00 [0.00;0.00] | 0.002 | 65 |
| Number of Cause of death (categorical), N (%): | 0.003 | 65 | |||||
| 0 | 53 (81.5%) | 15 (88.2%) | 16 (100%) | 8 (50.0%) | 14 (87.5%) | ||
| 1 | 10 (15.4%) | 2 (11.8%) | 0 (0.00%) | 6 (37.5%) | 2 (12.5%) | ||
| 2 | 2 (3.08%) | 0 (0.00%) | 0 (0.00%) | 2 (12.5%) | 0 (0.00%) | ||
| Cause of death (cutoff > = 1), N (%): | 0.003 | 65 | |||||
| No | 53 (81.5%) | 15 (88.2%) | 16 (100%) | 8 (50.0%) | 14 (87.5%) | ||
| Yes | 12 (18.5%) | 2 (11.8%) | 0 (0.00%) | 8 (50.0%) | 2 (12.5%) | ||
| Fatty liver diagnosed post-transplant, N (%): | 0.199 | 64 | |||||
| Yes | 11 (17.2%) | 4 (23.5%) | 3 (18.8%) | 0 (0.00%) | 4 (26.7%) | ||
| No | 53 (82.8%) | 13 (76.5%) | 13 (81.2%) | 16 (100%) | 11 (73.3%) | ||
| Diagnosis of HCC, N (%): | 0.597 | 65 | |||||
| No | 63 (96.9%) | 17 (100%) | 16 (100%) | 15 (93.8%) | 15 (93.8%) | ||
| Yes | 2 (3.08%) | 0 (0.00%) | 0 (0.00%) | 1 (6.25%) | 1 (6.25%) |
Discussion
Liver transplantation reverses some of the metabolic consequences of cirrhosis, but in terms of sarcopenia, data are scarce, results are not consistent, and clarification is needed. Sarcopenia in cirrhosis has been linked to numerous negative outcomes, notably higher wait-list and postoperative mortality, through increased infection and encephalopathy [8–10]. Mechanisms driving sarcopenia have been posited to be due to liver disease [8], and understanding muscle mass post-transplant is clinically relevant.
Sarcopenia reflects impaired immunity and physiological dysfunction and poses a risk for severe infections, sepsis and death in patients with cirrhosis, and is known to be one of the most common complications related to survival of patients with cirrhosis [11].
Muscular assessments using cross-sectional imaging obtained by computed tomography (CT) or magnetic resonance imaging (MRI) constitute objective and reproducible methods for nutritional assessment and detection of sarcopenia. Single abdominal CT or MRI cross-sectional images have emerged as a novel way to objectively and reproducibly assess nutritional status and detect muscle wasting in patients with cirrhosis [12].
CT and MRI have both been previously used in assessing psoas muscle area and have proven to be highly reproducible [13]. In our patient population, a majority of postoperative surveillance imaging was performed under CT. Software utilizing Hounsfield units was utilized to measure psoas muscle area (PMA) at L3. However, comparable software for PMA measurement on MRI was not available. Therefore, to reduce variations in data, only CT images were used in the assessment of PMA, with any postoperative MRI imaging being excluded from the data.
We examined the effects of sarcopenia on post-transplant mortality in liver patients with class 2 or higher obesity, by examining the psoas muscle index or PMI via CT imaging at L3. We found that sarcopenia worsened in the initial months after transplant, with PMI decreasing significantly from pre-transplant to 6 months and 1-year post-transplant. Other studies have shown persistent sarcopenia in the initial post-transplant months, and that post-transplant body weight increases were due to excess adipose tissue rather than excess of lean muscle mass [14].
Additionally, there are reports that sarcopenia rarely reverses post-transplant [6]. We conducted the study over longer periods than most, and we also found that PMI remained low at 3 years post-transplant, but this decrease was not statistically significant. There are data in the literature suggesting that muscle mass decline is most marked in the initial post-transplant period and either slows [15] or reverses later on [5, 16, 17]. In our study, loss of muscle mass remained low at 3 years without further decline or increase. However, our study numbers were not large, which may have limited statistical power.
Further, it is known that critically ill patients may have anasarca and more edema of muscle, falsely elevating their PMI and contributing to our results of a lack of statistical significance between those who survived and those who died because of their worse critical illness [18]. Sarcopenia cutoff values are lacking for patients with cirrhosis, and we did not utilize them to compare between the groups.
As liver transplant patients’ long-term survival improves, risks for late morbidity, such as cardiovascular risk factors, gain importance [19]. There are several strategies that are used to mitigate sarcopenia in patients with cirrhosis, pre- and post-transplantation, including supplemental nutrition and exercise as well as developing treatments with molecular targets such as myostatin and mTOR, and antioxidants [8]. Further studies are needed to examine the clinical relevance of early postoperative decline in PMI, and the implications for the care of post-transplant patients in terms of timing and intensity of interventions to prevent and mitigate sarcopenia.
The reasons for persistent sarcopenia post-transplant are not fully understood. Nutritional status such as poor appetite and inadequate dietary intake with relatively short periods of fasting in patients with cirrhosis results in the breakdown of fat and muscle [21] and contributes to sarcopenia. Some have suggested that the post-transplant immunosuppression, especially with calcineurin inhibitors plays a role [7, 16], though the mechanisms accounting for this remain speculative. Animal models point to calcineurin as an important mediator of muscle growth [20], and calcineurin inhibitors have been posited to influence sarcopenia via increased myostatin [6], but other studies have failed to show an association between the degree of exposure to calcineurin inhibitors and post-transplant sarcopenia [6, 15].
Examining post-transplant immunosuppression, we found that patients who lived were significantly more likely to be on tacrolimus post-transplant. However, this must be interpreted cautiously, as our findings may be confounded. For example, it is unclear whether tacrolimus itself confers overall mortality benefit or if patients without contraindications to tacrolimus were healthier and therefore more likely to survive.
We found that pre-transplant PMI and 6-month post-transplant PMI were not significantly associated with mortality. However, our PMI trajectories by survival status suggest that patients who survived had a relative stabilization in PMI, whereas patients who died exhibited a pronounced decline in PMI. Sarcopenia in cirrhosis is linked to several adverse outcomes. Patients with cirrhosis who have sarcopenia have higher mortality than those without sarcopenia, potentially through an increased risk of infection and encephalopathy [8–10]. However, the impact of sarcopenia after transplant on mortality is less clear, with conflicting data regarding an association or trend between sarcopenia and mortality [4, 6, 10, 14, 15, 22, 23].
Our results did not show a statistically significant association between PMI and mortality, which may be related to our limited sample size. In the literature, data point to potential impact of sarcopenia on mortality, though findings are heterogeneous and further research is needed. For example, Montano-Loza found that while muscle depletion was associated with increased length of stay after liver transplantation as well as bacterial infections in the initial post-transplant period, it was not associated with mortality [5]. Interestingly, however, this finding did not hold true for post-transplant sarcopenia. A subgroup analysis of patients who had data on follow-up of their sarcopenia after transplant showed that those whose sarcopenia had resolved had better survival compared to those whose sarcopenia persisted [5]. Similarly, Tsien and colleagues showed that worsening sarcopenia post-transplant had a trend toward higher mortality, although this result did not reach significance, likely due to small sample size [6]. Similarly, our small sample size may have constrained statistical significance. Our results highlight the need both for further study of the impact of sarcopenia on mortality, especially in the later post-transplant period, as well as the drivers of post-transplant sarcopenia and strategies to target these.
Our study has some limitations. As a retrospective, single-center study from a tertiary care center, the patients included may not be representative of the general population. Our PMI data were drawn from CT scans done for indications other than measuring PMI, introducing selection bias, with the potential for sicker patients to receive a higher number of CT scans, affecting our analysis of both PMI trajectories as well as survival associations. Moreover, the irregular observation timing from using imaging exams done for patient indications rather than at standardized intervals introduces bias into our longitudinal analysis. Lack of nutritional data pre- and post-transplant, and univariate analysis, introducing potential confounders such as disease severity, perioperative complications, length of hospitalization, or readmissions are also limitations. Our small sample size is a significant limitation, with our data representing a preliminary analysis. We intend to conduct an iterative study in the future that will include more patients beyond 2023. Moreover, further studies are needed to better understand both the clinical course of sarcopenia in the initial and later post-transplant periods as well as the impact of post-transplant sarcopenia on long-term mortality. While the skeletal muscle area at L3 normalized to height is more strongly correlated with total body protein than PMI [24], PMI has shown utility in investigating sarcopenia and mortality in post-LT patients [25, 26], and has the advantage of being calculated quickly without specialized software, decreasing barriers to utilization. Our study also has notable strengths. We included long-term outcomes up to 3 years of post-transplant, which are increasingly clinically relevant considering current improved long-term survival of liver transplant patients. Our preliminary data examining mortality, delineating the impact of pre-transplant and post-transplant PMI versus PMI trajectory also represent a strength of our study.
In conclusion, our study addresses gaps in the existing literature on long-term post-transplant effects of liver transplantation on muscle mass in patients with ≥ class 2 obesity. Our findings that PMI worsened significantly at 6 months and 1 year of post-transplant raise important questions on the optimal timing of interventions to mitigate post-transplant sarcopenia, though further research is needed to investigate the clinical significance of postoperative decline in PMI. We did not find a statistically significant association between PMI and mortality, possibly due to sample-size limitations, and potentially to muscle edema in patients who died, falsely elevating their PMI, highlighting the need for further studies.
Acknowledgments
Drs. Omar T. Sims and Jamile Wakim-Fleming contributed equally as co-senior authors
Author Contributions
Baila Elkin and Mohammad Alabbas contributed to study conception and design, data interpretation, manuscript drafting, and critical revision of the manuscript. Qijun Yang and Omar T. Sims contributed to statistical analysis, data interpretation, and revision of the manuscript. Blake Brandon and Christopher Coppa contributed to imaging methodology, radiologic data interpretation, and revision of the manuscript. Manal Abdelmalek contributed to data interpretation and critical revision of the manuscript. Jamile Wakim-Fleming contributed to study design, supervision, data interpretation, and critical revision of the manuscript. All authors reviewed and approved the final manuscript.
Funding
The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.
Data Availability
No datasets were generated or analyzed during the current study.
Declarations
Conflict of interest
The authors declare no competing interests.
Ethical approval
This retrospective study involving human participants was approved by the Cleveland Clinic Institutional Review Board and was performed in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki Declaration and its later amendments
Informed consent
The requirement for informed consent was waived by the Institutional Review Board because of the retrospective nature of the study
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
No datasets were generated or analyzed during the current study.