Clin Mol Hepatol > Volume 30(3); 2024 > Article
Hwang, Hwang, Shin, Kim, Kang, Yoo, Choi, Lee, Jun, and Cho: Bariatric intervention improves metabolic dysfunction-associated steatohepatitis in patients with obesity: A systematic review and meta-analysis



Bariatric intervention has been reported to be an effective way to improve metabolic dysfunction-associated steatotic liver disease (MASLD) in obese individuals. The current systemic review aimed to assess the changes in MRI-determined hepatic proton density fat fraction (MRI-PDFF) and nonalcoholic fatty liver disease activity score (NAS) after bariatric surgery or intragastric balloon/gastric banding in MASLD patients with obesity.


We searched various databases including PubMed, OVID Medline, EMBASE, and Cochrane Library. Primary outcomes were the changes in intrahepatic fat on MRI-PDFF and histologic features of metabolic dysfunction-associated steatohepatitis (MASH).


Thirty studies with a total of 3,134 patients were selected for meta-analysis. Bariatric intervention significantly reduced BMI (ratio of means, 0.79) and showed 72% reduction of intrahepatic fat on MRI-PDFF at 6 months after bariatric intervention (ratio of means, 0.28). Eight studies revealed that NAS was reduced by 60% at 3–6 months compared to baseline, 40% at 12–24 months, and 50% at 36–60 months. Nineteen studies revealed that the proportion of patients with steatosis decreased by 44% at 3–6 months, 37% at 12–24 months, and 29% at 36–60 months; lobular inflammation by 36% at 12–24 months and 51% at 36–60 months; ballooning degeneration by 38% at 12–24 months; significant fibrosis (≥F2) by 18% at 12–24 months and by 17% at 36–60 months after intervention.


Bariatric intervention significantly improved MRI-PDFF and histologic features of MASH in patients with obesity. Bariatric intervention might be the effective alternative treatment option for patients with MASLD who do not respond to lifestyle modification or medical treatment.

Graphical Abstract


Metabolic dysfunction-associated steatotic liver disease (MASLD), previously known as nonalcoholic fatty liver disease (NAFLD), includes a spectrum of liver conditions, characterized by excessive fat in the liver, without proven secondary cause of hepatic fat accumulation. Although the pathophysiology of MASLD is not completely understood due to its complex and multifactorial nature, insulin resistance is considered to be a key factor driving the development of the disease [1]. Therefore, MASLD is thought to be a component of metabolic syndrome, which is a cluster of interconnected metabolic risk factors that increase the risk of developing type 2 diabetes mellitus (DM), hypertension, and cardiovascular disease [2]. Besides, it can gradually progress through various liver stages, from simple steatosis to metabolic dysfunction-associated steatohepatitis (MASH), previously known as nonalcoholic steatohepatitis (NASH), liver fibrosis, cirrhosis, and eventually liver failure or hepatocellular carcinoma over several years or even decades [3]. The prevalence of MASLD has risen alongside the increasing prevalence of obesity and metabolic syndrome worldwide, with significantly higher prevalence in specific population, such as approximately 50–90% in obese individuals and 47–63% in patients with type 2 DM [4]. Considering its high prevalence and the implications in public health, addressing MASLD is of paramount importance.
The primary goal in addressing MASLD begins with lifestyle management aimed at achieving a weight loss, the only validated approach for the condition. Weight loss of more than 7–10% has been demonstrated to effectively improve liver steatosis, inflammation, and fibrosis [5]. In addition to lifestyle modification, medication, such as GLP-1 receptor agonist or GLP-1/GIP dual receptor agonist (a novel medication yielding the most potent result in weight loss), is known to improve the histological findings in MASLD [6]. However, apart from the cases of potential treatment failure, sustaining the reduced weight can indeed pose challenges, even with the assistance of new medications, particularly among certain populations. In such populations, surgical intervention may play a pivotal role in treating MASLD. Bariatric intervention is among the most effective weight loss interventions for morbidly obese individuals, even over long-term; it improves metabolic parameters as well as liver steatosis and inflammation. As of now, its indication includes those with BMI >35 kg/m2, regardless of comorbidities, or those with BMI >30 kg/m2 with the presence of MASH, type 2 DM or failure of non-surgical intervention [7].
Several meta-analyses have showed significant metabolic and histological improvements after bariatric surgery [8-12]. However, concerns regarding the controversial results regarding the effectiveness in more advanced forms of MASLD, such as MASH, persist [13,14]. Moreover, despite liver biopsy being the gold standard for diagnosis of MASLD, it is invasive and potentially life-threatening procedure, prompting the exploration of non-invasive evaluation methods for MASLD, such as magnetic resonance imaging proton-density fat fraction (MRI-PDFF). MRI-PDFF has garnered significant recognition for its diagnostic value, demonstrating high sensitivity and specificity in the assessment of MASLD [15]. Although several studies investigating the association between bariatric intervention and MASLD, assessed by MRI-PDFF, have been published till date, no meta-analysis using this method has been conducted yet.
In this study, we conducted a systemic review to evaluate the changes in BMI, NAS, as well as intrahepatic fat composition measured by MRI-PDFF, following bariatric intervention in patients with MASLD.


Data sources and search strategy

The protocol for this systemic review was registered with PROSPERO (International Prospective Register of Systemic Reviews, CRD42041241243). The aim of this study is to identify the effect of bariatric intervention on MASLD, determined by histologic findings and/or MRI findings. This study was conducted along with others that identified the effect of exercise intervention on MASLD [16], or validated the accuracy of noninvasive scoring system in assessing liver fibrosis [17]. Study selection followed the Preferred Reporting Items for Systemic Review and Meta-analyses extension for Diagnostic Test Accuracy (PRISMA-DTA) statements [18]. We searched the Ovid-MEDLINE, EMBASE, KMBASE, Korean Studies Information Service System (KISS), and Cochrane library, covering the period from database inception, through January 1, 1997 to October 31, 2023. We only included papers published in English. The search keywords used were: metabolic dysfunction-associated steatotic liver disease, MASLD, metabolic dysfunction-associated steatohepatitis, MASH, nonalcoholic fatty liver disease, nonalcoholic fatty liver, NAFLD, nonalcoholic steatohepatitis, NASH, obesity/obese, bariatric surgery, intragastric balloon, and gastric banding.

Study selection and data extraction

Two researchers (Y.C. and S.H.K.) reviewed the screened papers independently, by their titles and abstracts, in the first screening. In the secondary screening, full text of the papers that passed the first screening was examined, providing specific reasons for any exclusions. During the process of literature selection, any discordance between the two clinical researchers was resolved through mutual consultation. In cases where a consensus could not be reached, the final decision was made by the research committee through a formal meeting. The study design, outcome measure (histology vs. MRI-PDFF), sample size, intervention, mean age, duration of follow-up, and BMI changes in each study were extracted as basal characteristics. The entire search process was administered by a professional statistician (M.Y.C. and D.L.).

Inclusion and exclusion criteria

The following criteria were required for studies to be selected: (1) patients who underwent bariatric surgery or intragastric balloon/gastric banding for obesity; and (2) those who were diagnosed with histologically proven MASLD or MASH designs included randomized controlled trials, cross-sectional studies, and cohort studies, both prospective and retrospective. Studies were excluded based on the following criteria: (1) case reports; (2) case series, in which less than five patients in total were involved; (3) reviews; (4) cell or animal studies; (5) studies on chronic viral hepatitis, such as hepatitis B or hepatitis C; (6) studies on human immunodeficiency virus; (7) studies on population with significant alcohol consumption; (8) studies with no histology result provided; or (9) pediatric studies.

Outcome assessed

Studies that reported at least one histologic or MRI variable were included in the analyses. All included studies presented baseline and follow-up BMI. Histologic variables are as follows: (1) NALFD activity score (NAS), which assesses the severity of inflammation and hepatocellular injury in liver biopsy [19], (2) Histologic features of MASH, including steatosis, lobular inflammation, ballooning degeneration, and fibrosis, and (3) worsening MASH. MRI variable includes the change in steatosis and BMI.

Quality assessment

We performed the quality assessment of the final selection of papers, based on key questions, using RoBANS tool for non-randomized controlled studies and Cochrane risk-of-bias tool for randomized controlled study. QUADAS-2 evaluation tool was used to evaluate the diagnostic accuracy. The following factors were checked: comparability of participants, selection of participants, confounding variables, measurement of exposure, blinding of outcome assessment, outcome evaluation, incomplete outcome data, and selective reporting. Publication bias was evaluated by a funnel plot for studies investigating populations with more than ten individuals. The certainty of the evidence was evaluated by Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach, which considers factors such as risk of bias, inconsistency of results, indirectness of evidence, imprecision, and publication bias.

Statistical analysis

The process of meta-analysis with paired ratio of means data and proportion data involved the estimation of Hedge’s corrected standardized mean difference, under the assumption of a random-effects model, to account for heterogeneity across the studies. The pooled effect estimates between pre- and post-operation within each study’s specific time frame were derived to measure the effect size, using Freeman-Tukey variant of the arcsine square root transformation, along with a 95% confidence interval (CI). To address the differences in follow-up periods across the selected studies, we categorized the studies according to the length of the follow-up time in further analyses. Analysis of each pooled data is shown in a forest plot. Heterogeneity of the studies was assessed by Cochrane’s Q test; I2 statistics higher than 50% was considered indicative of significant heterogeneity, and more than 75% was considered “high” heterogeneity. Next, sensitivity analyses and meta-regression were conducted to assess the influence of other factors on diagnostic accuracy across the studies with significant heterogeneity. Cochrane Review Manager version 5.4 (London, UK), R Foundation for Statistical Computing version 4.1.2 (Vienna, Austria), and GRADEpro GDT were used in the analysis, with a significance level set at a P-value less than 0.05.


Study characteristics

From January 1, 1997 to October 31, 2023, a total of 1,546 papers were identified through preliminary data searching using search keywords described in the Methods section. The numbers of papers from each database are as follows: Ovid-MEDLINE (n=593), KMBASE (n=5), EMBASE (n=845), KISS (n=11), and Cochrane library (n=92). After removal of duplicates (n=1,069), 246 papers were excluded based on the title only. In the first screening, two researchers independently reviewed the screened papers by their titles and abstracts (n=231), followed by exclusion of 156 papers after review. Furthermore, we thoroughly examined the full-text articles of the remaining studies (n=75), resulting in an additional exclusion of 46 studies. Finally, thirty studies were incorporated into this analysis (Fig. 1). Out of all these papers, twenty-four were evaluated through histological examination while the remaining six were assessed using MRI. General characteristics of the selected studies are presented in Table 1. A total of 3,134 patients from the studies were analyzed. It was noteworthy that only two were randomized controlled studies [20], whereas others employed a cross-sectional design. To address the difference in follow-up duration, we categorized the data into three time periods, as follows: 3–6 months, 12–24 months, and 36–60 months, for further analyses.

Impact of bariatric intervention on BMI and histology in MASH

A total of thirty studies showed a significant reduction in BMI except for one randomized controlled trial with small sample size [20]. BMI was reduced by 19% at a rate of 0.81 (95% CI, 0.71–0.92) at 3–6 months, by 28% at a rate of 0.72 (95% CI, 0.68–0.76) at 12–24 months, and by 27% at a rate of 0.73 (95% CI, 0.68–0.79) at 36–60 months after intervention (Fig. 2A). The overall NAS, before and after bariatric intervention, with the ratio of their mean values, was examined in seven studies (Supplementary Table 1). NAS was reduced by 60% at a rate of 0.40 (95% CI, 0.30–0.54) at 3–6 months, by 40% at a rate of 0.60 (95% CI, 0.40–0.89) at 12–24 months, and by 50% at a rate of 0.50 (95% CI, 0.35–0.70) at 24–60 months (Fig. 2B). In the study conducted by von Schönfels et al. [21], post-NAS revealed a value of 0, rendering the calculation of confidence interval unattainable. The results of the histology were evaluated according to Brunt’s criteria and Kleiner score [19]. Nineteen studies revealed that the proportion of patients with steatosis decreased by 44% at 3–6 months, 37% at 12–24 months, and 29% at 36–60 months (Fig. 2C); lobular inflammation by 33% at 3–6 months, 36% at 12–24 months, and 51% at 36–60 months (Fig. 2D); ballooning degeneration by 20% at 3–6 months, 38% at 12–24 months, and 18% at 36–60 months (Fig. 2E). Remarkably, the proportion of patients with stage 2 fibrosis or higher (≥F2), or with more advanced form of MASLD, was found to decrease by 18% at 12–24 months, and by 17% at 36–60 months after intervention, compared to that before the operation (Fig. 2F, Supplementary Table 2). Most of these analyses revealed the I2 statistics exceeding 75%, signifying substantial heterogeneity across the studies. Subsequent sensitivity analysis and meta-regression were conducted; however, the source of heterogeneity remained unclear (data not shown).

Impact of bariatric intervention intrahepatic fat measured by MRI-PDFF

Six studies showed significant reduction of intrahepatic fat in MRI-PDFF at six months after bariatric intervention (Table 2). Ratio of the means of pre-operative to post-operative MRI-PDFF was 0.28 (95% CI, 0.24–0.33), which implied that 72% of intrahepatic fat was reduced after intervention with 21% of BMI reduction (Fig. 3). We observed a borderline heterogeneity in BMI, but no heterogeneity was identified in steatosis measured by MRI-PDFF.

Mortality after bariatric surgery and MASH aggravation

Two studies reported mortality rate after the bariatric surgery, with pooled mortality rate of 13% (95% CI, 0.07–0.21). The other three studies reported cases in which MASLD worsened based on liver histologic examination after the surgery, with a pooled proportion of 6% (95% CI, 0.04–0.09) (Supplementary Table 3).

Quality of the selected studies

Out of a total of thirty studies, most studies showed low risk of bias, whereas a few showed moderate/high (Supplementary Figs. 1 and 2). To visually inspect the potential publication bias, we also created funnel plots for studies investigating populations with more than ten individuals where BMI was measured within 12–24 months. We found significant publication bias (Supplementary Fig. 3). To address this bias, we applied trim and fill method, confirming the correction of publication bias in the modified result. Notably, the adjusted effect size values remained consistent with the trend observed in the analysis using raw values. For populations with a follow-up period of 12–24 months, the GRADE assessment was used to rate the quality of evidence (Supplementary Table 4).


The current study aimed to comprehensively assess the impact of bariatric intervention on hepatic steatosis and MASH, with particular focus on presenting the association using a novel measure, MRI-PDFF, which, to the best of our knowledge, has not been reported till date. MASLD is one of the most common causes of chronic liver disease worldwide. While the complete pathophysiology remains unclear, insulin resistance is considered a pivotal factor of the disease development. This condition leads to an increase in free fatty acids released from adipose tissue, which subsequently move to the liver and are taken up by hepatocytes. Moreover, insulin resistance upregulates fatty acid transport proteins, impairs mitochondrial fatty acid oxidation, and alters the adipokine profile, all of which can accelerate hepatic fat accumulation and inflammation [22]. Hence, the primary treatment goal has been focused on improving insulin resistance by managing obesity, particularly central obesity, in MASLD. Lifestyle modification and, if indicated, medications targeting weight loss are valid options for initial management of the disease. Among the medical options, GLP-1 receptor agonist has shown superiority over other drugs in managing MASH. In case these approaches fail to achieve substantial weight loss, the consideration of bariatric intervention for obese patients would be justified.
However, whether the impact of weight loss extends to more advanced liver conditions, such as MASH or liver fibrosis, when inflammation in the liver progresses, has remained a long-standing controversy. This is probably due not only to the disease progressing to an irreversible stage but also to the liver’s inability to tolerate the lipotoxicity arising from the massive release of free fatty acids, mainly originating from visceral fat, following rapid weight loss, which is particularly evident in the early stage of bariatric surgery [23]. Nevertheless, several previous meta-analyses have found a favorable effect of the surgery on improving MASH [9-11]. Notably, Lee et al. [10] reported their meta-analysis, wherein histological worsening of MASLD after bariatric surgery was 12%. Our study showed, in line with the above studies, a pooled mortality rate of 13% within a pooled follow-up time of 30.8 months, and a pooled worsening MASH rate of 6%. It would be worth noting that the number of studies reporting post-surgery deaths was considerably limited. Thus, we emphasized that the potential risks associated with bariatric surgery should not be disregarded, especially in advanced liver disease.
We have presented robust evidence of the significant impact of bariatric intervention on MASH, which aligns with the findings from prior meta-analyses. Moreover, we assessed the risk of bariatric intervention, which was not routinely evaluated in prior studies, emphasizing that the potential risk should not be overlooked when considering intervention. Our approach involved not only considering the type of liver histology but also incorporating NAS, a comprehensive tool for assessing MASLD. This enabled us to evaluate the effect of bariatric intervention from multiple perspectives. Finally, we showed, for the first time, that MRI-PDFF is a reliable indicator for assessing MASLD for bariatric intervention, particularly in its early stages. While several imaging modalities have been proposed as alternatives to liver biopsy, due to its invasive nature, MRI-PDFF demonstrated excellent sensitivity and specificity in diagnosing relatively early-stage MASLD [15].
Our study has several limitations. First, we encountered considerable heterogeneity in most analyses, despite categorizing by follow-up period and other interventions. This result was consistent with the GRADE assessment in our post hoc analyses. This methodological limitation has been identified in previous studies as well, suggesting that differences in study design and/or population may have significantly impacted this high heterogeneity. Nonetheless, the consistent and substantial impact of bariatric intervention has been evident across various study methodologies, reducing doubts about the reliability of this study result. Second, despite our meta-analysis showing the reliability of MRI as an alternative to liver biopsy in bariatric intervention, it would be important to note that the applicability of MRI-PDFF in more advanced liver diseases, such as MASH or liver cirrhosis, still remains a subject of scrutiny. Its limitations in establishing consistent correlations of the severity of steatohepatitis with advanced liver diseases underscore the necessity for further research in this area. Third, our analysis did not include the individual biochemical measures. However, the assessment of liver function through laboratory findings was thoroughly analyzed in prior meta-analyses, prompting us to avoid redundancy. Finally, the absence of individual patient data restricted the extent of more comprehensive analyses.
In conclusion, this meta-analysis reaffirmed the efficacy of bariatric intervention in the improvement of MASH for patients with obesity and MASLD while also highlighting the robust reliability of MRI-PDFF in assessing hepatic steatosis after bariatric intervention. Our study further reported that the favorable impact of bariatric intervention on MASH patients with obesity, like significant liver fibrosis or cirrhosis, remains uncertain due to potential risks of exacerbating liver conditions.


This research was supported by the grants of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute, funded by the Ministry of Health & Welfare, Republic of Korea (HI22C1948), the National Research Foundation of Korea grant funded by the Korea government (2021R1A2C4001401), and the National Cancer Center, Korea (2210420).


Authors’ contribution
All authors substantially participated in the analysis, data interpretation and preparation of manuscript. JH and HH should be considered joint first author.
Conflicts of Interest
The authors have no conflicts to disclose.


Supplementary material is available at Clinical and Molecular Hepatology website (
Supplementary Table 1.
Ratio of means of NAS meta-analysis of bariatric intervention in obese patients
Supplementary Table 2.
The result of histology between pre- and post-bariatric intervention
Supplementary Table 3.
Mortality and worsening MASH after bariatric surgery
Supplementary Table 4.
GRADE certainty assessment summary of findings table
Supplementary Figure 1.
Risk of bias summary.
Supplementary Figure 2.
Risk of bias summary for review author’s judgment.
Supplementary Figure 3.
Funnel plots. BMI, body mass index.

Figure 1.
Flowchart of the study selection. Flowchart showing the process of study inclusion and exclusion in the systematic review. KMBASE, Korean Medical Database; KISS, Korean Studies Information Service System.

Figure 2.
Meta-analysis forest plot of BMI and histology. (A) BMI, (B) NAS by biopsy, (C) Steatosis, (D) Lobular inflammation, (E) Ballooning degeneration, and (F) Fibrosis (≥F2). (A) and (B): risk of means was reported. (C), (D), (E), and (F): proportion difference was reported. and indicate same cohort with different follow-up time frame. BMI, body mass index; NAS, nonalcoholic fatty liver disease activity score.

Figure 3.
Meta-analysis forest plot of BMI and MRI-PDFF. (A) BMI, and (B) Steatosis by MRI-PDFF. and indicate same cohort with different follow-up time frame. BMI, body mass index; MRI, magnetic resonance imaging; PDFF, proton density fat fraction.


Table 1.
General characteristics of 30 studies
Author (year) Study design Method No. of samples Intervention Mean age (years) Follow-up duration Pre-BMI Post-BMI
Aldoheyan et al. (2017) [24] Prospective cohort Histology 27 Bariatric surgery 35±8 3 months 44.6±7.8 34.2±6.3
Barker et al. (2006) [25] Prospective cohort Histology 19 Roux-en-Y gastric bypass (RYGBP) 48.6 (35–58) 21.4 months (13.3–31.7) 46.8±4.4 28.8±5.2
Caiazzo et al. (2014a) [26], Prospective cohort Histology 681 RYGBP 41.1±11.1 1 year 49.8±8.2 36.0±6.9
Caiazzo et al. (2014b) [26], Prospective cohort Histology 555 Adjustable gastric banding (AGB) 40.3±11.4 1 year 46.8±6.5 39.9±6.7
Chaim et al. (2020) [27] Prospective cohort Histology 895 Bariatric surgery 39.4±10.2 21±22 months 35.9±2.8 25.7±3.8
Esquivel et al. (2018) [28] Prospective cohort Histology 63 Sleeve gastrectomy (SG) 40±10 1 year 44.9±5.6 30.5±4.2
Fazel et al. (2007) [29] Prospective cohort Histology 43 Modified Jejunoileal bypass surgery 35±10 60 months 46±7 32±6
Furuya et al. (2007) [30] Prospective cohort Histology 18 RYGBP 46.6±7.3 2 years 51.7±7.4 31±2
Jaskiewicz et al. (2006) [31] Prospective cohort Histology 87 Bariatric surgery 40.7±10.0 41 months 46.7±8.8 N/A
Kral et al. (2004) [13] Prospective cohort Histology 689 Biliopancreatic diversion 36.9±9 41±25 months 47±8.4 31±7.9
Lassailly et al. (2020) [32] Prospective cohort Histology 180 Bariatric surgery 46.7±10.6 5 year 48.1±7.9 36.1±7.8
Lee et al. (2012) [20] Randomized controlled trial Histology 8 Intragastric balloon 43±19.8 6 months 30.3±4.2 28.8±3.01
Liu et al. (2007) [33] Retrospective cohort Histology 39 Laparoscopic RYGBP 41.4±9 18 (6-41) months 47.7±6.2 29.5±5.6
Mathurin et al. (2009) [34] Prospective cohort Histology 381 Band, bypass, RYGBP 41.5±9.6 1 year, 5 years 50±7.8 39±8.2 (1 year), 37.7±8.4 (5 years)
Mattar et al. (2005) [35] Retrospective cohort Histology 70 Laparoscopic RYGBP, Laparoscopic AGB, LSG 49±9 15±9 months 56±11 39±10
Meinhardt et al. (2006) [36] Prospective cohort Histology 50 End-to-side JIB 37.9±7.6 67.0±42.8 months 52.8±7.5 35.7±7.5
Moretto et al. (2012) [37] Retrospective cohort Histology 78 Gastric bypass 39.5±11.4 1 year 45.4±8.1 29.7±3.9 & 29±6.5 (two groups)
Mottin et al. (2005) [38] Prospective cohort Histology 186 RYGBP 35.6±1.1 1 year 46.7±0.88 N/A
Parker et al. (2017) [39] Prospective cohort Histology 106 RYGBP 46±11 N/A 48±8 N/A
Russo et al. (2021) [40] Prospective cohort Histology 37 Biliopancreatic diversion 42±9 5 years 49.3±5.9 32.8±6.4
Salman et al. (2020) [41] Prospective cohort Histology 94 LSG 41.4±7.6 1 year 44.54±5.45 34.23±2.66
Salman et al. (2021) [42] Prospective cohort Histology 67 Gastric bypass 44.4±5.7 15 months 44.2±4.3 34.4±2.7
Taitano et al. (2015) [14] Prospective cohort Histology 160 Laparoscopic AGB or RYGBP 47±12 31±26 months 52±10 33±8
Verrasto et al. (2023a) [43], Randomized controlled trial Histology 77 RYGBP 46.4±8.5 1 year 43.39±4.14 29.70±4.26
Verrasto et al. (2023b) [43], Randomized controlled trial Histology 79 SG 46.8±8.8 1 year 40.76±3.74 30.82±4.08
von Schönfels et al. (2018) [21] Retrospective cohort Histology 257 SG or RYGBP 42±15 6 months 49.9±11.3 37±9
Folini et al. (2014) [44] Prospective cohort MR PDFF 18 Intragastric balloon or gastric banding 43.6±12.2 6 months 42.8±7.1 38.2±6.19
Hedderich et al. (2017) [45] Prospective cohort MR PDFF 19 RYGBP + LSG 41.4±12.5 6 months 44.1±5.2 33.8±5.6
Luo et al. (2018) [46] Prospective cohort MR PDFF 124 LSG, LRYGBP 50.9±10.8 6 months 45.3±5.9 34.4±5.1
Mamidipalli et al. (2020) [47] Prospective cohort MR PDFF 54 RYGBP or LSG 52±12 6 months 42.3±5.0 34.3±4.7
Pooler et al. (2019) [48] Retrospective cohort MR PDFF 50 Gastric bypass, sleeve, band, or plication 51±11.2 6 months 44.9±6.5 34.5±5.4
Tan et al. (2023) [49] Prospective cohort MR PDFF 9 LSG 45.1±9.0 6 months 39.7±5.3 32.4±4.8

BMI, body mass index; RYGB, Roux-en-Y gastric bypass; LSG, laparoscopic sleeve gastrectomy; SG, sleeve gastrectomy; AGB, adjustable gastric banding.

indicates different patient cohort according to surgery type.

Table 2.
Ratio of means of MRI-PDFF meta-analysis of the efficacy of bariatric intervention in obese patients
Author (year) No. of samples Ratio of mean (95% CI)
BMI Steatosis by MRI
After 3–6 months
Folini et al. (2014) [44] 18 0.87 (0.79–0.97) 0.46 (0.23–0.89)
Hedderich et al. (2017) [45] 19 0.77 (0.70–0.84) 0.31 (0.19–0.53)
Luo et al. (2018) [46] 124 0.76 (0.73–0.79) 0.26 (0.23–0.31)
Mamidipalli et al. (2020) [47] 54 0.81 (0.77–0.85) 0.32 (0.25–0.40)
Pooler et al. (2019) [48] 50 0.77 (0.72–0.82) 0.27 (0.21–0.34)
Tan et al. (2023) [49] 9 0.82 (0.72–0.93) 0.33
Overall 0.79 (0.75–0.83) 0.28 (0.24–0.33)
Heterogeneity - I2 50.9% (0.0–80.5%) 0% (0–79.2%)
P-value 0.070 0.417

MRI, magnetic resonance imaging; PDFF, proton density fat fraction; BMI, body mass index; CI, confidence interval.


magnetic resonance imaging
proton density fat fraction
metabolic dysfunction-associated steatotic liver disease
metabolic dysfunction-associated steatohepatitis
nonalcoholic fatty liver disease activity score


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