Global Trends in Scientific Output of Clinical Trials on Gastric Bypass: A Machine Learning–Based Bibliometric Study

Global Trends in Scientific Output of Clinical Trials on Gastric Bypass: A Machine Learning–Based Bibliometric Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Global Trends in Scientific Output of Clinical Trials on Gastric Bypass: A Machine Learning–Based Bibliometric Study Rômulo Ferreira Monteiro, Victor Celestino Pires, Tiago Rafael Onzi, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8854344/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Introduction Gastric bypass (GB) is a well-established metabolic bariatric surgery technique associated with substantial weight loss and significant metabolic benefits. Since the early 2000s, scientific output related to GB has shown sustained growth. This study aimed to analyze the global scientific production of clinical trials on GB, focusing on authorship patterns, country-level contributions, publication impact, and the temporal evolution of thematic research topics. Methods The search term “gastric bypass” was used to retrieve publications indexed in the Web of Science, PubMed, and Scopus databases between 2001 and 2024. Bibliometric indicators were combined with normalization strategies based on population size, number of bariatric procedures performed, and obesity prevalence. Data on authorship, countries, citation counts, and keywords were extracted and analyzed. Topic modeling was performed using Latent Dirichlet Allocation, a machine learning approach in bibliometric research. Results A total of 1,102 studies were included, showing an average annual growth rate of 10.6%, with marked expansion after 2010. The United States led in absolute publication volume, whereas European countries demonstrated higher relative productivity after normalization. The ten most cited studies accumulated more than 20,000 citations. Latent Dirichlet Allocation identified emerging, stable, and declining thematic topics, with a dominant and expanding topic related to metabolic outcomes and diabetes mellitus. Conclusion Bariatric surgery research is approaching a global stabilization phase projected until 2030. In GB research, the most prominent and expanding topics involve intestinal hormones and diabetes mellitus, while quality of life, sleep apnea, vitamin D, and gut microbiota remain underexplored and represent future opportunities. Gastric bypass Clinical trial Bibliometrics Bariatric surgery Machine learning Latent Dirichlet Allocation Figures Figure 1 Figure 2 Figure 3 Figure 4 Key Points • Projections suggest a stabilization of research output in the field through 2030. • The United States leads in absolute output, while Europe leads after normalization. • Differences in obsolescence reflect varying scientific impact and longevity. • Dominant topics focus on intestinal hormones and diabetes mellitus. Introduction Metabolic bariatric surgery (MBS) has historical records dating back to the 10th century, when King Sancho I of León reportedly had his mouth sutured in a primitive attempt to control body weight [1]. In contemporary practice, MBS comprises a group of procedures performed on the gastrointestinal tract with the aim of inducing weight loss in individuals with severe obesity and reducing the risk of associated diseases, such as type 2 diabetes mellitus and hypertension. These procedures act through gastric restriction, alterations in intestinal transit, and hormonal modifications that promote both weight reduction and metabolic control [2]. Obesity is recognized as one of the major public health challenges of the 21st century [3,4]. Its global prevalence has more than doubled since 1990, and in 2022 it was estimated that one in eight people worldwide was living with obesity. In its most severe forms, Obesity III (body mass index ≥ 40 kg/m²) is projected to affect more than 110 million adults by 2030, highlighting the worsening epidemiological scenario [5,6]. Within this context, MBS has been established as the reference treatment for severe obesity, owing to its effectiveness in achieving sustained weight loss and and improving obesity-associated metabolic diseases [7]. Against this backdrop, the number of metabolic bariatric surgery procedures performed worldwide has increased continuously. In 2014, a total of 100,092 procedures were reported, and by 2023 this number had risen to 598,736 surgeries, reflecting the global expansion of this therapeutic approach [8,9]. Among the techniques currently available in metabolic bariatric surgery, gastric bypass stands out as one of the oldest, most established, and most widely performed procedures [10], particularly due to its metabolic effects and the high percentage of excess weight loss (%EWL). Studies indicate that patients may achieve up to a 57% reduction in total body weight five years after surgery [11]. In parallel with the increasing prevalence of obesity and the growth in surgical volume, there has been a marked expansion in scientific production on this topic. A search conducted in August 2025 in the Web of Science, PubMed, and Scopus databases using the term “gastric bypass” retrieved more than 72,000 publications, highlighting both the magnitude of the field and the challenge of comprehensively tracking its scientific evolution. In this context, narrative and bibliometric literature reviews are frequently used by clinicians, researchers, and the general public as a primary source of up-to-date information on the subject [12]. Clinical trials play a central role in the development of health interventions, as they allow rigorous methodological evaluation of the efficacy and safety of new treatments, enabling investigations ranging from preliminary safety assessments to direct comparisons between different therapeutic approaches. By reducing bias and generating high-quality evidence, these studies provide the necessary foundation for informed clinical decision-making and for the adoption of effective therapeutic practices. Consequently, clinical trials constitute an essential pillar in the advancement of evidence-based practice and in ensuring increasingly safe and efficient healthcare [13,14]. Several bibliometric studies have characterized the international scientific output on bariatric surgery and have identified, since the early 2000s, a marked increase in publications, with gastric bypass accounting for a greater volume of research [15,16]. In contrast, sleeve gastrectomy, despite currently being the most frequently performed procedure, shows a lower cumulative volume of studies, likely because it was more recently incorporated as a primary surgical technique [17]. In this context, scientific production specifically focused on the sleeve gastrectomy procedure has been analyzed [18,19]; however, a clear gap remains with regard to bibliometric studies specifically addressing clinical trials on gastric bypass. In this context, the present study aimed to map the scientific production on gastric bypass (GB) through the analysis of clinical trials (CTs) indexed in the three largest international databases between 2001 and 2024. In addition, the study sought to identify and explore the main topics and thematic trends in the field using different machine learning and bibliometric techniques, thereby providing a comprehensive and systematized overview of this research area. Materials and Methods Data Sources and Search Strategy Searches were conducted in the Web of Science, PubMed/MEDLINE, and Scopus databases (WPS). The search was performed on September 5, 2025, and included clinical trials published between 2001 and 2024, with no language restrictions. The search strategy combined descriptors in the TITLE-ABS-KEY fields using the following terms: (“gastric bypass” OR “Roux-en-Y gastric bypass” OR “RYGB” (Roux-en-Y gastric bypass) OR “Laparoscopic Roux-en-Y gastric bypass” OR “LRYGB” (laparoscopic Roux-en-Y gastric bypass) OR “OAGB” (one anastomosis gastric bypass) OR “One Anastomosis Gastric Bypass” OR “Mini-Gastric Bypass” OR “Single Anastomosis Gastric Bypass”) AND (“clinical trial” OR “clinical trials” OR “randomized controlled trial” OR “randomised controlled trial” OR “RCT” (randomized controlled trial) OR “interventional study” OR “controlled clinical trial” OR “controlled trial” OR “clinical research” OR “clinical investigation” OR “therapeutic trial” OR “treatment trial”). The detailed, database-specific search strategies are provided in Supplementary Material 1. Inclusion Criteria and Study Selection The inclusion criteria comprised randomized and non-randomized clinical trials conducted in patients with obesity undergoing gastric bypass, specifically including the Roux-en-Y gastric bypass (RYGB) and the one anastomosis gastric bypass (OAGB), either as isolated procedures or in combination with other techniques. Studies involving participants of all age groups were considered eligible, provided they reported outcomes of any nature, including clinical, metabolic, anthropometric, surgical, or other relevant endpoints. The analysis period covered publications from 2001 to 2024 and was restricted exclusively to the English language, as the Latent Dirichlet Allocation (LDA) topic modeling algorithm requires linguistic homogeneity and supports only a single language during analysis. Initially, articles containing the predefined search descriptors in their titles or abstracts were selected. Identified studies were organized in an electronic spreadsheet (Microsoft Office Excel, version 2016) and independently assessed in pairs for readability and compliance with the inclusion criteria. All articles that did not qualify as clinical trials (randomized or non-randomized) were excluded, including observational studies, reviews, and other publication types such as letters, editorials, protocols, and preclinical studies. Articles focusing exclusively on bariatric techniques other than gastric bypass, such as sleeve gastrectomy, gastric banding, and related procedures, were also excluded, as were studies published in languages other than English, duplicate records, and articles published before 2001 or after 2024. In cases of uncertainty regarding eligibility, both reviewers performed a full-text assessment and reached a consensus decision on study inclusion or exclusion. Bibliometric and Statistical Analysis Methods Bibliometric data, including year of publication, authorship, keywords, study location, number of citations, and other relevant metadata, were organized in a Microsoft Excel spreadsheet to enable subsequent analyses. The complete metadata set is provided in Supplementary Material 2. To generate publication forecasts through 2030, an AutoRegressive Integrated Moving Average (ARIMA) model was fitted to the time series of annual publication counts from 2001 to 2024. Model adequacy was assessed through residual analysis and the Ljung–Box test, with a 95% confidence interval. Normalization of publication output was performed by dividing the total number of articles by the mean population between 2001 and 2024, expressed per million inhabitants For bariatric surgery volume, publication counts were normalized by the total number of procedures performed and reported as articles per 1,000 surgeries [21]. Finally, for obesity prevalence, the affected population in each country was estimated by multiplying the total population in 2024 by the obesity prevalence reported by the World Health Organization [22]. The obesity index was then calculated by dividing the number of publications by the estimated total number of individuals with obesity and multiplying the result by one million, yielding an indicator expressed as articles per million affected individuals. Regarding authorship, the following indicators were evaluated: total number of citations, coauthorship position, productivity per active year of publication (PAY), and number of active years, reflecting academic experience (NAY). In addition, Lotka’s law was applied to assess authors’ productivity patterns [23]. To characterize the most highly cited publications, journal impact factor values were obtained from the Journal Citation Reports (Clarivate Analytics/Web of Science, 2024). Citation counts for each article were retrieved using OpenCitations (OC) [24], which typically reports higher citation numbers than the Web of Science and Scopus databases and additionally provides citation data not available in PubMed [25]. Data extraction was performed through the public OC application programming interface (API), using the pandas, requests, and numpy packages implemented in Python [26]. For the calculation of citation half-life and obsolescence, the COCI/OpenCitations endpoint (/index/coci/api/v1/citations/{doi}) was used to extract, for each digital object identifier (DOI), the timespan field, defined as the interval between the publication dates of the cited and citing articles. This interval was converted into years (years + months/12 + days/365.25). Additional metrics, including total citations, citations per year, and normalized citations, were obtained using the bibliometrix package [12]. Sample size and intervention duration were manually extracted through full-text article review. To assess the level of evidence of the ten most cited articles, the Levels of Evidence scale of the Journal of Bone & Joint Surgery was applied [27]. For topic analysis, abstracts were extracted, organized in a Microsoft Excel spreadsheet (version 2016), and subsequently preprocessed in R. Text preprocessing included lowercasing, removal of punctuation, special characters, excess whitespace, bigrams, trigrams, English stopwords, and words with fewer than four characters. Topic modeling was performed using Latent Dirichlet Allocation (LDA) [28], with Gibbs sampling (1,000 iterations) and hyperparameters set to α = 0.1 and η = 0.1. Models with K ranging from 10 to 50 topics were tested, and model quality was evaluated using coherence metrics. The final model (K = 29) was selected for achieving the best balance between statistical fit and semantic interpretability. The descriptions of the named subtopics were subsequently reviewed and validated by an experienced bariatric and metabolic surgery specialist. Topic frequencies and linear trend classifications (rising, declining, or stable) were also assessed. The full analytical script is provided in Supplementary Material 3. Following topic estimation, the topic probability distribution (θ) was obtained for each document. To assess thematic evolution over time, topic proportions were aggregated by year of publication, generating an annual topic–year matrix based on mean topic probabilities. For each topic, a simple linear regression model was fitted to the annual mean proportions to evaluate temporal trends, with the slope coefficient (β₁) indicating directionality. A significance threshold of p 0), declining (β₁ < 0), or stable (β₁ ≈ 0), enabling identification of themes with increasing, decreasing, or stable relevance over the study period. For descriptive statistical analyses, means, standard deviations, and medians were calculated, and trends in scientific production were assessed using the Mann–Kendall test. Bibliometric analyses were conducted using the R software [29], with the bibliometrix package [12] and the Visualization of Similarities viewer (VOSviewer) (VOSviewer) [30]. Results The search strategy identified a total of 4,348 publications. However, when restricting the results to clinical trials, a reduction in the number of records was observed: Web of Science (1,019), PubMed (765), and Scopus (2,564). After duplicate removal and application of the inclusion criteria, 425 records from Web of Science, 94 from PubMed, and 583 from Scopus remained, resulting in a final sample of 1,102 articles included for analysis(Fig. 1). Scientific Production Of the total articles analyzed, 849 (77.0%) addressed gastric bypass (GB) exclusively, 221 (19.5%) investigated a combination of GB and sleeve gastrectomy, and 32 (3.2%) examined GB in association with other bariatric procedures, including sleeve gastrectomy, biliopancreatic diversion with duodenal switch, and adjustable gastric banding. Publication trends over the study period are presented in Fig. 2 and demonstrate a statistically significant annual growth rate of 10.61% (Kendall’s tau = 0.808; p < 0.001). An approximate 374% increase in publications was observed from the first decade (152 articles) to the second decade (664 publications) of the analyzed period. Between 2021 and 2024, a total of 286 publications were recorded, corresponding to nearly half of the total output of the preceding decade. For the period from 2025 to 2030, an additional 309 publications are projected (95% confidence interval: 118–496), suggesting a trend toward stabilization in the volume of scientific production. Prolific Countries Contributions to research on clinical trials in gastric bypass were identified from 47 countries. Regional analysis (Fig. 3 a) showed that North America and South America account for a substantial share of absolute scientific output, largely driven by the United States and Brazil. However, when publication data were normalized by national population size (Fig. 3 b), number of bariatric surgeries performed per country (Fig. 3 c), and per million individuals with obesity (Fig. 3 d), the overall pattern changed. Under these adjusted metrics, Europe emerged as the region with the highest relative publication density, surpassing the Americas and, to a lesser extent, Asia and Oceania. It should be noted that some normalization adjustments could only be calculated for a subset of the sample due to limitations in data availability from the International Federation for the Surgery of Obesity and Metabolic Disorders, the World Health Organization, and the United Nations. Complete results are presented in Supplementary Table 4. Author Productivity Across the total body of publications included in this study, 6118 authors contributed to clinical trials on gastric bypass. The mean number of authors per publication was 8.65, with international coauthorship accounting for 9.9% of the studies. Productivity distribution revealed that approximately 77% (4721/6118) of authors published only a single article, whereas only 1.4% (86/6118) authored five or more publications. Table 1 presents the ten most productive authors and the main characteristics of their scientific output. European authors predominated among the most productive researchers, and nine of the ten most cited authors demonstrated more than a decade of academic experience, as measured by the number of active years (NAY), which was associated with greater citation impact. Nevertheless, despite their extensive experience, the mean annual productivity did not exceed three publications per year, as indicated by productivity per active year (PAY). A predominance of coauthorship positions was also observed, particularly last authorship, which was occupied by most of these researchers. Table 1 The ten most prolific authors and their characteristics Rank Author Articles T. C. C.Y. F- L NAY-PAY 1 Olbers T (Sweden) 34 (3%) 8636 479.7 3–9 18 − 1,89 2 Hjelmesaeth J(Norway) 32 (2.9%) 966 74.3 2–19 13–2.46 3 Holst J(Denmark) 29 (2.6%) 2146 214.6 0–3 10 − 2.9 4 Le Roux CW (Irland) 27 (2.4%) 2773 213.3 3–9 13 − 2.1 5 Courcoulas A (USA) 23 (2.1%) 2299 191.5 6 − 3 12–1.92 6 Hofso D(Norway) 21 (1.9%) 764 76.4 5–5 10 − 2.1 7 Madsbad S (Denmark) 20 (1.8%) 1745 193.8 0–9 9–2.2 8 Sandbu R(Norway) 19 (1.7%) 553 50.2 0–2 11 − 1.7 9 Kirwan JP(USA) 18 (1.6%) 6489 540 1–3 12 − 1.5 10 Peltonen M(Finlândia) 18 (1.6%) 6798 679.8 0–1 10 − 1.8 % = Percentage of clinical trials published relative to the total number of articles T.C. = Total citations C.Y. = Citations per year F = Number of times the author appeared as first author L = Number of times the author appeared as last author NAY = Number of active years PAY = Productivity per active year of publication The Ten Most Cited Publications Table 2 presents the main characteristics of the ten most cited publications. Collectively, these studies accumulated 20921 citations, with individual citation counts ranging from 1008 to 4040. This volume corresponds to 26.6% (20921/78619) of the total citations across all analyzed articles, indicating that approximately one quarter of all citations were concentrated in only ten publications. In addition, 155 citation classics were identified, of which 131 had more than 100 citations and 24 had more than 400 citations (see Supplementary Table 4). The mean number of authors per publication was 12.4 (standard deviation = 5.33), with a median of 11.5. A strong concentration of publications in very high–impact journals was observed, with eight of the ten articles published in journals with a Journal Impact Factor (JIF) greater than 70, including The New England Journal of Medicine (JIF 2024: 78.5) and The Lancet (JIF 2024: 88.5).Medicine (JIF 2024: 78.5) e no The Lancet (JIF 2024: 88.5). With regard to citation half-life, the most cited article, “Effects of Bariatric Surgery on Mortality in Swedish Obese Subjects–2007” [31], exhibited a citation half-life exceeding 7 years, indicating moderate obsolescence. Only the article “Lifestyle, Diabetes, and Cardiovascular Risk Factors 10 Years after Bariatric Surgery–2004” [32] demonstrated slow obsolescence, with a citation half-life longer than 9 years. In contrast, rapid obsolescence (3.17 years) was observed in the study “Bariatric Surgery versus Intensive Medical Therapy for Diabetes–3-Year Outcomes–2014” [33]. All ten publications showed normalized citation values above 6, indicating that they were cited more than six times above the average for articles published in the same year. A predominance of randomized clinical trials (level of evidence I) was observed, along with methodological diversity, as nine publications investigated different surgical techniques. Additionally, a wide variation in sample size was noted (ranging from 33 to 4,047 participants), with a predominance of longitudinal study designs and follow-up periods of five years or less. Table 2 Ten most cited articles on gastric bypass and their characteristics Rank Authors Title Source title P.Y. T.C. A.V. C.H.L N. C. L.E. S.S. D.I. 1 L. Sjöström, et al. [31] Effects of Bariatric Surgery on Mortality in Swedish Obese Subjects(SOS)–Não randomizado -Suécia The New England Journal of Medicine- JIF 2024–78.5 2007 4040 212 7.33 10.94 II 4047 10.9 2 L. Sjöström, et al. [32] Lifestyle, Diabetes, and Cardiovascular Risk Factors 10 Years after Bariatric Surgery(SOS)- Não randomizado- Suécia The New England Journal of Medicine- JIF 2024–78.5 2004 3975 180 9.46 7.12 II 4047 10 3 Philip R. Schauer et al.[33] Bariatric Surgery versus Intensive Medical Therapy for Diabetes − 5-Year Outcomes - Randomizado-EUA The New England Journal of Medicine- JIF 2024–78.5 2017 2140 237 4.0 27.23 I 150 5 4 David E. Cummings, J. et al. [34] Plasma Ghrelin Levels after Diet-Induced Weight Loss or Gastric Bypass Surgery -Não randomizado-EUA The New England Journal of Medicine- JIF 2024–78.5 2002 2137 89 8.67 7 II 33 0.6 5 Philip R. Schauer et al. [35] Bariatric Surgery versus Intensive Medical Therapy in Obese Patients with Diabetes-Randamizado- EUA The New England Journal of Medicine- JIF 2024–78.5 2012 1985 141 4.0 9.73 I 150 1 6 Geltrude Mingrone, et al. [36] Bariatric Surgery versus Conventional Medical Therapy for Type 2 Diabetes-Randomizado-Itália The New England Journal of Medicine- JIF 2024–78.5 2012 1601 114 4.0 8.37 I 60 2 7 Geltrude Mingrone, et al. [37] Bariatric–metabolic surgery versus conventional medical treatment in obese patients with type 2..Randomised -Itália The Lancet -JIF 2024 − 88.5 2015 1459 132 5.0 18.80 I 60 5 8 Philip R. Schauer, et al. [38] Bariatric Surgery versus Intensive Medical Therapy for Diabetes − 3-Year Outcomes- Randomizado-EUA The New England Journal of Medicine- JIF 2024–78.5 2014 1374 114 3.17 14.52 I 150 3 9 Lars Sjöström, Markku et al. [39] Bariatric Surgery and Long-term Cardiovascular Events (SOS)-Não randomizado-Suécia JAMA Network- JIF 2024 − 9.7 2012 1202 85 5.0 6.01 II 4047 14.7 10 Ralph Peterli, MD; et al. [40] Effect of Laparoscopic Sleeve Gastrectomy vs Laparoscopic Roux-en-Y Gastric Bypass on Weight Loss in Patients -Randomizado- Suíça JAMA Network- JIF 2024–9.7 2018 1008 126 3.66 17.13 I 212 5 P.Y.=Publication year S.S.=Sample size T. C.=Total citation D.I.=Duration of intervention in years A.V.=Average per year a,b Letras idênticas indicam que os dados foram obtidos a partir do mesmo estudo. C.H.L=Citation half-life N. C.= Normalized citation L.E=Level of evidence Analysis of Emerging Topics and Temporal Evolution Using Latent Dirichlet Allocation (LDA) Topic modeling performed using the Latent Dirichlet Allocation (LDA) algorithm enabled the identification of clusters of keywords organized according to semantic coherence. Representative labels were assigned to these clusters, characterizing them as subtopics. This approach allowed both joint and individual interpretation, as well as the analysis of temporal trends and the frequency of documents associated with each identified topic (Table 3). A total of 29 topics were identified, of which nineteen exhibited stable trends, eight showed increasing trends, and only two demonstrated declining trends. When the sets of keywords were examined collectively, topics clearly emerged that encompassed all stages involved in gastric bypass. Prominent themes included technical and procedural aspects and surgical techniques, perioperative care and postoperative complications, clinical and metabolic outcomes of bariatric surgery, weight loss and recurrent weight gain, cardiometabolic markers, lipid profile, systemic inflammation, and cardiovascular risk. It is noteworthy that, beyond these specific domains, topics with a multidisciplinary scope were also identified, such as eating behavior, psychological aspects, physical exercise, functional capacity, and health-related quality of life, reflecting a multidimensional approach to the effects of bariatric surgery. Conversely, according to topic frequency analysis, relatively few clinical trials addressed issues related to bone health, quality of life, cholelithiasis, sleep apnea, respiratory aspects, vitamin D, and gut microbiota, indicating underrepresented areas within the current research landscape. Table 3 Subtopics and keywords derived from the topics identified by the LDA model Topic (Frequency) Trend keywords Subtopic 1 (52) Stable laparoscopic_roux_en_y, laparoscopic_sleeve_gastrectomy, gastric_bypass_lrygb Laparoscopic Surgical Techniques morbid_obesity, obesity_related, body_mass_index_bmi Clinical Classification of Obesity co_morbidities, related_comorbidities Obesity-associated diseases gastroesophageal_reflux, reflux_disease, disease_gerd Gastroesophageal Reflux Disease major_complications, complication Surgical Complications 2 (29) Stable clinical_trial, single_center, primary_outcome, led_trial Clinical Trial excess_weight_loss(EWL), post_bariatric, high_risk Weight Loss Outcomes liver_disease, fatty_liver, liver_function, pmol_l Liver Diseases 3 (50) Rising weight_loss, total_weight_loss, weight_loss_twl, greater_weight_loss, weight_loss_compared, weight_regain, body_mass_index_bmi, gastric_bypass_rygb Weight Loss and Recurrent weight gain long_term, year_follow_up, term_follow_up, first_year, term_effects,gastric_bypass_rygb Long Term Outcomes eating_behavior, binge_eating, depressive_symptoms Eating Behavior and Psychological Aspects american_society Clinical Guidelines 4 (38) Stable insulin_resistance, homa_ir, plasma_glucose, fasting_glucose, fasting_blood_glucose, glucose_insulin, fasting_insulin, homeostasis, mg_dl Glucose Metabolism and Insulin Resistance total_cholesterol, density_lipoprotein, low_density, lipoprotein_cholesterol, mmol_l Lipid Profile and Cholesterol metabolic_syndrome Metabolic Syndrome body_mass_index_bmi, bmi_kg Body Mass Index (BMI) 5 (35) Rising exercise_training, physical_training, supervised_physical, training_program, aerobic_exercise. Exercise Based Interventions physical_function, functional_capacity, muscle_strength. Functional Capacity and Muscle Strength bariatric_surgery, post bariatric_surgery, pre_surgery, rygb, usual_care Bariatric Surgery body_composition Body Composition 6 (31) Stable clinical_trial, led_trial, double_blind, blind_led, primary_outcome, trial_registration Clinical Trials bariatric_surgery, obesity_undergoing, Biliopancreatic Diversion with Duodenal Switch, small_intestine, morbid_obesity Bariatric Surgery gallstone_formation Gallstone Formation excess_skin Excess Skin 7 (33) Stable roux-en-Y Gastric Bypass, gastric_bypass, RYGBP Roux en Y Gastric Bypass c-reactive protein (CRP), TNF-alpha, necrosis_factor, interleucina, inflammatory_markers, mortality_risk, metabolic_syndrome, body_mass_index Inflammatory Markers and Metabolic Syndrome 8 (45) Stable gastric_bypass_surgery, undergoing_gastric_bypass, gastric_pouch,. Technical Aspects of Gastric Bypass roux_stasis Roux en Y Stasis Syndrome preoperative_weight_loss, post_operatively, ope_d, non_ope, bmi_kg Perioperative Weight Management bile_acids, bile_acid Metabolism and Bile Acids 9 (50) Stable type 2 diabetes mellitus, diabetes_mellitus, dm_remission, complete_remission, remission, long_term, HbA1c, hemoglobin_A1c, obese morbidly_obese_patient, body_mass_index_bmi. Type 2 Diabetes Mellitus and Remission gastric_bypass_rygb, sleeve_gastrectomy_sg RYGB versus Sleeve Gastrectomy 10 (83) Rising glucagon_like, like_peptide, peptide_glp, peptide_yy, gut_hormones, glp_secretion, glucose_dependent Intestinal Hormones and Incretins plasma_glucose, glucose_insulin, glucose_tolerance, oral_glucose, cell_function, beta_cell, insulin_secretion, tolerance_test, type 2 diabetes Glucose and Insulin Metabolism gastric_bypass_rygb Roux en Y Gastric Bypass 11 (25) Stable gastric_banding, adjustable_gastric, laparoscopic_adjustable, gastric_band, banding_lagb, gastric_bypass_rygb, underwent_gastric_bypass, bariatric_procedures, bariatric_procedure, bariatric_surgeries, bariatric_surgical, surgical_procedures, surgical_procedure, different_bariatric, long_term Adjustable Gastric Banding and Roux en Y Gastric Bypass 12 (27) Stable related_quality_of_life, health_related, weight_related, obesity, short_form, form_health, health_survey Health Related Quality of Life surgical_treatment, non_surgical, clinical_trial number_nct, morbid_obesity Surgical and Non Surgical Treatment sodium_excretion, urinary_sodium. Urinary Sodium Excretion vitamin_d, nmol_l. Vitamin D 13 (34) Stable medical_therapy, medical_treatment, intensive_medical, best_medical, therapy_alone, type_diabetes, glycated_hemoglobin, mm_hg. Medical Treatment of Type 2 Diabetes metabolic_surgery, biliopancreatic_diversion, gastric_bypass, surgical Metabolic and Bariatric Surgery randomly_assigned, open_label, design_setting, per_protocol, primary_endpoint, year_follow_up Methodological Design 14 (30) Stable body_composition, body_weight, body_mass, body_fat, fat_mass, fat_free, free_mass, lean_body, lean_mass, bmi_kg, ray_absorptiometry, dual_energy, x_ray Body Composition energy_expenditure, energy Energy Expenditure protein_supplementation, protein_intake Protein Intake and Supplementation gastric_bypass_rygb, hernia_repair Hernia Repair Associated with RYGB 15 (34) Rising gastric_bypass_rygb, undergoing_rygb, following_rygb, pre_surgery, post_surgery, post_rygb, following_surgery, year_post, weeks_post, surgery_induced Perioperative Management of Gastric Bypass apo_b, c_imt (Carotid Intima-Media Thickness), ly_decreased, ly_increased, objectively_measured Cardiometabolic Markers iron_deficiency. Iron Deficiency 16 (20) Rising type_diabetes, hba_c, hemoglobin_a_c, mmol_mol, c_mmol, glucose_lowering, type___diabetes_remission, american_diabetes, diabetes_association Type 2 Diabetes Mellitus and Remission rygb_vs medical_management, greater_weight_loss, randomly_assigned Gastric Bypass versus Medical Treatment 17 (24) Rising metabolic_surgery, gastric_bypass_rygb, rygb, rygb_vs, rygb_versus, rygb_compared, sleeve_gastrectomy_sg, underwent_sg, type_diabetes, hba1c, remission Gastric Bypass versus Sleeve Gastrectomy gut_microbiota. Gut Microbiota 18 (41) Stable gastric_bypass_rygb, gastric_bypass_surgery, rygb_surgery, pyy_levels, ghrelin_levels, plasma_concentration, plasma_concentrations, concentration_time, time_curve, single_dose, blood_samples, ng_ml, pg_ml, ml_p Gastric Bypass and Gastrointestinal Hormones oxidative_stress. Oxidative Stress morbidly_obese_patient, body_weight, body_mass_index_kg. Nutritional Status Assessment 19 (19) Rising gastric_bypass_surgery, laparoscopic_gastric_bypass, small_bowel, mesenteric_defects, internal_herniation, bowel_obstruction, non_closure, defect_closure, postoperative_complications, abdominal_pain. Mesenteric Issues, Internal Hernia, and Intestinal Obstruction gallstone_disease, symptomatic_gallstone, ursodeoxycholic_acid Cholelithiasis sleep_apnoea Obstructive Sleep Apnea 20 (35) Declining morbidly_obese_patient, obese_patient_undergoing, obese_women, central_obesity, body_mass_index_bmi Patient Profile postoperative_period, postoperative_day, first_postoperative, early_postoperative, immediate_postoperative, postoperative_complications Postoperative Period pulmonary_function, inspiratory_muscle, inspiratory_pressure, cmh_o, muscle_strength Pulmonary Function and Respiratory Muscle Function 21 (25) Stable Duodenal-Jejunal Bypass with Sleeve Gastrectomy Combined Bariatric Procedures co_morbidities, Obesity-related, Related Diseases, Comorbidities informed_consent, patient_characteristics Ethical Aspects antifactor_xa Anticoagulation ims_score, liver_volume Hepatic Assessment 22 (28) Stable gastric_bypass_rygb, sleeve_gastrectomy_sg, bone_health, bone_loss, bone_mass, bone_turnover, turnover_markers, secondary_hyperparathyroidism, bone_mineral, mineral_density, density_bmd, lumbar_spine, femoral_neck, total_hip Bone Health parathyroid_hormone, hydroxyvitamin_d, calcium_cit, plasma_levels. Bone and Mineral Metabolism 23 (28) Stable gastric_bypass_oagb, one_anastomosis_gastric_bypass, one_anastomosis, distal_gastric_bypass, anastomosis_gastric_bypass, standard_rygb, Gastric Bypass and Variations limb_length, limb_lengths, limb_cm, cm_biliopancreatic, biliopancreatic_limb, roux_limb, alimentary_limb, common_channel, gastric_pouch Limb Length and Surgical Measurements bile_reflux Biliary Reflux 24 (26) Stable obese_subjects, swedish_obese, underwent_bariatric_surgery, design_setting, prospective_led, led_trial, usual_care, main_outcome, primary_outcome, cardiovascular_events, median_follow_up, long_term, increased_risk Swedish Obese Subjects (SOS) Study 25 (25) Stable lifestyle_intervention, intensive_lifestyle Non Surgical Interventions gastric_bypass_surgery, obesity_surgery, surgery, following_bariatric_surgery, bmi_kg, obese_individuals, clinical_trial, one_year Bariatric Surgery ventilation, arterial_blood, sleep_apnea, obstructive_sleep, orbid_obesity, morbidly_obese, obesity_related, nt_probnp Respiratory Function and Ventilation 26 (62) Declining laparoscopic_gastric_bypass, laparoscopic_roux_en_y, laparoscopic_gbp, open_gastric_bypass, open_gbp, underwent_laparoscopic, operative_time, operating_time, min, blood_loss, staple_line, gastrojejunal_anastomosis, two, hospital_stay, incisional_hernia, anastomotic_leaks, randomly_assigned Comparison of Laparoscopic and Open Surgical Techniques morbidly_obese_patient, morbid_obesity Severely Obese Population 27 (33) Rising undergoing_bariatric_surgery, gastric_bypass_rygb, rygb, sadi_s, Bariatric Procedures wls_forte, vitamin_b, vitamin_and_mineral, iron_absorption Vitamins and Minerals post_operative, body_weight, bmi_kg, preoperative_bmi Perioperative Anthropometric Assessment 28 (74) Stable gastric_bypass_surgery, laparoscopic_roux_en_y, laparoscopic_gastric_bypass, laparoscopic_bariatric_surgery, undergoing_laparoscopic Laparoscopic Procedures postoperative_pain, pain_scores, tap_block, opioid_consumption, morphine_consumption, opioid_use, mg_kg, kg_h Analgesia and Pain Assessment postoperative_nausea, hospital_stay, care_unit, post_operative, first Postoperative Outcomes 29 (53) Stable type 2 diabetes, non_diabetic, insulin_sensitivity, glucose_homeostasis, glucose_tolerance, glucose_production, gene_expression Glucose Metabolism and Insulin Sensitivity body_weight, induced_weight_loss, weight_loss_induced,gastric_bypass_rygb, morbidly_obese, obese_subjects, obese_women Weight Loss Outcomes adipose_tissue, skeletal_muscle, whole_body, fatty_acids Adipose and Muscle Tissue low_calorie, calorie_diet Hypocaloric Diets Topic = Topics: topics identified using the Dirichlet Latent Allocation (LDA) model. Frequency = number of documents associated with each topic. Trend = Trend: trends associated with each topic over time. Figure 4 illustrates the temporal evolution of topics based on the annual mean topic probabilities and their statistically significant trends. Overall, a heterogeneous pattern was observed throughout the analyzed period. Topics shown in red predominantly related to weight loss and recurrent weight gain, eating behavior, psychological aspects, physical exercise, muscle strength, type 2 diabetes mellitus, intestinal hormones, cardiometabolic markers, gut microbiota, and sleep apnea—exhibited positive coefficients with significant upward trends, indicating that these themes have gained increasing relevance over the study period. Topics displayed in blue, characterized by negative coefficients, were mainly associated with respiratory aspects, patient profile, perioperative care, and comparisons between laparoscopic and open surgical techniques. The significant downward trends observed for these topics suggest a progressive decline in their relative relevance over time. Despite occasional fluctuations, the majority of topics demonstrated stable behavior (shown in black), indicating relatively constant relevance within the analyzed literature. This group includes themes such as obesity-associated diseases, liver disease, glucose metabolism, metabolic syndrome, excess skin, inflammatory markers, surgical techniques, vitamin D, body composition, energy expenditure, ethical aspects, bone health, pain, and nutritional interventions. Discussion Metabolic bariatric surgery is widely recognized as an effective method for weight loss. Among the available procedures, gastric bypass developed in 1967 by Edward E. Mason and Chikashi Ito [41], stands out as one of the oldest and most established techniques in the field [42]. To the best of our knowledge, there is no comprehensive systematization of publications specifically focused on clinical trials in gastric bypass, despite the continuous growth of this research area. This gap becomes even more evident when consulting the World Health Organization’s International Clinical Trials Registry Platform, which reports 755 registered studies for the term “sleeve gastrectomy” up to 2024, whereas the present analysis identified 1,102 clinical trials related to gastric bypass. An accelerated growth in scientific production related to clinical trials on gastric bypass was observed, particularly from the second decade of the evaluated period (2010–2019). This trend paralleled the global rise in obesity frequently described as a “public health crisis”—as well as the continuous increase in obesity-associated diseases. It is reasonable to assume that this scenario led to greater demand for effective weight control interventions, thereby driving both the volume of bariatric surgeries and scientific interest in the field [4]. In addition, technological advances and improvements in surgical techniques, especially the development and consolidation of minimally invasive laparoscopic approaches and robotic procedures, contributed to increased procedural safety and reduced morbidity and mortality [42–44], further fostering scientific output. The stabilization of scientific production, followed by a slight decline from 2021 onward, suggests that external factors particularly the COVID-19 pandemic may have played a central role in slowing research activity. During this period, the medical community’s focus shifted primarily to the management of patients infected with COVID-19, placing bariatric surgery and related research in a less prominent position [45]. Indeed, reports have documented the suspension of bariatric surgical procedures [46], as well as a reduction in global scientific production within the biomedical field [47,48]. Although growth rates have not immediately returned to pre-pandemic levels, a stabilization trend is projected through 2030. This pattern may be associated with the possibility that certain areas of metabolic and bariatric surgery are entering a phase of knowledge consolidation, which typically leads to a reduction in scientific output. Our findings indicate declining trends in specific domains, such as perioperative and respiratory aspects, as well as comparisons between laparoscopic and open surgical approaches. This scenario contributes to a linear rather than exponential growth pattern in scientific production within the field [15]. Regarding country-level scientific production, particularly in relation to specific surgical techniques, the United States previously led research output on laparoscopic sleeve gastrectomy between 1998 and 2019 [18], a pattern that was also observed for gastric bypass in the present study. This finding is likely associated with substantial national investment in medical research [49], as well as the high prevalence of obesity in the country, which reached approximately 40.3% of adults between 2021 and 2023 [50,51]. However, when scientific output was adjusted per million inhabitants, per thousand bariatric surgeries performed, and per million individuals with obesity, European countries exhibited higher prevalence and the highest productivity indices, followed by Asian and Oceanian countries. These findings are consistent with previous reports [15,17,52] and indicate that scientific production in these regions—despite smaller populations and lower absolute surgical volumes compared with large countries such as the United States and Brazil—is supported by healthcare systems strongly integrated with universities, a high density of academic centers, and a well-established culture of clinical and collaborative research. These structural factors contribute to greater relative efficiency in knowledge generation. Brazil stands out as the only developing country among the ten most productive nations and, in absolute terms, ranks immediately after the United States. After normalization, Brazilian productivity becomes comparable to that of the United States, identifying Brazil as the most productive Latin American country in bariatric surgery research [53]. This phenomenon may also be related to the increasing prevalence of severe obesity in the country, which doubled between 2006 and 2021, consequently intensifying interest in treatment modalities such as bariatric surgery [54]. With respect to authorship, we incorporated additional metrics beyond those typically reported in bibliometric studies, including fractional authorship (FA), frequency of first and last authorship (F and L), number of active years (NAY), and productivity per active year (PAY). These indicators enabled assessment of scientific leadership, consistency of contribution, and productivity intensity. Among all authors, Olbers T. was the most productive, presenting not only the highest publication volume but also the greatest total and annual citation counts, indicating both high productivity and strong scientific impact. This author also contributed to two of the most cited articles in the gastric bypass field, reinforcing his influence in this area. Conversely, authors with fewer publications, such as Kirwan J.P. (United States) and Peltonen M. (Finland), each with 18 publications, also achieved high citation volumes (6,489 and 6,798, respectively). This finding highlights that substantial scientific impact can be achieved with a smaller number of publications, provided that the studies are of high relevance and scientific quality. It was observed that the most highly cited articles were predominantly published in high impact factor journals, which may have contributed to their higher citation counts [55] This association is consistent with previous evidence indicating a positive correlation between journal impact factor and citation frequency, representing one of the factors influencing article visibility [56]. In addition, these publications demonstrated high methodological rigor, an attribute that enhances the reliability of findings and may favor their scientific recognition. Nevertheless, it is important to emphasize that high impact journals do not always publish studies with high methodological quality [57], just as citation counts do not necessarily reflect the methodological rigor of an article in a direct manner [58]. Several studies exhibited moderate obsolescence [31,33,35–37,39], indicating that they remain relevant for long periods after publication and continue to be widely cited. These findings are consistent with reports from the basic and biomedical sciences, in which obsolescence is typically moderate, with mean values ranging between four and seven years [59,60], more recently described as a second phase or maturation period [61]. Only the article “Lifestyle, Diabetes, and Cardiovascular Risk Factors 10 Years after Bariatric Surgery” [32], published more than two decades ago, demonstrated slow obsolescence, with a citation half life of 9.46 years, indicating prolonged persistence as a key reference in the field. Publications with this profile are considered essential reading for researchers interested in the topic [61]. Topic modeling identified thematic axes that have not been described in previous bibliometric analyses [16,17,19] encompassing increasingly relevant areas such as bone metabolism, gut microbiota, eating behavior, and psychological aspects, in addition to topics related to cardiovascular and respiratory function and nutritional status. Moreover, this approach allowed the assessment of how frequently these themes are addressed in the literature, as well as their temporal trends over the evaluated period, providing a comprehensive overview of the main research topics in the field of metabolic bariatric surgery Topic 10, the most recurrent and exhibiting significant growth, was related to type 2 diabetes mellitus, glucose metabolism, and hormones such as glucagon like peptide 1 (GLP 1). GLP 1 is an incretin hormone involved in appetite regulation, delayed gastric emptying, and glycemic control, functions that are typically favorably modified by metabolic bariatric surgery. These effects have also motivated the development of pharmacological agents designed to mimic its action. Evidence from a systematic review and meta analysis demonstrated significant reductions in body weight, as well as consistent decreases in total fat mass and visceral adipose tissue, associated with the use of GLP 1 analogues such as liraglutide [62]. However, discontinuation of pharmacological treatment is associated with partial weight regain, underscoring the importance of effective weight reduction interventions such as metabolic bariatric surgery, as well as the need for maintenance strategies that integrate pharmacotherapy with sustained lifestyle modifications [63,64]. With respect to type 2 diabetes mellitus, which is frequently associated with the term Roux en Y gastric bypass, a close relationship between the surgical procedure and metabolic effects was observed, as evidenced by the presence of terms such as glucose_tolerance, cell_function, beta_cell, insulin_secretion, among others. The high density of studies in this context reinforces the relevance of investigations focused on the mechanisms underlying type 2 diabetes mellitus remission and other hormonal changes in the postoperative period, an area that has expanded substantially and highlights the consolidation of the concept of metabolic bariatric surgery [33,65,66]. Trend analysis indicated that Topic 5, related to physical exercise, muscle strength, and functional capacity, has gained greater prominence in more recent years, showing a significant upward trend. It is plausible that muscle strength has received increased attention in this context, particularly because functional capacity indicators, such as gait speed and walking performance, demonstrate significant improvement after bariatric surgery [67]. However, available evidence suggests that these improvements are predominantly associated with body weight reduction rather than with significant increases in muscle strength during the postoperative period [68]. In this field, existing evidence remains limited, underscoring the need for robust clinical trials to enhance the reliability and generalizability of findings. Topic 2, although not exhibiting a growing trend, reflects an important area concerning the metabolic effects of metabolic bariatric surgery on liver function. Evidence indicates that bariatric surgery promotes consistent reductions in alanine aminotransferase and aspartate aminotransferase levels in individuals with obesity, suggesting improvement in hepatic steatosis and inflammation [69]. Findings from a retrospective cohort demonstrated that improvements in alanine aminotransferase levels after bariatric surgery occur independently of the magnitude of weight loss, indicating metabolic effects beyond weight reduction [70]. Overall, surgical intervention contributes to lowering transaminase levels and promotes a global improvement in liver function [71]. Only two topics, Topics 20 and 26, exhibited declining trends, suggesting reduced scientific interest in themes related to surgical techniques, respiratory aspects, and perioperative care. This pattern may reflect the consolidation and standardization of these domains over time, which reduces the need for predominantly technical studies. This finding is consistent with observations from a previous study reporting that most publications were focused on “how I do it”–type descriptions, emphasizing technical execution, perioperative risk assessment, and the balance between risks and benefits, while broader issues such as psychosocial impacts, quality of life, and behavioral aspects were addressed secondarily. Over time, however, research focus has expanded to include multidisciplinary dimensions, reflecting a more comprehensive understanding of obesity [72]. This shift is evident in our findings, which identified significantly growing topics that extend beyond the technical surgical focus, including eating behavior, psychological aspects, and physical exercise. Topic frequency analysis revealed a low representation of clinical trials addressing outcomes such as bone health, quality of life, cholelithiasis, sleep apnea, respiratory aspects, vitamin D, and gut microbiota. These findings suggest that, despite the recognized clinical relevance of these outcomes in the long term follow up of patients undergoing bariatric surgery, scientific production remains predominantly centered on metabolic outcomes and technical aspects. One possible explanation for this pattern is the greater methodological complexity and longer follow up periods required to evaluate these outcomes, which may limit their inclusion in clinical trial designs. Finally, it is important to note that bibliometric studies are often limited by the use of a single database, which restricts the scope of the analyzed literature [16,73]. To address this limitation, the present study incorporated the three main international databases in health sciences, namely Web of Science, PubMed/MEDLINE, and Scopus [74]. Although PubMed/MEDLINE presents constraints due to the lack of citation data [75], these limitations were mitigated through the use of open access initiatives, particularly via OpenCitations [76]. In addition, this study highlights the application of machine learning techniques in bibliometric analysis, with emphasis on Latent Dirichlet Allocation topic modeling, which remains underexplored in this field [77]. Conversely, it is reasonable to acknowledge the heterogeneity of metadata across the Web of Science, Scopus, and PubMed/MEDLINE databases, as information is organized differently in each source. Such variation may generate inconsistencies in author identification, even after data normalization, potentially leading to distortions in the results. The adoption of a unified metadata standard would be ideal to reduce these discrepancies. Conclusion The global research landscape in the field of gastric bypass currently reflects a phase of stabilization following a prolonged period of robust growth. In quantitative terms, scientific production remains largely concentrated in the United States. However, European countries assume prominent positions when output is adjusted for key indicators such as population size, obesity prevalence, and number of surgeries performed. With respect to productivity, high impact factor journals, experienced researchers, and studies with strong methodological rigor contribute substantially to the relevance of the published literature, as reflected by slow obsolescence and high citation counts. Regarding thematic content, although discussions on intestinal hormones and diabetes mellitus in bariatric surgery are not new, these topics remain recurrent and widely debated in the literature. Similarly, themes associated with metabolic markers and psychosocial aspects, including weight loss and weight regain, eating behavior, physical exercise, and gut microbiota, have emerged as areas of increasing interest among researchers. Nevertheless, relatively few clinical trials address other clinically relevant topics related to metabolic bariatric surgery, such as bone health, quality of life, cholelithiasis, sleep apnea, respiratory aspects, vitamin D, robotic bariatric surgery, and gut microbiota. These areas represent clear gaps in the literature and, consequently, important opportunities for future research and scientific production. Finally, the use of robust analytical methods, such as machine learning approaches with emphasis on the Latent Dirichlet Allocation algorithm, proved essential for identifying thematic structures within the field and for complementing traditional bibliometric techniques. In addition, integrating three major international databases enhanced the scope and reliability of the findings, enabling a global perspective on the evolution of knowledge in clinical trials on gastric bypass. Overall, the results of this study contribute to a deeper understanding of the trajectory of this research field throughout the 21st century, highlighting its main thematic focuses and temporal dynamics. Declarations Funding Grant number blinded Conflict of Interest Declarations The authors declare that they have no conflicts of interest. Ethical Declarations This article does not contain any studies with human participants or animals performed by any of the authors Author Contribution R.F.M.: Study conception and design, definition of the methodology, data analysis and interpretation, and manuscript drafting.V.C.: Study selection and screening of included articles, and review of the translation.J.B.: Critical revision of the manuscript for important intellectual content, scientific supervision, and overall study oversight.G.F.D.D. and T.R.O.: Manuscript review. Data Availability The datasets generated and analyzed during the current study will be made available in a public repository upon publication. For the purposes of double-anonymous peer review, repository details and access links have been temporarily blinded. **Referência** References Hopkins KD, Lehmann ED. Successful medical treatment of obesity in 10th century Spain. Lancet. 1995 Aug 12;346(8972):452. doi: 10.1016/s0140-6736(95)92830-8. PMID: 7623606. 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Efficacy of GLP-1 Receptor Agonists on Weight Loss, BMI, and Waist Circumference for Patients With Obesity or Overweight: A Systematic Review, Meta-analysis, and Meta-regression of 47 Randomized Controlled Trials. Diabetes Care. 2025;48:292–300. Berg S, Stickle H, Rose SJ, Nemec EC. Discontinuing glucagon‐like peptide‐1 receptor agonists and body habitus: A systematic review and meta‐analysis. Obes Rev. 2025;26. Drucker DJ, Nauck MA. The incretin system: glucagon-like peptide-1 receptor agonists and dipeptidyl peptidase-4 inhibitors in type 2 diabetes. Lancet. 2006;368:1696–705. Mingrone G, Panunzi S, De Gaetano A, Guidone C, Iaconelli A, Capristo E, et al. Metabolic surgery versus conventional medical therapy in patients with type 2 diabetes: 10-year follow-up of an open-label, single-centre, randomised controlled trial. Lancet. 2021;397:293–304. Rubino F, Nathan DM, Eckel RH, Schauer PR, Alberti KGMM, Zimmet PZ, et al. Metabolic Surgery in the Treatment Algorithm for Type 2 Diabetes: A Joint Statement by International Diabetes Organizations. Diabetes Care. 2016;39:861–77. Reinmann A, Gafner SC, Hilfiker R, Bruyneel A-V, Pataky Z, Allet L. Bariatric Surgery: Consequences on Functional Capacities in Patients With Obesity. Front Endocrinol (Lausanne). 2021;12. Bullo V, Pavan D, Gobbo S, Bortoletto A, Cugusi L, Di Blasio A, et al. From surgery to functional capacity: muscle strength modifications in women post sleeve gastrectomy. BMC Sports Sci Med Rehabil. 2024;16:118. Burza MA, Romeo S, Kotronen A, Svensson P-A, Sjöholm K, Torgerson JS, et al. Long-Term Effect of Bariatric Surgery on Liver Enzymes in the Swedish Obese Subjects (SOS) Study. Targher G, editor. PLoS One. 2013;8:e60495. Azulai S, Grinbaum R, Beglaibter N, Eldar SM, Rubin M, Ben-Haroush Schyr R, et al. Sleeve Gastrectomy Is Associated with a Greater Reduction in Plasma Liver Enzymes Than Bypass Surgeries—A Registry-Based Two-Year Follow-Up Analysis. J Clin Med. 2021;10:1144. Zadeh MH, Zamaninour N, Ansar H, Kabir A, Pazouki A, Farsani GM. Changes in serum albumin and liver enzymes following three different types of bariatric surgery: six-month follow-up. A retrospective cohort study. Sao Paulo Med J. 2021;139:598–606. Nomine-Criqui C, Reibel N, Brunaud L. Bariatric surgery: Have we reached the age of maturity? J Visc Surg. 2023;160:S1–2. Zhao N, Tao K, Wang G, Xia Z. Global obesity research trends during 1999 to 2017. Medicine (Baltimore). 2019;98:e14132. Tarazi A. Comparative Analysis of the Bibliographic Data Sources Using PubMed, Scopus, Web of Science, and Lens. High Yield Med Rev. 2024;2. Liang Z, Mao J, Lu K, Li G. Finding citations for PubMed: a large-scale comparison between five freely available bibliographic data sources. Scientometrics. 2021;126:9519–42. OpenCitations. COCI, the OpenCitations Index of Crossref open DOI-to-DOI citations. Available in: https://opencitations.net/index/coci. Marzi G, Balzano M, Caputo A, Pellegrini MM. Guidelines for Bibliometric‐Systematic Literature Reviews: 10 steps to combine analysis, synthesis and theory development. Int J Manag Rev. 2025;27:81–103. Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterial1SearchStrategy.docx SupplementaryMaterial2StudyMetadata.xlsx SupplementaryMaterial3machineleaningLDA.r SupplementaryMaterial4Normalizationtable.docx SupplementaryMaterial5classiccitations.xlsx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 07 Mar, 2026 Reviews received at journal 27 Feb, 2026 Reviewers agreed at journal 27 Feb, 2026 Reviews received at journal 25 Feb, 2026 Reviewers agreed at journal 25 Feb, 2026 Reviewers invited by journal 20 Feb, 2026 Editor assigned by journal 20 Feb, 2026 Submission checks completed at journal 19 Feb, 2026 First submitted to journal 11 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8854344","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":592203254,"identity":"042f1430-a675-4cdd-99d9-e40f7f684a4f","order_by":0,"name":"Rômulo Ferreira Monteiro","email":"data:image/png;base64,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","orcid":"","institution":"Universidade Federal de Santa Catarina","correspondingAuthor":true,"prefix":"","firstName":"Rômulo","middleName":"Ferreira","lastName":"Monteiro","suffix":""},{"id":592203256,"identity":"82cce5d8-7f38-4912-8ea6-e060f60a6076","order_by":1,"name":"Victor Celestino Pires","email":"","orcid":"","institution":"Universidade Federal de Santa Catarina","correspondingAuthor":false,"prefix":"","firstName":"Victor","middleName":"Celestino","lastName":"Pires","suffix":""},{"id":592203259,"identity":"a715b9e5-d5fa-41f9-9de9-55d610fbabdf","order_by":2,"name":"Tiago Rafael Onzi","email":"","orcid":"","institution":"Universidade Federal de Santa Catarina","correspondingAuthor":false,"prefix":"","firstName":"Tiago","middleName":"Rafael","lastName":"Onzi","suffix":""},{"id":592203261,"identity":"087c275b-5ec6-423e-a3b2-74506d89e31e","order_by":3,"name":"Giovani Firpo Del Duca","email":"","orcid":"","institution":"Universidade Federal de Santa Catarina","correspondingAuthor":false,"prefix":"","firstName":"Giovani","middleName":"Firpo Del","lastName":"Duca","suffix":""},{"id":592203262,"identity":"6bdf8162-1a6b-4b01-b039-b95b0d4a9953","order_by":4,"name":"Jucemar Benedet","email":"","orcid":"","institution":"Universidade Federal de Santa Catarina","correspondingAuthor":false,"prefix":"","firstName":"Jucemar","middleName":"","lastName":"Benedet","suffix":""}],"badges":[],"createdAt":"2026-02-11 17:25:59","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8854344/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8854344/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102895068,"identity":"176a75b0-5cb7-4443-89dc-04117c8aeafa","added_by":"auto","created_at":"2026-02-18 06:17:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":151018,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram of the study selection process across the three databases.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8854344/v1/f4f80b7cb0c4d53b339a15ee.png"},{"id":102963871,"identity":"479bef4a-bc10-4812-8dac-3c400f116fad","added_by":"auto","created_at":"2026-02-19 04:20:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":150994,"visible":true,"origin":"","legend":"\u003cp\u003eAnnual number of articles published from 2001 to 2024 and forecast for the period from 2025 to 2030. The smoothing line shows the growth in publications between 2001 and 2019, followed by a gradual decline. The estimated output is approximately 306 publications for the period from 2025 to 2030.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8854344/v1/cec66978c14fae1518b67203.png"},{"id":102963630,"identity":"624ba578-f2a2-4a8a-b386-378464b9a3e2","added_by":"auto","created_at":"2026-02-19 04:19:31","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":131998,"visible":true,"origin":"","legend":"\u003cp\u003eFig. 3a. The ten most productive countries based on total publication output.\u003c/p\u003e\n\u003cp\u003eFig. 3b. The ten most productive countries per million inhabitants.\u003c/p\u003e\n\u003cp\u003eFig. 3c. The ten most productive countries per thousand bariatric surgeries performed.\u003c/p\u003e\n\u003cp\u003eFig. 3d. The ten most productive countries per million individuals with obesity.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8854344/v1/321c47b7d5c02960471d25b0.png"},{"id":102964586,"identity":"5bc55bde-7b1c-426a-9554-5355c2b1ebda","added_by":"auto","created_at":"2026-02-19 04:22:54","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":283915,"visible":true,"origin":"","legend":"\u003cp\u003eTrends of topics over time: the red line represents rising topics, the blue line indicates declining topics, and the black line reflects temporal variations. B1 = slope coefficient; p = p-value; * = significant at p \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8854344/v1/f4a35120c7d9430d53dafe28.png"},{"id":102965649,"identity":"11770b90-78a5-4875-8463-e62d6225d7a5","added_by":"auto","created_at":"2026-02-19 04:32:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1673715,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8854344/v1/b15bb527-c748-4a8f-a496-dffbbc23e444.pdf"},{"id":102963470,"identity":"fe8edb93-8434-4380-aa72-e90191c48db5","added_by":"auto","created_at":"2026-02-19 04:18:10","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":20804,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial1SearchStrategy.docx","url":"https://assets-eu.researchsquare.com/files/rs-8854344/v1/cf5a796a9c62058d1bf3c464.docx"},{"id":102963891,"identity":"dcd9944e-d413-4ff0-98e2-77ba1e261ff1","added_by":"auto","created_at":"2026-02-19 04:20:48","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1723432,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial2StudyMetadata.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8854344/v1/9f3624f54d2f1a287aa0ed6d.xlsx"},{"id":102963818,"identity":"7fd906a3-a42e-4e75-a5f7-53acabcea20e","added_by":"auto","created_at":"2026-02-19 04:20:38","extension":"r","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":15775,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial3machineleaningLDA.r","url":"https://assets-eu.researchsquare.com/files/rs-8854344/v1/83d5ed77cf88bd74cda71a89.r"},{"id":102963606,"identity":"18c12399-4ae4-427b-b42f-f7274970175e","added_by":"auto","created_at":"2026-02-19 04:19:20","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":50245,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial4Normalizationtable.docx","url":"https://assets-eu.researchsquare.com/files/rs-8854344/v1/570d9db074940ba6b3a7d6b8.docx"},{"id":102963882,"identity":"9f52ec39-bc5b-482a-a4da-deba381d7e61","added_by":"auto","created_at":"2026-02-19 04:20:47","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":31561,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial5classiccitations.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8854344/v1/50d213377ea4bf270c2a23d7.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Global Trends in Scientific Output of Clinical Trials on Gastric Bypass: A Machine Learning–Based Bibliometric Study","fulltext":[{"header":"Key Points","content":"\u003cp\u003e\u0026bull; Projections suggest a stabilization of research output in the field through 2030.\u003c/p\u003e\u003cp\u003e\u0026bull; The United States leads in absolute output, while Europe leads after normalization.\u003c/p\u003e\u003cp\u003e\u0026bull; Differences in obsolescence reflect varying scientific impact and longevity.\u003c/p\u003e\u003cp\u003e\u0026bull; Dominant topics focus on intestinal hormones and diabetes mellitus.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eMetabolic bariatric surgery (MBS) has historical records dating back to the 10th century, when King Sancho I of Le\u0026oacute;n reportedly had his mouth sutured in a primitive attempt to control body weight [1]. In contemporary practice, MBS comprises a group of procedures performed on the gastrointestinal tract with the aim of inducing weight loss in individuals with severe obesity and reducing the risk of associated diseases, such as type 2 diabetes mellitus and hypertension. These procedures act through gastric restriction, alterations in intestinal transit, and hormonal modifications that promote both weight reduction and metabolic control [2].\u003c/p\u003e \u003cp\u003eObesity is recognized as one of the major public health challenges of the 21st century [3,4]. Its global prevalence has more than doubled since 1990, and in 2022 it was estimated that one in eight people worldwide was living with obesity. In its most severe forms, Obesity III (body mass index\u0026thinsp;\u0026ge;\u0026thinsp;40 kg/m\u0026sup2;) is projected to affect more than 110\u0026nbsp;million adults by 2030, highlighting the worsening epidemiological scenario [5,6]. Within this context, MBS has been established as the reference treatment for severe obesity, owing to its effectiveness in achieving sustained weight loss and and improving obesity-associated metabolic diseases [7].\u003c/p\u003e \u003cp\u003eAgainst this backdrop, the number of metabolic bariatric surgery procedures performed worldwide has increased continuously. In 2014, a total of 100,092 procedures were reported, and by 2023 this number had risen to 598,736 surgeries, reflecting the global expansion of this therapeutic approach [8,9]. Among the techniques currently available in metabolic bariatric surgery, gastric bypass stands out as one of the oldest, most established, and most widely performed procedures [10], particularly due to its metabolic effects and the high percentage of excess weight loss (%EWL). Studies indicate that patients may achieve up to a 57% reduction in total body weight five years after surgery [11].\u003c/p\u003e \u003cp\u003eIn parallel with the increasing prevalence of obesity and the growth in surgical volume, there has been a marked expansion in scientific production on this topic. A search conducted in August 2025 in the Web of Science, PubMed, and Scopus databases using the term \u0026ldquo;gastric bypass\u0026rdquo; retrieved more than 72,000 publications, highlighting both the magnitude of the field and the challenge of comprehensively tracking its scientific evolution. In this context, narrative and bibliometric literature reviews are frequently used by clinicians, researchers, and the general public as a primary source of up-to-date information on the subject [12].\u003c/p\u003e \u003cp\u003eClinical trials play a central role in the development of health interventions, as they allow rigorous methodological evaluation of the efficacy and safety of new treatments, enabling investigations ranging from preliminary safety assessments to direct comparisons between different therapeutic approaches. By reducing bias and generating high-quality evidence, these studies provide the necessary foundation for informed clinical decision-making and for the adoption of effective therapeutic practices. Consequently, clinical trials constitute an essential pillar in the advancement of evidence-based practice and in ensuring increasingly safe and efficient healthcare [13,14].\u003c/p\u003e \u003cp\u003eSeveral bibliometric studies have characterized the international scientific output on bariatric surgery and have identified, since the early 2000s, a marked increase in publications, with gastric bypass accounting for a greater volume of research [15,16]. In contrast, sleeve gastrectomy, despite currently being the most frequently performed procedure, shows a lower cumulative volume of studies, likely because it was more recently incorporated as a primary surgical technique [17]. In this context, scientific production specifically focused on the sleeve gastrectomy procedure has been analyzed [18,19]; however, a clear gap remains with regard to bibliometric studies specifically addressing clinical trials on gastric bypass.\u003c/p\u003e \u003cp\u003eIn this context, the present study aimed to map the scientific production on gastric bypass (GB) through the analysis of clinical trials (CTs) indexed in the three largest international databases between 2001 and 2024. In addition, the study sought to identify and explore the main topics and thematic trends in the field using different machine learning and bibliometric techniques, thereby providing a comprehensive and systematized overview of this research area.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Sources and Search Strategy\u003c/h2\u003e \u003cp\u003eSearches were conducted in the Web of Science, PubMed/MEDLINE, and Scopus databases (WPS). The search was performed on September 5, 2025, and included clinical trials published between 2001 and 2024, with no language restrictions. The search strategy combined descriptors in the TITLE-ABS-KEY fields using the following terms: (\u0026ldquo;gastric bypass\u0026rdquo; OR \u0026ldquo;Roux-en-Y gastric bypass\u0026rdquo; OR \u0026ldquo;RYGB\u0026rdquo; (Roux-en-Y gastric bypass) OR \u0026ldquo;Laparoscopic Roux-en-Y gastric bypass\u0026rdquo; OR \u0026ldquo;LRYGB\u0026rdquo; (laparoscopic Roux-en-Y gastric bypass) OR \u0026ldquo;OAGB\u0026rdquo; (one anastomosis gastric bypass) OR \u0026ldquo;One Anastomosis Gastric Bypass\u0026rdquo; OR \u0026ldquo;Mini-Gastric Bypass\u0026rdquo; OR \u0026ldquo;Single Anastomosis Gastric Bypass\u0026rdquo;) AND (\u0026ldquo;clinical trial\u0026rdquo; OR \u0026ldquo;clinical trials\u0026rdquo; OR \u0026ldquo;randomized controlled trial\u0026rdquo; OR \u0026ldquo;randomised controlled trial\u0026rdquo; OR \u0026ldquo;RCT\u0026rdquo; (randomized controlled trial) OR \u0026ldquo;interventional study\u0026rdquo; OR \u0026ldquo;controlled clinical trial\u0026rdquo; OR \u0026ldquo;controlled trial\u0026rdquo; OR \u0026ldquo;clinical research\u0026rdquo; OR \u0026ldquo;clinical investigation\u0026rdquo; OR \u0026ldquo;therapeutic trial\u0026rdquo; OR \u0026ldquo;treatment trial\u0026rdquo;). The detailed, database-specific search strategies are provided in Supplementary Material 1.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eInclusion Criteria and Study Selection\u003c/h3\u003e\n\u003cp\u003eThe inclusion criteria comprised randomized and non-randomized clinical trials conducted in patients with obesity undergoing gastric bypass, specifically including the Roux-en-Y gastric bypass (RYGB) and the one anastomosis gastric bypass (OAGB), either as isolated procedures or in combination with other techniques. Studies involving participants of all age groups were considered eligible, provided they reported outcomes of any nature, including clinical, metabolic, anthropometric, surgical, or other relevant endpoints. The analysis period covered publications from 2001 to 2024 and was restricted exclusively to the English language, as the Latent Dirichlet Allocation (LDA) topic modeling algorithm requires linguistic homogeneity and supports only a single language during analysis. Initially, articles containing the predefined search descriptors in their titles or abstracts were selected. Identified studies were organized in an electronic spreadsheet (Microsoft Office Excel, version 2016) and independently assessed in pairs for readability and compliance with the inclusion criteria.\u003c/p\u003e \u003cp\u003eAll articles that did not qualify as clinical trials (randomized or non-randomized) were excluded, including observational studies, reviews, and other publication types such as letters, editorials, protocols, and preclinical studies. Articles focusing exclusively on bariatric techniques other than gastric bypass, such as sleeve gastrectomy, gastric banding, and related procedures, were also excluded, as were studies published in languages other than English, duplicate records, and articles published before 2001 or after 2024. In cases of uncertainty regarding eligibility, both reviewers performed a full-text assessment and reached a consensus decision on study inclusion or exclusion.\u003c/p\u003e\n\u003ch3\u003eBibliometric and Statistical Analysis Methods\u003c/h3\u003e\n\u003cp\u003eBibliometric data, including year of publication, authorship, keywords, study location, number of citations, and other relevant metadata, were organized in a Microsoft Excel spreadsheet to enable subsequent analyses. The complete metadata set is provided in Supplementary Material 2.\u003c/p\u003e \u003cp\u003eTo generate publication forecasts through 2030, an AutoRegressive Integrated Moving Average (ARIMA) model was fitted to the time series of annual publication counts from 2001 to 2024. Model adequacy was assessed through residual analysis and the Ljung\u0026ndash;Box test, with a 95% confidence interval.\u003c/p\u003e \u003cp\u003eNormalization of publication output was performed by dividing the total number of articles by the mean population between 2001 and 2024, expressed per million inhabitants For bariatric surgery volume, publication counts were normalized by the total number of procedures performed and reported as articles per 1,000 surgeries [21]. Finally, for obesity prevalence, the affected population in each country was estimated by multiplying the total population in 2024 by the obesity prevalence reported by the World Health Organization [22]. The obesity index was then calculated by dividing the number of publications by the estimated total number of individuals with obesity and multiplying the result by one million, yielding an indicator expressed as articles per million affected individuals.\u003c/p\u003e \u003cp\u003eRegarding authorship, the following indicators were evaluated: total number of citations, coauthorship position, productivity per active year of publication (PAY), and number of active years, reflecting academic experience (NAY). In addition, Lotka\u0026rsquo;s law was applied to assess authors\u0026rsquo; productivity patterns [23].\u003c/p\u003e \u003cp\u003eTo characterize the most highly cited publications, journal impact factor values were obtained from the Journal Citation Reports (Clarivate Analytics/Web of Science, 2024). Citation counts for each article were retrieved using OpenCitations (OC) [24], which typically reports higher citation numbers than the Web of Science and Scopus databases and additionally provides citation data not available in PubMed [25]. Data extraction was performed through the public OC application programming interface (API), using the pandas, requests, and numpy packages implemented in Python [26]. For the calculation of citation half-life and obsolescence, the COCI/OpenCitations endpoint (/index/coci/api/v1/citations/{doi}) was used to extract, for each digital object identifier (DOI), the timespan field, defined as the interval between the publication dates of the cited and citing articles. This interval was converted into years (years\u0026thinsp;+\u0026thinsp;months/12\u0026thinsp;+\u0026thinsp;days/365.25). Additional metrics, including total citations, citations per year, and normalized citations, were obtained using the bibliometrix package [12]. Sample size and intervention duration were manually extracted through full-text article review. To assess the level of evidence of the ten most cited articles, the Levels of Evidence scale of the Journal of Bone \u0026amp; Joint Surgery was applied [27].\u003c/p\u003e \u003cp\u003eFor topic analysis, abstracts were extracted, organized in a Microsoft Excel spreadsheet (version 2016), and subsequently preprocessed in R. Text preprocessing included lowercasing, removal of punctuation, special characters, excess whitespace, bigrams, trigrams, English stopwords, and words with fewer than four characters. Topic modeling was performed using Latent Dirichlet Allocation (LDA) [28], with Gibbs sampling (1,000 iterations) and hyperparameters set to α\u0026thinsp;=\u0026thinsp;0.1 and η\u0026thinsp;=\u0026thinsp;0.1. Models with K ranging from 10 to 50 topics were tested, and model quality was evaluated using coherence metrics. The final model (K\u0026thinsp;=\u0026thinsp;29) was selected for achieving the best balance between statistical fit and semantic interpretability. The descriptions of the named subtopics were subsequently reviewed and validated by an experienced bariatric and metabolic surgery specialist. Topic frequencies and linear trend classifications (rising, declining, or stable) were also assessed. The full analytical script is provided in Supplementary Material 3.\u003c/p\u003e \u003cp\u003eFollowing topic estimation, the topic probability distribution (θ) was obtained for each document. To assess thematic evolution over time, topic proportions were aggregated by year of publication, generating an annual topic\u0026ndash;year matrix based on mean topic probabilities. For each topic, a simple linear regression model was fitted to the annual mean proportions to evaluate temporal trends, with the slope coefficient (β₁) indicating directionality. A significance threshold of p\u0026thinsp;\u0026lt;\u0026thinsp;0.01 was adopted to reduce type I error. Topics were classified as rising (β₁ \u0026gt; 0), declining (β₁ \u0026lt; 0), or stable (β₁ \u0026asymp; 0), enabling identification of themes with increasing, decreasing, or stable relevance over the study period. For descriptive statistical analyses, means, standard deviations, and medians were calculated, and trends in scientific production were assessed using the Mann\u0026ndash;Kendall test. Bibliometric analyses were conducted using the R software [29], with the bibliometrix package [12] and the Visualization of Similarities viewer (VOSviewer) (VOSviewer) [30].\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe search strategy identified a total of 4,348 publications. However, when restricting the results to clinical trials, a reduction in the number of records was observed: Web of Science (1,019), PubMed (765), and Scopus (2,564). After duplicate removal and application of the inclusion criteria, 425 records from Web of Science, 94 from PubMed, and 583 from Scopus remained, resulting in a final sample of 1,102 articles included for analysis(Fig. 1).\u003c/p\u003e\n\u003ch3\u003eScientific Production\u003c/h3\u003e\n\u003cp\u003eOf the total articles analyzed, 849 (77.0%) addressed gastric bypass (GB) exclusively, 221 (19.5%) investigated a combination of GB and sleeve gastrectomy, and 32 (3.2%) examined GB in association with other bariatric procedures, including sleeve gastrectomy, biliopancreatic diversion with duodenal switch, and adjustable gastric banding.\u003c/p\u003e\n\u003cp\u003ePublication trends over the study period are presented in Fig. 2 and demonstrate a statistically significant annual growth rate of 10.61% (Kendall\u0026rsquo;s tau\u0026thinsp;=\u0026thinsp;0.808; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). An approximate 374% increase in publications was observed from the first decade (152 articles) to the second decade (664 publications) of the analyzed period. Between 2021 and 2024, a total of 286 publications were recorded, corresponding to nearly half of the total output of the preceding decade. For the period from 2025 to 2030, an additional 309 publications are projected (95% confidence interval: 118\u0026ndash;496), suggesting a trend toward stabilization in the volume of scientific production.\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eProlific Countries\u003c/h2\u003e\n \u003cp\u003eContributions to research on clinical trials in gastric bypass were identified from 47 countries. Regional analysis (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea) showed that North America and South America account for a substantial share of absolute scientific output, largely driven by the United States and Brazil. However, when publication data were normalized by national population size (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eb), number of bariatric surgeries performed per country (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ec), and per million individuals with obesity (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ed), the overall pattern changed. Under these adjusted metrics, Europe emerged as the region with the highest relative publication density, surpassing the Americas and, to a lesser extent, Asia and Oceania.\u003c/p\u003e\n \u003cp\u003eIt should be noted that some normalization adjustments could only be calculated for a subset of the sample due to limitations in data availability from the International Federation for the Surgery of Obesity and Metabolic Disorders, the World Health Organization, and the United Nations. Complete results are presented in Supplementary Table 4.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eAuthor Productivity\u003c/h3\u003e\n\u003cp\u003eAcross the total body of publications included in this study, 6118 authors contributed to clinical trials on gastric bypass. The mean number of authors per publication was 8.65, with international coauthorship accounting for 9.9% of the studies. Productivity distribution revealed that approximately 77% (4721/6118) of authors published only a single article, whereas only 1.4% (86/6118) authored five or more publications. Table\u0026nbsp;1 presents the ten most productive authors and the main characteristics of their scientific output.\u003c/p\u003e\n\u003cp\u003eEuropean authors predominated among the most productive researchers, and nine of the ten most cited authors demonstrated more than a decade of academic experience, as measured by the number of active years (NAY), which was associated with greater citation impact. Nevertheless, despite their extensive experience, the mean annual productivity did not exceed three publications per year, as indicated by productivity per active year (PAY). A predominance of coauthorship positions was also observed, particularly last authorship, which was occupied by most of these researchers.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\"\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e The ten most prolific authors and their characteristics\u003c/div\u003e\n \u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRank\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAuthor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eArticles\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eT. C.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eC.Y.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eF- L\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNAY-PAY\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOlbers T (Sweden)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34 (3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8636\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e479.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u0026ndash;9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u0026thinsp;\u0026minus;\u0026thinsp;1,89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHjelmesaeth J(Norway)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (2.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u0026ndash;19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u0026ndash;2.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHolst J(Denmark)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (2.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e214.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u0026ndash;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u0026thinsp;\u0026minus;\u0026thinsp;2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLe Roux CW (Irland)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27 (2.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2773\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e213.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u0026ndash;9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u0026thinsp;\u0026minus;\u0026thinsp;2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCourcoulas A (USA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (2.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2299\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e191.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u0026thinsp;\u0026minus;\u0026thinsp;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u0026ndash;1.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHofso D(Norway)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (1.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e764\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026ndash;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u0026thinsp;\u0026minus;\u0026thinsp;2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMadsbad S (Denmark)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (1.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1745\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e193.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u0026ndash;9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u0026ndash;2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSandbu R(Norway)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e553\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u0026ndash;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u0026thinsp;\u0026minus;\u0026thinsp;1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKirwan JP(USA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (1.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6489\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e540\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u0026thinsp;\u0026minus;\u0026thinsp;1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePeltonen M(Finl\u0026acirc;ndia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (1.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6798\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e679.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u0026ndash;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u0026thinsp;\u0026minus;\u0026thinsp;1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e% = Percentage of clinical trials published relative to the total number of articles\u003c/p\u003e\n\u003cp\u003eT.C. = Total citations\u003c/p\u003e\n\u003cp\u003eC.Y. = Citations per year\u003c/p\u003e\n\u003cp\u003eF = Number of times the author appeared as first author\u003c/p\u003e\n\u003cp\u003eL = Number of times the author appeared as last author\u003c/p\u003e\n\u003cp\u003eNAY = Number of active years\u003c/p\u003e\n\u003cp\u003ePAY = Productivity per active year of publication\u003c/p\u003e\n\u003ch3\u003eThe Ten Most Cited Publications\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;2 presents the main characteristics of the ten most cited publications. Collectively, these studies accumulated 20921 citations, with individual citation counts ranging from 1008 to 4040. This volume corresponds to 26.6% (20921/78619) of the total citations across all analyzed articles, indicating that approximately one quarter of all citations were concentrated in only ten publications. In addition, 155 citation classics were identified, of which 131 had more than 100 citations and 24 had more than 400 citations (see Supplementary Table\u0026nbsp;4).\u003c/p\u003e\n\u003cp\u003eThe mean number of authors per publication was 12.4 (standard deviation\u0026thinsp;=\u0026thinsp;5.33), with a median of 11.5. A strong concentration of publications in very high\u0026ndash;impact journals was observed, with eight of the ten articles published in journals with a Journal Impact Factor (JIF) greater than 70, including The New England Journal of Medicine (JIF 2024: 78.5) and The Lancet (JIF 2024: 88.5).Medicine (JIF 2024: 78.5) e no The Lancet (JIF 2024: 88.5).\u003c/p\u003e\n\u003cp\u003eWith regard to citation half-life, the most cited article, \u0026ldquo;Effects of Bariatric Surgery on Mortality in Swedish Obese Subjects\u0026ndash;2007\u0026rdquo; [31], exhibited a citation half-life exceeding 7 years, indicating moderate obsolescence. Only the article \u0026ldquo;Lifestyle, Diabetes, and Cardiovascular Risk Factors 10 Years after Bariatric Surgery\u0026ndash;2004\u0026rdquo; [32] demonstrated slow obsolescence, with a citation half-life longer than 9 years. In contrast, rapid obsolescence (3.17 years) was observed in the study \u0026ldquo;Bariatric Surgery versus Intensive Medical Therapy for Diabetes\u0026ndash;3-Year Outcomes\u0026ndash;2014\u0026rdquo; [33].\u003c/p\u003e\n\u003cp\u003eAll ten publications showed normalized citation values above 6, indicating that they were cited more than six times above the average for articles published in the same year. A predominance of randomized clinical trials (level of evidence I) was observed, along with methodological diversity, as nine publications investigated different surgical techniques. Additionally, a wide variation in sample size was noted (ranging from 33 to 4,047 participants), with a predominance of longitudinal study designs and follow-up periods of five years or less.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2\u0026nbsp;\u003c/strong\u003eTen most cited articles on gastric bypass and their characteristics\u003c/p\u003e\n \u003ctable id=\"Tabb\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRank\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAuthors\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTitle\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSource title\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP.Y.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eT.C.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eA.V.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eC.H.L\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN. C.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eL.E.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eS.S.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eD.I.\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eL. Sj\u0026ouml;str\u0026ouml;m, et al. [31]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEffects of Bariatric Surgery on Mortality in Swedish Obese Subjects(SOS)\u0026ndash;N\u0026atilde;o randomizado -Su\u0026eacute;cia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe New England Journal of Medicine- JIF 2024\u0026ndash;78.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eL. Sj\u0026ouml;str\u0026ouml;m, et al. [32]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLifestyle, Diabetes, and Cardiovascular Risk Factors 10 Years after Bariatric Surgery(SOS)- N\u0026atilde;o randomizado- Su\u0026eacute;cia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe New England Journal of Medicine- JIF 2024\u0026ndash;78.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3975\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhilip R. Schauer et al.[33]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBariatric Surgery versus Intensive Medical Therapy for Diabetes\u0026thinsp;\u0026minus;\u0026thinsp;5-Year Outcomes - Randomizado-EUA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe New England Journal of Medicine- JIF 2024\u0026ndash;78.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDavid E. Cummings, J. et al. [34]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePlasma Ghrelin Levels after Diet-Induced Weight Loss or Gastric Bypass Surgery -N\u0026atilde;o randomizado-EUA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe New England Journal of Medicine- JIF 2024\u0026ndash;78.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhilip R. Schauer et al. [35]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBariatric Surgery versus Intensive Medical Therapy in Obese Patients with Diabetes-Randamizado- EUA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe New England Journal of Medicine- JIF 2024\u0026ndash;78.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1985\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGeltrude Mingrone, et al. [36]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBariatric Surgery versus Conventional Medical Therapy for Type 2 Diabetes-Randomizado-It\u0026aacute;lia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe New England Journal of Medicine- JIF 2024\u0026ndash;78.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1601\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGeltrude Mingrone, et al. [37]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBariatric\u0026ndash;metabolic surgery versus conventional medical treatment in obese patients with type 2..Randomised -It\u0026aacute;lia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe Lancet -JIF 2024\u0026thinsp;\u0026minus;\u0026thinsp;88.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1459\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhilip R. Schauer, et al. [38]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBariatric Surgery versus Intensive Medical Therapy for Diabetes\u0026thinsp;\u0026minus;\u0026thinsp;3-Year Outcomes- Randomizado-EUA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe New England Journal of Medicine- JIF 2024\u0026ndash;78.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1374\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLars Sj\u0026ouml;str\u0026ouml;m, Markku et al. [39]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBariatric Surgery and Long-term Cardiovascular Events (SOS)-N\u0026atilde;o randomizado-Su\u0026eacute;cia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJAMA Network- JIF 2024\u0026thinsp;\u0026minus;\u0026thinsp;9.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRalph Peterli, MD; et al. [40]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEffect of Laparoscopic Sleeve Gastrectomy vs Laparoscopic Roux-en-Y Gastric Bypass on Weight Loss in Patients -Randomizado- Su\u0026iacute;\u0026ccedil;a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJAMA Network- JIF 2024\u0026ndash;9.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eP.Y.=Publication year S.S.=Sample size\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eT. C.=Total citation \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;D.I.=Duration of intervention in years\u003c/p\u003e\n\u003cp\u003eA.V.=Average per year \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u003csup\u003ea,b\u0026nbsp;\u003c/sup\u003eLetras id\u0026ecirc;nticas indicam que os dados foram obtidos a partir do mesmo estudo. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eC.H.L=Citation half-life \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eN. C.=\u0026nbsp;Normalized citation\u003c/p\u003e\n\u003cp\u003eL.E=Level of evidence\u003c/p\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eAnalysis of Emerging Topics and Temporal Evolution Using Latent Dirichlet Allocation (LDA)\u003c/h2\u003e\n \u003cp\u003eTopic modeling performed using the Latent Dirichlet Allocation (LDA) algorithm enabled the identification of clusters of keywords organized according to semantic coherence. Representative labels were assigned to these clusters, characterizing them as subtopics. This approach allowed both joint and individual interpretation, as well as the analysis of temporal trends and the frequency of documents associated with each identified topic (Table\u0026nbsp;3).\u003c/p\u003e\n \u003cp\u003eA total of 29 topics were identified, of which nineteen exhibited stable trends, eight showed increasing trends, and only two demonstrated declining trends. When the sets of keywords were examined collectively, topics clearly emerged that encompassed all stages involved in gastric bypass. Prominent themes included technical and procedural aspects and surgical techniques, perioperative care and postoperative complications, clinical and metabolic outcomes of bariatric surgery, weight loss and recurrent weight gain, cardiometabolic markers, lipid profile, systemic inflammation, and cardiovascular risk.\u003c/p\u003e\n \u003cp\u003eIt is noteworthy that, beyond these specific domains, topics with a multidisciplinary scope were also identified, such as eating behavior, psychological aspects, physical exercise, functional capacity, and health-related quality of life, reflecting a multidimensional approach to the effects of bariatric surgery. Conversely, according to topic frequency analysis, relatively few clinical trials addressed issues related to bone health, quality of life, cholelithiasis, sleep apnea, respiratory aspects, vitamin D, and gut microbiota, indicating underrepresented areas within the current research landscape.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\"\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e Subtopics and keywords derived from the topics identified by the LDA model\u003c/div\u003e\n \u003ctable id=\"Tabc\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTopic (Frequency)\u003c/p\u003e\n \u003cp\u003eTrend\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ekeywords\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSubtopic\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e(52)\u003c/p\u003e\n \u003cp\u003eStable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elaparoscopic_roux_en_y, laparoscopic_sleeve_gastrectomy, gastric_bypass_lrygb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLaparoscopic Surgical Techniques\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emorbid_obesity, obesity_related, body_mass_index_bmi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClinical Classification of Obesity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eco_morbidities, related_comorbidities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eObesity-associated diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egastroesophageal_reflux, reflux_disease, disease_gerd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGastroesophageal Reflux Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emajor_complications, complication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSurgical Complications\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e(29)\u003c/p\u003e\n \u003cp\u003eStable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eclinical_trial, single_center, primary_outcome, led_trial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClinical Trial\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eexcess_weight_loss(EWL), post_bariatric, high_risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeight Loss Outcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eliver_disease, fatty_liver, liver_function, pmol_l\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLiver Diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e(50)\u003c/p\u003e\n \u003cp\u003eRising\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eweight_loss, total_weight_loss, weight_loss_twl, greater_weight_loss, weight_loss_compared, weight_regain, body_mass_index_bmi, gastric_bypass_rygb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeight Loss and Recurrent weight gain\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elong_term, year_follow_up, term_follow_up, first_year, term_effects,gastric_bypass_rygb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLong Term Outcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eeating_behavior, binge_eating, depressive_symptoms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEating Behavior and Psychological Aspects\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eamerican_society\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClinical Guidelines\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e(38)\u003c/p\u003e\n \u003cp\u003eStable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003einsulin_resistance, homa_ir, plasma_glucose, fasting_glucose, fasting_blood_glucose, glucose_insulin, fasting_insulin, homeostasis, mg_dl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGlucose Metabolism and Insulin Resistance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003etotal_cholesterol, density_lipoprotein, low_density, lipoprotein_cholesterol, mmol_l\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLipid Profile and Cholesterol\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emetabolic_syndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMetabolic Syndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ebody_mass_index_bmi, bmi_kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBody Mass Index (BMI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003cp\u003e(35)\u003c/p\u003e\n \u003cp\u003eRising\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eexercise_training, physical_training, supervised_physical, training_program, aerobic_exercise.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExercise Based Interventions\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ephysical_function, functional_capacity, muscle_strength.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFunctional Capacity and Muscle Strength\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ebariatric_surgery, post bariatric_surgery, pre_surgery, rygb, usual_care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBariatric Surgery\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ebody_composition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBody Composition\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e(31)\u003c/p\u003e\n \u003cp\u003eStable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eclinical_trial, led_trial, double_blind, blind_led, primary_outcome, trial_registration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClinical Trials\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ebariatric_surgery, obesity_undergoing, Biliopancreatic Diversion with Duodenal Switch, small_intestine, morbid_obesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBariatric Surgery\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egallstone_formation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGallstone Formation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eexcess_skin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExcess Skin\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e(33)\u003c/p\u003e\n \u003cp\u003eStable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eroux-en-Y Gastric Bypass, gastric_bypass, RYGBP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRoux en Y Gastric Bypass\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ec-reactive protein (CRP), TNF-alpha, necrosis_factor, interleucina, inflammatory_markers, mortality_risk, metabolic_syndrome, body_mass_index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInflammatory Markers and Metabolic Syndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003cp\u003e(45)\u003c/p\u003e\n \u003cp\u003eStable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egastric_bypass_surgery, undergoing_gastric_bypass, gastric_pouch,.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTechnical Aspects of Gastric Bypass\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eroux_stasis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRoux en Y Stasis Syndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epreoperative_weight_loss, post_operatively, ope_d, non_ope, bmi_kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePerioperative Weight Management\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ebile_acids, bile_acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMetabolism and Bile Acids\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e(50)\u003c/p\u003e\n \u003cp\u003eStable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003etype 2 diabetes mellitus, diabetes_mellitus, dm_remission, complete_remission, remission, long_term, HbA1c, hemoglobin_A1c, obese morbidly_obese_patient, body_mass_index_bmi.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eType 2 Diabetes Mellitus and Remission\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egastric_bypass_rygb, sleeve_gastrectomy_sg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRYGB versus Sleeve Gastrectomy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003cp\u003e(83)\u003c/p\u003e\n \u003cp\u003eRising\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eglucagon_like, like_peptide, peptide_glp, peptide_yy, gut_hormones, glp_secretion, glucose_dependent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIntestinal Hormones and Incretins\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eplasma_glucose, glucose_insulin, glucose_tolerance, oral_glucose, cell_function, beta_cell, insulin_secretion, tolerance_test, type 2 diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGlucose and Insulin Metabolism\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egastric_bypass_rygb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRoux en Y Gastric Bypass\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003cp\u003e(25)\u003c/p\u003e\n \u003cp\u003eStable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egastric_banding, adjustable_gastric, laparoscopic_adjustable, gastric_band, banding_lagb, gastric_bypass_rygb, underwent_gastric_bypass, bariatric_procedures, bariatric_procedure, bariatric_surgeries, bariatric_surgical, surgical_procedures, surgical_procedure, different_bariatric, long_term\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdjustable Gastric Banding and Roux en Y Gastric Bypass\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003cp\u003e(27)\u003c/p\u003e\n \u003cp\u003eStable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003erelated_quality_of_life, health_related, weight_related, obesity, short_form, form_health, health_survey\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealth Related Quality of Life\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esurgical_treatment, non_surgical, clinical_trial number_nct, morbid_obesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSurgical and Non Surgical Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esodium_excretion, urinary_sodium.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUrinary Sodium Excretion\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003evitamin_d, nmol_l.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVitamin D\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003cp\u003e(34)\u003c/p\u003e\n \u003cp\u003eStable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emedical_therapy, medical_treatment, intensive_medical, best_medical, therapy_alone, type_diabetes, glycated_hemoglobin, mm_hg.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedical Treatment of Type 2 Diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emetabolic_surgery, biliopancreatic_diversion, gastric_bypass, surgical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMetabolic and Bariatric Surgery\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003erandomly_assigned, open_label, design_setting, per_protocol, primary_endpoint, year_follow_up\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMethodological Design\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003cp\u003e(30)\u003c/p\u003e\n \u003cp\u003eStable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ebody_composition, body_weight, body_mass, body_fat, fat_mass, fat_free, free_mass, lean_body, lean_mass, bmi_kg, ray_absorptiometry, dual_energy, x_ray\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBody Composition\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eenergy_expenditure, energy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEnergy Expenditure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eprotein_supplementation, protein_intake\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProtein Intake and Supplementation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egastric_bypass_rygb, hernia_repair\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHernia Repair Associated with RYGB\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003cp\u003e(34)\u003c/p\u003e\n \u003cp\u003eRising\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egastric_bypass_rygb, undergoing_rygb, following_rygb, pre_surgery, post_surgery, post_rygb, following_surgery, year_post, weeks_post, surgery_induced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePerioperative Management of Gastric Bypass\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eapo_b, c_imt (Carotid Intima-Media Thickness), ly_decreased, ly_increased, objectively_measured\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCardiometabolic Markers\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eiron_deficiency.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIron Deficiency\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003cp\u003e(20)\u003c/p\u003e\n \u003cp\u003eRising\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003etype_diabetes, hba_c, hemoglobin_a_c, mmol_mol, c_mmol, glucose_lowering, type___diabetes_remission, american_diabetes, diabetes_association\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eType 2 Diabetes Mellitus and Remission\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003erygb_vs medical_management, greater_weight_loss, randomly_assigned\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGastric Bypass versus Medical Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003cp\u003e(24)\u003c/p\u003e\n \u003cp\u003eRising\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emetabolic_surgery, gastric_bypass_rygb, rygb, rygb_vs, rygb_versus, rygb_compared, sleeve_gastrectomy_sg, underwent_sg, type_diabetes, hba1c, remission\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGastric Bypass versus Sleeve Gastrectomy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egut_microbiota.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGut Microbiota\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003cp\u003e(41)\u003c/p\u003e\n \u003cp\u003eStable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egastric_bypass_rygb, gastric_bypass_surgery, rygb_surgery, pyy_levels, ghrelin_levels, plasma_concentration, plasma_concentrations, concentration_time, time_curve, single_dose, blood_samples, ng_ml, pg_ml, ml_p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGastric Bypass and Gastrointestinal Hormones\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eoxidative_stress.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOxidative Stress\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emorbidly_obese_patient, body_weight, body_mass_index_kg.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNutritional Status Assessment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003cp\u003e(19)\u003c/p\u003e\n \u003cp\u003eRising\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egastric_bypass_surgery, laparoscopic_gastric_bypass, small_bowel, mesenteric_defects, internal_herniation, bowel_obstruction, non_closure, defect_closure, postoperative_complications, abdominal_pain.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMesenteric Issues, Internal Hernia, and Intestinal Obstruction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egallstone_disease, symptomatic_gallstone, ursodeoxycholic_acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCholelithiasis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esleep_apnoea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eObstructive Sleep Apnea\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003cp\u003e(35)\u003c/p\u003e\n \u003cp\u003eDeclining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emorbidly_obese_patient, obese_patient_undergoing, obese_women, central_obesity, body_mass_index_bmi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePatient Profile\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epostoperative_period, postoperative_day, first_postoperative, early_postoperative, immediate_postoperative, postoperative_complications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePostoperative Period\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epulmonary_function, inspiratory_muscle, inspiratory_pressure, cmh_o, muscle_strength\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePulmonary Function and Respiratory Muscle Function\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003cp\u003e(25)\u003c/p\u003e\n \u003cp\u003eStable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDuodenal-Jejunal Bypass with Sleeve Gastrectomy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCombined Bariatric Procedures\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eco_morbidities, Obesity-related, Related Diseases,\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eComorbidities\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003einformed_consent, patient_characteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEthical Aspects\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eantifactor_xa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnticoagulation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eims_score, liver_volume\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHepatic Assessment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003cp\u003e(28)\u003c/p\u003e\n \u003cp\u003eStable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egastric_bypass_rygb, sleeve_gastrectomy_sg, bone_health, bone_loss, bone_mass, bone_turnover, turnover_markers, secondary_hyperparathyroidism, bone_mineral, mineral_density, density_bmd, lumbar_spine, femoral_neck, total_hip\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBone Health\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eparathyroid_hormone, hydroxyvitamin_d, calcium_cit, plasma_levels.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBone and Mineral Metabolism\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003cp\u003e(28)\u003c/p\u003e\n \u003cp\u003eStable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egastric_bypass_oagb, one_anastomosis_gastric_bypass, one_anastomosis, distal_gastric_bypass, anastomosis_gastric_bypass, standard_rygb,\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGastric Bypass and Variations\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elimb_length, limb_lengths, limb_cm, cm_biliopancreatic, biliopancreatic_limb, roux_limb, alimentary_limb, common_channel, gastric_pouch\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLimb Length and Surgical Measurements\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ebile_reflux\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiliary Reflux\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003cp\u003e(26)\u003c/p\u003e\n \u003cp\u003eStable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eobese_subjects, swedish_obese, underwent_bariatric_surgery, design_setting, prospective_led, led_trial, usual_care, main_outcome, primary_outcome, cardiovascular_events, median_follow_up, long_term, increased_risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSwedish Obese Subjects (SOS) Study\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003cp\u003e(25)\u003c/p\u003e\n \u003cp\u003eStable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elifestyle_intervention, intensive_lifestyle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon Surgical Interventions\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egastric_bypass_surgery, obesity_surgery, surgery, following_bariatric_surgery, bmi_kg, obese_individuals, clinical_trial, one_year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBariatric Surgery\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eventilation, arterial_blood, sleep_apnea, obstructive_sleep, orbid_obesity, morbidly_obese, obesity_related, nt_probnp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRespiratory Function and Ventilation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003cp\u003e(62)\u003c/p\u003e\n \u003cp\u003eDeclining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elaparoscopic_gastric_bypass, laparoscopic_roux_en_y, laparoscopic_gbp, open_gastric_bypass, open_gbp, underwent_laparoscopic, operative_time, operating_time, min, blood_loss, staple_line, gastrojejunal_anastomosis, two, hospital_stay, incisional_hernia, anastomotic_leaks, randomly_assigned\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eComparison of Laparoscopic and Open Surgical Techniques\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emorbidly_obese_patient, morbid_obesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSeverely Obese Population\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003cp\u003e(33)\u003c/p\u003e\n \u003cp\u003eRising\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eundergoing_bariatric_surgery, gastric_bypass_rygb, rygb, sadi_s,\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBariatric Procedures\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ewls_forte, vitamin_b, vitamin_and_mineral, iron_absorption\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVitamins and Minerals\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epost_operative, body_weight, bmi_kg, preoperative_bmi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePerioperative Anthropometric Assessment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003cp\u003e(74)\u003c/p\u003e\n \u003cp\u003eStable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egastric_bypass_surgery, laparoscopic_roux_en_y, laparoscopic_gastric_bypass, laparoscopic_bariatric_surgery, undergoing_laparoscopic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLaparoscopic Procedures\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epostoperative_pain, pain_scores, tap_block, opioid_consumption, morphine_consumption, opioid_use, mg_kg, kg_h\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnalgesia and Pain Assessment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epostoperative_nausea, hospital_stay, care_unit, post_operative, first\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePostoperative Outcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003cp\u003e(53)\u003c/p\u003e\n \u003cp\u003eStable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003etype 2 diabetes, non_diabetic, insulin_sensitivity, glucose_homeostasis, glucose_tolerance, glucose_production, gene_expression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGlucose Metabolism and Insulin Sensitivity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ebody_weight, induced_weight_loss, weight_loss_induced,gastric_bypass_rygb, morbidly_obese, obese_subjects, obese_women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeight Loss Outcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eadipose_tissue, skeletal_muscle, whole_body, fatty_acids\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdipose and Muscle Tissue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elow_calorie, calorie_diet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypocaloric Diets\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eTopic = Topics: topics identified using the Dirichlet Latent Allocation (LDA) model.\u003c/p\u003e\n \u003cp\u003eFrequency = number of documents associated with each topic.\u003c/p\u003e\n \u003cp\u003eTrend = Trend: trends associated with each topic over time.\u003c/p\u003e\n \u003cp\u003eFigure 4 illustrates the temporal evolution of topics based on the annual mean topic probabilities and their statistically significant trends. Overall, a heterogeneous pattern was observed throughout the analyzed period. Topics shown in red predominantly related to weight loss and recurrent weight gain, eating behavior, psychological aspects, physical exercise, muscle strength, type 2 diabetes mellitus, intestinal hormones, cardiometabolic markers, gut microbiota, and sleep apnea\u0026mdash;exhibited positive coefficients with significant upward trends, indicating that these themes have gained increasing relevance over the study period.\u003c/p\u003e\n \u003cp\u003eTopics displayed in blue, characterized by negative coefficients, were mainly associated with respiratory aspects, patient profile, perioperative care, and comparisons between laparoscopic and open surgical techniques. The significant downward trends observed for these topics suggest a progressive decline in their relative relevance over time.\u003c/p\u003e\n \u003cp\u003eDespite occasional fluctuations, the majority of topics demonstrated stable behavior (shown in black), indicating relatively constant relevance within the analyzed literature. This group includes themes such as obesity-associated diseases, liver disease, glucose metabolism, metabolic syndrome, excess skin, inflammatory markers, surgical techniques, vitamin D, body composition, energy expenditure, ethical aspects, bone health, pain, and nutritional interventions.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eMetabolic bariatric surgery is widely recognized as an effective method for weight loss. Among the available procedures, gastric bypass developed in 1967 by Edward E. Mason and Chikashi Ito [41], stands out as one of the oldest and most established techniques in the field [42]. To the best of our knowledge, there is no comprehensive systematization of publications specifically focused on clinical trials in gastric bypass, despite the continuous growth of this research area. This gap becomes even more evident when consulting the World Health Organization\u0026rsquo;s International Clinical Trials Registry Platform, which reports 755 registered studies for the term \u0026ldquo;sleeve gastrectomy\u0026rdquo; up to 2024, whereas the present analysis identified 1,102 clinical trials related to gastric bypass.\u003c/p\u003e \u003cp\u003eAn accelerated growth in scientific production related to clinical trials on gastric bypass was observed, particularly from the second decade of the evaluated period (2010\u0026ndash;2019). This trend paralleled the global rise in obesity frequently described as a \u0026ldquo;public health crisis\u0026rdquo;\u0026mdash;as well as the continuous increase in obesity-associated diseases. It is reasonable to assume that this scenario led to greater demand for effective weight control interventions, thereby driving both the volume of bariatric surgeries and scientific interest in the field [4]. In addition, technological advances and improvements in surgical techniques, especially the development and consolidation of minimally invasive laparoscopic approaches and robotic procedures, contributed to increased procedural safety and reduced morbidity and mortality [42\u0026ndash;44], further fostering scientific output.\u003c/p\u003e \u003cp\u003eThe stabilization of scientific production, followed by a slight decline from 2021 onward, suggests that external factors particularly the COVID-19 pandemic may have played a central role in slowing research activity. During this period, the medical community\u0026rsquo;s focus shifted primarily to the management of patients infected with COVID-19, placing bariatric surgery and related research in a less prominent position [45]. Indeed, reports have documented the suspension of bariatric surgical procedures [46], as well as a reduction in global scientific production within the biomedical field [47,48].\u003c/p\u003e \u003cp\u003eAlthough growth rates have not immediately returned to pre-pandemic levels, a stabilization trend is projected through 2030. This pattern may be associated with the possibility that certain areas of metabolic and bariatric surgery are entering a phase of knowledge consolidation, which typically leads to a reduction in scientific output. Our findings indicate declining trends in specific domains, such as perioperative and respiratory aspects, as well as comparisons between laparoscopic and open surgical approaches. This scenario contributes to a linear rather than exponential growth pattern in scientific production within the field [15].\u003c/p\u003e \u003cp\u003eRegarding country-level scientific production, particularly in relation to specific surgical techniques, the United States previously led research output on laparoscopic sleeve gastrectomy between 1998 and 2019 [18], a pattern that was also observed for gastric bypass in the present study. This finding is likely associated with substantial national investment in medical research [49], as well as the high prevalence of obesity in the country, which reached approximately 40.3% of adults between 2021 and 2023 [50,51].\u003c/p\u003e \u003cp\u003eHowever, when scientific output was adjusted per million inhabitants, per thousand bariatric surgeries performed, and per million individuals with obesity, European countries exhibited higher prevalence and the highest productivity indices, followed by Asian and Oceanian countries. These findings are consistent with previous reports [15,17,52] and indicate that scientific production in these regions\u0026mdash;despite smaller populations and lower absolute surgical volumes compared with large countries such as the United States and Brazil\u0026mdash;is supported by healthcare systems strongly integrated with universities, a high density of academic centers, and a well-established culture of clinical and collaborative research. These structural factors contribute to greater relative efficiency in knowledge generation. Brazil stands out as the only developing country among the ten most productive nations and, in absolute terms, ranks immediately after the United States. After normalization, Brazilian productivity becomes comparable to that of the United States, identifying Brazil as the most productive Latin American country in bariatric surgery research [53]. This phenomenon may also be related to the increasing prevalence of severe obesity in the country, which doubled between 2006 and 2021, consequently intensifying interest in treatment modalities such as bariatric surgery [54].\u003c/p\u003e \u003cp\u003eWith respect to authorship, we incorporated additional metrics beyond those typically reported in bibliometric studies, including fractional authorship (FA), frequency of first and last authorship (F and L), number of active years (NAY), and productivity per active year (PAY). These indicators enabled assessment of scientific leadership, consistency of contribution, and productivity intensity. Among all authors, Olbers T. was the most productive, presenting not only the highest publication volume but also the greatest total and annual citation counts, indicating both high productivity and strong scientific impact. This author also contributed to two of the most cited articles in the gastric bypass field, reinforcing his influence in this area. Conversely, authors with fewer publications, such as Kirwan J.P. (United States) and Peltonen M. (Finland), each with 18 publications, also achieved high citation volumes (6,489 and 6,798, respectively). This finding highlights that substantial scientific impact can be achieved with a smaller number of publications, provided that the studies are of high relevance and scientific quality.\u003c/p\u003e \u003cp\u003eIt was observed that the most highly cited articles were predominantly published in high impact factor journals, which may have contributed to their higher citation counts [55] This association is consistent with previous evidence indicating a positive correlation between journal impact factor and citation frequency, representing one of the factors influencing article visibility [56]. In addition, these publications demonstrated high methodological rigor, an attribute that enhances the reliability of findings and may favor their scientific recognition. Nevertheless, it is important to emphasize that high impact journals do not always publish studies with high methodological quality [57], just as citation counts do not necessarily reflect the methodological rigor of an article in a direct manner [58].\u003c/p\u003e \u003cp\u003eSeveral studies exhibited moderate obsolescence [31,33,35\u0026ndash;37,39], indicating that they remain relevant for long periods after publication and continue to be widely cited. These findings are consistent with reports from the basic and biomedical sciences, in which obsolescence is typically moderate, with mean values ranging between four and seven years [59,60], more recently described as a second phase or maturation period [61]. Only the article \u0026ldquo;Lifestyle, Diabetes, and Cardiovascular Risk Factors 10 Years after Bariatric Surgery\u0026rdquo; [32], published more than two decades ago, demonstrated slow obsolescence, with a citation half life of 9.46 years, indicating prolonged persistence as a key reference in the field. Publications with this profile are considered essential reading for researchers interested in the topic [61].\u003c/p\u003e \u003cp\u003eTopic modeling identified thematic axes that have not been described in previous bibliometric analyses [16,17,19] encompassing increasingly relevant areas such as bone metabolism, gut microbiota, eating behavior, and psychological aspects, in addition to topics related to cardiovascular and respiratory function and nutritional status. Moreover, this approach allowed the assessment of how frequently these themes are addressed in the literature, as well as their temporal trends over the evaluated period, providing a comprehensive overview of the main research topics in the field of metabolic bariatric surgery Topic 10, the most recurrent and exhibiting significant growth, was related to type 2 diabetes mellitus, glucose metabolism, and hormones such as glucagon like peptide 1 (GLP 1). GLP 1 is an incretin hormone involved in appetite regulation, delayed gastric emptying, and glycemic control, functions that are typically favorably modified by metabolic bariatric surgery. These effects have also motivated the development of pharmacological agents designed to mimic its action. Evidence from a systematic review and meta analysis demonstrated significant reductions in body weight, as well as consistent decreases in total fat mass and visceral adipose tissue, associated with the use of GLP 1 analogues such as liraglutide [62]. However, discontinuation of pharmacological treatment is associated with partial weight regain, underscoring the importance of effective weight reduction interventions such as metabolic bariatric surgery, as well as the need for maintenance strategies that integrate pharmacotherapy with sustained lifestyle modifications [63,64].\u003c/p\u003e \u003cp\u003eWith respect to type 2 diabetes mellitus, which is frequently associated with the term Roux en Y gastric bypass, a close relationship between the surgical procedure and metabolic effects was observed, as evidenced by the presence of terms such as glucose_tolerance, cell_function, beta_cell, insulin_secretion, among others. The high density of studies in this context reinforces the relevance of investigations focused on the mechanisms underlying type 2 diabetes mellitus remission and other hormonal changes in the postoperative period, an area that has expanded substantially and highlights the consolidation of the concept of metabolic bariatric surgery [33,65,66].\u003c/p\u003e \u003cp\u003eTrend analysis indicated that Topic 5, related to physical exercise, muscle strength, and functional capacity, has gained greater prominence in more recent years, showing a significant upward trend. It is plausible that muscle strength has received increased attention in this context, particularly because functional capacity indicators, such as gait speed and walking performance, demonstrate significant improvement after bariatric surgery [67]. However, available evidence suggests that these improvements are predominantly associated with body weight reduction rather than with significant increases in muscle strength during the postoperative period [68]. In this field, existing evidence remains limited, underscoring the need for robust clinical trials to enhance the reliability and generalizability of findings.\u003c/p\u003e \u003cp\u003eTopic 2, although not exhibiting a growing trend, reflects an important area concerning the metabolic effects of metabolic bariatric surgery on liver function. Evidence indicates that bariatric surgery promotes consistent reductions in alanine aminotransferase and aspartate aminotransferase levels in individuals with obesity, suggesting improvement in hepatic steatosis and inflammation [69]. Findings from a retrospective cohort demonstrated that improvements in alanine aminotransferase levels after bariatric surgery occur independently of the magnitude of weight loss, indicating metabolic effects beyond weight reduction [70]. Overall, surgical intervention contributes to lowering transaminase levels and promotes a global improvement in liver function [71].\u003c/p\u003e \u003cp\u003eOnly two topics, Topics 20 and 26, exhibited declining trends, suggesting reduced scientific interest in themes related to surgical techniques, respiratory aspects, and perioperative care. This pattern may reflect the consolidation and standardization of these domains over time, which reduces the need for predominantly technical studies. This finding is consistent with observations from a previous study reporting that most publications were focused on \u0026ldquo;how I do it\u0026rdquo;\u0026ndash;type descriptions, emphasizing technical execution, perioperative risk assessment, and the balance between risks and benefits, while broader issues such as psychosocial impacts, quality of life, and behavioral aspects were addressed secondarily. Over time, however, research focus has expanded to include multidisciplinary dimensions, reflecting a more comprehensive understanding of obesity [72]. This shift is evident in our findings, which identified significantly growing topics that extend beyond the technical surgical focus, including eating behavior, psychological aspects, and physical exercise.\u003c/p\u003e \u003cp\u003eTopic frequency analysis revealed a low representation of clinical trials addressing outcomes such as bone health, quality of life, cholelithiasis, sleep apnea, respiratory aspects, vitamin D, and gut microbiota. These findings suggest that, despite the recognized clinical relevance of these outcomes in the long term follow up of patients undergoing bariatric surgery, scientific production remains predominantly centered on metabolic outcomes and technical aspects. One possible explanation for this pattern is the greater methodological complexity and longer follow up periods required to evaluate these outcomes, which may limit their inclusion in clinical trial designs.\u003c/p\u003e \u003cp\u003eFinally, it is important to note that bibliometric studies are often limited by the use of a single database, which restricts the scope of the analyzed literature [16,73]. To address this limitation, the present study incorporated the three main international databases in health sciences, namely Web of Science, PubMed/MEDLINE, and Scopus [74]. Although PubMed/MEDLINE presents constraints due to the lack of citation data [75], these limitations were mitigated through the use of open access initiatives, particularly via OpenCitations [76]. In addition, this study highlights the application of machine learning techniques in bibliometric analysis, with emphasis on Latent Dirichlet Allocation topic modeling, which remains underexplored in this field [77]. Conversely, it is reasonable to acknowledge the heterogeneity of metadata across the Web of Science, Scopus, and PubMed/MEDLINE databases, as information is organized differently in each source. Such variation may generate inconsistencies in author identification, even after data normalization, potentially leading to distortions in the results. The adoption of a unified metadata standard would be ideal to reduce these discrepancies.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe global research landscape in the field of gastric bypass currently reflects a phase of stabilization following a prolonged period of robust growth. In quantitative terms, scientific production remains largely concentrated in the United States. However, European countries assume prominent positions when output is adjusted for key indicators such as population size, obesity prevalence, and number of surgeries performed. With respect to productivity, high impact factor journals, experienced researchers, and studies with strong methodological rigor contribute substantially to the relevance of the published literature, as reflected by slow obsolescence and high citation counts.\u003c/p\u003e \u003cp\u003eRegarding thematic content, although discussions on intestinal hormones and diabetes mellitus in bariatric surgery are not new, these topics remain recurrent and widely debated in the literature. Similarly, themes associated with metabolic markers and psychosocial aspects, including weight loss and weight regain, eating behavior, physical exercise, and gut microbiota, have emerged as areas of increasing interest among researchers. Nevertheless, relatively few clinical trials address other clinically relevant topics related to metabolic bariatric surgery, such as bone health, quality of life, cholelithiasis, sleep apnea, respiratory aspects, vitamin D, robotic bariatric surgery, and gut microbiota. These areas represent clear gaps in the literature and, consequently, important opportunities for future research and scientific production.\u003c/p\u003e \u003cp\u003eFinally, the use of robust analytical methods, such as machine learning approaches with emphasis on the Latent Dirichlet Allocation algorithm, proved essential for identifying thematic structures within the field and for complementing traditional bibliometric techniques. In addition, integrating three major international databases enhanced the scope and reliability of the findings, enabling a global perspective on the evolution of knowledge in clinical trials on gastric bypass. Overall, the results of this study contribute to a deeper understanding of the trajectory of this research field throughout the 21st century, highlighting its main thematic focuses and temporal dynamics.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGrant number blinded\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest Declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis article does not contain any studies with human participants or animals performed by any of the authors\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eR.F.M.: Study conception and design, definition of the methodology, data analysis and interpretation, and manuscript drafting.V.C.: Study selection and screening of included articles, and review of the translation.J.B.: Critical revision of the manuscript for important intellectual content, scientific supervision, and overall study oversight.G.F.D.D. and T.R.O.: Manuscript review.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study will be made available in a public repository upon publication. For the purposes of double-anonymous peer review, repository details and access links have been temporarily blinded. **Refer\u0026ecirc;ncia**\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHopkins KD, Lehmann ED. Successful medical treatment of obesity in 10th century Spain. Lancet. 1995 Aug 12;346(8972):452. doi: 10.1016/s0140-6736(95)92830-8. PMID: 7623606. \u003c/li\u003e\n\u003cli\u003ePeri K, Eisenberg M. Review on obesity management: bariatric surgery. BMJ Public Heal. 2024;2:e000245. \u003c/li\u003e\n\u003cli\u003eArd J, Huett-Garcia A, Bildner M. Tackling the complexity of obesity in the US through adaptation of public health strategies. Front Public Heal. 2025;13. \u003c/li\u003e\n\u003cli\u003eAhmed SK, Mohammed RA. Obesity: Prevalence, causes, consequences, management, preventive strategies and future research directions. Metab Open. 2025;27:100375. \u003c/li\u003e\n\u003cli\u003eWorld Obesity Federation. World Obesity Atlas 2022. 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Guidelines for Bibliometric‐Systematic Literature Reviews: 10 steps to combine analysis, synthesis and theory development. Int J Manag Rev. 2025;27:81\u0026ndash;103. \u003cstrong\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"obesity-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"obsu","sideBox":"Learn more about [Obesity Surgery](https://link.springer.com/journal/11695)","snPcode":"11695","submissionUrl":"https://submission.springernature.com/new-submission/11695/3","title":"Obesity Surgery","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Gastric bypass, Clinical trial, Bibliometrics, Bariatric surgery, Machine learning, Latent Dirichlet Allocation","lastPublishedDoi":"10.21203/rs.3.rs-8854344/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8854344/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction \u003c/strong\u003eGastric bypass (GB) is a well-established metabolic bariatric surgery technique associated with substantial weight loss and significant metabolic benefits. Since the early 2000s, scientific output related to GB has shown sustained growth. This study aimed to analyze the global scientific production of clinical trials on GB, focusing on authorship patterns, country-level contributions, publication impact, and the temporal evolution of thematic research topics.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods \u003c/strong\u003eThe search term “gastric bypass” was used to retrieve publications indexed in the Web of Science, PubMed, and Scopus databases between 2001 and 2024. Bibliometric indicators were combined with normalization strategies based on population size, number of bariatric procedures performed, and obesity prevalence. Data on authorship, countries, citation counts, and keywords were extracted and analyzed. Topic modeling was performed using Latent Dirichlet Allocation, a machine learning approach in bibliometric research.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults \u003c/strong\u003eA total of 1,102 studies were included, showing an average annual growth rate of 10.6%, with marked expansion after 2010. The United States led in absolute publication volume, whereas European countries demonstrated higher relative productivity after normalization. The ten most cited studies accumulated more than 20,000 citations. Latent Dirichlet Allocation identified emerging, stable, and declining thematic topics, with a dominant and expanding topic related to metabolic outcomes and diabetes mellitus.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion \u003c/strong\u003eBariatric surgery research is approaching a global stabilization phase projected until 2030. In GB research, the most prominent and expanding topics involve intestinal hormones and diabetes mellitus, while quality of life, sleep apnea, vitamin D, and gut microbiota remain underexplored and represent future opportunities.\u003c/p\u003e","manuscriptTitle":"Global Trends in Scientific Output of Clinical Trials on Gastric Bypass: A Machine Learning–Based Bibliometric Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-18 06:17:32","doi":"10.21203/rs.3.rs-8854344/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-07T21:34:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-27T15:29:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"128955785589099423500511534678882274010","date":"2026-02-27T11:27:03+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-25T11:19:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"218921191047706895182687729585835423988","date":"2026-02-25T10:58:02+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-20T22:03:37+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-20T17:39:15+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-20T02:06:06+00:00","index":"","fulltext":""},{"type":"submitted","content":"Obesity Surgery","date":"2026-02-11T16:37:22+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"obesity-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"obsu","sideBox":"Learn more about [Obesity Surgery](https://link.springer.com/journal/11695)","snPcode":"11695","submissionUrl":"https://submission.springernature.com/new-submission/11695/3","title":"Obesity Surgery","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"115e899a-bccd-40b8-8554-22b03b5efa68","owner":[],"postedDate":"February 18th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-12T23:08:58+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-18 06:17:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8854344","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8854344","identity":"rs-8854344","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}