BMC Endocrine Disorders最新文献

{"title":"Interpretable XGBoost model identifies idiopathic central precocious puberty in girls using four clinical and imaging features.","authors":"Lu Tian, Yan Zeng, Helin Zheng, Jinhua Cai","doi":"10.1186/s12902-025-01983-4","DOIUrl":"10.1186/s12902-025-01983-4","url":null,"abstract":"<p><strong>Background: </strong>The study aimed to develop interpretable machine learning models for the identification of idiopathic central precocious puberty (ICPP) in girls, without the need for the expensive and time-consuming gonadotropin-releasing hormone (GnRH) stimulation test, which is currently the gold standard for diagnosing ICPP.</p><p><strong>Methods: </strong>A total of 246 female paediatric patients who had secondary sexual characteristics before 8 years old and had taken a GnRH stimulation test were randomly divided into a training set (172 patients, 70%) and a validation set (74 patients, 30%). Characteristic parameters were extracted from easily available clinical data and were statistically analysed. The least absolute shrinkage and selection operator (LASSO) method was used to select essential characteristic parameters associated with ICPP and were used to construct logistic regression (LR) and five machine learning (ML) models, including support vector machine (SVM), Gaussian naive bayes (GaussianNB), extreme gradient boosting (XGBoost), random forest (RF), and k- nearest neighbor algorithm (kNN). Then, the area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, false positive and negative values, Youden's index, accuracy, positive and negative likelihood ratios, calibration plots, and decision curve analysis (DCA) were used to evaluate the models' effectiveness. Finally, the shapley additive explanations (SHAP) package was used to interpret the best-performing model.</p><p><strong>Results: </strong>Four essential characteristic parameters, namely uterine volume, bone age/chronological age (BA/CA), basal follicle-stimulating hormone (FSH), and basal luteinizing hormone (LH), were selected using the LASSO method. Based on these characteristic parameters, the LR and five machine learning models achieved AUC values ranging from 0.72 to 0.96 in the training set and AUC values ranging from 0.65 to 0.90 in the validation set for diagnosing ICPP. Among the LR and five machine learning models, the XGBoost model demonstrated superior performance, achieving the highest AUC values, accuracy, specificity, and sensitivity in both the training and validation sets. Moreover, calibration plots and DCA confirmed that this model exhibited the best calibration and clinical utility.</p><p><strong>Conclusions: </strong>An accurate and interpretable ML-based model has been developed to aid clinicians in the diagnosis of ICPP, assisting in clinical decision-making.</p>","PeriodicalId":9152,"journal":{"name":"BMC Endocrine Disorders","volume":"25 1","pages":"159"},"PeriodicalIF":2.8,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12219956/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144538772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The prevalence of all stype of diabetes and pre‑diabetes in the Eastern Mediterranean countries: a meta‑analysis study.","authors":"Asra Moradkhani, Mobin Azami, Pardis Mohammadzadeh, Hamid Reza Baradaran, Lotfolah Saed, Kianush Asvad, Rojina Kakaei, Sorour Khateri, Farhad Moradpour, Yousef Moradi","doi":"10.1186/s12902-025-01959-4","DOIUrl":"10.1186/s12902-025-01959-4","url":null,"abstract":"<p><strong>Background and aim: </strong>Given the high prevalence, incidence, and impact on Disability-Adjusted Life Years (DALYs) associated with diabetes, coupled with the limited availability of meta-analysis studies examining its prevalence in the Eastern Mediterranean Regional Office (EMRO) countries, the main objective of this study was to investigate the combined prevalence of type 1 (T1DM) and type 2 diabetes (T2DM), gestational diabetes, and pre-diabetes within the Eastern Mediterranean region.</p><p><strong>Methods: </strong>To implement a comprehensive search strategy aligned with the objectives of this meta-analysis, searches were conducted across international databases, including PubMed (Medline), Scopus, Embase, Web of Science, and the Cumulative Index to Nursing and Allied Health Literature (CINHAL) from January 1967 to December 2022. The quality of the selected studies was assessed using the JBI critical appraisal checklist for analytical cross-sectional studies. Subgroup analyses were conducted based on factors such as gender, country, geographic area, criteria for diagnosis, and Gross Domestic Product (GDP) level.</p><p><strong>Results: </strong>Out of 5,238 primary studies initially screened, 186 articles were included in the meta-analysis. The pooled prevalence of diabetes was found to be 15% (95% CI: 13 - 16%), of which 6% (95% CI: 4 - 7%) represented undiagnosed cases, while 8% (95% CI: 7 - 10%) were known cases. The prevalence of T2DM was 13% (95% CI: 11 - 16%), while T1DM was found to have a prevalence of 1% (95% CI: 1 - 2%). Pre-diabetes had a pooled prevalence of 15% (95% CI: 13 - 18%), with impaired glucose tolerance (IGT) and impaired fasting glycemia (IFG) representing 9% (95% CI: 7 - 11%) and 8% (95% CI: 6 - 11%) of cases, respectively. The prevalence of gestational diabetes mellitus (GDM) was found to be 11% (95% CI: 9 - 14%) in the EMRO.</p><p><strong>Conclusion: </strong>The findings emphasize the need for enhanced healthcare programs, including early screening, effective management, and lifestyle interventions such as healthy eating and physical activity. The analysis also highlights the importance of considering socioeconomic factors like urbanization, diet changes, and healthcare access when developing diabetes prevention and management strategies. The results call for policymakers and healthcare providers to collaborate in addressing the growing public health burden of diabetes in the region.</p>","PeriodicalId":9152,"journal":{"name":"BMC Endocrine Disorders","volume":"25 1","pages":"149"},"PeriodicalIF":2.8,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12211881/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144538820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association between serum tumor markers and diabetic nephropathy in type 2 diabetes patients: a cross-sectional survey in Western China.","authors":"Li Tao, Tong Yao, Yan Zhang, Yangyang Gong, Lun Huang, Ya Zhao, Naichuan Chen, Jian Yin, Li Xue, Chaoliang Xiong, Xuanxi Li, YanPing Zhang","doi":"10.1186/s12902-025-01932-1","DOIUrl":"10.1186/s12902-025-01932-1","url":null,"abstract":"<p><strong>Background: </strong>Diabetic nephropathy (DN) is a common and serious microvascular complication of type 2 diabetes mellitus (T2DM). However, there is limited clinical research on the use of tumor markers in DN, and the relationship between serum tumor markers and DN in T2DM patients is not well understood.</p><p><strong>Purpose: </strong>This study seeks to examine the potential association between serum tumor biomarkers and DN in individuals with T2DM in Western China.</p><p><strong>Methods: </strong>This cross-sectional study involved 620 T2DM patients, including 253 with DN and 367 without. Differences between the groups were analyzed using Student's t-test, Mann-Whitney U-test, and Pearson's Chi-squared test. Logistic regression assessed the link between serum tumor biomarkers and DN presence, while Spearman's correlation analyzed the relationship between these biomarkers and kidney damage indicators. The diagnostic efficacy of the biomarkers was evaluated through receiver operating characteristic (ROC) curve analysis.</p><p><strong>Results: </strong>In patients with T2DM and DN, the serum levels of carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), cancer antigen 211 (CA211), cancer antigen 125 (CA125), cancer antigen 199 (CA199), and squamous cell carcinoma antigen (SCC) were significantly elevated compared to those in the non-DN group, while serum levels of pro-gastrin-releasing peptide (ProGRP) were lower than those in the DN group (P < 0.01). After adjusting for potential confounding variables, serum levels of CEA, CA199, and CA125 were found to be independently associated with DN in T2DM patients. The odds ratio (OR) for elevated CEA in relation to DN was 1.41 (95% confidence interval [CI]: 1.17-1.70), for elevated CA125 was 1.02 (95% CI: 1.005-1.036), and for elevated CA199 was 1.021 (95% CI: 1.010-1.032). In this study, the levels of CA125 and CA199 exhibited a negative correlation with estimated glomerular filtration rate (eGFR), with correlation coefficients of -0.16, and -0.089, respectively. Conversely, these biomarkers were positively correlated with albumin-to-creatinine ratio (ACR), with correlation coefficients of 0.56, 0.55, and 0.22, respectively, and with cystatin C levels, with correlation coefficients of 0.17, 0.23, and 0.07, respectively. ROC curve analysis showed that combining CEA, CA125, and CA199 improves the accuracy in distinguishing DN patients, with an AUC of 0.82 (95% CI: 0.79-0.86, P < 0.001).</p><p><strong>Conclusions: </strong>This study shows that serum tumor markers (CEA, CA125, and CA199) are strongly linked to the presence of DN in type 2 diabetes patients, providing new insights into their role in DN and suggesting potential prevention strategies.</p><p><strong>Clinical trial number: </strong>Not applicable.</p>","PeriodicalId":9152,"journal":{"name":"BMC Endocrine Disorders","volume":"25 1","pages":"150"},"PeriodicalIF":2.8,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12211909/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144538807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association between vitamin D level and insulin resistance among patients with type 2 diabetes mellitus in Sana'a City.","authors":"Ali Salman Al-Shami, Mokhtar Alzumor, Adnan Aladhal, Abdulhakim Al-Saban","doi":"10.1186/s12902-025-01972-7","DOIUrl":"10.1186/s12902-025-01972-7","url":null,"abstract":"<p><strong>Background: </strong>Numerous biological functions recognize vitamin D. The existence of vitamin D receptors on different tissues explains its diversity of actions. Insulin resistance and a higher risk of diabetes are associated with reduced levels of vitamin D.</p><p><strong>Objectives: </strong>This study evaluated the association between vitamin D levels and insulin resistance in type 2 diabetic patients in Sana'a city.</p><p><strong>Methods: </strong>This cross-sectional study included a total of 50 participants.</p><p><strong>Patients: </strong>Individuals aged 23 to 65 years. Control Group (Healthy Individuals): Interviews were conducted with patients aged 22 to 55 years diagnosed with type 2 diabetes mellitus to collect personal information, daily habits, dietary practices, and clinical characteristics. We assessed fasting blood sugar, vitamin D, insulin, and HbA1c as biochemical parameters. Body mass index (BMI) was calculated, and HOMA-IR and HOMA-β were measured in mmol/L as indicators of insulin resistance. A statistical software package was used for data analysis.</p><p><strong>Results: </strong>Participants in the study ranged in age from 20 to 69 years. The study found that patients with type 2 diabetes mellitus had a 40% prevalence of vitamin D deficiency, compared to 20% in healthy individuals.</p><p><strong>Conclusions: </strong>The findings indicate a significant association between low levels of vitamin D and insulin resistance, as measured by HOMA-B and HOMA-IR. Consequently, a deficiency in vitamin D among patients with type 2 diabetes mellitus may lead to increased insulin resistance.</p>","PeriodicalId":9152,"journal":{"name":"BMC Endocrine Disorders","volume":"25 1","pages":"152"},"PeriodicalIF":2.8,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12211317/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144538766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Progression from isolated growth hormone deficiency to a combined pituitary hormone deficiency in a cohort of paediatrics patients with pituitary morphology abnormalities on MRI.","authors":"Cristina Aguilar-Riera, Diego Yeste, Núria González-Llorens, Eduard Mogas, Ariadna Campos-Martorell, Paula Fernandez-Alvarez, Elida Vázquez, María Clemente","doi":"10.1186/s12902-025-01980-7","DOIUrl":"10.1186/s12902-025-01980-7","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate the baseline and follow-up clinical and radiological characteristics of a paediatric cohort initially diagnosed with isolated congenital growth hormone deficiency (IGHD) and pituitary morphology abnormality in MRI.</p><p><strong>Patients and methods: </strong>Observational, ambispective and longitudinal review of paediatric patients with an initial diagnosis of growth hormone deficiency with pituitary morphology abnormality in MRI followed-up in a single tertiary hospital.</p><p><strong>Results: </strong>After mean 11.3 (± 3.5DS) years of follow-up, the thirty patients (20 males) were classified into two groups: (1) isolated congenital growth hormone deficiency (IGHD) with 24 patients (9.5 years median follow up), and (2) combined pituitary hormone deficiencies (CPHD) with 6 patients (13.5 years median follow up). Median age at diagnosis was IGHD 3.0 [2.0-4.0] and CPHD 3.0 [1.5-5.2] years. Regarding the cerebral MRI scan results, 2 patients had septo-optic dysplasia (CPHD), 5 had pituitary stalk interruption syndrome (3 IGHD), one had ectopic posterior pituitary (IGHD), 16 had anterior pituitary hypoplasia (15 IGHD) and 6 had the latter two conditions combined (5 IGHD). In genetic studies, 1 of 25 patients had positive NGS panel results and it was in the IGHD group. The target gene detected was GLI2. Clinical exome sequencing was performed with six patients, yielding inconclusive results (1 in the IGHD group and 5 in the CPHD group). Array CGH was performed with eight patients (4 in the IGHD group and 4 in the CPHD group) and was negative in all patients. In the CPHD group, associated deficiencies begin to appear after 5 years [4.0-6.0] median follow-up, with thyrotropin being the most frequent (80%), followed by gonadotropin deficiency. ACTH and AVP deficiencies were less frequent.</p><p><strong>Conclusions: </strong>Multiple hormone deficiencies were diagnosed during this cohort's follow-up evaluation, whose first presentation was isolated growth hormone deficiency and pituitary morphology abnormality in MRI. Pathogenic gene variant involved in congenital hypopituitarism (GLI2) was found in one patient. Regular follow up of pituitary hormonal function in such patients is advisable due to the risk of new added deficiencies.</p>","PeriodicalId":9152,"journal":{"name":"BMC Endocrine Disorders","volume":"25 1","pages":"157"},"PeriodicalIF":2.8,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12220797/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144538818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Establishment of age-related AMH screening cutoffs in Chinese women with PCOS: a retrospective study using propensity score matching analysis.","authors":"Zhen Wang, Xiaojing Teng, Yanfei Liu, Yonghai Shen, Lin Ma, Yu Chen","doi":"10.1186/s12902-025-01975-4","DOIUrl":"10.1186/s12902-025-01975-4","url":null,"abstract":"<p><strong>Background: </strong>Polycystic ovary syndrome (PCOS) is a common endocrine disorder that affects 5-18% of women worldwide. This disorder is characterized by two core pathological features: ovulatory dysfunction and hyperandrogenism.</p><p><strong>Method: </strong>A retrospective analysis was conducted on cases treated at Hangzhou Women's Hospital from July 2021 to November 2023. Based on age, we conducted propensity score matching analysis in a 1:1 ratio and statistical analysis using SPSS software, plotted receiver operating characteristic curves, and obtained the area under the curve, the optimal anti-Müllerian hormone screening threshold, corresponding sensitivity, specificity, Youden index, correct diagnostic rate, positive predictive value, negative predictive value. Age-related anti-Müllerian hormone screening criteria with polycystic ovary syndrome were established and evaluated based on the optimal anti-Müllerian hormone screening cutoff for each group. The above results were validated by the validation group. And Kappa consistency test was conducted between the age-related anti-Müllerian hormone screening test and 2003 Rotterdam criteria for polycystic ovary syndrome.</p><p><strong>Results: </strong>The screening criteria for age-related anti-Müllerian hormone with polycystic ovary syndrome were: ≥7.46 ng/ml (20-24-year-old), ≥ 4.55 ng/ml (25-29-year-old), ≥ 4.19 ng/ml (30-34-year-old), ≥ 3.57 ng/ml (35-39-year-old).</p><p><strong>Conclusion: </strong>Our research indicates that age specific AMH threshold values show promising sensitivity and specificity for PCOS screening in the validation cohort. These findings indicate the potential utility of AMH based screening, but emphasize the need for optimization and validation in larger multicenter studies before clinical implementation.</p><p><strong>Clinical trial number: </strong>Not applicable.</p>","PeriodicalId":9152,"journal":{"name":"BMC Endocrine Disorders","volume":"25 1","pages":"153"},"PeriodicalIF":2.8,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12210944/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144538769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predictive value of MetS-IR for the glucose status conversion in prediabetes: a multi-center retrospective cohort study.","authors":"Dixing Liu, Jiana Zhong, Wenting Xuan, Weikun Chen, Jiajing Yuan, Xiuwei Zhang, Lingjie He","doi":"10.1186/s12902-025-01974-5","DOIUrl":"10.1186/s12902-025-01974-5","url":null,"abstract":"<p><strong>Background: </strong>The metabolic score for insulin resistance (METS-IR), a surrogate parameter for insulin resistance, is closely correlated with glucose metabolism. This study aims to investigate the impact of METS-IR in the progression from prediabetes to diabetes, as well as the reversion to normoglycemia in individuals with prediabetes.</p><p><strong>Methods: </strong>This retrospective cohort study comprised 15,424 prediabetes patients from 32 sites across 11 cities in China. We monitored changes in the glycemic status of these patients over the follow-up period, including the reversion from prediabetes to normoglycemia, progression to diabetes, or maintenance of the prediabetic condition. Cox proportional hazard regression analysis and restricted cubic splines (RCS) were conducted to investigate the correlation between METS-IR and the progression to diabetes or reversion to normoglycemia. Additionally, the predictive value of MetS-IR for changes in glucose status was evaluated using receiver operating characteristic (ROC) curve analysis.</p><p><strong>Results: </strong>During the median follow-up of 2.92 years, 6682 individuals (43.3%) reverted from prediabetes to normoglycemia, 6992 individuals (45.3%) remained in prediabetes status, and 1750 individuals (11.3%) progressed to diabetes. Notably, an increase in the baseline METS-IR quartile was associated with a heightened risk of diabetes development and a reduced likelihood of reverting to normoglycemia (both P for trend < 0.001). Multivariate Cox regression and RCS analysis showed that METS-IR was significantly associated with both the progression to diabetes and the reversion to normoglycemia, exhibiting a non-linear relationship in both cases. Compared with the lowest METS-IR quartile, the adjusted hazard ratio (HR) (95% confidence interval [CI]) for diabetes progression and normoglycemic reversion in the highest METS-IR quartile was 2.11 (1.78, 2.50) and 0.57 (0.53, 0.62), respectively. The ROC curves analysis showed that METS-IR was the most effective predictor of glycemic status transition in individuals with prediabetes, with an area under the curve (AUC) surpassing those of triglyceride glucose (TyG), atherogenic index of plasma (AIP), and body mass index (BMI).</p><p><strong>Conclusion: </strong>Our study reveals a significant correlation between METS-IR and prediabetes reversion/progression. Regular monitoring of METS-IR in clinical practice may help predict the conversion of glucose status in prediabetes patients and enhance the early identification of populations at elevated risk for diabetes.</p>","PeriodicalId":9152,"journal":{"name":"BMC Endocrine Disorders","volume":"25 1","pages":"162"},"PeriodicalIF":2.8,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12220004/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144538817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"International expert consensus on surgery for type 2 diabetes mellitus.","authors":"Mohammad Kermansaravi, Islam Omar, Nicholas Finer, Carel Le Roux, Miguel A Carbajo, David Sarwer, Luca Busetto, Jaime Ponce, Jennifer Logue, Helen M Parretti, Mary O'Kane, Shahab Shahabi, Kamlesh Khunti, Alexandra I Blakemore, Erik Stenberg, Sally Abbott, Aayed Alqahtani, Ali Aminian, Bassem Amr, Jose M Balibrea, Rachel L Batterham, Estuardo Behrens, Deepak L Bhatt, Paul Chesworth, Pradeep Chowbey, Ken Clare, Manoel Galvao Neto, Yitka Graham, Ramen Goel, Wasim Hanif, Miguel F Herrera, Kazunori Kasama, Radwan Kassir, Filip K Knop, Shanu N Kothari, Jon A Kristinsson, Barbara McGowan, Andrew McKechnie, Karl Miller, Alex D Miras, John Morton, Jane Ogden, Ralph Peterli, Jonathan H Pinkney, Dimitri Pournaras, Sjaak Pouwels, Gerhard Prager, Paulina Salminen, Mireille J Serlie, Asim Shabbir, Rishi Singhal, Shahrad Taheri, Abd A Tahrani, Rudolf Weiner, Scott A Shikora, Kamal Mahawar","doi":"10.1186/s12902-025-01961-w","DOIUrl":"10.1186/s12902-025-01961-w","url":null,"abstract":"<p><strong>Introduction: </strong>Metabolic and bariatric surgery (MBS) has been an established treatment option for patients with Type 2 diabetes mellitus (T2DM), but there is a relative paucity of evidence-based guidelines on preoperative, operative, and postoperative considerations concerning metabolic surgery for T2DM patients. To address this gap, we initiated a Delphi consensus process with a diverse group of international multidisciplinary experts.</p><p><strong>Method: </strong>We embarked on a Delphi consensus-building exercise to propose an evidence-based expert consensus covering various aspects of MBS in patients with T2DM. We defined the scope of the exercise and proposed statements and surveyed the literature through electronic databases. The literature summary and voting process were conducted by 52 experts, who evaluated 44 statements. The quality of evidence was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) criteria.</p><p><strong>Results: </strong>Consensus, defined as > 80% agreement, was reached for 43 out of 44 statements. The experts reached an agreement on the nature, terminology, and mechanisms of action of MBS. The currently available scores for predicting remission of T2DM after surgery are not robust enough for routine clinical use, and there is a need for further research to enable more personalized treatment. Additionally, they agreed that metabolic surgery for T2DM is cost-effective, and MBS procedures for treating T2DM vary in their safety and efficacy.</p><p><strong>Conclusion: </strong>This Delphi expert consensus statement guides clinicians on various aspects of metabolic surgery for T2DM and also grades the quality of the available evidence for each of the proposed statements.</p>","PeriodicalId":9152,"journal":{"name":"BMC Endocrine Disorders","volume":"25 1","pages":"151"},"PeriodicalIF":2.8,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12211331/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144538771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evidence on the link between hypothyroidism and non-alcoholic fatty liver disease: an updated systematic review.","authors":"Nazanin Pourseyedi, Sara Arefhosseini, Helda Tutunchi, Mehrangiz Ebrahimi-Mameghani","doi":"10.1186/s12902-025-01977-2","DOIUrl":"10.1186/s12902-025-01977-2","url":null,"abstract":"<p><strong>Background: </strong>Numerous studies have investigated the relationship between hypothyroidism and non-alcoholic fatty liver disease (NAFLD), while the underlying mechanisms are not well understood. This systematic review evaluated the mentioned relationship among non-diabetic adults.</p><p><strong>Methods: </strong>This systematic review was written in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A comprehensive literature search was conducted using PubMed, Scopus, Web of Science, and Google Scholar until January 2024. After a critical analysis, 29 observational studies were included in the present systematic review.</p><p><strong>Results: </strong>The available observational evidence suggests a potential association between hypothyroidism and NAFLD. Regarding this complex relationship, patients with hypothyroidism may be more likely to develop NAFLD compared to those with normal thyroid function. Several factors are involved in the development of hypothyroidism-induced NAFLD.</p><p><strong>Conclusions: </strong>Thyroid hormones regulate energy and metabolism, suggesting their relevance in NAFLD. Increased awareness and optimized strategies are needed for mutual screening and managing thyroid disease and NAFLD coexistence.</p>","PeriodicalId":9152,"journal":{"name":"BMC Endocrine Disorders","volume":"25 1","pages":"154"},"PeriodicalIF":2.8,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12211774/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144538770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association of predicted basal metabolic rate and insulin resistance in a Chinese general population.","authors":"Linghuan Wang, Tingting Lu, Peixin Wu, Kang Chen, Yiming Mu","doi":"10.1186/s12902-025-01976-3","DOIUrl":"10.1186/s12902-025-01976-3","url":null,"abstract":"<p><strong>Background: </strong>Although basal metabolic rate (BMR) is involved in glucose homeostasis, existing evidence regarding its association with insulin resistance (IR) remains inconsistent across populations. This study aimed to clarify the relationship between predicted BMR and the prevalence of IR in a large, community-based Chinese population.</p><p><strong>Methods: </strong>A total of 36,115 participants aged ≥ 40 years were included from the REACTION study. Individuals with cardiovascular disease, thyroid dysfunction, malignancy, or who were using glucose-, lipid-, or blood pressure-lowering medications were excluded. BMR was estimated using the Singapore equation, and participants were categorized into quartiles (Q1-Q4) based on BMR distribution. Logistic regression models were employed to assess the association between BMR and IR, defined by the homeostasis model assessment of insulin resistance (HOMA-IR). Covariates included sex, age, smoking status, alcohol consumption, glycemic and lipid profiles, liver and kidney function, and anthropometric indices. Sensitivity analyses using inverse probability weighting and restricted cubic spline regression were conducted to verify the robustness of the findings.</p><p><strong>Results: </strong>This cross-sectional study demonstrated a positive association between higher predicted BMR quartiles and increased IR risk in the overall population (P < 0.05), with a stronger association observed in women (P < 0.05). A significant interaction between gender and BMR (P for interaction < 0.05) further supported a sex-specific pattern in the BMR-IR relationship. Stratified analyses revealed consistent positive association in various subgroups stratified by age, blood pressure, body mass index (BMI), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) levels (P < 0.05). This association persisted across participants with different glucose tolerance statuses, particularly among those with normal glucose tolerance and impaired glucose regulation. The association also remained significant in both premenopausal and postmenopausal women. Sensitivity analyses confirmed the stability of the results.</p><p><strong>Conclusions: </strong>Predicted BMR is independently and positively associated with IR in Chinese general population, particularly in woman. The relationship demonstrated a clear dose-response pattern and remained robust across various subgroups. Monitoring BMR dynamics and targeting modifiable metabolic factors may serve as preventive strategies against IR-relate diabetes mellitus. Further longitudinal studies are warranted to validate causality.</p>","PeriodicalId":9152,"journal":{"name":"BMC Endocrine Disorders","volume":"25 1","pages":"156"},"PeriodicalIF":2.8,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12217542/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144538767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}