International Journal of Endocrinology最新文献

Objectives: Prior research has identified a significant correlation between elevated serum ferritin (SF) levels and comorbidities in Type 2 diabetes mellitus (T2DM) patients. However, the association between SF levels and kidney stone occurrence in T2DM remains unexplored. This study aimed to assess the relationship between SF levels and kidney stone risk in T2DM patients.

Methods: This study collected data from 50,583 patients with T2DM who received treatment at the First Affiliated Hospital of University of Science and Technology of China from December 2015 to December 2023. Ultimately, 1024 eligible patients were included for analysis. Multivariable logistic regression models were used to determine the odds ratio (OR) and 95% confidence interval (95% CI) for the association between SF and kidney stones. A multivariable-adjusted restricted cubic spline model was constructed to establish the OR curves to examine the possible nonlinear dose-response association between SF and kidney stones.

Results: Of 1024 patients included in this study (mean age, 56.31 ± 9.82 years-old; 686 [67.0%] male), 148 (14.5%) reported having kidney stones, while 876 (85.5%) did not. After adjusting for potential confounders, the SF levels were associated with kidney stones (OR = 1.001; 95% CI, 1.000-1.002; p < 0.001). Participants in the highest quartile (Q4) of SF levels (333.60 ≤ SF ≤ 1867.00 ng/mL) had an adjusted OR for kidney stones of 2.901 (95% CI, 1.710-4.901; p trend < 0.001) compared to those in the lowest quartile (Q1) (6.20 ≤ SF ≤ 99.35 ng/mL). The multivariable restricted cubic spline showed a nonlinear association between SF levels and kidney stones (p=0.033). Subgroup analyses showed that SF levels were associated with kidney stones in male (OR = 2.04; 95% CI, 1.06-4.14), individuals ≤ 60 years-old of age (OR = 2.34; 95% CI, 1.21-4.73), with no smoke history (OR = 2.00; 95% CI, 1.06-3.85).

Conclusion: Elevated SF levels are associated with kidney stones in T2DM patients.

Background: Acromegaly is a rare but severe condition characterized by the excessive secretion of growth hormone (GH), leading to various metabolic alterations. Treatment options include surgery, pharmacotherapy, and radiotherapy (RT). RT can control the disease biochemically, either alone or in conjunction with medical therapy. This study aimed to evaluate the effectiveness of conventional RT in patients with postoperative acromegaly over a 15-year follow-up period, using specific cutoff criteria.

Methods: A retrospective analysis was performed on 55 acromegaly patients who were monitored for an average of 15 (13.3-16.7) years and treated with conventional RT (median dose of 52 Gy) following pituitary surgery. Hormonal assessments included baseline and glucose-suppressed GH and IGF-1 levels, and side effects associated with RT were evaluated.

Results: The baseline GH level decreased from 20.7 (16-25.4) μg/L to 11.2 (8.3-14.1) μg/L (p < 0.001) at 2 years, further dropping to 5.8 (4.99-6.61) μg/L (p < 0.001) at 5 years, and to 2.2 (1.66-2.74) μg/L (p < 0.001) at 10 years after RT. Rates of patients achieving suppressed GH levels < 1 μg/L rose from 9% at 2 years to 25% at 5 years, 42% at 10 years, and 76% at 15 years. IGF-1 levels normalized in 5% of participants at 2 years, 14% at 5 years, 38% at 10 years, and 60% at 15 years. After 10 years, 78% of patients experienced hypogonadism, 80% experienced hypothyroidism, and 82% experienced hypocortisolism. Neurological complications were reported in 4% of patients 10 years post-RT, while 4% developed visual impairments and optic neuropathy within 5 years.

Conclusion: The results suggest that conventional RT is an effective long-term management strategy for patients who do not respond adequately to medical therapy or surgery. However, the high incidence of late-onset hypopituitarism must be taken into account.

Objective: To assess the therapeutic effects of gonadotropin-releasing hormone agonist (GnRHa) on children with familial central precocious puberty (FCPP) due to Makorin ring finger Protein 3 (MKRN3) gene mutations.

Methods: Children with central precocious puberty (CPP) who were admitted to the Pediatric Endocrinology Department of Shanghai Ruijin Hospital from 2014 to 2021 were enrolled, of whom 4 FCPP children with MKRN3 gene mutations, including 3 girls and 1 boy, were selected as research subjects. Their height, weight, body mass index (BMI), predicted adult height (PAH), bone age, bone age advance (BAA, bone age minus chronological age), height-based standard deviation scores (Ht-SDS) corresponding to the chronological age, concentrations of sex hormones (luteinizing hormone [LH] and follicle-stimulating hormone [FSH]), and development of sexual organs were compared before and after at least 2 years of GnRHa treatment.

Results: After at least 2-year GnRHa treatment, mean volume of uterus of three girls decreased from 5.72 ± 2.58 to 2.12 ± 1.62 mL (p < 0.05) and mean volume of ovaries decreased from 3.61 ± 1.67 to 0.62 ± 0.22 mL (p < 0.05) as well, indicating that the gonadal development was effectively inhibited. Basal concentrations of LH and FSH in serum decreased, indicating that the secretion of gonadotropin in the anterior pituitary is inhibited. BAA and Ht-SDS decreased, suggesting that the bone age was restrained, and the growth rate was slowed down to some extent. Both average BMI and obesity prevalence (X ² = 7.188, p=0.029) decreased during the treatment. No obvious adverse reaction was found.

Conclusion: Long-term GnRHa treatment could effectively inhibit the gonadal development and FSH secretion in FCPP children with MKRN3 gene mutations, while this inhibitory effect on the bone age and growth rate was not obvious. Adverse reactions such as increased prevalence of obesity were not found. A large-scale, long-term follow-up study is required to indicate whether patients' final height (FH) could reach PAH or target height (TH).

Objective: To investigate the effects of the G protein-coupled estrogen receptor (GPER) on the balance of regulatory T-helper/new effector T-cells (Treg/Th17) in the peripheral blood of patients with Hashimoto's thyroiditis (HT) and healthy individuals.

Methods: A total of 230 participants were enrolled in this study, including 206 patients with new-onset HT (HT group) and 24 healthy physical examinees (normal control [NC] group). Venous blood samples were obtained from the participants and tested for serum GPER levels using an enzyme-linked immunosorbent assay. The peripheral blood proportion of Treg and Th17 cells and the Treg/Th17 ratio were determined using flow cytometry. Thyroid function, antibody levels, and biochemical and anthropometric tests were performed. Data management and statistical analyses were performed using SPSS Version 25.0.

Results: The serum GPER levels among the HT group participants were significantly higher than those among the NC group (p < 0.001). Among the HT group participants with increasing serum GPER levels, the peripheral blood proportion of Treg cells and the Treg/Th17 ratio increased significantly (p < 0.001), even after adjusting for relevant confounding factors. However, with increasing serum GPER levels, the peripheral blood proportion of Th17 cells decreased significantly (p < 0.001), even after adjusting for confounding factors.

Conclusion: The results confirmed that the serum GPER expression level in the initial HT group was significantly higher than that in the NC group and was positively correlated with the Treg/Th17 ratio, peroxidase antibody, and thyroglobulin antibody. Our findings suggest that a compensatory increase in the proportion of Treg/Th17 cells may be related to increased serum GPER levels.

Background and purpose: One of the most common complications of diabetes is impaired healing of diabetic wounds. Given the antidiabetic and antimicrobial effects of the Dorema aucheri plant, the present study was conducted to determine the impact of the alcoholic extract of this plant on the healing of full-thickness diabetic wounds in male rats.

Materials and methods: In this experimental study, 48 male rats were randomly divided into 6 groups: control wound, diabetic wound, diabetic wound with carboxymethylcellulose base gel, and diabetic wounds with the combination of D. aucheri extract with percentages of 2%, 5%, and 10%. The wound in all groups was the full thickness of the skin. The drugs were administered topically, once daily, for 14 days. Also, to measure the percentage of wound healing, we took photographs of the samples on Days 0, 3, 7, and 14. Finally, skin samples were taken from the wound repair site for stereological evaluation.

Results: In comparison to the other groups, the group treated with 5% D. aucheri extract showed a better healing speed, volume of re-epithelialization, density of collagen deposition, and neovascularization (p ≤ 0.05). The fibroblast number density, collagen density, and hair follicle volume densities were all lower in the 10% D. aucheri-treated group than in the other groups (p ≤ 0.001).

Conclusion: The hydroalcoholic extract of the D. aucheri plant, particularly at a concentration of 5%, has beneficial effects on the healing process of diabetic wounds.

Background: Metabolic syndrome (MetS) is one of the most common chronic disease complications and significantly increases the prevalence of chronic diseases. This study aims to identify different patterns of MetS development using longitudinal data and explore their influencing factors.

Method: Based on the physical examination cohort of Shanghai railway workers, longitudinal data spanning 5 years (from January 1, 2019, to December 31, 2023) were collected to analyze the development trajectories of 1954 participants with MetS. Latent growth mixture model (LGMM) was employed to classify the development trajectories of MetS into distinct groups. Additionally, mixed-effect models were utilized to explore the influencing factors, and machine learning models were constructed for trajectory prediction.

Results: The LGMM model classified patients into four groups: the progressively increasing group, the steadily increasing group, the progressively decreasing group, and the steadily decreasing group. Compared to the other three groups, the progressively increasing group exhibited the highest levels of weight, body mass index (BMI), heart rate, γ-glutamyltransferase, aspartate aminotransferase, alanine aminotransferase, uric acid, and white blood cell count. Conversely, compared to the other three groups, the group with progressive decreases showed the highest levels of systolic blood pressure, total bilirubin, direct bilirubin, urea nitrogen, fasting blood glucose, high-density lipoprotein cholesterol (HDL-C), and triglycerides (TGs). Mixed-effect models revealed that an increase in BMI and TG (OR > 1, p < 0.001) significantly increased the probability of being classified into the progressively increasing group, whereas HDL-C (OR < 1, p < 0.001) had the opposite effect. Variables selected through feature engineering were utilized to construct five machine learning prediction models, among which Random Forest (with an area under the curve, AUC = 0.852) demonstrated the best overall prediction performance and was therefore chosen to develop a MetS risk calculator based on Shiny.

Conclusion: BMI, TG, and HDL-C were the key to influence the developmental trajectories of MetS. Therefore, these three indicators should be closely monitored, and the progression of MetS can be controlled by adjusting dietary patterns.

Introduction: Muscle function and strength are related to magnesium (Mg). The risk of low muscle mass in type 2 diabetes mellitus (T2DM) is higher compared to healthy individuals. This study aimed to evaluate the association between serum Mg and low muscle mass in people with T2DM.

Methods: This study included 1074 inpatients with T2DM with measured skeletal muscle index (SMI) and serum Mg concentrations, along with collected clinical characteristics. SMI was measured using dual-energy X-ray absorptiometry. Logistic regression analysis and linear regression analysis were employed to examine the associations between serum Mg concentrations and low muscle mass or SMI, respectively.

Results: The prevalence of low muscle mass was 20.28% in males and 14.20% in females. Serum Mg concentration was significantly higher in the low muscle mass group compared to the normal muscle mass group. Furthermore, among female patients with T2DM, a negative correlation was observed between Mg levels and SMI. Multivariate logistic regression analysis revealed that high Mg levels were significantly associated with an increased risk of low muscle mass. Specifically, in females, higher serum Mg levels significantly increased the risk of low muscle mass. The odds ratios (95% confidence intervals) across increasing tertiles (T1 to T3) of serum Mg were 1.00 (reference), 1.321 (95% CI, 0.626-2.790), and 2.071 (95% CI, 1.011-4.243), respectively, with a significant trend (p for trend = 0.039).

Conclusion: Low muscle mass in T2DM patients is associated with serum Mg levels. Notably, among female patients, higher serum Mg concentrations showed a significant linear trend and were negatively correlated with low muscle mass.

Objectives: Insufficient or excessive sleep and dyslipidemia are significant cardiovascular risk factors. Whilst the relationship between sleep duration and traditional lipid indices are well described, the connection to novel lipid and anthropometric indices remains unclear. This study examines these associations using National Health and Nutrition Examination Survey (NHANES) data from 2005 to 2020.

Methods: This cross-sectional study analyzed data from 9847 adults from NHANES 2005-2020, excluding those with major cardiovascular disease and cancer. Sleep duration was categorized as insufficient (< 7 h), normal (7-8 h), and excessive (> 8 h). Self-reported sleep disturbance was documented. Novel indices included non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR), Triglyceride to HDL-Cholesterol (TG/HDL), Triglyceride-Glucose (TyG) Index, Visceral Adiposity Index (VAI), Lipid Accumulation Product (LAP), Conicity Index (CI), Body-Roundness Index (BRI), A Body Shape Index (ABSI), and Weight-adjusted waist index (WWI). Generalized additive models (GAMs) with spline smoothing and threshold analysis assessed nonlinear associations, adjusting for confounders. Weighted multivariate linear regression evaluated linear associations.

Results: Insufficient sleep was associated with higher TyG combined with waist-to-height ratio (TyG-WHtR) (p = 0.003). Excessive sleep was linked to higher TyG-WHtR, CI, BRI, ABSI, and WWI (p < 0.001). Sleep disturbance was associated with elevated TyG-WHtR, TyG-WC, LAP, CI, BRI, ABSI, and WWI (p < 0.001). Threshold analysis confirmed significant changes in several indices, emphasizing the impact of both insufficient and excessive sleep.

Conclusions: Insufficient, excessive sleep duration and sleep disturbance are associated with adverse lipid and anthropometric profiles, indicating increased cardiometabolic risk. Optimal sleep duration and addressing sleep disturbance could mitigate these risks. Further research is needed to understand the underlying mechanisms.

Background: Polycystic ovary syndrome (PCOS) is a complex reproductive-endocrine disorder with an ambiguous etiology, presenting significant challenges for clinical management. Recently, inflammation has been identified as a pivotal factor in the pathogenesis of PCOS, attracting considerable attention within the scientific community. In this study, we used bibliometric and visualization analyses to investigate the research hotspots and developmental trends associated with inflammation in PCOS to obtain valuable insights for future research.

Methods: The core collection of the Web of Science database was accessed to retrieve literature on inflammation and PCOS published from 2004 to 2024. Bibliometric analysis and visualization were performed using software tools including CiteSpace, VOSviewer, and GraphPad Prism. The analysis focused on publication year, country, institution, journal, author, publication, and literature keywords.

Results: From January 1, 2004, to July 25, 2024, a total of 2568 articles were published on PCOS and inflammation, which involved 10,920 authors from 2902 research institutions across 92 countries. The volume of literature in this field had consistently increased, with significant contributions from the United States and China. Tehran University of Medical Sciences and the Egyptian Knowledge Base were identified as the most active and influential institutions. "Gynecological Endocrinology" was the leading journal in terms of the number of relevant articles published. Among the published authors, Asemi and Zatollah had the highest publication counts, while Azziz R.'s work received the most citations. Commonly occurring keywords included insulin resistance, obesity, and oxidative stress. Recent literature clustering and keyword analysis identified that resveratrol, granulosa cells, follicular fluid, gut microbiota, and probiotics are current research hotspots in this field. Gut microbiota and infertility are recognized as significant directions for future research.

Conclusions: This bibliometric analysis provides a detailed overview of research on inflammation and PCOS, highlighting its importance in disease progression and the potential for therapeutic targeting of inflammatory pathways.

Background: Identifying undiagnosed cases of metabolic syndrome (MetS) is important because timely recognition may help reduce the risk of associated complications, including cardiovascular disease (CVD), Type 2 diabetes mellitus (T2DM), stroke, nonalcoholic fatty liver disease (NAFLD), and chronic kidney disease (CKD). This study aims to provide a comprehensive evaluation of MetS and obesity levels among patients attending an outpatient clinic.

Methods: This cross-sectional study was conducted at the outpatient clinics of Istanbul, Maltepe University Hospital, Türkiye, between January 2018 and December 2019, involving adults between the ages of 18 and 70. Demographic and lifestyle information (age, sex, marital status, education, employment, smoking, and comorbidities) was collected through a structured questionnaire. Weight, height, waist circumference, and blood pressure were recorded for all participants. Body mass index (BMI), fasting glucose, HDL cholesterol, triglyceride levels, extractable nuclear antigen (ENA) profiles, and fluorescent antinuclear antibody (FANA) levels were assessed. The Turkish Endocrinology and Metabolism Society's criteria were used to diagnose MetS.

Results: Of the 504 study participants, 55.9% (n = 282) were female, with a mean age of 52.2 ± 10.8 years. The overall prevalence of MetS was 32.7% (n = 165), with 32.9% (n = 93) in females and 32.4% (n = 72) in males. Despite similar MetS rates between sexes, lower education and unemployment were associated with higher prevalence. High BMI and a high prevalence of obesity were associated with MetS. Key indicators for MetS diagnosis among participants included weight, height, triglyceride, and HDL levels. The relationship between ENA profiles, FANA levels, and MetS showed significance upon analysis.

Conclusion: In this study, one-third of adults were diagnosed with MetS, with no significant difference in overall prevalence between sexes. Men had lower HDL-C and higher triglycerides, while women showed higher abdominal obesity. In addition, 15.5% of participants were positive for ENA and FANA antibodies despite no clinical autoimmune disease. Socioeconomic disparities, including lower education and unemployment, were also associated with higher MetS prevalence. These findings highlight the importance of integrating both sex-related and socioeconomic factors into targeted screening strategies.