BMC Endocrine Disorders最新文献

Background: Altered thyroid function has been linked to insulin resistance (IR), but its relationship with the Metabolic Score for Insulin Resistance (METS-IR), a novel non-insulin-based index of IR, remains unclear. This study aimed to investigate the association between thyroid function status and METS-IR in a U.S.

Population:

Methods: This cross-sectional study utilized data from 6,507 adults (aged ≥ 20 years) participating in the National Health and Nutrition Examination Survey from 2007 to 2012. Thyroid function status was categorized into five groups based on thyroid-stimulating hormone and free thyroxine levels. METS-IR was calculated from measures of fasting glucose, triglycerides, high-density lipoprotein cholesterol (HDL-C), and body mass index (BMI). Multivariate regression analyzed the relationship between thyroid status and METS-IR after adjusting for potential confounders.

Results: Higher thyroid-stimulating hormone levels were positively associated with METS-IR (β = 0.003, 95% CI 0.001-0.004, p = 0.021). Subclinical hypothyroidism in males and subclinical hyperthyroidism in females showed significant correlations with higher METS-IR. Thyroid peroxidase antibodies (TPO Ab) positivity strengthened the association between overt hypothyroidism and METS-IR.

Conclusions: This study demonstrates significant associations between thyroid function status, particularly subclinical thyroid dysfunction, and insulin resistance as measured by METS-IR in a U.S.

Population: Thyroid status may serve as an early marker of insulin resistance risk.

Objective: Infertility is associated with obesity. The Body Roundness Index (BRI) is a body measurement index related to obesity that more accurately assesses body and visceral fat levels. However, the relationship between BRI and infertility remains unclear. Therefore, this study aims to determine the relationship between BRI and infertility.

Methods: This study utilized data from the National Health and Nutrition Examination Survey (NHANES) from 2013 to 2018 and included 3,528 women aged 18-45 years. Multivariate logistic regression was employed to investigate the association between BRI and infertility. Restricted cubic spline (RCS) analysis explored the linear or non-linear relationship between BRI and infertility. Interaction analyses were conducted on subgroups to validate the findings. To verify the robustness of the results, we performed several sensitivity analyses, including propensity score matching(PSM) and multiple imputations for missing data. Furthermore, the predictive capabilities of various anthropometric indices-including BRI, weight-adjusted waist index (WWI), body mass index (BMI), and weight-on infertility incidence were assessed using Receiver Operating Characteristic (ROC) curve analysis.

Results: There was a significant positive association between BRI and infertility. After adjusting for covariates, for each unit increase in BRI, there was a 12% increase in the probability of infertility (P < 0.001). This positive correlation persisted when BRI was categorized into quartiles. Moreover, as BRI increased, there was a trend towards higher infertility prevalence (P for trend < 0.001). The dose-response curve indicated a linear association between BRI and infertility, with higher BRI associated with higher infertility risk. The correlation between BRI and infertility persisted in subgroup analysis and multiple imputations. The ROC curve analysis revealed that BRI had a superior predictive capability compared to traditional obesity indices, with an area under the curve (AUC) of 0.618 (95% CI, 0.588-0.648).

Conclusion: The results of this study show a strong positive correlation between BRI and the prevalence of infertility.

Clinical trial number: Not Applicable.

Background: Medications targeting the glucagon-like peptide-1 (GLP-1) pathway are an important therapeutic class currently used for the treatment of Type 2 diabetes (T2D). However, there is not enough known about which subgroups of patients would receive the most benefit from these medications.

Objective: The goal of this study was to develop a predictive model for patient responsiveness to medications, here collectively called GLP-1 M, that include GLP-1 receptor agonists and dipeptidyl peptidase-4 (DPP4) inhibitors (that normally degrade endogenously-produced GLP-1). Such a model could guide clinicians to consider certain patient characteristics when prescribing second line medications for T2D.

Methods: We analyzed de-identified electronic health records of 7856 subjects with T2D treated with GLP-1 M drugs at Vanderbilt University Medical Center from 2003-2019. Using common clinical features (including commonly ordered lab tests, demographic information, other T2D medications, and diabetes-associated complications), we compared four different models: logistic regression, LightGBM, artificial neural network (ANN), and support vector classifier (SVC).

Results: Our analysis revealed that the traditional logistic regression model outperforms the other machine learning models, with an area under the Receiver Operating Characteristic curve (auROC) of 0.77.Our model showed that higher pre-treatment HbA1C is a dominant feature for predicting better response to GLP-1 M, while features such as use of thiazolidinediones or sulfonylureas is correlated with poorer response to GLP-1 M, as assessed by lowering of hemoglobin A1C (HbA1C), a standard marker of glycated hemoglobin used for assessing glycemic control in individuals with diabetes. Among female subjects under 40 taking GLP-1 M, the simultaneous use of non-steroidal anti-inflammatory drugs (NSAIDs) was associated with a greater reduction in HbA1C (0.82 ± 1.72% vs 0.28 ± 1.70%, p = 0.008).

Conclusion: These findings indicate a thorough analysis of real-world electronic health records could reveal new information to improve treatment decisions for the treatment of T2D. The predictive model developed in this study highlights the importance of considering individual patient characteristics and medication interactions when prescribing GLP-1 M drugs.

Introduction: Many patients with polycystic ovary syndrome (PCOS) also experience thyroid disorders. There is a notable similarity in energy metabolism among PCOS, C1q/tumor necrosis factor (TNF)-related proteins (CTRP-5)deficiency, C3a/desArg (also known as acylation-stimulating protein (ASP)) deficiency, and hypothyroidism. This study aimed to investigate the relationship between serum levels of these factors and hypothyroidism in patients with PCOS. Improved clarity and vocabulary, corrected minor grammatical issues, and enhanced readability.

Methods: This case-control study involved three groups: healthy women (control group), women with PCOS and hypothyroidism, and women with PCOS without hypothyroidism. Serum levels of FBS, total cholesterol, triglycerides, and HDL-C were measured using enzymatic and colorimetric methods. TSH, T4, T3, and anti-thyroid peroxidase (Anti-TPO) levels were determined by ELISA to screen for hypothyroidism in women with PCOS. Additionally, serum levels of luteinizing hormone (LH), follicle-stimulating hormone (FSH), CTRP-5, ASP, and complement C3 were assessed using the ELISA method.

Results: The results indicated that reduced blood levels of CTRP-5, along with elevated levels of ASP (C3a/desArg) and complement C3 in patients with PCOS, may be linked to dysregulation of the thyroid gland. Furthermore, the study observed that changes in these parameters, in conjunction with thyroid dysfunction, are associated with pathological alterations in lipid profiles and blood glucose levels.

Conclusion: While changes in CTRP-5, ASP, and complement C3 can influence energy expenditure and storage in PCOS and thyroid function, the complex nature of PCOS requires further research to investigate the prevalence of hypothyroidism in individuals with PCOS.

Clinical trial number: Not applicable.

Background: The impact of night shift work on the incidence of type 2 diabetes mellitus (T2DM) is not well understood. This meta-analysis assesses the association between night shift work and the risk of developing T2DM and explores this relationship across various subgroups.

Methods: We systematically searched PubMed, Web of Science, EBSCO, and the Cochrane Library from their inception until February 2024. We employed hazard ratios (HR) and 95% confidence intervals (95%CI) to quantify the association between night shift work and T2DM risk.

Results: Our analysis synthesized data from 9 articles encompassing 10 cohort studies. Overall, night shift workers exhibited a 30% increased incidence of T2DM compared to their daytime counterparts (HR = 1.30, 95% CI: [1.18, 1.43], P < 0.001). Among females, night shift workers had a higher incidence of T2DM (HR = 1.28, 95% CI: [1.16, 1.41]); however, in males, the association was not statistically significant (95% CI: [0.89, 2.63]). For individuals with a body mass index (BMI) > 30 kg/m², night shift work was associated with an increased T2DM risk (HR = 1.14, P = 0.007), whereas there was no significant association for those with a BMI ≤ 30 kg/m² (P = 0.255). Further, the risk of T2DM increased with longer durations of night shift work; workers with more than 10 years of night shift work faced a higher T2DM risk than those with 10 years or fewer (HR for > 10 years = 1.17, 95% CI: [1.10, 1.24]; HR for ≤ 10 years = 1.06, 95% CI: [1.03, 1.10]).

Conclusion: Findings suggest potential link between night shift work and T2DM risk. Longer durations of night shift work may increase the risk of T2DM. There may be gender differences (greater harm in women, but the male sample size is small) and obesity differences.

Background: The global health concern regarding the low prevalence of diagnosed diabetes mellitus (DDM) is evident, but the prevalence of DDM is increasing. This is attributed to the frequent underestimation of undiagnosed diabetes mellitus (UDM). Given the limited research on this matter in Bangladesh, there is a need to investigate sex differences in both the prevalence and risk factors of DDM among Bangladeshi adults.

Methods: This study utilizes the latest data from the Bangladesh Demographic and Health Survey (BDHS) conducted between 2017 and 2018, involving 11,911 adult participants. The research focuses on exploring sex-specific differences in the prevalence of diagnosed diabetes mellitus (DDM) and undiagnosed diabetes mellitus (UDM). Multinomial logistic regression models are applied to examine the sex effect after adjusting socio-demographic, household, and community-related factors associated with these conditions.

Results: In the group of 5127 (43%) males, the prevalence of diagnosed diabetes mellitus (DDM) and undiagnosed diabetes mellitus (UDM) stood at 344 (7%) and 94 (2%), respectively. Among 6784 (57%) females, these figures were slightly lower at 424(6%) for DDM and 138 (2%) for UDM. In males aged 30-39, UDM exhibited significantly (RRR: 6.83, 95% CI: 2.01-23.18), associations, in contrast to the nonsignificant association observed for DDM. Unemployed female had a high risk of diagnosed (RRR: 1.28, 95% CI: 1.02-1.6) and undiagnosed (RRR: 1.52, 95% CI: 1.01-2.31) diabetes. Age, hypertension, wealth, overweight status, and residing in Dhaka had significant relationship with DDM and UDM for both males and females.

Conclusions: This study reveals that diabetes prevalence in Bangladesh is influenced by various risk factors, with distinct impacts on men and women. Women living in Dhaka who are unemployed are at a significantly higher risk of both diagnosed and undiagnosed diabetes compared to men. To effectively combat the rising diabetes rate, we must implement targeted interventions that address these sex-specific disparities. These interventions should focus on age, wealth, regional variations, and especially on unemployed women in Dhaka, considering their heightened risk.

Background: Reninoma is a rare cause of secondary hypertension, which can be cured with surgery if identified early before any target organ damage occurs. It leads to hypokalaemia and hypertension and typically responds well to treatment with renin-angiotensin-aldosterone system blockers. However, confirmation of the diagnosis and the localisation of this rare culprit lesion can be challenging.

Case presentation: We describe a case of young-onset hypertension in a 19-year-old girl due to a reninoma. She had resistant hypertension with marked hypokalaemia, which required exceedingly high doses of potassium supplements. Biochemical Investigations revealed secondary hyperaldosteronism. Thus, she underwent a renal angiogram to exclude a renovascular cause for her hypertension. While the renal artery anatomy was normal, there was an exophytic renal lesion in the lower pole of the left kidney. Hence, the diagnosis of a reninoma was suspected. She underwent renal vein sampling to confirm the functionality of the detected tumour, but the results were inconclusive. After a multidisciplinary discussion, based on the clinical evidence, the renal lesion was thought to be a reninoma and a partial nephrectomy was done, removing the lesion. Immediately following resection, her blood pressure and potassium normalised without further drug treatment, and the resected lesion was later confirmed to be a reninoma by histopathological examination.

Conclusion: In young people with hypokalemic hypertension, reninoma should be considered when the more common causes are excluded since prompt treatment with excision of the culprit lesion can cure hypertension and prevent associated morbidity and mortality.

Background: Type 2 diabetes mellitus (T2DM) represents a significant global health challenge, with its prevalence steadily rising across diverse populations. Understanding the factors associated with T2DM is crucial for effective prevention and management strategies. In Cape Verde, an archipelago nation off the coast of West Africa, the burden of T2DM is of particular concern, yet comprehensive studies investigating its determinants in this context remain sparse. This study aims to narrow the knowledge gap by assessing the prevalence of prediabetes, T2DM and its associated factors among the adult Cape Verdean population.

Methods: Data from the WHO STEPs survey were used. We analyzed data from 1,936 adults aged 18-69 years. The outcome variable was diabetes status computed using the fasting blood glucose (mg/dl). The data was weighted before the analysis to account for sampling biases. Multinomial logistic regression models were computed in STATA version 18.

Results: The overall prevalence of prediabetes and T2DM was 7.8% (95% CI: 6.1-9.9) and 3.9% (95% CI: 3.1-4.9), respectively. Increasing age was associated with a higher odd of prediabetes and T2DM with the highest odds observed among older adults [(prediabetes: AORs = 3.20, 95%CI: 1.88-5.54) and T2DM: AOR = 3.51, 95%CI: 1.71-7.18)]. Additionally, high total cholesterol levels were linked to increased odds of T2DM (AOR = 2.48, 95%CI: 1.64-3.76). Individuals who consumed less than four servings of vegetables daily had higher odds of T2DM (AOR = 1.74, 95%CI: 1.12-2.71) while being overweight/obese was associated with higher odds of prediabetes (AOR = 1.57, 95%CI: 1.10-2.23). Urban residents had higher odds of T2DM than rural residents (AOR = 1.92, 95%CI: 1.23-3.00). Also, higher educational attainment was associated with lower odds of T2DM only (AOR = 0.33, 95%CI: 0.12-0.88) but not statistically significant for prediabetes.

Conclusion: Based on the findings, we conclude that ageing, overweight/obesity, vegetable consumption and total cholesterol level are important predictors of pre-diabetes and T2DM in Cape Verde. As such, weight management and cholesterol management should be integral parts of T2DM prevention strategies. Additionally, clinicians and diabetes societies in Cape Verde must make the promotion of vegetable consumption a key component of their health advice and advocacy.

Clinical trial number: Not applicable.