BMC Endocrine Disorders最新文献

Objective: One of the main features of polycystic ovary syndrome (PCOS) is increased adipose tissue, which can result in hormonal disturbances. In the present study, we aimed to investigate which indicator of obesity could better associate with hormonal disturbances in PCOS women.

Methods: In this cross-sectional analysis, women with PCOS were included according to the Rotterdam criteria. Fasting blood samples were analyzed for biochemical, metabolic, and hormonal parameters. Anthropometric measures comprised body composition indices (assessed by bioelectric impedance analysis [BIA]), waist circumference, body mass index (BMI), and waist-to-height ratio (WHtR). Linear regression modeling was used to assess the association between anthropometric indices and hormonal imbalance, adjusted for age, mensuration status, and the homeostasis model assessment-estimated insulin resistance (HOMA-IR). Receiver operating characteristics (ROC) curves were utilized to ascertain the sensitivity, specificity, and optimal cut-off points of various anthropometric indices in identifying hyperandrogenism.

Results: A total of 129 PCOS women with a median (interquartile range [IQR]) age of 32.0 (23.0-32.0) years and a median BMI of 26.3 (23.00-29.70) kg/m² were enrolled. In the adjusted linear regression model, BMI (β = 0.053, P < 0.001), waist circumference (β = 0.021, P = 0.001), WHtR (β = 3.325, P = 0.002), total fat mass (β = 0.021, P = 0.002), trunk fat mass (β = 0.038, P = 0.006), and leg fat mass (β = 0.045, P = 0.004) were positively associated with free androgen index (FAI). In addition, BMI (β=-0.017, P = 0.003), waist circumference (β=-0.008, P = 0.002), WHtR (β=-1.167, P = 0.004), total fat mass (β=-0.008, P=0.003), trunk fat mass (β=-0.017, P=0.001), and leg fat mass (β=-0.018, P=0.004) were negatively associated with the serum level of sex hormone binding globulin (SHBG). WHtR showed the greatest area under the curve (AUC) value (AUC = 0.676, P = 0.001) for identifying hyperandrogenism (FAI ≥ 4.97 or total testosterone ≥ 0.7 ng/mL) in PCOS women with corresponding sensitivity of 87.30% and specificity of 39.70%.

Conclusions: WHtR is related to hyperandrogenism in PCOS better than other anthropometric measures.

Objective: This study aimed to compare the salivary gland ultrasonography(SGUS) findings in patients with primary Sjögren's Syndrome (pSS) and diabetes mellitus(DM) patients with sicca symptoms and to examine the relationship between salivary gland ultrasonography (SGUS) findings with clinical and laboratory parameters.

Methods: In this study, 34 patients with pSS and 34 DM patients with sicca symptoms were included. In all patients, bilateral parotid, and submandibular gland ultrasonography (totally 272 glands) was performed by blinded rheumatologist, using the Hocevar and the Outcome Measures in Rheumatology (OMERACT) scoring system. Clinic and ultrasonographic variables were compared between groups. The association between SGUS score and disease duration was analyzed by correlation analysis.

Results: Patients with pSS presented significantly higher SGUS scores than patients with DM (the Hocevar score; 20.93(± 9.65) vs. 3.82(± 3.71); p < 0.05, the OMERACT score; 5.96(± 2.30) vs. 2.07(± 1.65); p < 0.05, respectively). In patients with pSS, the submandibular gland scores were significantly higher than the parotid gland scores (right; p < 0.05 vs. left; p < 0.01) while DM patients showed significantly higher parotid gland scores (right; p < 0.05 vs. left; p < 0.05). In pSS patients, the SGUS scores were associated with disease duration (r = 0.57; r = 0.50; p < 0.05), symptom duration (r = 50; r = 0.47; p < 0.05), and the European League Against Rheumatism Sjögren's Syndrome Patient Reported Index (ESSPRI)-dryness score (r = 0.35, r = 0.36; p < 0.05). However, in DM patients, the SGUS scores are highly correlated with the ESSPRI-dryness (r = 0.74, r = 0.72; p < 0.05) and HbA1C level (r = 0.91, r = 0.86; p < 0.05).

Conclusions: This study demonstrated that major salivary gland involvement was more severe and correlated with disease duration, and submandibular gland was dominantly affected in pSS. Contrarily, in DM patients, salivary gland involvement was milder, parotid dominant and related to level of dryness and HbA1C, rather than disease duration when compared to pSS.

Background: The thyroid function test (free triiodothyronine [FT3], free thyroxine [FT4], and thyroid-stimulating hormone [TSH]) is one of the key determinant of glucose homeostasis by regulating the balance of insulin. Thyroid dysfunction alters glucose metabolism, leading to insulin resistance (IR). This study aimed to assess the association between thyroid function and IR in pregnant Sudanese women.

Method: A cross-sectional study was conducted in Saad Abuelela Hospital, Khartoum-Sudan, from January to April 2021. Obstetric/sociodemographic characteristics were gathered through questionnaires. Serum TSH, FT3, FT4, fasting plasma glucose (FPG), and fasting insulin levels were measured and evaluated, and IR was estimated using the homeostatic model assessment for insulin resistance (HOMA-IR) equation.

Results: In total, the study included 127 pregnant women with a median age of 27.0 years (interquartile range [IQR] 23.0‒31.2) and a median gestational (IQR) age of 25.0 (IQR 25.0‒27.0) weeks. The medians (IQRs) of the TSH, FT3, and FT4 were 1.600 (1.162‒2.092) IU/ml, 2.020(1.772‒2.240) nmol/l, and 10.70 (9.60‒11.90) pmol/l, respectively. The median (IQR) of the FPG and fasting blood insulin level was [69.0 (62.00‒78.00) mg/dl] and [5.68(2.99‒11.66) IU/ml], respectively. The median (IQR) of the HOMA-IR level was 0.9407 (0.4356‒2.1410). There was a positive correlation between HOMA -IR and FT3 levels (r = 0.375; P < 0.001) and a negative correlation with FT4 levels (r= -0.312; P < 0.001). Also, a significant positive correlation was found between fasting insulin levels and FT3 levels (r = 0.438; P < 0.001) and a negative correlation with FT4 levels (r= -0.305; P < 0.001).

Conclusions: This study indicated that FT3 has positive correlation with HOMA-IR, while FT4 has negative correlation among healthy pregnant women without a history of thyroid dysfunction. This may indicate screening of euthyroid pregnant women for thyroid dysfunction and IR. Further studies are needed.

Background: Klotho plays a pivotal role in human aging. Metabolic syndrome (MetS) is composed of multiple conditions that are also risk factors for cardiovascular disease and diabetes. We try to discuss gender-specific differences in Klotho and the associations between Klotho and MetS components.

Materials and methods: The National Health and Nutrition Examination Survey database from cycle 2015-2016 was analyzed. MetS was defined according to the 2005 updated criteria by the American Heart Association and National Heart Lung and Blood Institute. Gender-specific differences in serum Klotho, and associations between Klotho level and MetS components were examined.

Results: A total of 2475 participants (40-79 years old) with comprehensive data were included (52% women). In general, lower Klotho was associated with advanced age, male sex, tobacco use, elevated triglycerides, renal insufficiency, inflammation, low estradiol, and low sex hormone-binding globulin (SHBG). The correlation between MetS and Klotho was more obvious in women, mainly in waist circumference and triglyceride. There were no gender-specific differences in the associations between Klotho and renal dysfunction, but multivariate linear regression analysis showed gender differences in other factors associated with Klotho. Estradiol, SHBG, high-density lipoprotein cholesterol (HDL), and high-sensitivity C-reactive protein (CRP) were associated with Klotho levels independent of age and renal function in men, whereas in women, Klotho was independently associated with triglycerides and white blood cell count.

Conclusion: Klotho levels had gender disparities regardless of age, renal function, and sex hormones. In the current cohort, triglycerides were the major component of MetS that was independently associated with serum Klotho levels, and the association was particularly seen in women. However, HDL was found to be the male-specific MetS component independently associated with Klotho.

Background: Diabetes Mellitus is a major predictor for severity and mortality that is increased by 50% in COVID-19 infection. The aim of this study is to estimate the prevalence of new-onset DM among patients with COVID-19 and examined the short clinical outcomes of the disease.

Method: This is a retrospective study of revising electronic medical records to assess the prevalence of new-onset DM in COVID-19 patients and its impact on the severity of the disease. Adult patients with confirmed COVID-19 during the period from June 2020 to December 2021 were enrolled.

Results: 725 patients were included. 53.8% of them were males and 46.2 were females, the mean age was 43.35 ± 16.76. 13.2% were diabetics; 2.2% with preexisting DM and 11.0% had new-onset DM. 6.34% had coexisting medical conditions. DKA at presentation was observed in 6 patients (0.8%) of newly diagnosed DM. There is a significant correlation between age and family history (FH), and BMI and new-onset DM (P < 0.05). The overall mortality rate was 2.2%, and it was significantly higher in diabetics in comparison to non-diabetics (P < 0.001). 8.6% had persistent hyperglycemia after 4 months of follow-up.

Conclusion: The prevalence of COVID-19 related new-onset DM was correlated significantly with disease severity and mortality rate. Age, FH, and BMI, were the major predictors. We recommend that frequent monitoring of blood glucose for patients with COVID-19 infections to detect DM, therefore, prompt treatment can be initiated.

Objective: The primary objective of this study was to investigate the risk factors for diabetic peripheral neuropathy (DPN) and to establish an early diagnostic prediction model for its onset, based on clinical data and biochemical indices.

Methods: Retrospective data were collected from 1,446 diabetic patients at the First Affiliated Hospital of Anhui University of Chinese Medicine and were split into training and internal validation sets in a 7:3 ratio. Additionally, 360 diabetic patients from the Second Affiliated Hospital were used as an external validation cohort. Feature selection was conducted within the training set, where univariate logistic regression identified variables with a p-value < 0.05, followed by backward elimination to construct the logistic regression model. Concurrently, the random forest algorithm was applied to the training set to identify the top 10 most important features, with hyperparameter optimization performed via grid search combined with cross-validation. Model performance was evaluated using ROC curves, decision curve analysis, and calibration curves. Model fit was assessed using the Hosmer-Lemeshow test, followed by Brier Score evaluation for the random forest model. Ten-fold cross-validation was employed for further validation, and SHAP analysis was conducted to enhance model interpretability.

Results: A nomogram model was developed using logistic regression with key features: limb numbness, limb pain, diabetic retinopathy, diabetic kidney disease, urinary protein, diastolic blood pressure, white blood cell count, HbA1c, and high-density lipoprotein cholesterol. The model achieved AUCs of 0.91, 0.88, and 0.88 for the training, validation, and test sets, respectively, with a mean AUC of 0.902 across 10-fold cross-validation. Hosmer-Lemeshow test results showed p-values of 0.595, 0.418, and 0.126 for the training, validation, and test sets, respectively. The random forest model demonstrated AUCs of 0.95, 0.88, and 0.88 for the training, validation, and test sets, respectively, with a mean AUC of 0.886 across 10-fold cross-validation. The Brier score indicates a good calibration level, with values of 0.104, 0.143, and 0.142 for the training, validation, and test sets, respectively.

Conclusion: The developed nomogram exhibits promise as an effective tool for the diagnosis of diabetic peripheral neuropathy in clinical settings.

Background/aim: In the current study, we aimed to assess the association of carbohydrate quality index (CQI) with the risk of non-alcoholic fatty liver disease (NAFLD) in Iranian adults.

Methods: This case-control study was conducted on 225 newly diagnosed NAFLD patients and 450 controls, aged 20-60 years. A food frequency questionnaire was used to calculate the CQI and its components, including fiber intake, glycemic index, whole grains: total grains ratio, and solid carbohydrates: total carbohydrates ratio. Multivariable logistic regression was used to estimate the odds ratio (OR) of NAFLD across the tertile of CQI and its components.

Results: The participant's mean ± SD of body mass index and age were 26.8 ± 4.3 kg/m² and 38.1 ± 8.8 years, respectively. The median (interquartile) CQI score in participants of the case and control groups was 20 (15-25) and 23 (18-28), respectively. In the multivariable-adjusted model, the risk of NAFLD decreased significantly across the tertiles of the CQI [(OR: 0.20; %95CI: 0.11-0.39), P_trend <0.001)]. Also, the odds of NAFLD decreased across tertiles of solid carbohydrates to total carbohydrates ratio [(OR: 0.39; 95%CI: 0.22-0.69), P_trend <0.001)]. However, a high dietary glycemic index (GI) was associated with increased odds of NAFLD [(OR:7.47; 95%CI: 3.89-14.33, P_trend<0.001)]. There was no significant relationship between other CQI components, including fiber intake and whole grain/total grains and the risk of NAFLD.

Conclusions: Our results revealed that a diet with a high quality of carbohydrates, characterized by higher intakes of solid carbohydrates, whole grain, and low GI carbohydrates, can be related to a reduced risk of NAFLD.