Experimental and Clinical Endocrinology & Diabetes最新文献

Objectives To investigate the association between liver fibrosis score and diabetic kidney disease (DKD) in type 2 diabetes mellitus (T2DM).

Methods A total of 897 hospitalized patients with T2DM were included in this study. Each patient completed DKD screening. Logistic regression analysis was used to assess the predictive value of non-alcoholic fatty liver disease fibrosis score (NAFLD-FS) and fibrosis-4 (FIB-4) for the occurrence of DKD and risk for DKD progression, respectively.

Results The prevalence of DKD and risk for its progression significantly increased with increasing NAFLD-FS risk category. DKD prevalence also increased with increasing FIB-4 risk category. Multivariate logistic regression analysis showed that the “high-risk” NAFLD-FS had a significantly higher risk of DKD (odds ratio [OR]: 1.89, 95% confidence interval [CI]: 1.16–3.08) and risk for DKD progression (OR: 2.88, 95% CI: 1.23–6.78), and the “intermediate-risk” FIB-4 had a significantly higher risk of DKD (OR: 1.41, 95% CI: 1.00–1.98). Subgroup analysis showed that the association between NAFLD-FS and FIB-4 and DKD was significant in the female subgroup, whereas the association between the “high-risk” NAFLD-FS and risk for DKD progression was significant in the male subgroup.

Conclusions NAFLD-FS and FIB-4 are strongly associated with DKD and risk for DKD progression in patients with T2DM. Additionally, sexual dimorphism exists in this association.

Aim: To evaluate the effects of aerobic training on hippocampal volume and cognitive function in patients with type 2 diabetes mellitus (T2DM) with normal cognition.

Materials and methods: One hundred patients with T2DM aged 60-75 years who met inclusion criteria were randomized into the aerobic training group (n=50) and control group (n=50). The aerobic training group received 1 year of aerobic training, while the control group maintained their lifestyle without additional exercise intervention. The primary outcomes were hippocampal volume measured by MRI and Mini-mental State Examination (MMSE) score or Montreal Cognitive Assessment scale (MoCA) scores.

Results: Eighty-two participants completed the study (aerobic training group, n=40; control group, n=42). There was no significant difference between the two groups at baseline (P>0.05). After one year of moderate aerobic training, increase in total and right hippocampal volume in the aerobic training group were significantly higher than in the control group (P=0.027, P=0.043, respectively). In the aerobic group, total hippocampal volume significantly increased after the intervention compared with baseline (P=0.034). The between-group difference in the change of MMSE and MoCA scores was statistically significant (P=0.015, P=0.027, respectively). Logistic regression showed strong correlations between aerobic training and increase in total hippocampal volume (OR:1.091, [95%CI 0.969, 1.228], P=0.002), improvement of MMSE scores (OR:1.127, [95%CI 1.005, 1.263], P=0.041) or MoCA scores (OR:2.564, [95%CI 2.098.2.973], P=0.045).

Conclusions: One-year moderate aerobic training increased total and right hippocampal volume and protected cognitive function for T2DM patients with normal cognition. Early intervention focusing on cognition protection should be considered for T2DM patients in clinical settings.

Aim: This study investigated the effects of insulin glargine and exenatide on the muscle mass of patients with newly diagnosed type 2 diabetes (T2DM) and nonalcoholic fatty liver disease (NAFLD).

Methods: We performed a post-hoc analysis of our previously study, a 24-week randomized controlled multicenter clinical trial (ClinicalTrials.gov, NCT02303730). Seventy-six patients were randomly assigned 1:1 to receive insulin glargine or exenatide treatment. The changes in psoas muscle area (PMA) (mm²) were obtained with the cross-sectional Dixonfat magnetic resonance images at the fourth lumber vertebra.

Results: There were no significant differences in age, BMI, gender, and PMA in insulin glargine and exenatide groups at baseline. After treatment, PMA tended to increase by 13.13 (-215.52, 280.80) mm² in the insulin glargine group and decrease by 149.09 (322.90-56.39) mm² in the exenatide group (both p>0.05). Subgroup analysis showed a 560.64 (77.88, 1043.40) (mm²) increase of PMA in the insulin group relative to the Exenatide group in patients with BMI<28 kg/m² (p0.031) after adjusting for gender, age, and research center. Interaction analysis showed an interaction between BMI and treatment (p0.009). However, no interaction was observed among subgroups with a BMI≥28 kg/m² or with different genders and ages.

Conclusion: Compared to exenatide, insulin glargine can relativity increase PMA in patients with T2DM having BMI<28 kg/m² and NAFLD.

Introduction: The current ultrasound scan classification system for thyroid nodules is time-consuming, labor-intensive, and subjective. Artificial intelligence (AI) has been shown to increase the accuracy of predicting the malignancy rate of thyroid nodules. This study aims to demonstrate the state-of-the-art Swin Transformer to classify thyroid nodules.

Materials and methods: Ultrasound images were collected prospectively from patients who received fine needle aspiration biopsy for thyroid nodules from January 2016 to June 2021. One hundred thirty-nine patients with malignant thyroid nodules were enrolled, while 235 patients with benign nodules served as controls. Images were fed to Swin-T and ResNeSt50 models to classify the thyroid nodules.

Results: Patients with malignant nodules were younger and more likely male compared to those with benign nodules. The average sensitivity and specificity of Swin-T were 82.46% and 84.29%, respectively. The average sensitivity and specificity of ResNeSt50 were 72.51% and 77.14%, respectively. Receiver operating characteristics analysis revealed that the area under the curve of Swin-T was higher (AUC=0.91) than that of ResNeSt50 (AUC=0.82). The McNemar test evaluating the performance of these models showed that Swin-T had significantly better performance than ResNeSt50.Swin-T classifier can be a useful tool in helping shared decision-making between physicians and patients with thyroid nodules, particularly in those with high-risk characteristics of sonographic patterns.

Idiopathic isolated adrenocorticotrophic hormone deficiency (IIAD) is rare, with high clinical omission and misdiagnosis rates. This study retrospectively collected information on clinical presentation, laboratory findings, and treatment response of 17 patients with IIAD at Jining No. 1 People's Hospital from January 2014 to December 2022. The clinical characteristics were summarized, and the pertinent data were analyzed. As a result, most of the patients with IIAD were male (94.12%), with age at onset ranging from 13 to 80 years. The primary manifestations were anorexia (88.24%), nausea (70.59%), vomiting (47.06%), fatigue (64.71%), and neurological or psychiatric symptoms (88.24%). The median time to diagnosis was 2 months and the longest was 10 years. Laboratory tests mostly showed hyponatremia (88.24%) and hypoglycemia (70.59%). The symptoms and laboratory indicators returned to normal after supplementing patients with glucocorticoids. IIAD has an insidious onset and atypical symptoms; it was often misdiagnosed as gastrointestinal, neurological, or psychiatric disease. The aim of this study was to improve clinicians' understanding of IIAD, patients with unexplained gastrointestinal symptoms, neurological and psychiatric symptoms, hyponatremia, or hypoglycemia should be evaluated for IIAD and ensure early diagnosis and treatment.

Objective: Adrenal tumors are generally rare in children and can be a part of familial cancer syndrome. This research was conducted to examine the clinical outcomes, histopathological results, and genetic etiologies of adrenal tumors in children and adolescents.

Methods: Thirty-one children and adolescents with adrenal tumors were included. Data on clinical outcomes and endocrine and radiologic results were retrospectively analyzed. Molecular analysis was conducted in select patients according to their phenotype and family history.

Results: The median age at diagnosis was 7.9 years (range: 0.8-17.8 years) with 5.1±1.8 cm of maximum tumor diameter. Adrenal adenoma (n=7), carcinoma (n=5), borderline (n=2), isolated micronodular adrenocortical disease (n=2), pheochromocytoma (n=8), paraganglioma (n=3), and ganglioneuroma (n=4) are all pathological diagnoses. The most common presenting symptom was excess production of adrenocortical hormones (n=15), including virilization and Cushing syndrome. Non-functioning adrenocortical tumors were found in a patient with congenital adrenal hyperplasia. Genetic etiologies were identified in TP53 (n=5), VHL (n=4), and PRKACA (n=1). Patients with mutations in TP53 were young (1.5±0.5 years) and had large masses (6.1±2.3 cm).

Conclusions: This study describes clinical outcomes and the pathological spectrum of adrenal tumors in children and adolescents. Adrenocortical tumors mostly presented with an excess of the adrenocortical hormone. Patients with genetic defects presented at a young age and large size of tumors, necessitating genetic testing in patients at a young age.

Background: The present study aimed to identify individuals with different personalities using latent class analysis and further distinguish those with a high risk of diabetes among different clusters.

Methods: Data were utilized from a large-scale, cross-sectional epidemiological survey conducted in 2018 across 23 provinces in China, employing a multi-stage, stratified sampling technique. Latent class cluster analysis was performed to identify distinct personality clusters based on a series of variables concerning life attitudes. Logistic regression was used to calculate adjusted odds ratios (AORs) after controlling for potential confounding variables, including age, gender, body mass index, smoking status, alcohol consumption, hypertension, and physical activity levels, to determine the association between these groups and diabetes.

Results: Four distinct personality clusters were identified, namely the energy-poor (2.0%), self-domination (61.3%), optimistic (21.3%), and irritable (15.4%) groups. The prevalence of diabetes in these groups was 14.6%, 9.7%, 9.3%, and 11.6%, respectively. After adjusting for potential confounders, the "energy-poor group" exhibited more odds of having diabetes as compared to the "optimistic group" (AOR 1.683, 95%CI: 1.052-2.693; P=0.030).

Conclusion: This study identified an energy-poor group of individuals with a high risk of diabetes. Targeted interventions should consider the emotional and personality characteristics of the elderly.

Background: We previously published an algorithm predicting 24 h basal insulin infusion profiles in insulin pump-treated subjects with type 1 diabetes profiles from six subject characteristics. This algorithm was to be externally validated in an independent environment and patient population.

Methods: Thirty-two patients with pump-treated type diabetes were switched to their individually algorithm-derived basal insulin infusion profile, and the appropriateness of fasting glycemic control was scrutinized by means of a supervised 24 h fast. Primary endpoint was appropriate fasting glycemic control according to pre-defined criteria in at least 80% of the cohort.

Results: In 24 out of 32 patients switching to the algorithm-derived basal insulin infusion rate and undergoing a 24-h fasting period, appropriate glycemic control was achieved (=75%, lower than the pre-defined threshold of 80%), two patients discontinued the fast due to hyperglycemia, and six finished the fasting period, however, with inappropriate fasting glycemic control (entirely due to hyperglycemic episodes). There were no obvious differences in baseline characteristics between those with appropriate vs. inappropriate fasting glycemic control on the basal insulin infusion rate provided by the algorithm.

Conclusion: In conclusion, when testing fasting glycemic control with an algorithm-derived individual basal insulin infusion profile during a 24 h fasting period in a cohort unrelated in terms of the hospital environment and catchment area, the success rate was lower than a pre-defined threshold for concluding utility of this algorithm. Therefore, applying this algorithm in order to initiate or optimize basal insulin infusion profiles in type 1 diabetes cannot be generally recommended.

Aims: Transition from pediatric to adult care is difficult for patients with chronic diseases. In this study, factors associated with metabolic control in childhood-onset type 1 diabetes (T1D) after transfer to adult care were analyzed.

Methods: Overall, 224 persons with T1D were contacted yearly from 1998 to 2019. They voluntarily answered a questionnaire about their current hemoglobin A1c (HbA1c) levels, diabetes-associated complications, kind of care, living conditions, and family situation. Then, mixed longitudinal-cross-sectional analyses were carried out.

Results: Overall, 190 patients answered at least once (mean age: 26.6 years). Diabetes complications were mentioned by 10 patients (5 microalbuminuria, 5 retinopathy). Most patients (92.6%) were in diabetes-specific care during the first year after transfer, with a trend to leave diabetes-specific care during the observation period. Patients in diabetes-specific care displayed lower HbA1c levels (%/mmol/mol) (7.1/54 vs. 7.5/58). An important predictor for HbA1c after transfer was HbA1c during the year before transfer (r=0.67, p <0.001). Patients living alone showed no difference in HbA1c levels from those living with their parents. Married patients had lower HbA1c levels (7.0/53 vs. 7.3/56, p<0.05) than unmarried ones. Patients with children (15.8%) presented lower HbA1c levels (6.9/52 vs. 7.3/56, p <0.01) than those without.

Conclusions: Good metabolic results are favored in patients followed-up in specialized care, are married, and are parents. We recommend transfer to a diabetologist with experience in T1D at an individual age.