Endocrine Practice最新文献

Background: Copeptin stimulation tests can be used in the differential diagnosis of polyuria polydipsia syndrome. Current stimulation methods rely on intravenous or subcutaneous administration. Oral stimulus can further simplify the diagnostic approach. The levodopa stimulation test is widely used in the evaluation of growth hormone deficiency (GHD), and the dopamine pathway was reported to be associated with arginine vasopressin secretion. The study aimed to investigate the effect of oral levodopa on copeptin secretion.

Methods: The study was a prospective observational single-center cohort study. Patients < 18 years old with short stature and no symptoms of polyuria or polydipsia undergoing levodopa stimulation test for suspected GHD were recruited from May 2023 to Nov 2023. Copeptin and growth hormone (GH) were measured at 0, 30, 60, 90, and 120min in the levodopa test. The insulin tolerance test with copeptin and GH measured at the same time points was conducted in part of patients.

Results: Forty-four participants were included in the final analysis. In the levodopa stimulation test, the median (interquartile range, IQR) copeptin concentration increased from 5.20 (3.51, 8.25) pmol/L to maximum 19.36 (8.97, 108.08) pmol/L (P < 0.001), 3.94 (1.41, 13.88) times of the baseline (P < 0.001). Compared with insulin tolerance test, peak copeptin in the levodopa test was significantly higher (34.61 (13.67, 98.96) vs 8.88 (7.14, 15.42) pmol/L, P = 0.009). Higher copeptin was associated with larger dose of levodopa.

Conclusions: Oral levodopa could be used to stimulate copeptin.

Objective: To evaluate the effects of teprotumumab on ophthalmological and biochemical findings and assess potential genetic markers for TED responses.

Methods: This is a retrospective study. Participants were 18-76 years old. All subjects were treated with teprotumumab. The primary outcome was the change in proptosis before and after teprotumumab treatment. Secondary outcomes include change in other ophthalmic measures and thyroid laboratory tests. Human leukocyte antigens (HLA) were also analyzed as markers for response to teprotumumab.

Results: Twenty-six patients were included in the final analysis. There was a significant decrease in TSI and TRAb levels and significant increases in HbA1c, fasting glucose, and total T3 levels. There was also significant reduction in proptosis, clinical activity score (CAS), retinal nerve fiber layer (RNFL) thickness, ganglion cell thickness (GCA), and intraocular pressure (IOP). HLA haplotypes were distinct between responders and non-responders, with HLA-DRB3*02:02:01G, HLA-DRB4*neg, and HLA-DQB1*02:01:01G demonstrating better response to teprotumumab and HLA-A*23:01:01G strongly correlating to non-response.

Conclusions: Patients with both acute and chronic TED treated with teprotumumab had a significant reduction in TSI and TRAb levels and improvement in proptosis, CAS, RNFL and GCA thickness, and IOP. HLA may predict responders vs. non-responders. Further studies with longer duration and larger population comparing teprotumumab with steroids or other immunomodulatory agents (tocilizumab, rituximab, etc) may be helpful.

Objectives: To evaluate the efficacy of combining predictive artificial intelligence (AI) and image similarity model to risk stratify thyroid nodules, using retrospective external validation study.

Methods: Two datasets were used to determine efficacy of the AI application. One was Stanford dataset ultrasound images of 192 nodules between April 2017 to May 2018 and the second was private practice consisting of 118 thyroid nodule images between January 2018 to December 2023. The nodules had definitive diagnosis by cytology or surgical pathology. The AI application was used to predict the diagnosis and American College of Radiology Thyroid Imaging and Data System (ACR TI-RADS) score.

Results: In the Stanford dataset, the AI application predicted malignancies with sensitivity of 1.0 and specificity of 0.55. Positive predictive value (PPV) was 0.18 and negative predictive value (NPV) was 1.0. The Area Under the Curve - Receiver Operating Characteristic (AUC-ROC) was 0.78. ACR TI-RADS based clinical recommendation had a polychoric correlation of 0.67. In the private dataset, the AI application predicted malignancies with sensitivity of 0.91 and specificity of 0.95. PPV was 0.8 and NPV was 0.98. AUC-ROC was 0.93 and accuracy was 0.94. ACR TI-RADS based score had a polychoric correlation of 0.94.

Conclusion: The AI application showed good performance for sensitivity and NPV between the two datasets and demonstrated potential for 61.5% reduction in the need for fine needle aspiration (FNA) and strong correlation to ACR TI-RADS. However, PPV was variable between the datasets possibly from variability in image selection and prevalence of malignancy. If implemented widely and consistently among various clinical settings, this could lead to decreased patient burden associated with an invasive procedure and possibly to decreased health care spending.

Background: We examined the association of objective measures of cardiometabolic risk with progression to a high-risk for advanced fibrosis in patients with metabolic dysfunction-associated steatotic liver disease (MASLD) at initially low- and indeterminate-risk for advanced fibrosis.

Methods: We performed a retrospective cohort study of primary care patients with MASLD between 2012 and 2021. We evaluated patients with MASLD and low- or indeterminate-risk Fibrosis-4 Index (FIB-4) scores and followed them until the outcome of a high-risk FIB-4 (≥2.67), or the end of the study period. Exposures of interest were body mass index, systolic blood pressure, hemoglobin A1c, cholesterol, estimated glomerular filtration rate, and smoking status. Variables were categorized by the threshold for primary care therapy intensification. Unadjusted and adjusted Cox regression models were developed for the outcome of time to a high-risk FIB-4 value.

Results: The cohort included 1347 patients with a mean follow-up of 3.6 years (SD 2.7). Of the cohort, 258 (19%) had a subsequent FIB-4 > 2.67. In the fully adjusted Cox regression models, mean systolic blood pressure ≥ 150 mm Hg (1.57; 95% confidence interval (CI) 1.02-2.41) and glomerular filtration rate ≤ 59 ml/min (hazard ratio 2.78; 95%CI 2.17-3.58) were associated with an increased hazard of a high-risk FIB-4, while receiving a statin prescription (hazard ratio 0.51; 95%CI 0.39-0.66) was associated with a lower risk.

Conclusions: Nearly 1 in 5 primary care patients with MASLD transitioned to a high-risk FIB-4 score during 3.6 years of follow-up, and uncontrolled blood pressure and reduced kidney function were associated with an increased hazard of a FIB-4 at high-risk for advanced fibrosis.

Objective: As the population of older adults in the United States continues to rise, understanding modifiable risk factors that contribute to cognitive decline and dementia becomes increasingly important. This narrative review summarizes existing literature on the association between thyroid function in the euthyroid range, hypothyroidism and hyperthyroidism, and cognitive outcomes in older adults.

Methods: A comprehensive literature search of the PubMed and Ovid/Medline databases was conducted. Randomized controlled trials, systematic reviews, meta-analyses, and observational studies published in English between January 2000 and December 2023 were included.

Results: Overall, existing studies yielded conflicting results, failing to delineate a concrete relationship between thyroid function and cognitive outcomes and/or dementia in older adults. There may be a possible association between higher thyroid stimulating hormone in the reference range and lower risk of incident dementia, which may be more pronounced in women. Majority of studies elucidated a possible association between low thyroid stimulating hormone and incident dementia, with suggestion that duration of hyperthyroidism may contribute to increasing dementia risk. Even though evidence on the association of hypothyroidism and cognitive decline are disparate, current data do not support treatment of subclinical hypothyroidism to improve cognitive outcomes in older adults.

Conclusion: Despite numerous studies, there is no conclusive evidence that supports a direct relationship between hyperthyroidism or hypothyroidism and cognitive decline. Study limitations include heterogeneity in study designs, measurement methodologies, and cognitive assessment tools. Future research is needed to better delineate whether an association exists and whether treatment of thyroid dysfunction ameliorates cognitive impairment.

Objective: Metformin is clinically effective in treating polycystic ovary syndrome (PCOS) with insulin resistance (IR), while its efficacy varies among individuals. This study aims to develop a machine learning model to predict the efficacy of metformin in improving insulin sensitivity among women with PCOS and IR.

Methods: This is a retrospective analysis of a multicenter, randomized controlled trial involving 114 women diagnosed with PCOS and IR. All women received metformin treatment for 4 months. We incorporated 27 baseline clinical variables of the women into the construction of our machine learning model. We firstly compared 4 commonly used feature selection methods to screen valuable clinical variables. Then we used the valuable variables as inputs to evaluate the performance of 5 machine learning models, including k-Nearest Neighbors, Support Vector Machine, Logistic Regression, Random Forest, and Extreme Gradient Boosting, in predicting the efficacy of metformin.

Results: Among the 5 machine learning models, Support Vector Machine performed the best with an area under the receiver operating characteristic curve of 0.781 (95% confidence interval [CI]: 0.772-0.791). The key predictive variables identified were homeostasis model assessment of insulin resistance, body mass index, and low-density lipoprotein cholesterol.

Conclusion: The developed machine learning model could be applied to predict the efficacy of metformin in improving insulin sensitivity among women with PCOS and IR. The result could help doctors evaluate the efficacy of metformin in advance, optimize treatment plans, and thereby enhance overall clinical outcomes.

Objective: This white paper provides practical guidance for clinicians encountering bilateral adrenal masses.

Methods: A case-based approach to the evaluation and management of bilateral adrenal masses. Specific clinical scenarios presented here include cases of bilateral adrenal adenomas, hemorrhage, pheochromocytomas, metastatic disease, myelolipomas, as well as primary bilateral macronodular adrenal hyperplasia.

Results: Bilateral adrenal masses represent approximately 10% to 20% of incidentally discovered adrenal masses. The general approach to the evaluation and management of bilateral adrenal masses follows the same protocol as the evaluation of unilateral adrenal masses, determined based on the patient's clinical history and examination as well as the imaging characteristics of each lesion, whether the lesions could represent a malignancy, demonstrate hormone excess, or possibly represent a familial syndrome. Furthermore, there are features unique to bilateral adrenal masses that must be considered, including the differential diagnosis, the evaluation, and the management depending on the etiology. Therefore, considerations for the optimal imaging modality, treatment (medical vs surgical therapy), and surveillance are included. These recommendations were developed through careful examination of existing published studies as well as expert clinical opinion consensus.

Conclusion: The evaluation and management of bilateral adrenal masses require a comprehensive systematic approach which includes the assessment and interpretation of the patient's clinical history, physical examination, dynamic hormone evaluation, and imaging modalities to determine the key radiographic features of each adrenal nodule. In addition, familial syndromes should be considered. Any final treatment options and approaches should always be considered individually.