Hasil untuk "Diseases of the endocrine glands. Clinical endocrinology"

Wen Lou, Adrián A. Díaz-Faes, Jiangen He et al.

Clinical trials shape medical evidence and determine who gains access to experimental therapies. Whether participation in these trials reflects the global burden of disease remains unclear. Here we analyze participation inequality across more than 62,000 randomized controlled trials spanning 16 major disease categories from 2000 to 2024. Linking 36.8 million trial participants to country-level disease burden, we show that global inequality in clinical trials participation is overwhelmingly shaped by country rather than disease burden. Country-level factors explain over 90% of variation in participation, whereas disease-specific effects contribute only marginally. Removing entire disease categories-including those traditionally considered underfunded-has little effect on overall inequality. Instead, participation is highly concentrated geographically, with a small group of countries enrolling a disproportionate share of participants across nearly all diseases. These patterns have persisted despite decades of disease-targeted funding and increasing alignment between research attention and disease burden within diseases. Our findings indicate that disease-vertical strategies alone cannot correct participation inequality. Reducing global inequities in clinical research requires horizontal investments in research capacity, health infrastructure, and governance that operate across disease domains.

Mujeeb Ur Rehman, Imran Rehan, Sohail Khalid

Identifying type 2 diabetes mellitus can be challenging, particularly for primary care physicians. Clinical decision support systems incorporating artificial intelligence (AI-CDSS) can assist medical professionals in diagnosing type 2 diabetes with high accuracy. This study aimed to assess an AI-CDSS specifically developed for the diagnosis of type 2 diabetes by employing a hybrid approach that integrates expert-driven insights with machine learning techniques. The AI-CDSS was developed (training dataset: n = 650) and tested (test dataset: n = 648) using a dataset of 1298 patients with and without type 2 diabetes. To generate predictions, the algorithm utilized key features such as body mass index, plasma fasting glucose, and hemoglobin A1C. Furthermore, a clinical pilot study involving 105 patients was conducted to assess the diagnostic accuracy of the system in comparison to non-endocrinology specialists. The AI-CDSS showed a high degree of accuracy, with 99.8% accuracy in predicting diabetes, 99.3% in predicting prediabetes, 99.2% in identifying at-risk individuals, and 98.8% in predicting no diabetes. The test dataset revealed a 98.8% agreement between endocrinology specialists and the AI-CDSS. Type 2 diabetes was identified in 45% of 105 individuals in the pilot study. Compared with diabetes specialists, the AI-CDSS scored a 98.5% concordance rate, greatly exceeding that of nonendocrinology specialists, who had an 85% agreement rate. These findings indicate that the AI-CDSS has the potential to be a useful tool for accurately identifying type 2 diabetes, especially in situations in which diabetes specialists are not readily available.

Tanja Maier, Laura-Sophie Landwehr, Alexandra Triebig et al.

BackgroundIn advanced adrenocortical carcinoma (ACC), the response rate to immune checkpoint inhibition (ICI) is only ~15%. Glucocorticoid (GC) secretion and the activation of the Wnt/β-catenin pathway have been suggested to contribute to low tumour immune cell infiltration. The transcription factor lymphoid enhancer factor 1 (LEF-1) transduces β-catenin (CTNNB1)-mediated transcriptional activation.ObjectiveTo understand the contribution of Wnt/β-catenin pathway activation and glucocorticoid receptor (GR) signalling to the immunologically cold ACC tumour microenvironment.MethodsSemi-quantitative immunohistochemistry (IHC) of β-catenin (CTNNB1), LEF-1, GR and T cell markers CD3, CD4, CD8, Fox P3 in 59 ACC samples. Targeted RNA expression analysis of 354 immune-related genes in 58 additional ACC tissue specimens. Correlative analyses with clinical data.ResultsNuclear LEF-1 and CTNNB1 protein expression were positively correlated in ACC tissue (Pearson R2 = 0.1283, p=0.0046). High, moderate and low protein expression was detected in 24.1%, 53.2% and 19.3% of samples for LEF-1, and 30.6%, 43.5% and 19.3% for CTNNB1, respectively. We found higher LEF-1 expression in GC-secreting tumours which did not differ from inactive tumours in terms of GR expression. T cell markers, as evaluated by IHC, were not associated with expression of Wnt/β-catenin pathway markers. At RNA level, tumours with high LEF-1 expression showed significant downregulation of 37 transcripts (including 8 involved in antigen presentation). High LEF-1 expression levels correlated with worse overall survival in this cohort. This was not the case for CTNNB1 and GR.ConclusionLef-1 expression is useful as a biomarker of activated Wnt/β-catenin signalling in ACC. Wnt/β-catenin pathway activation was not associated with reduced immune cell markers in ACC but GC secretion and may be related to tumoural antigen presentation.

Hung‐Chun Chen, Yi‐Hsuan Lai, Yi‐Der Jiang

ABSTRACT Recent updates on the efficacy of continuous glucose monitoring (CGM) and a critical examination of the current challenges in its implementation were summarized. The barriers to widespread adoption of this technology should be addressed, considering the impact of different cultural contexts. The strategies to overcome these obstacles and the benefits of CGM for future glucose management will be discussed.

Shaheer Ahmad Khan, Muhammad Usamah Shahid, Ahmad Abdullah et al.

This study addresses a critical gap in the healthcare system by developing a clinically meaningful, practical, and explainable disease surveillance system for multiple chronic diseases, utilizing routine EHR data from multiple U.S. practices integrated with CureMD's EMR/EHR system. Unlike traditional systems--using AI models that rely on features from patients' labs--our approach focuses on routinely available data, such as medical history, vitals, diagnoses, and medications, to preemptively assess the risks of chronic diseases in the next year. We trained three distinct models for each chronic disease: prediction models that forecast the risk of a disease 3, 6, and 12 months before a potential diagnosis. We developed Random Forest models, which were internally validated using F1 scores and AUROC as performance metrics and further evaluated by a panel of expert physicians for clinical relevance based on inferences grounded in medical knowledge. Additionally, we discuss our implementation of integrating these models into a practical EMR system. Beyond using Shapley attributes and surrogate models for explainability, we also introduce a new rule-engineering framework to enhance the intrinsic explainability of Random Forests.

Abdullah Al Shafi, Rowzatul Zannat, Abdul Muntakim et al.

Disease-symptom datasets are significant and in demand for medical research, disease diagnosis, clinical decision-making, and AI-driven health management applications. These datasets help identify symptom patterns associated with specific diseases, thus improving diagnostic accuracy and enabling early detection. The dataset presented in this study systematically compiles disease-symptom relationships from various online sources, medical literature, and publicly available health databases. The data was gathered through analyzing peer-reviewed medical articles, clinical case studies, and disease-symptom association reports. Only the verified medical sources were included in the dataset, while those from non-peer-reviewed and anecdotal sources were excluded. The dataset is structured in a tabular format, where the first column represents diseases, and the remaining columns represent symptoms. Each symptom cell contains a binary value, indicating whether a symptom is associated with a disease. Thereby, this structured representation makes the dataset very useful for a wide range of applications, including machine learning-based disease prediction, clinical decision support systems, and epidemiological studies. Although there are some advancements in the field of disease-symptom datasets, there is a significant gap in structured datasets for the Bangla language. This dataset aims to bridge that gap by facilitating the development of multilingual medical informatics tools and improving disease prediction models for underrepresented linguistic communities. Further developments should include region-specific diseases and further fine-tuning of symptom associations for better diagnostic performance

Yu Feng Shang, Yi Yang Shen, Meng Chen Zhang et al.

The production and secretion of saliva is an essential function of the salivary glands. Saliva is a complicated liquid with different functions, including moistening, digestion, mineralization, lubrication, and mucosal protection. This review focuses on the mechanism and neural regulation of salivary secretion, and saliva is secreted in response to various stimuli, including odor, taste, vision, and mastication. The chemical and physical properties of saliva change dynamically during physiological and pathophysiological processes. Moreover, the central nervous system modulates salivary secretion and function via various neurotransmitters and neuroreceptors. Smell, vision, and taste have been investigated for the connection between salivation and brain function. The immune and endocrine functions of the salivary glands have been explored recently. Salivary glands play an essential role in innate and adaptive immunity and protection. Various immune cells such as B cells, T cells, macrophages, and dendritic cells, as well as immunoglobins like IgA and IgG have been found in salivary glands. Evidence supports the synthesis of corticosterone, testosterone, and melatonin in salivary glands. Saliva contains many potential biomarkers derived from epithelial cells, gingival crevicular fluid, and serum. High level of matrix metalloproteinases and cytokines are potential markers for oral carcinoma, infectious disease in the oral cavity, and systemic disease. Further research is required to monitor and predict potential salivary biomarkers for health and disease in clinical practice and precision medicine.

Kehao Le, Lei Jin, Fangfang Zhong et al.

PurposeTo assess tumor growth using tumor doubling rate (TDR) during active surveillance (AS) in China.MethodsBetween January 2016 and June 2020, a total of 219 patients with low-risk papillary thyroid microcarcinoma (PTMC) (aged 23-75 years) were consecutively enrolled in the AS program.ResultsFour sections of TDR, >0.5, 0.1~0.5, -0.1~0.1 and <-0.1, corresponded with four categories of tumor volume kinetics: rapid growth, slow growth, stable, and decreased size. We found that 10.5% of PTMCs exhibited rapid growth, 33.33% exhibited slow growth, 26.48% were stable, and 29.68% decreased in size. Tumor growth was associated with two factors: age and volume of PTMC at diagnosis. 85.72% of elderly patients (≥ 61 years old) had tumors that remained stable or even shrank and rapidly growing tumors were not found in them. When the volume was small (≤14.13 mm3), the proportion of rapid growth was high (41.67%), whereas when the volume was large (> 179.5 mm3), the proportion of non-growth was 68.75%.ConclusionTDR may be a better metric for evaluating tumor growth in observational PTMCs. A certain proportion of PTMCs grow during the period of AS and tumor growth was associated with age and volume of PTMC at initial diagnosis. Therefore, how to block tumor growth during the AS period, especially for young patients and patients with early-stage PTMC (size ≤ 5 mm), will be a new challenge.

Yash V. Chauhan, Mahesh D. Hakke, Prudwiraj Sanamandra et al.

Introduction: The effect and mechanism of skipping breakfast on glycemic control in type 2 diabetes mellitus (T2DM) in Asian-Indians is unknown. Methods: Cross-over, within-group study recruiting 5 habitual breakfast eaters (BE) and 5 habitual breakfast skippers (BS) with uncontrolled T2DM (HbA1c 7-9%). Patients underwent testing after three days of following their usual breakfast habits and after seven days of crossing over to the other arm. Fasting values and incremental area under the curve (iAUC0-180) of post-lunch levels of glucose, insulin, C-peptide, glucagon-like peptide 1 (GLP-1), and glucagon were measured. Continuous glucose monitoring (CGM) parameters assessed were area under the curve (AUC0-180) of post-meal glucose values, 24-hour average blood glucose (ABG), time in range (TIR), and glycemic variability. Results: BS led to significantly higher fasting (133.5 ± 34.5 mg/dl vs 110 ± 31.50 mg/dl, P = 0.009) and peak post-lunch (214.6 ± 35.07 mg/dl vs 175.4 ± 39.26 mg/dl, P < 0.001) plasma glucose, and HOMA-IR (3.05 ± 3.89 vs 2.03 ± 1.76, P = 0.007) as compared to BE. Post-lunch iAUC0-180 during BS was significantly higher for plasma glucose (7623 ± 2947.9 mg/dl × min vs 1922.4 ± 1902.1 mg/dl × min, P < 0.001), insulin (2460 ± 1597.50 mIU/ml × mins vs 865.71 ± 1735.73 mIU/ml × mins, P = 0.028), C-peptide (418.4 ± 173.4 ng/ml × mins vs 127.8 ± 117.1 ng/ml × mins, P < 0.001) and glucagon (7272.7 ± 4077 pg/ml × mins vs 4568.8 ± 2074.9 pg/ml × mins, P = 0.044) as compared to BE, while GLP-1 (1812.7 ± 883 pmol/l × mins during BS vs 1643 ± 910 pmol/l × mins during BE, P = 0.255) did not significantly differ between the two visits. CGM revealed a higher post-lunch AUC0-180 during BS. There was no difference in post-dinner AUC0-180, ABG, TIR, or glycemic variability. Conclusion: Skipping breakfast led to higher post-lunch glucose excursions, possibly due to higher glucagon excursion and increased insulin resistance.

Vanja Ivković, Martin Windpessl, Ilay Berke et al.

Background: Anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) frequently affects the kidney. Glomerulonephritis (GN) in AAV, ANCA-GN, not only dictates therapeutic decisions but is also of relevance for overall survival influencing the risk of cardiovascular disease and serious infections. Summary: A diagnosis of ANCA-GN includes laboratory investigations including urinalysis and a thorough assessment of potential organ involvement. A kidney biopsy can be performed to ascertain the diagnosis but has an additional prognostic relevance and tools have been established to predict long-term kidney survival. Experimental biomarkers indicating kidney inflammation include urinary soluble CD163 and the presence of urinary T cells. Therapeutic options are refined and some of these therapies, such as the added value of performing plasma exchange, are the matter of controversial discussions. Safe reduction of cumulative exposure to glucocorticoids and eventually the use of avacopan to substantially reduce glucocorticoid exposure has been implemented in most centers. In the remission of maintenance, the optimal duration of therapy is still unclear, but extended use of rituximab as maintenance agent has shown long-term remission rates, thus limiting the damage accrued by relapsing disease and thus also reducing the risk of end-stage kidney disease (ESKD). Avacopan has been the first agent with a glomerular filtration rate-sparing effect, likely due to more rapid control of kidney inflammation. Those reaching ESKD should be evaluated for kidney transplantation and the risk of remaining on dialysis must be balanced against the risk of recurrence of disease following transplantation. Key Messages: The advent of a magnitude of landmark studies in ANCA-GN has refined diagnostic approaches, implemented tools to predict kidney outcome, and eventually led to the approval of newer therapies with avacopan, the latest addition to the armamentarium. Once ESKD is present, patients should be considered for kidney transplantation as remaining on dialysis portends poor overall prognosis. Background: Anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) frequently affects the kidney. Glomerulonephritis (GN) in AAV, ANCA-GN, not only dictates therapeutic decisions but is also of relevance for overall survival influencing the risk of cardiovascular disease and serious infections. Summary: A diagnosis of ANCA-GN includes laboratory investigations including urinalysis and a thorough assessment of potential organ involvement. A kidney biopsy can be performed to ascertain the diagnosis but has an additional prognostic relevance and tools have been established to predict long-term kidney survival. Experimental biomarkers indicating kidney inflammation include urinary soluble CD163 and the presence of urinary T cells. Therapeutic options are refined and some of these therapies, such as the added value of performing plasma exchange, are the matter of controversial discussions. Safe reduction of cumulative exposure to glucocorticoids and eventually the use of avacopan to substantially reduce glucocorticoid exposure has been implemented in most centers. In the remission of maintenance, the optimal duration of therapy is still unclear, but extended use of rituximab as maintenance agent has shown long-term remission rates, thus limiting the damage accrued by relapsing disease and thus also reducing the risk of end-stage kidney disease (ESKD). Avacopan has been the first agent with a glomerular filtration rate-sparing effect, likely due to more rapid control of kidney inflammation. Those reaching ESKD should be evaluated for kidney transplantation and the risk of remaining on dialysis must be balanced against the risk of recurrence of disease following transplantation. Key Messages: The advent of a magnitude of landmark studies in ANCA-GN has refined diagnostic approaches, implemented tools to predict kidney outcome, and eventually led to the approval of newer therapies with avacopan, the latest addition to the armamentarium. Once ESKD is present, patients should be considered for kidney transplantation as remaining on dialysis portends poor overall prognosis.

Jeiver Aldubar Contreras Romero, Kevin Guillermo Castro Gomez, Maria Paula Morales Ortigoza et al.

Contexto: la prolactina es una hormona con múltiples funciones neuroendocrinas, el rol más estudiado es en la función reproductiva, aún no es claro por qué su deficiencia causa disfunción sexual, sin embargo, se ha relacionado con la función gonadal. Objetivo: presentar la información actual sobre la estructura y aspectos moleculares de la PRL, el papel de la serotonina, y la relación fisiopatológica de la hipoprolactinemia y la disfunción sexual masculina. Metodología: revisión de la literatura en las bases de datos PubMed, Lilacs, Embase, Scopus, Scielo, Google Académico y literatura gris utilizando vocabulario controlado DE MeSH, DeCS y Emtree. Resultados: existe poca evidencia acerca de la hipoprolactinemia y disfunción sexual, sin embargo, parecen ser manifestaciones de una alteración serotoninérgica y sus efectos metabólicos, siendo importante conocer los aspectos básicos, fisiopatológicos y clínicos que convierten a esta entidad en una de las causas asociadas a este síndrome. Conclusiones: la hipoprolactinemia es uno de los factores de menor protagonismo por la escasa información disponible con respecto a su rol en la disfunción sexual, esto motiva a desarrollar investigaciones que profundicen el entendimiento de la enfermedad.

Catarina Botelho, Alberto Abad, Tanja Schultz et al.

Speech is a rich biomarker that encodes substantial information about the health of a speaker, and thus it has been proposed for the detection of numerous diseases, achieving promising results. However, questions remain about what the models trained for the automatic detection of these diseases are actually learning and the basis for their predictions, which can significantly impact patients' lives. This work advocates for an interpretable health model, suitable for detecting several diseases, motivated by the observation that speech-affecting disorders often have overlapping effects on speech signals. A framework is presented that first defines "reference speech" and then leverages this definition for disease detection. Reference speech is characterized through reference intervals, i.e., the typical values of clinically meaningful acoustic and linguistic features derived from a reference population. This novel approach in the field of speech as a biomarker is inspired by the use of reference intervals in clinical laboratory science. Deviations of new speakers from this reference model are quantified and used as input to detect Alzheimer's and Parkinson's disease. The classification strategy explored is based on Neural Additive Models, a type of glass-box neural network, which enables interpretability. The proposed framework for reference speech characterization and disease detection is designed to support the medical community by providing clinically meaningful explanations that can serve as a valuable second opinion.

Jinge Wu, Hang Dong, Zexi Li et al.

Rare diseases pose significant challenges in diagnosis and treatment due to their low prevalence and heterogeneous clinical presentations. Unstructured clinical notes contain valuable information for identifying rare diseases, but manual curation is time-consuming and prone to subjectivity. This study aims to develop a hybrid approach combining dictionary-based natural language processing (NLP) tools with large language models (LLMs) to improve rare disease identification from unstructured clinical reports. We propose a novel hybrid framework that integrates the Orphanet Rare Disease Ontology (ORDO) and the Unified Medical Language System (UMLS) to create a comprehensive rare disease vocabulary. The proposed hybrid approach demonstrates superior performance compared to traditional NLP systems and standalone LLMs. Notably, the approach uncovers a significant number of potential rare disease cases not documented in structured diagnostic records, highlighting its ability to identify previously unrecognized patients.

Dennis M. Styne

Yisi Liu, Yanhong Zheng, Xiao Lin et al.

Abstract Background Thyroid disorders (TD) is a common complication of pegylated-interferon alpha (Peg-IFNα) therapy. Few studies have investigated the relationship between TD and the efficacy of interferon therapy for chronic hepatitis B (CHB). Therefore, we analyzed the clinical characteristics of TD in patients with CHB treated with Peg-IFNα, and evaluated the correlation between TD and Peg-IFNα treatment efficacy. Methods In this retrospective study, the clinical data of 146 patients with CHB receiving Peg-IFNα therapy were collected and analyzed. Results During the course of Peg-IFNα therapy, positive conversion of thyroid autoantibodies and TD occurred in 7.3% (85/1158) and 8.8% (105/1187) patients, respectively, and was diagnosed more often in women. The most common thyroid disorder was hyperthyroidism (53.3%), followed by subclinical hypothyroidism (34.3%). We found that thyroid function returned to normal in 78.7% of patients with CHB, and thyroid antibody levels returned to the negative range in approximately 50% of patients after interferon treatment cessation. Only 25% of patients with clinical TD required treatment. Compared with patients with hypothyroidism/subclinical hypothyroidism, patients with hyperthyroidism/subclinical hyperthyroidism showed greater reduction and seroclearance of hepatitis B surface antigen (HBsAg) levels. Conclusions TD are not an absolute contraindication for interferon therapy; however, patients should be monitored closely during interferon therapy. In pursuit of functional cure, a balance between efficacy and safety must be achieved.

Runsheng Zhao, Kaiyu Fan, Weiqing Wan

Abstract Background To prevent thyroid storm and ensure surgical safety, it is imperative to regulate excessive thyroid hormone levels in patients with thyrotropin-secreting pituitary adenomas (TSHoma) prior to surgery. Somatostatin analogues (SSAs), such as octreotide, have showed efficacy in shrinking tumors, which may facilitate surgical resection. This retrospective study aimed to investigate the effect of shortterm preoperative octreotide treatment on the surgical outcome of TSHoma. Methods A total of 65 TSHoma patients from January 2010 to July 2019 were included in the study. Of these,41 patients received short-term preoperative octreotide (Sandostatin, intermittent subcutaneous injection) treatment and all patients subsequently underwent surgery. The following data were recorded: clinical manifestations, laboratory examinations, sellar region MRI, postoperative pathological and electron microscopy data, intraoperative situation, and follow-up (> 3 months) regarding hormone levels and tumor recurrence. Results There was no significant difference in the consistency and blood supply of the tumor between patients who received short-term preoperative octreotide treatment and those who did not. Additionally, preoperative short-term octreotide treatment (median of 10 days with a range of 6–18 days) did not significantly improve the rates of gross total resection (GTR) or biochemical remission. Moreover, electron microscopy revealed subcellular level impairments and cell apoptotic in the octreotide treated TSHoma specimens. Conclusion Preoperative octreotide treatment for the purpose of reducing excessive thyroid hormones may not enhance surgical outcomes, and the duration of octreotide treatment needs to be extended to fully benefit from the tumor-shrinking effects of SSAs.

Michael J. Sharkey, Krit Dwivedi, Samer Alabed et al.

Purpose: Lung disease assessment in precapillary pulmonary hypertension (PH) is essential for appropriate patient management. This study aims to develop an artificial intelligence (AI) deep learning model for lung texture classification in CT Pulmonary Angiography (CTPA), and evaluate its correlation with clinical assessment methods. Materials and Methods: In this retrospective study with external validation, 122 patients with pre-capillary PH were used to train (n=83), validate (n=17) and test (n=10 internal test, n=12 external test) a patch based DenseNet-121 classification model. "Normal", "Ground glass", "Ground glass with reticulation", "Honeycombing", and "Emphysema" were classified as per the Fleishner Society glossary of terms. Ground truth classes were segmented by two radiologists with patches extracted from the labelled regions. Proportion of lung volume for each texture was calculated by classifying patches throughout the entire lung volume to generate a coarse texture classification mapping throughout the lung parenchyma. AI output was assessed against diffusing capacity of carbon monoxide (DLCO) and specialist radiologist reported disease severity. Results: Micro-average AUCs for the validation, internal test, and external test were 0.92, 0.95, and 0.94, respectively. The model had consistent performance across parenchymal textures, demonstrated strong correlation with diffusing capacity of carbon monoxide (DLCO), and showed good correspondence with disease severity reported by specialist radiologists. Conclusion: The classification model demonstrates excellent performance on external validation. The clinical utility of its output has been demonstrated. This objective, repeatable measure of disease severity can aid in patient management in adjunct to radiological reporting.

Isotta Landi, Eugenia Alleva, Alissa A. Valentine et al.

Despite being a unique source of information on patients' status and disease progression, clinical notes are characterized by high levels of duplication and information redundancy. In general domain text, it has been shown that deduplication does not harm language model (LM) pretraining, thus helping reduce the training cost. Although large LMs have proven to learn medical knowledge, they still require specialized domain adaptation for improved downstream clinical tasks. By leveraging large real-world clinical corpora, we first provided a fine-grained characterization of duplicates stemming from common writing practices and clinical relevancy. Second, we demonstrated that deduplicating clinical text can help clinical LMs encode less redundant information in a more efficient manner and do not harm classification tasks via prompt-based learning.

Sadia Aslam, Muhammad Asif, Ifrah Nadeem et al.

Abstract Disclosure: S. Aslam: None. M. Asif: None. I. Nadeem: None. W.J. Khan: None. Background Goiter, most often, is first noticed as a visible neck mass; however, some patients may present with signs and symptoms of hypothyroidism, or hyperthyroidism. Retrosternal extension can cause compression of the trachea, esophagus, and jugular veins resulting in dysfunction of these viscera. CaseA 68-year-old male presented with SOB, and weakness for 5 days. He had SaO2 79% on room air requiring oxygen, RR 28/min, HR 78/min and Temp.101.6 F, BP 94/48 mmHg. The lung exam revealed bilateral rhonchi and coarse crypts. Minimal non-tender nodularity was noted on the thyroid palpation not previously noticed by the patient or his family. Chest x-ray showed bilateral airspace opacities. CT chest revealed a large upper mediastinal mass displacing the trachea and esophagus to the right, a nodule in the left lobe of thyroid, subcarinal and right hilar lymphadenopathy and bilateral dependent consolidative opacities suggesting aspiration pneumonia but no PE. A barium esophagogram showed a 7.5 cm mediastinal mass causing 50% narrowing and displacement of esophagus and compression with left sided deviation of trachea. A barium swallow study was done, and the patient was found to have aspiration with all administered food types due to an abnormal swallowing mechanism. The patient was advised NPO and placed on NG tube feeding to prevent further aspiration. The patient underwent bronchoscopy and EBUS from station 4 lymph node, the pathology of which did not show any malignant cells. However, due to high clinical suspicion of a malignant process, the patient underwent a CT-guided biopsy of the mediastinal mass that showed bland thyroid tissue. Ultrasound of thyroid revealed multiple right and left lobe nodules. TSH and free T4, and calcitonin were WNL. The patient's hypoxia and fever resolved after completion of the antibiotics including ceftriaxone and doxycycline and being nothing per oral within 7 days. Due to persistent dysphagia, he was placed on PEG tube feeding and discharged from the hospital to a nursing home. The patient underwent ultrasound-guided fine needle biopsy of 1 right-sided and 2 left-sided thyroid nodules that resulted as papillary thyroid cancer. He underwent a successful right-sided thoracotomy and removal of large sized thyroid mass. The patient is seeing endocrinology as an outpatient for radioactive iodine and hormone replacement therapy. Conclusion We treated a patient of follicular carcinoma who presented with extrathyroidal symptoms. Retrosternal or ectopic thyroid tumors can present as euthyroid state without obvious enlargement of the normal thyroid gland. A meticulous clinical evaluation should include the differential diagnosis of retrosternal goiter or ectopic thyroid with cancer when treating patients who preset with sign and symptoms concerning for mediastinal disease. Presentation Date: Saturday, June 17, 2023

Wafa Dawahir, J. Gilden, Alvia Moid et al.

Abstract Background Lithium is a drug used in the management of psychiatric condition such as acute mania and bipolar disorder. Lithium is generally known to decrease thyroid hormone synthesis and release, causing hypothyroidism and thyromegaly. Much less commonly, lithium can cause elevated thyroid function tests; we describe such a case. Clinical Case A 21-year-old man with bipolar disorder and polysubstance abuse, presented with acute mania and was started on Lithium. Baseline TSH was 1.42 [0.358-3.74 µIU/mL], but one week after starting Lithium, TSH was 0.1 uIU/mL [0.358 - 3.74 µIU/mL] with free T4 of 0.95 [0.76-1.46 ng/dL]. Three weeks later, TSH was 0. 01 µIU/mL [0.358 - 3.74 µIU/mL], FT4 1.52 ng/dL [0.76 - 1.46 ng/dL], FT3 6.16 pg/mL [ 2.18 - 3.98 pg/mL], total T3 221 ng/dL [76–181 ng/dL]. Six weeks after starting Lithium, TSH remained suppressed at <0. 005 µIU/mL [0.358 - 3.74 µIU/mL], FT4 1.66 ng/dL [0.76 - 1.46 ng/dL], FT3 6.21 pg/mL [ 2.18 - 3.98 pg/mL]. During this time the patient's only complaint was tremor, with no other symptoms of hyperthyroidism. Physical exam showed mild tachycardia, with no evidence of thyroid eye disease, and the thyroid gland was normal size and nontender. TSI was negative with normal thyroglobulin and iodine levels, negative thyroglobulin and peroxidase antibodies. Lithium was in the therapeutic range. Thyroid US was normal without thyromegaly, normal echogenicity and color flow and without nodules or masses. I-123 thyroid uptake and scan showed low uptake and no nodules. The patient was diagnosed with Lithium-induced silent thyroiditis. He was treated with propranolol 10 mg PO BID for tremors, which was stopped later, due to bradycardia and dizziness. Due to persistent suppression of TSH and elevated FT4 and FT3 eight weeks after initiation of Lithium, this was discontinued, and Depakote was started. Conclusion Prior studies have shown that Lithium-induced thyrotoxicosis occurs in 2.7 cases/per 1000 person-years, with Lithium-associated Graves’ disease in 1.4 cases/1000 person-years, and silent thyroiditis only in 1.3 cases/per 1000 person-years. Although rare, our case highlights the importance of considering silent thyroiditis in patients treated with lithium and hyperthyroidism. References: K. K. Miller and G. H. Daniels, Association between lithium use and thyrotoxicosis caused by silent thyroiditis. Clinical Endocrinology 2001; 55, 501-508Kibirige et al. Spectrum of lithium induced thyroid abnormalities: a current perspective. Thyroid Research 2013; 6: 3 Presentation: No date and time listed