Braukylienė, Rugilė

Introduction

Autoimmune polyglandular syndrome (APS) is a rare group of immune-mediated disorders. APS type 2 is the most common subtype with a characteristic clinical triad, which includes adrenal insufficiency, autoimmune thyroiditis and diabetes mellitus (DM) type 1.

Case Presentation

A 37-year-old woman with Down syndrome (DS) and autoimmune thyroiditis treated with levothyroxine, was admitted to the emergency department with an 8-day history of progressive weakness, nausea, and dizziness. The patient's height 142 cm, weight 47 kg, BMI 23 kg/m2.,Initial laboratory evaluation revealed hyperkalemia 8.02 mmol/L (3.5-5.1) and hyponatremia 130 nmol/L (136-144). Patient was hospitalized to the intensive care unit. Patient developed persistent hypotension (79/50 mmHg) and ongoing hyperkalemia (6.1 mmol/L), hyponatremia (130 nmol/L) raising suspicion for adrenal crisis. Diagnostic evaluation confirmed adrenal insufficiency with markedly elevated ACTH level of 210.8 pmol/L (1.63-14.5) and low cortisol level of 101.18 nmol/L. Immediate treatment consisted of intravenous hydrocortisone 100 mg IV bolus. Hydrocortisone 200 mg /24 h was administered further using automatic syringe pump. After correcting the electrolyte imbalance, maintaining stable blood pressure, oral hydrocortisone was administered, gradually decreasing to a maintenance dose (30 mg/day). In the presence of a tendency to slight hypotension, with signs of aldosterone deficiency, elevated renin concentration of 134.9 ng/L (3.78-32.61), fludrocortisone was added resulting in systolic blood pressure increase toto 90-100 mmHg. Anti-GAD65, anti-IA2 antibodies were negative and glucose tolerance test was within normal range. At discharge, the patient's treatment consisted of hydrocortisone (15/10/5 mg), fludrocortisone 50 μg per day and levothyroxine 75 μg per day. A month later, laboratory tests revealed elevated renin level of 401 ng/L (3.78-32.61) and elevated TSH level of 14.78 mU/L (0.4-3.6), sodium 133 mmo/L (135-144), potassium 4.7 nmol/L (3.5-5.1), a tendency to a lower blood pressure was found. Fludrocortisone dose was increased to 75 μg per day and levothyroxine—to 100 μg per day, hydrocortisone dose was unchanged and follow up visit was planned in 2 months.

In conclusion, DS is associated with an increased risk of autoimmune diseases due to disruption of immune tolerance. This case highlights the challenges and risks of APS type 2 in patients with DS, indicating the need for screening and timely treatment of these serious endocrine conditions.

Introduction Lipodystrophy syndromes are a heterogeneous group of diseases, where the primary defect is the loss of functional adipocytes. This leads to ectopic steatosis, severe dyslipidemia, and insulin resistance [1,2]. Case Presentation A 34-year-old woman with type 1 diabetes, hypertriglyceridemia, polycystic ovary syndrome (PCOS), and arterial hypertension (HTN) was hospitalized in the Endocrinology Department of LSMU Kaunas Clinics due to poorly controlled glycemia. At admission, she was at 18 weeks of gestation (gravida III, para II). Family history was significant for diabetes, affecting the patient’s brother, sister, and both grandmothers. Due to suspected genetically inherited diabetes, the patient was sent for genetic consultation. Conclusion of the Genetic Evaluation: Peroxisome Proliferator-Activated Receptor Gamma (PPARG) gene mutation causing familial partial lipodystrophy (FPLD3). Following a multidisciplinary team meeting, leptin therapy was not indicated during pregnancy. Furthermore, amniocentesis revealed a PPARG gene mutation. The patient’s brother and sister were referred for genetic consultation, as both have symptoms characteristic of FPLD3. A 32-year-old brother has HTN, hypertriglyceridemia, and type 2 diabetes. 36-year-old sister - HTN, unspecified diabetes with insulin resistance, hypertriglyceridemia with need for plasmapheresis, suspected of PCOS. Conclusion of the Genetic Evaluation: PPARG gene mutation. Discussion FPLD3 is the most common form and is usually an autosomal dominant Mendelian disorder. It has been estimated that their global prevalence is 1.7–2.8 cases per million for FPLD3 [2]. The main symptoms are hypertriglyceridemia, diabetes, HTN, PCOS, and liver steatosis [3]. No welldefined diagnostic criteria have been established for lipodystrophy. Thus, its diagnosis is based on medical history, physical examination, body composition, and the evaluation of metabolic complications [2]. Treatment focuses on intensive management of metabolic complications. Leptin replacement therapy with metreleptin is indicated in FPLD3 patients with severe metabolic complications and low leptin levels [4]. Conclusions Familial partial lipodystrophy is a very rare disease [1-4]. This clinical case highlights the importance of thoroughly evaluating not only the patient but also at-risk family members.

Introduction Intrathyroidal parathyroid adenoma is a rare anomaly with an incidence of 1.4-6% [1]. Case Presentation A 67 – years old female patient presented with 3 years of general and muscle weakness, fatigue. Anamnesis: partial gastrectomy due to stomach carcinoma, hysterectomy, osteoporosis. In the laboratory tests were found increased levels of PTH, calcium, anti-TPO and low level of vitamin D. Patient was treated with Colecalciferolum 25000 TV. In dynamics PTH increased from 26,47 to 210 pmol/l, calcium from 2,71 to 2,79 mmol/l over 4 months. Thyroid ultrasound showed EU-TIRADS 3-4. During physical examination thyroid gland was mobile, a mobile induration was palpable, no peripheral lymph nodes were detected. After 18 months thyroid ultrasound was repeated and FNA was performed. In biopsy: epithelium hyperplasia (III category of Bethesda). Thyroid scintigraphy performed: radiopharmaceutical-accumulating nodule in the right lobe of the thyroid (possibly adenoma). Radiopharmaceuticalaccumulating parathyroid glands were not visible. Radiologist suggested FNA with staining due to parathyroid gland adenoma, based on repeated thyroid scintigraphy and FNA after 4 months. It showed parathyroid gland tissue in the thyroid. Multidisciplinary team performed right hemithyroidectomy - removing right thyroid lobe with intrathyroidal hyperplastic parathyroid gland. After the biopsy report, the final diagnosis: right parathyroid gland adenoma. Status post right hemithyroidectomy. Autoimmune thyroiditis (euthyrosis). Osteoporosis. Discussion Primary hyperparathyroidism (PHPT) is a common endocrine disease. Intrathyroidal parathyroid adenoma (ITPA) is a rare reason for PHPT and site of ectopia [2]. The latter may be located ectopically in 11-25% of cases [1]. Clinical scenarios in which an ectopic parathyroid adenoma should be considered in clinical practice include patients with PHPT in whom preoperative imaging suggests the presence of an ectopic parathyroid adenoma or initial preoperative imaging fails to identify a target adenoma [3]. Conclusions Intrathyroidal parathyroid adenoma is rare disease in patient with PHPT. Diagnosis and management are challenging, and it requires a combination of tests.

Background: Early safety outcomes following transcatheter aortic valve implantation (TAVI) for severe aortic stenosis are critical for patient prognosis. Accurate prediction of adverse events can enhance patient management and improve outcomes. Aim: This study aimed to develop a machine learning model to predict early safety outcomes in patients with severe aortic stenosis undergoing TAVI. Methods: We conducted a retrospective single-centre study involving 224 patients with severe aortic stenosis who underwent TAVI. Seventy-seven clinical and biochemical variables were collected for analysis. To handle unbalanced classification problems, an adaptive synthetic (ADASYN) sampling approach was used. A fined-tuned random forest (RF) machine learning model was developed to predict early safety outcomes, defined as all-cause mortality, stroke, life-threatening bleeding, acute kidney injury (stage 2 or 3), coronary artery obstruction requiring intervention, major vascular complications, and valve-related dysfunction requiring repeat procedures. Shapley Additive Explanations (SHAPs) were used to explain the output of the machine learning model by attributing each variable’s contribution to the final prediction of early safety outcomes. Results: The random forest model identified left femoral artery diameter and aortic valve calcification volume as the most influential predictors of early safety outcomes. SHAPs analysis demonstrated that smaller left femoral artery diameter and higher aortic valve calcification volume were associated with poorer early safety prognoses. Conclusions: The machine learning model highlights of early safety outcomes after TAVI. These findings suggest that incorporating these variables into pre-procedural assessments may improve risk stratification and inform clinical decision-making to enhance patient care.

Background: Acute Myocardial Infarction (AMI) represents a significant clinical challenge with diverse outcomes. Predicting patient-oriented composite endpoints (POCE) (all-cause death, any stroke, any AMI, or any revascularization) can significantly enhance post-AMI care. Incorporating clinical data with neuroendocrine biomarkers may offer improved prognostic capabilities. Objective: To develop and validate a machine learning model to predict POCE in AMI patients, utilizing clinical parameters and neuroendocrine biomarkers. Methods: There was prospective, observational, single-center study. Three approaches have been used to obtain the predictions for POCE event. First, as the dataset was imbalanced, an adaptive synthetic (ADASYN) sampling approach was used to generate synthetic instances, particularly focusing on those that are difficult-to-learn by using a weighted distribution. Then, random forest classifier (RF) was used to build a machine learning model to predict POCE. The model was tuned via a grid-search algorithm for optimal hyperparameters and validated using a 10-fold stratified cross-validation. Finally, the feature importance was determined by Shapley Additives, which measure the average marginal contribution of a feature value across all potential feature combinations. For the comparative purpose, the Gini index, which also shows the feature importance but in terms of mean decrease in impurity, was calculated. Results: The study incorporated data from 315 patients, examining 47 variables and identifying 72 instances of POCE. After applying the ADASYN algorithm, the class distribution within the dataset was effectively equalized, facilitating the training of a robust RF model. Upon training with 252 instances, the model distinguished POCE with an accuracy of 83.8%, demonstrating a sensitivity of 80% and a specificity of 86%. During 10-fold cross-validation, the model's accuracy slightly dipped to 75%, with a sensitivity of 56% and specificity of 82%, indicating a balance between generalizability and overfitting. Testing mirrored these results, underscoring the model’s consistent performance. Notably, SHAP value analysis highlighted C-Reactive Protein (CRP) and alanine transaminase (ALT) as the most influential features, underscoring their significance in the context of AMI (Figure 1-2). The predictive power of each feature was further demonstrated by the mean decrease in Gini index (Figure 1-2). Conclusion: Our study highlights the feasibility of employing machine learning to predict POCE post-AMI using an integrative dataset of clinical and neuroendocrine markers. The predictive model has the potential to revolutionize post-AMI care by allowing clinicians to identify high-risk patients early, tailor interventions, and allocate resources efficiently. Future research could explore the integration of this model into clinical workflows and its impact on patient outcomes.

Introduction: The research focused on the impact of transcatheter aortic valve implantation (TAVI) on patients with severe aortic stenosis, a critical concern in cardiovascular disease management. TAVI has revolutionized the treatment approach, especially for high-risk surgical patients, by offering a less invasive alternative. The research aims to scrutinize the cardiovascular outcomes and procedural implications of TAVI, emphasizing a comprehensive clinical evaluation of 224 patients. It delves into various factors such as age, kidney function, body surface area, left ventricular ejection fraction (LVEF), and the presence of calcified non-coronary anomalies to assess patient risk and predict outcomes. Additionally, it examines the impact of procedural variables like fluoroscopy duration and contrast volume on patient morbidity and mortality. By analyzing clinical, laboratory, echocardiographic, and CT data, and exploring how procedural factors relate to survival rates, this study offers insights into the nuanced effects of TAVI. The goal is to enhance understanding within interventional cardiology, potentially leading to improved clinical protocols and patient care in cardiovascular treatments. [...].

Introduction The NR3C2 gene encodes mineralocorticoid receptor (MR) protein, which is responsible for regulating sodium concentration in the body. Lately MR has gained attention, it is considered one of the most important stress-related genes. Currently, no data is available concerning the association of NR3C2 gene polymorphism rs5522 with the events of ST segment elevation myocardial infarction (STEMI) and non-ST segment elevation acute myocardial infarction (NSTEMI). Aim To evaluate the relationship between the genetic polymorphism rs5522 of NR3C2 gene and the event rate of STEMI and NSTEMI. [...].