Edward Franek

Background: Lipedema is a chronic adipose tissue disorder characterized by disproportionate lower-limb fat accumulation, pain, and resistance to conventional weight-loss strategies. Tirzepatide produces substantial weight loss, but evidence in lipedema is limited. Methods: This single-center ambispective pilot case series described a 22–25-week routine clinical course in 2025. During the first 8–9 weeks, all participants received only a low-carbohydrate Mediterranean diet and recommendations for aerobic and resistance exercise; no participant received tirzepatide during this phase. After completion of the 8–9-week non-pharmacological phase, four participants started tirzepatide (2.5–7.5 mg once weekly) and continued it for the remaining 14–16 weeks, whereas one participant declined pharmacotherapy. After approval by the Bioethics Committee (Resolution No. 12/2026, 4 February 2026), the 2025 data were analyzed retrospectively; participants gave verbal consent to further follow-up in March–April 2026 and were followed up prospectively, and all signed written consent for publication of their data and photographs in October 2026. Anthropometric, ultrasound, biochemical, pain, and quality-of-life outcomes were summarized descriptively for each case. Where available, changes are reported separately for the diet-and-exercise phase (T1–T2) and the tirzepatide phase (T2–T3). Results: Weight loss among the five completers ranged from 7.7 to 17.1 kg. Body fat percentage decreased in four of five participants, whereas skeletal muscle mass decreased numerically in all four tirzepatide-treated participants. Lower-limb circumferences and subcutaneous adipose tissue thickness generally decreased, although the magnitude and distribution of changes differed between participants. Fasting glucose and HOMA-IR decreased in most cases, whereas lipid changes were mixed. Patient-reported SF-36 scores (assessed only at T2 and T3) generally improved among the four participants receiving tirzepatide, particularly for bodily pain, while pressure pain threshold responses (T2 to T3) were heterogeneous. No adverse events, gastrointestinal symptoms, dose reductions, treatment interruptions, discontinuations, or serious adverse events were reported by the four tirzepatide-treated participants; the study was not designed to assess safety. Conclusions: This ambispective pilot case series provides preliminary, hypothesis-generating observations on a multimodal intervention that included tirzepatide in four of five women with lipedema and excess body weight. The observed changes cannot be attributed to tirzepatide or interpreted as a lipedema-specific effect because all participants received concurrent dietary, exercise, and supplementation interventions, and the participant who declined pharmacotherapy was not a comparator or control.

Background/Objective: Ultrasound is the first-line imaging modality for thyroid nodule assessment; however, it remains highly operator-dependent and subject to interobserver variability. Artificial intelligence (AI)-based systems have been proposed to improve reproducibility, yet evidence regarding their agreement with clinician assessment—particularly at the level of individual sonographic features—remains limited. Importantly, most available studies evaluate concordance rather than true diagnostic accuracy against an independent reference standard. To evaluate agreement between an AI-based ultrasound system and expert clinician assessment in thyroid nodule evaluation, focusing on concordance of size measurements, agreement in sonographic feature classification, and exploratory diagnostic performance relative to cytological outcomes. Methods: This retrospective single-center study included 74 thyroid nodules from adult patients undergoing routine ultrasound examination. Archived ultrasound images were independently assessed by an experienced clinician and an AI-based system. Agreement for quantitative measurements was evaluated using Bland–Altman analysis, while categorical features were assessed using percent agreement and Cohen’s kappa coefficients. Calibration was examined using scatter plots with the line of identity. Cytological results, when available, were used as a non-uniform exploratory reference standard for diagnostic analyses. Exploratory diagnostic performance was assessed using receiver operating characteristic (ROC) curves and area under the curve (AUROC) estimates. Given the study design, analyses primarily reflect agreement and measurement concordance rather than true diagnostic accuracy. Results: AI-derived and clinician measurements demonstrated strong agreement across all dimensions, with minimal systematic bias and stable calibration patterns. A small but consistent underestimation of one measurement axis by approximately 1 mm was observed. For categorical features, agreement ranged from fair to moderate (κ = 0.196–0.368), with the highest concordance for echogenic foci and lowest for echogenicity. Exploratory analyses showed variable diagnostic discrimination, with the best performance observed for size measurements and selected sonographic features. Conclusions: AI-based ultrasound analysis demonstrates robust agreement with clinician assessment for quantitative thyroid nodule measurements, while agreement for categorical feature classification remains moderate and variable. The findings highlight that the present study evaluates concordance rather than definitive diagnostic accuracy, particularly given the lack of a uniform independent reference standard. These results support the role of AI as an assistive tool in thyroid ultrasound practice, improving measurement reproducibility while requiring ongoing clinician oversight for qualitative interpretation.

Background: Type 2 diabetes (T2D) is the leading cause of chronic kidney disease (CKD), responsible for approximately 60% of cases. Diabetic kidney disease (DKD) affects 20–50% of individuals with diabetes, with diabetes-related ESKD cases rising steadily worldwide from 22.1% in 2000 to 31.3% in 2015. Methods: This review examines the literature published up to 25 February 2025, using a systematic search in PubMed and Scopus. Keywords included uremic toxins and diabetic kidney disease and/or gut microbiota, or dysbiosis or gut–kidney axis. Studies were independently assessed by a minimum of three authors, with discrepancies resolved through consensus. Results: Gut microbiota dysbiosis is a key driver of DKD progression, making the gut–kidney axis a promising therapeutic target. A “nuts and fruits” dietary pattern reduces the DKD risk by 43.3%, while an animal protein intake lowers the diabetic peripheral neuropathy risk by 42.8%. High-fiber diets and supplements like resistant starch may reduce uremic toxins through microbiota modulation. Conclusions: Microbiota-targeted interventions, including probiotics, synbiotic, and dietary modifications, show potential in reducing uremic toxin production and inflammation, though DKD-specific evidence remains limited. Lactobacillus and Bifidobacterium strains may help lower urea and creatinine levels, but outcomes vary by disease stage. Further research is needed to confirm the efficacy of dietary and probiotic approaches in DKD management.

Background: Diabetic kidney disease (DKD) affects 20–50% of individuals with diabetes. The aim of this review was to identify interventions that positively influence the gut microbiota in DKD. Methods: Identification of relevant studies was conducted via a systematic search of databases and registers using the PRISMA guidelines. This review examined the relevant literature published up to 5 January 2025, using a systematic search in PubMed and Scopus. The search was conducted with combinations of keywords including DKD and therapy, supplementation and gut microbiota, and supplementation or probiotics or fecal microbiota transplant. The initial search fielded 132 results from PubMed and 72 from Scopus, which was narrowed to 135 relevant studies. The exclusion criteria included non-English language studies, letters to the editor, and conference abstracts. Eligible studies were independently assessed by a minimum of three authors, with discrepancies resolved through consensus. Results: Gut microbiota-targeted interventions, including probiotics, synbiotics, and dietary modifications, show promise in modulating the gut microbiota, but evidence specific to DKD remains limited. Some natural food components such as polyphenols and anthocyanins modulate the composition of the gut microbiota translocation of uremic toxins, which slows down the progression of diabetic kidney disease. In animal models, fecal microbiota transplantation (FMT) has shown positive effects in regulating dysbiosis and beneficial effects in chronic kidney disease, but studies involving humans with DKD are insufficient. Conclusions: Lactobacillus and Bifidobacterium strains, administered at doses ranging from 0.6 to 90 billion CFU, may help lower urea and creatinine levels, but outcomes vary by disease stage, duration of therapy, and amount used. High-fiber diets (>10.1 g/1000 kcal/day) and supplements such as resistant starch and curcumin (400–1500 mg/day) may reduce uremic toxins through gut microbiota modulation and reduction in oxidative stress. The effect of sodium butyrate requires further human studies.