Search Results (22)

This review introduces a novel integrative framework linking gut dysbiosis, systemic inflammation, and cardiovascular risk in patients with inflammatory bowel disease (IBD). We highlight emerging biomarkers, including short-chain fatty acids (SCFAs), calprotectin, and zonulin, that reflect alterations in the gut microbiome and increased intestinal permeability, which contribute to cardiovascular pathology. Cardiovascular diseases (CVDs) remain the leading cause of morbidity and mortality worldwide, and recent evidence identifies IBD, encompassing ulcerative colitis (UC) and Crohn’s disease (CD), as a significant non-traditional risk factor for CVD. This review synthesizes current knowledge on how dysbiosis-driven inflammation in IBD patients exacerbates endothelial dysfunction, hypercoagulability, and atherosclerosis, even in the absence of traditional risk factors. Additionally, we discuss how commonly used IBD therapies may modulate cardiovascular risk. Understanding these multifactorial mechanisms and validating reliable biomarkers are essential for improving cardiovascular risk stratification and guiding targeted prevention strategies in this vulnerable population. Full article

Mitochondrial dysfunction is a pivotal driver in the pathogenesis of acute kidney injury (AKI), chronic kidney disease (CKD), and congenital anomalies of the kidney and urinary tract (CAKUT). The kidneys, second only to the heart in mitochondrial density, rely on oxidative phosphorylation to meet the high ATP demands of solute reabsorption and filtration. Disrupted mitochondrial dynamics, such as excessive fission mediated by Drp1, exacerbate tubular apoptosis and inflammation in AKI models like ischemia–reperfusion injury. In CKD, persistent mitochondrial dysfunction drives oxidative stress, fibrosis, and metabolic reprogramming, with epigenetic mechanisms (DNA methylation, histone modifications, non-coding RNAs) regulating genes critical for mitochondrial homeostasis, such as PMPCB and TFAM. Epigenetic dysregulation also impacts mitochondrial–ER crosstalk, influencing calcium signaling and autophagy in renal pathology. Mitophagy, the selective clearance of damaged mitochondria, plays a dual role in kidney disease. While PINK1/Parkin-mediated mitophagy protects against cisplatin-induced AKI by preventing mitochondrial fragmentation and apoptosis, its dysregulation contributes to fibrosis and CKD progression. For instance, macrophage-specific loss of mitophagy regulators like MFN2 amplifies ROS production and fibrotic responses. Conversely, BNIP3/NIX-dependent mitophagy attenuates contrast-induced AKI by suppressing NLRP3 inflammasome activation. In diabetic nephropathy, impaired mitophagy correlates with declining eGFR and interstitial fibrosis, highlighting its diagnostic and therapeutic potential. Emerging therapeutic strategies target mitochondrial dysfunction through antioxidants (e.g., MitoQ, SS-31), mitophagy inducers (e.g., COPT nanoparticles), and mitochondrial transplantation, which mitigates AKI by restoring bioenergetics and modulating inflammatory pathways. Nanotechnology-enhanced drug delivery systems, such as curcumin-loaded nanoparticles, improve renal targeting and reduce oxidative stress. Epigenetic interventions, including PPAR-α agonists and KLF4 modulators, show promise in reversing metabolic reprogramming and fibrosis. These advances underscore mitochondria as central hubs in renal pathophysiology. Tailored interventions—ranging from Drp1 inhibition to mitochondrial transplantation—hold transformative potential to mitigate kidney injury and improve clinical outcomes. Additionally, dietary interventions and novel regulators such as adenogens are emerging as promising strategies to modulate mitochondrial function and attenuate kidney disease progression. Future research should address the gaps in understanding the role of mitophagy in CAKUT and optimize targeted delivery systems for precision therapies. Full article

Artificial intelligence (AI) and machine learning (ML) are transforming the management of acute appendicitis by enhancing diagnostic accuracy, optimizing treatment strategies, and improving patient outcomes. This study reviews AI applications across all stages of appendicitis care, from triage to postoperative management, using sources from PubMed/MEDLINE, IEEE Xplore, arXiv, Web of Science, and Scopus, covering publications up to 14 February 2025. AI models have demonstrated potential in triage, enabling rapid differentiation of appendicitis from other causes of abdominal pain. In diagnostics, ML algorithms incorporating clinical, laboratory, imaging, and demographic data have improved accuracy and reduced uncertainty. These tools also predict disease severity, aiding decisions between conservative management and surgery. Radiomics further enhances diagnostic precision by analyzing imaging data. Intraoperatively, AI applications are emerging to support real-time decision-making, assess procedural steps, and improve surgical training. Postoperatively, ML models predict complications such as abscess formation and sepsis, facilitating early interventions and personalized recovery plans. This is the first comprehensive review to examine AI’s role across the entire appendicitis treatment process, including triage, diagnosis, severity prediction, intraoperative assistance, and postoperative prognosis. Despite its potential, challenges remain regarding data quality, model interpretability, ethical considerations, and clinical integration. Future efforts should focus on developing end-to-end AI-assisted workflows that enhance diagnosis, treatment, and patient outcomes while ensuring equitable access and clinician oversight. Full article

Background/Objectives: Large language models (LLMs) have shown significant potential to transform various aspects of healthcare. This review aims to explore the current applications, challenges, and future prospects of LLMs in medical education, clinical decision support, and healthcare administration. Methods: A comprehensive literature review was conducted, examining the applications of LLMs across the three key domains. The analysis included their performance, challenges, and advancements, with a focus on techniques like retrieval-augmented generation (RAG). Results: In medical education, LLMs show promise as virtual patients, personalized tutors, and tools for generating study materials. Some models have outperformed junior trainees in specific medical knowledge assessments. Concerning clinical decision support, LLMs exhibit potential in diagnostic assistance, treatment recommendations, and medical knowledge retrieval, though performance varies across specialties and tasks. In healthcare administration, LLMs effectively automate tasks like clinical note summarization, data extraction, and report generation, potentially reducing administrative burdens on healthcare professionals. Despite their promise, challenges persist, including hallucination mitigation, addressing biases, and ensuring patient privacy and data security. Conclusions: LLMs have transformative potential in medicine but require careful integration into healthcare settings. Ethical considerations, regulatory challenges, and interdisciplinary collaboration between AI developers and healthcare professionals are essential. Future advancements in LLM performance and reliability through techniques such as RAG, fine-tuning, and reinforcement learning will be critical to ensuring patient safety and improving healthcare delivery. Full article

Despite technological advancements, healthcare professionals must actively prioritize patient safety. Reporting adverse drug reactions is a critical aspect of this responsibility, and the most accessible healthcare providers, community pharmacists, and pharmacy technicians play a key role. Therefore, this study assessed their knowledge and practices regarding adverse drug reaction reporting in Croatia. A total of 180 participants were included. Pharmacists demonstrated significantly better knowledge than technicians (94.78 vs. 73.97, p = 0.024). Chronic medication users also showed greater understanding compared to non-users (104.96 vs. 85.39, p = 0.021). Knowledge improved with the number of adverse drug reactions reported, and most participants (72.78%) had reported adverse drug reactions. Pharmacists were 83.60% more likely to report adverse drug reactions than technicians (p < 0.001). These findings reveal a gap in pharmacy technicians’ integration into pharmacovigilance, underscoring a need to strengthen their role in adverse drug reaction reporting and patient safety. Full article

Food–drug interactions (FDIs) are pharmacokinetic or pharmacodynamic changes in drug effects caused by the presence of specific foods. To identify and prevent FDIs, pharmacists, alongside other healthcare professionals, should possess a certain level of knowledge. This study aimed to assess knowledge of FDIs among Croatian pharmacists. A total of 206 participants were included in this cross-sectional study. The median knowledge score among Croatian pharmacists was 69.44%, with an interquartile range of 19.44. Croatian pharmacists most commonly recognized FDIs involving theophylline, warfarin, and tetracycline, while the lowest rate of correct answers was observed with digoxin interactions. Future studies should evaluate pharmacists’ clinical practice concerning FDIs. Additionally, more research is needed to develop educational programs on this topic, either at the university level or for continuing education. Full article

With the rapid development of the pharmaceutical industry and constant growth of drug usage, ecopharmacovigilance (EPV) has emerged as a way of coping with and minimizing the effects that drugs have on the environment. EPV concerns and describes unwanted effects that the use of a specific drug could have on the environment. The US, EU and Cananda are the improving position of EPV, both in legislation and practice. EPV requires further development as previous studies have shown that neither the general population nor healthcare professionals have enough knowledge about the subject. Improving awareness and knowledge about this topic is a key task for the future of EPV. The main objective was to determine students’ level of knowledge about ecopharmacovigilance and to examine ways of storing and disposing of unused and expired drugs. Students’ knowledge and habits were examined by a previously published survey. The survey contains twenty questions divided into three parts and the possibility of writing an additional note. There was no difference in the level of knowledge between the students of different studies. Also, students who had a family member working as healthcare professional did not show a higher level of knowledge compared to the others. Pharmacy students had a greater intention to educate their environment about EPV when compared to students of the other studies. This is in the line with a previous study which showed that the general public expects that pharmacists and physicians educate them about EPV. Medicine and dental medicine students will become prescribers after finishing their studies, and as such, they should be informed about eco-directed sustainable prescribing (EDSP) as part of an EPV strategy. More than half of the participants reported good adherence to prescribers’ instruction, which decreased the amount of unused drugs. Most of the students found that the drug expiration date was legible, but they did not check it often. In comparison with similar studies, Croatian students had more knowledge and better practices concerning EPV and drug disposal. Structured learning strategies and curriculum implementation for EPV are much needed for further raising awareness about the subject among healthcare professionals and the public. Full article

Background and Objectives: The assessment of cardiac function in patients with end-stage renal disease (ESRD) is vital due to their high cardiovascular risk. However, contemporary echocardiographic indices and their association with hemodialysis-to-hemodiafiltration transfer are underreported in this population. Materials and Methods: This prospective cohort study enrolled 36 ESRD patients undergoing hemodialysis-to-hemodiafiltration transfer, with baseline and 3-month post-transfer comprehensive echocardiographic assessments. The key parameters included the global work index, global constructed work, global wasted work (GWW), global work efficiency (GWE), and global longitudinal strain (GLS), with secondary measures from conventional echocardiography. The baseline measures were compared to general population reference values and changes pre- to post-transfer were analyzed using the Mann–Whitney U test. Results: Patients exhibited significant deviations from reference ranges in GWW (179.0 vs. 53.0–122.2 mmHg%), GWE (90.0 vs. 53.0–122.2%), and GLS (−16.0 vs. −24.0–(−16.0)%). Post-transfer left ventricular myocardial work and longitudinal strain remained unchanged (p > 0.05), except for increased GWW (179.0, IQR 148.0–217.0 to 233.5, IQR 159.0-315.0 mmHg%, p = 0.037) and improved mid-inferior peak systolic longitudinal strain ((−17.0, IQR −19.0–(−11.0) to −18.7, IQR −20.0–(−18.0)%, p = 0.016). The enrolled patients also showed higher left atrial diameters, left ventricular volumes, and mass, with impaired systolic function in both ventricles compared to reference values. Conclusions: This study highlights baseline impairments in contemporary echocardiographic measures (GWW, GWE, GLS) in ESRD patients versus reference values, but found no association between hemodialysis-to-hemodiafiltration transfer and most myocardial work and strain parameters. Full article

The aim of this study was to establish whether multiple blood parameters might predict an early treatment response to intravitreal bevacizumab injections in patients with diabetic macular edema (DME). Seventy-eight patients with non-proliferative diabetic retinopathy (NPDR) and DME were included. The treatment response was evaluated with central macular thickness decrease and best corrected visual acuity increase one month after the last bevacizumab injection. Parameters of interest were the neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), vitamin D, and apolipoprotein B to A-I ratio (ApoB/ApoA-I). The NLR (2.03 ± 0.70 vs. 2.80 ± 1.08; p < 0.001), MLR (0.23 ± 0.06 vs. 0.28 ± 0.10; p = 0.011), PLR (107.4 ± 37.3 vs. 135.8 ± 58.0; p = 0.013), and SII (445.3 ± 166.3 vs. 675.3 ± 334.0; p < 0.001) were significantly different between responder and non-responder groups. Receiver operator characteristics analysis showed the NLR (AUC 0.778; 95% CI 0.669–0.864), PLR (AUC 0.628; 95% CI 0.511–0.735), MLR (AUC 0.653; 95% CI 0.536–0.757), and SII (AUC 0.709; 95% CI 0.595–0.806) could be predictors of response to bevacizumab in patients with DME and NPDR. Patients with severe NPDR had a significantly higher ApoB/ApoA-I ratio (0.70 (0.57–0.87) vs. 0.61 (0.49–0.72), p = 0.049) and lower vitamin D (52.45 (43.10–70.60) ng/mL vs. 40.05 (25.95–55.30) ng/mL, p = 0.025). Alterations in the NLR, PLR, MLR, and SII seem to provide prognostic information regarding the response to bevacizumab in patients with DME, whilst vitamin D deficiency and the ApoB/ApoA-I ratio could contribute to better staging. Full article

Introduction: This research was performed to examine the effects of air and oxygen prebreathing on bubble formation, flow-mediated dilatation, and psychomotor performance after scuba dives. Methods: Twelve scuba divers performed two dives using a gas mixture of oxygen, nitrogen, and helium (trimix). In a randomized protocol, they breathed air or oxygen 30 min before the trimix dives. Venous bubble formation, flow-mediated dilatation, and psychomotor performance were evaluated. The participants solved three psychomotor tests: determining the position of a light signal, coordination of complex psychomotor activity, and simple arithmetic operations. The total test solving time, minimum single-task solving time, and median solving time were analyzed. Results: The bubble grade was decreased in the oxygen prebreathing protocol in comparison to the air prebreathing protocol (1.5 vs. 2, p < 0.001). The total test solving times after the dives, in tests of complex psychomotor coordination and simple arithmetic operations, were shorter in the oxygen prebreathing protocol (25 (21–28) vs. 31 (26–35) and 87 (82–108) vs. 106 (90–122) s, p = 0.028). Conclusions: In the oxygen prebreathing protocol, the bubble grade was significantly reduced with no change in flow-mediated dilatation after the dives, indicating a beneficial role for endothelial function. The post-dive psychomotor speed was faster in the oxygen prebreathing protocol. Full article

Breast cancer is a significant health issue affecting women worldwide, and accurately detecting lymph node metastasis is critical in determining treatment and prognosis. While traditional diagnostic methods have limitations and complications, artificial intelligence (AI) techniques such as machine learning (ML) and deep learning (DL) offer promising solutions for improving and supplementing diagnostic procedures. Current research has explored state-of-the-art DL models for breast cancer lymph node classification from radiological images, achieving high performances (AUC: 0.71–0.99). AI models trained on clinicopathological features also show promise in predicting metastasis status (AUC: 0.74–0.77), whereas multimodal (radiomics + clinicopathological features) models combine the best from both approaches and also achieve good results (AUC: 0.82–0.94). Once properly validated, such models could greatly improve cancer care, especially in areas with limited medical resources. This comprehensive review aims to compile knowledge about state-of-the-art AI models used for breast cancer lymph node metastasis detection, discusses proper validation techniques and potential pitfalls and limitations, and presents future directions and best practices to achieve high usability in real-world clinical settings. Full article

Background: Due to recent changes in breast cancer treatment strategy, significantly more patients are treated with neoadjuvant systemic therapy (NST). Radiological methods do not precisely determine axillary lymph node status, with up to 30% of patients being misdiagnosed. Hence, supplementary methods for lymph node status assessment are needed. This study aimed to apply and evaluate machine learning models on clinicopathological data, with a focus on patients meeting NST criteria, for lymph node metastasis prediction. Methods: From the total breast cancer patient data (n = 8381), 719 patients were identified as eligible for NST. Machine learning models were applied for the NST-criteria group and the total study population. Model explainability was obtained by calculating Shapley values. Results: In the NST-criteria group, random forest achieved the highest performance (AUC: 0.793 [0.713, 0.865]), while in the total study population, XGBoost performed the best (AUC: 0.762 [0.726, 0.795]). Shapley values identified tumor size, Ki-67, and patient age as the most important predictors. Conclusion: Tree-based models achieve a good performance in assessing lymph node status. Such models can lead to more accurate disease stage prediction and consecutively better treatment selection, especially for NST patients where radiological and clinical findings are often the only way of lymph node assessment. Full article

Background: Children with Down syndrome (DS) lag behind typical children in the acquisition of developmental milestones, which could differ depending on body proportionality. We aimed to determine the difference in the acquisition of developmental milestones in children with DS with a disproportionate cephalization index (CI) compared to a proportionate CI. We created a motor development model that predicted milestone acquisition times. Methods: In this 20-year prospective cohort study, 47 children with DS aged 3 months to 5 years, followed up to 2020, were grouped according to the ratio of head circumference to birth weight (HC/BW) or CI into proportionate (CI < 1.1) and disproportionate (CI ≥ 1.1). We used a modified Munich Functional Developmental Diagnostic Scale that was assessed for reliability and content validity (Levene’s test and discriminant analysis) to determine 28 motor milestones. Linear regression was used to predict time to milestone acquisition, controlling for sex, maternal age, and birth weight. Results: Compared to proportionate CI, children with disproportionate CI were delayed in the milestone acquisition of a prone position by 2.81 months, standing before walking by 1.29 months, and a supine position by 1.61 months. Both groups required more time to reach standing after the acquisition of independent walking, but children with disproportionate CI reached those milestones later (4.50 vs. 4.09 months, p < 0.001). Conclusion: Children with disproportionate CI acquired milestones in a predictable order but slower than those with a proportionate CI. Our findings support the need to classify the degree of motor developmental delay in children with DS into unique functional groups rather than rely on clinicians’ arbitrary descriptions of the timing of developmental delays in children with DS. Full article

CD44 expressed in monocytes and lymphocytes seems to play a crucial role in gastrointestinal inflammation, such as the one occurring in the context of inflammatory bowel diseases. Differentially methylated genes are distinctly expressed across monocyte subpopulations related to the state of Crohn’s disease. Hence, the aim of this study was to detect CD44 expression in leukocyte subpopulations in relation to the type of IBD, therapy, and disease duration. Monocyte subpopulations CD14⁺⁺CD16⁻, CD14⁺⁺CD16⁺⁺, and CD14⁺CD16⁺ as well as other leukocytes were analyzed for their CD44 expression using flow cytometry in 46 patients with IBD and 48 healthy controls. Patients with Crohn’s disease treated with non-biological therapy (NBT) exhibited a lower percentage of anti-inflammatory CD14⁺CD16⁺⁺ monocytes, whereas NBT-treated patients with ulcerative colitis had lower expression of CD44 on CD14⁺CD44⁺ lymphocytes in comparison to controls, respectively. Conversely, patients with Crohn’s disease treated with biological therapy had a higher percentage of CD44⁺ granulocytes but lower expression of CD44 on anti-inflammatory monocytes compared to controls. Median fluorescence intensity (MFI) of CD44 on CD44⁺CD14⁺ lymphocytes was higher in ulcerative colitis patients treated with biological therapy compared to NBT. The percentage of classical CD14⁺⁺CD16⁻ monocytes was lower in the <9 years of IBD duration subgroup compared with the longer disease duration subgroup. The present study addresses the putative role of differentiation and regulation of leukocytes in tailoring IBD therapeutic regimes. Full article

Basic and clinical knowledge about Helicobacter pylori infections has been improved in the past. However, the translation of this knowledge into public health intervention has remained poor. A survey based cross-sectional study was performed to assess the factors regarding the H. pylori infection in the general population. The survey was conducted using a previously developed questionnaire, adapted for the population in Croatia. Respondents (N = 1131) had a good knowledge score with a median of 4 out of 5 correct answers (interquartile range: 2–4). Senior participants had a lower frequency of high knowledge answers about H. pylori (43.1%) compared to younger (56.1%) and middle-aged participants (51.5%, p = 0.014). Rural participants had a higher frequency of low knowledge answers compared to urban and suburban ones (21.7% vs. 9.5% and 9.4%, p = 0.011). Only 315 participants (27.9%) were screened for the H. pylori infection, despite high support for the screening programs among the untested (74.7%) and tested (85.7%). Habits of smoking (p = 0.036) and coffee drinking (p = 0.008) were associated with more symptoms after eradication therapy. Further education is needed for the groups at risk for H. pylori infection, especially to raise the awareness of the importance of screening programs. More research is warranted to assess the effects of dietary changes on therapy outcomes. Full article