Category Archives: Review

Sodium-glucose transporter 2 inhibitors and their antiarrhythmic role: New insights and future perspective

Diana-Ioana Prația-Aron1, Dan-Alexandru Cozac1,2,3, Alina Scridon2,4

1. Emergency Institute for Cardiovascular Diseases and Transplantation of Targu Mures, Targu Mures, Romania
2. Physiology Department, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, Targu Mures, Romania
3. Doctoral School of Medicine and Pharmacy, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, Targu Mures, Romania
4. Center for Advanced Medical and Pharmaceutical Research, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, Targu Mures, Romania

DOI: 10.2478/amma-2025-0042

Sodium-glucose transporter 2 inhibitors have been identified as pleiotropic pharmacological agents with demonstrated efficacy in a wide range of pathologies. Given the strong association between arrhythmias and significant comorbidities, exploring the potential antiarrhythmic effects of sodium-glucose transporter 2 inhibitors represents a critical therapeutic opportunity, particularly considering the limited efficacy and adverse profile of current antiarrhythmic drugs. The antiarrhythmic mechanisms of sodium-glucose transporter 2 inhibitors operate through direct cardiac ion channel modulation. Along with the ion channel effects, sodium-glucose transporter 2 inhibitors improve gap junction coupling by modulating connexin-43, lower sympathetic tone, maximize mitochondrial function, and induce metabolic reprogramming through adenosine monophosphate-activated protein kinase/sirtuin 1 activation and autophagy enhancement. Translating these encouraging mechanisms into focused antiarrhythmic strategies still requires establishing clear cause-and-effect links between sodium-glucose transporter 2 inhibitor therapy and arrhythmia prevention. Nevertheless, the current evidence regarding these effects remains inconsistent, underscoring the necessity for further research to elucidate the underlying mechanisms and resolve existing controversies.

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Role of artificial intelligence in detecting and grading cataracts using color fundus photographs: A systematic review and meta-analysis

Pande Komang Wahyu Pradana1, Ida Ayu Prama Yanthi1,2, Abdi Sastra Gunanegara1

1. Division of Ophthalmology, RS Dharma Kerti Tabanan, Indonesia
2. Department of Ophthalmology, Udayana University, Indonesia

DOI: 10.2478/amma-2026-0005

Background: Cataracts are a leading cause of blindness and visual impairment worldwide, affecting millions of people. Early detection and accurate grading of cataracts are critical for timely intervention and improving patient outcomes. Artificial intelligence (AI), particularly deep learning, has emerged as a powerful tool for automating the detection and grading of cataracts using color fundus photographs.
Methods: A systematic review and meta-analysis was undertaken in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines; a thorough literature search through databases such as PubMed, IEEE Xplore, and Google Scholar was conducted. The search parameters were restricted to studies published within the time frame of January 2020 to March 2025.
Results: A total of six studies were included in this systematic review and meta-analysis. Utilizing DTA meta-analysis, sensitivity ranged from 0.88 to 0.99, while specificity ranged from 0.89 to 0.99. Diagnostic Odds Ratio was estimated at 88.5, indicating that patients with cataracts are nearly 89 times more likely to be correctly identified by the AI model than non-cataract patients being misclassified.
Conclusion: AI particularly deep learning, has made significant strides in detecting and grading cataracts using color fundus photographs. The high accuracy, cost-effectiveness, and accessibility of AI models make them a valuable tool for improving cataract screening and management. As research continues to advance, AI has the potential to revolutionize cataract care, enabling early detection and timely intervention for millions of people worldwide.

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Intrauterine growth restriction – monitoring and pregnancy outcomes: A narrative review

Liviu Moraru1, Melinda-Ildiko Mitranovici2, Raluca Moraru1

1. Department of Anatomy, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, Targu Mures, Romania
2. Department of Obstetrics and Gynecology, Emergency County Hospital Hunedoara, Hunedoara, Romania

DOI: 10.2478/amma-2026-0003

Intrauterine growth restriction is described as a fetus not reaching its growth potential during pregnancy. Placental malperfusion is the main cause of Intrauterine growth restriction . Management of Intrauterine Gowth Restriction includes monitoring and determining the time of birth in order to reduce the risks of complications. Our review explore the current knowledge with regard to the monitoring of pregnancies with Intrauterine Growth Restriction and the role of biomarkers in this process. The importance of this issue is based on the poor outcomes of the pregnacies with severe intrauterine growth restriction. Our results show that different organizations make different recommendations for diagnosis and management in case of intrauterine growth restriction, somehow contradictory. Which means that in addition to ultrasound measurements, Doppler velocimetry, cardiotocography, biomarkers for prediction and diagnosis should be identified. Different biomarkers such as angiogenic factors, proteomics, genomics etc have been explored, poor pregnancy outcomes being associated with severe intrauterine growth restriction. Finding specific biomarkers is of crucial importance, in the context of multidisciplinary management.

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Precision oncology: A narrative review of recent developments and challenges

Carolyn Muruthi1, Japheth Wambani Rapando2

1. Department of Biomedical Sciences, Medical College, Aga Khan University, Nairobi, Kenya
2. Department of Medical Microbiology and Parasitology, School of Medicine, Moi University, Eldoret, Kenya

DOI: 10.2478/amma-2025-0056

The mainstay generic therapies of cancer including chemotherapy, are partly effective in a subset of the patient population due to the complexity and heterogenous nature of the disease. Nevertheless, the inherent variability of cancer has steered cancer therapy towards the concept of precision medicine. The approach focuses on matching effective and accurate treatment on the genetic profile of a patient and different unique characteristics that distinguishes one patient from another. Currently, precision oncology has been driven by various innovations including liquid biopsy, next generation sequencing (NGS) and multi-omics integration. Recent advances in next generation-based sequences have enabled the analysis of analytes including circulating DNA and genomic DNA. Liquid biopsy has enabled minimal invasion alternative and real-time monitoring of tumour dynamics and analysis of treatment responses. Moreover, emerging technologies including artificial intelligence and nanotechnology has enhanced the sensitivity of liquid biopsy. Similarly, multi-omics integration offers insights into the interactions between transcriptomic, proteomic, epigenomic and genomic enabling the unravelling the complex molecular mechanism driving carcinogenesis. These advances have resulted in the discovery of novel biomarkers and diverse therapeutic targets for different types of cancers. However, despite the promising advancements, challenges remain, such as concerns on data privacy, need for clinical validation and computational limitations. Ongoing research is, therefore, critical to embrace precision oncology in routine clinical care.

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A data-driven approach to PCOS Diagnosis: Systematic review of machine learning applications in reproductive health

Akshay V P1, Ritvik Sriram2, Keerthana3, Delna N S4, Pranav Verma5, Bhanu Verma6, Mansi Trivedi7, Shanmukhi Mogalipuvvu8, Sasikala Kathiresan9, Lalitha Soumya Johnson10, Bhavit Bansal11, Muhammed Asif12, Shubhrit Shrivastava13, Liya Sebastian14

1. Mansarovar Global University, Bhopal, India
2. Tirunelveli Medical College, Tirunelveli, Tamil Nadu, India
3. IQVIA Bengaluru, Karnataka, India
4. BioDeskINDIA Labs, Bhopal, India
5. Chitkara college of pharmacy, Chitkara University, Rajpura, India
6. University School of Pharmaceutical Sciences, Rayat Bahra University, Sahauran, India
7. Humera Khan College of Pharmacy, University of Mumbai, Mumbai, India
8. Mamata academy of medical sciences, Hyderabad, Telangana, India
9. All India Institute of Medical Sciences, Madurai, India
10. Dr. Janaki Ammal Campus, Kannur University, Kannur, Kerala, India
11. Central Council for Research in Yoga and Naturopathy, Delhi, India
12. Centennial College, Toronto, Canada
13. BioDeskINDIA Labs, Bhopal, India
14. Nikola Tesla STEM High School, Redmond, USA

DOI: 10.2478/amma-2025-0054

Background and aim: Polycystic Ovary Syndrome (PCOS) is a prevalent endocrine disorder in reproductive-aged women, characterized by hormonal imbalances, anovulation, and metabolic abnormalities. This systematic review aims to evaluate the effectiveness, types, and diagnostic performance of ML algorithms applied in PCOS detection and classification, and to identify the most frequently used input features and methodological challenges in existing studies.
Methods: A systematic search was conducted across scholarly databased, but not limited to PubMed, Scopus, and Google Scholar for studies published between 2014 and 2024 using keywords related to PCOS and machine learning. Inclusion criteria focused on original, peer-reviewed studies applying ML models for PCOS diagnosis. Data were extracted on model type, input features, diagnostic accuracy, and study design. Quality assessment was performed using the PROBAST tool.
Results: Out of 450 identified studies, 34 met the inclusion criteria and passed the quality assessment. Supervised learning models such as Random Forest, SVM, and XGBoost showed high accuracy (up to 99%). Deep learning approaches, particularly Convolutional Neural Networks (CNNs), achieved accuracies between 95% and 99.89% in analyzing ultrasound images. Hybrid models integrating clinical and imaging data further enhanced performance. Common input features included BMI, LH/FSH ratio, AMH, and ultrasound-based ovarian morphology. However, few studies validated models on external datasets, and input feature selection lacked standardization.
Conclusion: Machine learning models such as supervised, deep learning, and hybrid approaches show strong potential in improving PCOS diagnosis by identifying complex patterns across multi-dimensional datasets. Challenges such as limited generalizability and data standardization remain, therefore future studies should focus on developing explainable ML tools, validating models in clinical settings, and leveraging diverse data types for robust, personalized PCOS diagnosis.

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Quantitative Real-Time PCR testing in the control of hepatitis B and C: Progress and challenges towards eradication by 2030

Iulia Patrascu

Clinical County Emergency Hospital Bistrita-Nasaud, Bistrița, Romania

DOI: 10.2478/amma-2025-0046

Worldwide, chronic hepatitis B and C infections remain a significant public health challenge, causing millions of cases of liver disease globally.
The objective of this article is to highlight the need for testing and monitoring hepatitis B and C virus infections using Real-Time PCR, as well as to analyze the implementation of strategies for the eradication of hepatitis in accordance with WHO targets for 2030.
This narrative review highlights the necessity, performance, advantages, limitations, and challenges of implementing Real-Time PCR testing in clinical practice and public health policies for hepatitis B and C.
The results show that Real-Time PCR has superior sensitivity and specificity in the early detection of active infection and monitoring of viral load, facilitating optimal therapeutic management. Serological testing retains its essential role in initial screening, identifying exposure to viruses. Vulnerable groups, including hemodialysis patients, people who inject drugs, HIV-positive patients, healthcare workers, and marginalized populations, have increased prevalence and require prioritization in testing. The main limitations reported include unequal access to PCR technology and potential technical errors. Proposed strategies for improving testing include expanding access to molecular techniques, awareness campaigns, standardization of protocols, and international collaborations to support screening and treatment.
The conclusions emphasize that integrating serological testing with Real-Time PCR and focusing on vulnerable groups are crucial for achieving the objectives.

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Polycystic ovary syndrome and infertility: A narrative review of diagnostic and therapeutic approaches

Adelina-Georgiana Vârciu1,2

1. Bistrița County Emergency Hospital, Bistrița, Romania
2. Platinia Medical Center, Bistrița, Romania

DOI: 10.2478/amma-2025-0050

Objective: To synthesize current evidence on mechanisms, diagnostic evaluation, and treatment of infertility in PCOS, with emphasis on phenotype-specific implications and integrative management.
Methods: A narrative review was conducted using PubMed, Scopus, and Web of Science from January 2015 to March 2024. Search terms included “PCOS,” “infertility,” “phenotype,” “letrozole,” “metformin,” “gonadotropins,” and “ART.” Eligible studies involved human females aged 18–45 years, written in English, and focused on PCOS-related infertility. Randomized trials, meta-analyses, and international guidelines were critically assessed for methodological rigor and clinical relevance.
Results: PCOS accounts for 70–80% of anovulatory infertility, with marked variability across phenotypes. Phenotype A, combining hyperandrogenism, ovulatory dysfunction, and polycystic ovarian morphology, carries the greatest reproductive and metabolic burden. Biomarkers such as AMH, testosterone, DHEAS, fasting insulin, and HOMA-IR improve risk stratification. Lifestyle modification restores ovulation in up to 60% of overweight patients. Letrozole is superior to clomiphene, while gonadotropins and ART are effective in resistant cases. Metformin enhances ovulatory and pregnancy outcomes in insulin-resistant women. IVF protocols using antagonists and agonist triggers improve safety by reducing ovarian hyperstimulation syndrome. Psychological comorbidities, particularly anxiety and depression, are frequent and negatively affect fertility outcomes.
Conclusion: PCOS-related infertility requires a personalized, multidisciplinary approach. Integration of phenotype-based assessment, biomarker evaluation, lifestyle intervention, and tailored reproductive strategies optimizes outcomes. Addressing metabolic and psychological dimensions further improves reproductive success and long-term health.

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Autonomic modulation in ventricular arrhythmias: Clinical insights and therapeutic opportunities

Ovidiu Șerban Marcu1, Dan Alexandru Cozac1,2,3, Alina Scridon3,4

1. Emergency Institute for Cardiovascular Diseases and Transplantation of Targu Mures, Targu Mures, Romania
2. Doctoral School of Medicine and Pharmacy, George Emil Palade University of Medicine, Pharmacy, Science, and Technology Targu Mures, Targu Mures, Romania
3. Physiology Department, George Emil Palade University of Medicine, Pharmacy, Science, and Technology Targu Mures, Targu Mures, Romania
4. Center for Advanced Medical and Pharmaceutical Research, George Emil Palade University of Medicine, Pharmacy, Science, and Technology Targu Mures, Targu Mures, Romania

DOI: 10.2478/amma-2025-0040

Recent evidence establishes robust causal relationships between autonomic nervous system dysfunction and ventricular arrhythmias through multiple converging mechanisms. Direct neural recording studies demonstrate that sympathetic discharge from the left stellate ganglion immediately precedes ventricular fibrillation. At the same time, mechanistic investigations reveal that nerve growth factor-mediated sympathetic sprouting creates heterogeneous innervation patterns, directly triggering arrhythmogenesis. Although genetic syndromes like Brugada syndrome show opposing patterns with parasympathetic dominance driving arrhythmic events, disease-specific autonomic patterns have emerged, with heart failure and post-myocardial infarction displaying sympathetic overactivation and parasympathetic withdrawal. Current predictive tools show significant advances, but implementation challenges persist. The most clinically validated method is meta-iodobenzylguanidine imaging, and when using standardized protocols, heart rate variability analysis shows dependable prognostic value. Therapeutic interventions reveal mixed clinical outcomes. While beta-blockers remain effective in reduced ejection fraction populations, questions regarding benefits in preserved ejection fraction patients persist. Stellate ganglion blocks show promise for managing electrical storms, achieving a 62% reduction in ventricular arrhythmias. However, major clinical trials have yielded disappointing results for spinal cord stimulation and cardiac sympathetic denervation. Future directions emphasize personalized medicine approaches integrating genetic data, advanced imaging, and artificial intelligence for biomarker-guided therapy selection, representing the next frontier in precision cardiology for arrhythmia management.

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Pharmacological management of intraoperative hypertensive crises in pheochromocytoma: A narrative review of esmolol, nicardipine, and sodium nitroprusside

Gabriela Salari, Mihaela Butiulca

Targu Mures County Emergency Clinical Hospital, Mures, Romania

DOI: 10.2478/amma-2025-0029

Management of pheochromocytoma, particularly in the perioperative period, requires a tailored pharmacological approach to address hemodynamic instability and hypertensive crises. This review evaluates the safety, efficacy, and clinical context of esmolol, nicardipine, and sodium nitroprusside in managing blood pressure and heart rate during pheochromocytoma resection. Esmolol, an ultra-short-acting β1-adrenergic antagonist, is essential in controlling tachyarrhythmias and myocardial stress in the perioperative period. Its rapid onset and short half-life enable precise titration, though continuous monitoring is required to mitigate the risk of bradycardia and hypotension. Nicardipine, a dihydropyridine calcium channel blocker, is effective in controlling acute hypertensive episodes and maintaining coronary perfusion. Its selectivity for vascular smooth muscle makes it an ideal agent for patients with low ejection fraction, minimizing cardiac depression. In contrast, sodium nitroprusside, a direct nitric oxide donor, provides immediate and reversible vasodilation, which is crucial for managing hypertensive crises during surgery. However, its use necessitates close monitoring due to the risk of cyanide and thiocyanate toxicity with prolonged use.
Choosing the most appropriate antihypertensive therapy depends on patient-specific factors such as comorbidities and the severity of hemodynamic changes. Each medication’s therapeutic effect, side effects, and risk profiles should be carefully considered to optimize clinical outcomes in high-risk patients undergoing pheochromocytoma surgery. This review highlights the importance of understanding the pharmacodynamics and appropriate use of these agents in clinical practice to improve patient management and outcomes.

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Point-of-care ultrasound in palliative care management of malignant pleural effusion in outpatients and nursing home residents: A narrative review

Corina Marginean1, Bianca Emilia Ciurba2, Bianca Liana Grigorescu3

1. Pulmonology Department, Mures County Clinical Hospital, Targu Mures, Romania; Oncology Department, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, Romania
2. Pulmonology Department, Bistrita County Emergency Clinical Hospital, Bistrita, Romania
3. Anesthesiology and Intensive Therapy Department, Emergency Mures County Clinical Hospital, Targu Mures, Romania; Anesthesiology and Intensive Therapy Department, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, Romania

DOI: 10.2478/amma-2025-0021

Early integration of palliative care for patients with malignant pleural effusion (MPE) significantly improves symptom control, quality of life, and reduces healthcare costs. Despite well-developed palliative care services in Romania, timely access to multidisciplinary care remains challenging, particularly in outpatient settings and nursing homes. Point-of-Care Ultrasound (POCUS) has emerged as a valuable diagnostic and therapeutic tool in managing malignant pleural effusions within various clinical settings, including hospitals, outpatient clinics, home care, and nursing homes. Its diagnostic advantages include high accuracy in identifying small effusions and differentiating malignant from benign conditions. Therapeutically, POCUS significantly enhances the safety and effectiveness of procedures such as thoracentesis, reducing complications and the need for hospital transfers.
This review highlights how POCUS aligns with key palliative care principles by alleviating patient burden and enhancing comfort. We advocate for its adoption as standard practice in both inpatient and outpatient palliative care, supported by targeted training and standardized protocols. Further studies should assess the long-term clinical benefits and economic implications of routine POCUS use in palliative care.

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