Obesity remains a dominant risk factor for cardiovascular disease, yet its classification continues to rely heavily on body mass index (BMI)—a metric that fails to capture individual variability in fat distribution, metabolic health, and cardiometabolic risk. This narrative review analyzes 35 articles published between 2018 and 2025 to explore the limitations of BMI and outlines emerging strategies for obesity redefinition through a precision medicine lens. Drawing from recent advances in imaging, metabolomics, and genomic profiling, we highlight alternative metrics such as visceral adipose tissue (VAT), epicardial adipose tissue (EAT), waist-to-hip ratio (WHR), and multi-omic phenotyping that provide superior predictive value for cardiovascular outcomes. The review synthesizes data on metabolically healthy and unhealthy phenotypes, emphasizes the pathophysiological role of EAT in heart failure and arrhythmogenesis, and discusses the cardioprotective effects of pharmacologic agents such as glucagon-like peptide-1 (GLP-1) receptor agonists. Clinical implications include improved risk stratification, earlier disease detection, and individualized therapeutic targeting. Despite current barriers to widespread implementation—such as imaging cost, access to omics, and lack of guideline integration—this paradigm shift holds promise for refining cardiovascular prevention strategies. Redefining obesity using biologically informed, phenotype-based models is indispensable for aligning clinical practice with the complexities of modern cardiometabolic disease.

Background and Objectives: Impaired cognition and pain after surgery contribute to prolonged hospital stays and increased mortality rates. Thus, the development of preemptive algorithms for reducing their impact should be prioritized. The main objectives of the present study were to evaluate the efficiency of using virtual reality (VR) to treat postoperative cognitive decline and pain perception. Materials and Methods: The study was a prospective, monocentric, clinical study that included 51 patients who have undergone major abdominal surgery. The patients were divided into two groups: Control (n = 25) and VR (n = 26). The VR sessions consisted of 5–8 min exposure at 24–48 h after surgery. We considered the outcome variables, the mini-mental state examination, and visual analogue scale at 24–48 h after surgery. The dependent variables were age, social status, educational level, and duration of surgery. Results: We did not observe any differences in postoperative cognition deficit with regard to VR. The VR, however, successfully reduced postoperative pain intensity. Moreover, the patients’ age, surgery duration, level of education, and social status influenced the MMSE score at 24–48 h after surgery. Conclusions: Even if using VR does not alleviate short-term postoperative cognitive impairments, it could affect pain perception. Further studies are needed to support the use of VR in perioperative contexts.

Sepsis is one of the most common causes of morbidity and mortality worldwide. Despite the remarkable advances in modern medicine throughout the last century, the mortality rates associated with sepsis have remained significantly elevated, both in high- and low-income countries. The main difficulty in the diagnosis and treatment of septic patients is the tremendous heterogeneity of this condition. The vast heterogeneity that characterizes sepsis ranges from the clinical presentation to the biological aspects of the disease. Evidence-based medicine approaches sepsis as a homogenous syndrome and does not consider the individual discrepancies between septic patients. This approach may contribute to the poor outcomes of septic patients. In recent years, personalized medicine has gained significant interest. This novel form of medicine underlines the importance of understanding the genetic, epigenetic, and molecular basis of a disease in order to provide a more tailored approach for the patient. The study of “omics”, such as cytomics, genomics, epigenomics, transcriptomics, proteomics, and metabolomics, provides a deeper comprehension of the complex interactions between the host, the disease, and the environment. The aim of this review is to summarize the potential role of a personalized approach in sepsis management, considering the interactions between various “omics”.

Despite medical advances, sepsis and septic shock remain some of the leading causes of mortality worldwide, with a high inter-individual variability in prognosis, clinical manifestations and response to treatment. Evidence suggests that pulmonary sepsis is one of the most severe forms of sepsis, while liver dysfunction, left ventricular dysfunction, and coagulopathy impact the prognostic. Sepsis-related hypothermia and a hypoinflammatory state are related to a poor outcome. Given the heterogeneity of sepsis and recent technological progress amongst machine learning analysis techniques, a new, personalized approach to sepsis is being intensively studied. Despite the difficulties when tailoring a targeted approach, with the use of artificial intelligence-based pattern recognition, more and more publications are becoming available, highlighting novel factors that may intervene in the high heterogenicity of sepsis. This has led to the devise of a phenotypical approach in sepsis, further dividing patients based on host and trigger-related factors, clinical manifestations and progression towards organ deficiencies, dynamic prognosis algorithms, and patient trajectory in the Intensive Care Unit (ICU). Host and trigger-related factors refer to patients’ comorbidities, body mass index, age, temperature, immune response, type of bacteria and infection site. The progression to organ deficiencies refers to the individual particularities of sepsis-related multi-organ failure. Finally, the patient’s trajectory in the ICU points out the need for a better understanding of interindividual responses to various supportive therapies. This review aims to identify the main sources of variability in clustering septic patients in various clinical phenotypes as a useful clinical tool for a precision-based approach in sepsis and septic shock.

Cardiometabolic and cardiovascular risks are commonly assessed using body mass index (BMI) and static measures of adiposity; however, individuals with similar BMI frequently exhibit markedly different metabolic and cardiovascular outcomes. This heterogeneity reflects not only differences in fat distribution but also variation in adipose tissue function and its temporal regulation. Adipose tissue contains intrinsic circadian clocks that coordinate daily rhythms in lipid storage and mobilization, insulin sensitivity, adipokine secretion, and immune activity in alignment with sleep–wake and feeding–fasting cycles. Circadian misalignment, as occurs with shift work, irregular sleep, or mistimed food intake, disrupts this coordination and promotes adipose tissue dysfunction characterized by impaired rhythmic lipid handling, altered endocrine signaling, inflammation, fibrosis, and oxidative stress. Emerging evidence suggests that circadian dysregulation may differentially affect adipose depots, including visceral, epicardial, and perivascular fat, thereby linking chronodisruption to insulin resistance, endothelial dysfunction, atherosclerosis, heart failure phenotypes, and arrhythmia susceptibility. This narrative review synthesizes human, experimental, and translational studies examining adipose tissue circadian regulation as a functional determinant of cardiometabolic and cardiovascular risk beyond BMI. We also discuss the clinical implications of circadian-informed strategies, including chrononutrition and time-restricted eating, as potential tools to improve risk stratification and cardiometabolic health.

Antibody-mediated rejection (AMR) is a leading cause of kidney graft failure. Complement activation is involved in the AMR process. Our aim is to provide the current understanding of the pathophysiology related to complement-mediated injury in AMR, to present the current evidence regarding complement blockade in AMR management, and to point out emerging therapies and future directions in this area. The complement system plays an important role in the onset and progression of AMR. There is a balance between complement-dependent and -independent mechanisms in the development of rejection lesions. Classic and leptin pathways are involved in this process. C4d positivity is no longer a mandatory feature for AMR diagnosis but remains an independent predictor of negative outcomes. The current evidence regarding AMR treatment is limited. Terminal and proximal complement blockade has gained recognition in clinical practice. Eculizumab and C1 inhibitors are effective in the treatment of AMR as adjuvant therapies to the standard of care. The availability of novel complement inhibitors will lead to more effective and tailored treatment strategies.