Antibiotic resistance presents a critical challenge in healthcare, particularly among the elderly, where multidrug-resistant organisms (MDROs) contribute to increased morbidity, mortality, and healthcare costs. This review focuses on the mechanisms underlying resistance in key bacterial pathogens and highlights how aging-related factors like immunosenescence, frailty, and multimorbidity increase the burden of infections from MDROs in this population. Novel strategies to mitigate resistance include the development of next-generation antibiotics like teixobactin and cefiderocol, innovative therapies such as bacteriophage therapy and antivirulence treatments, and the implementation of antimicrobial stewardship programs to optimize antibiotic use. Furthermore, advanced molecular diagnostic techniques, including nucleic acid amplification tests and next-generation sequencing, allow for faster and more precise identification of resistant pathogens. Vaccine development, particularly through innovative approaches like multi-epitope vaccines and nanoparticle-based platforms, holds promise in preventing MDRO infections among the elderly. The role of machine learning (ML) in predicting resistance patterns and aiding in vaccine and antibiotic development is also explored, offering promising solutions for personalized treatment and prevention strategies in the elderly. By integrating cutting-edge diagnostics, therapeutic innovations, and ML-based approaches, this review underscores the importance of multidisciplinary efforts to address the global challenge of antibiotic resistance in aging populations.

The process of aging leads to a progressive decline in the immune system function, known as immunosenescence, which compromises both innate and adaptive responses. This includes impairments in phagocytosis and decreased production, activation, and function of T- and B-lymphocytes, among other effects. Bacteria exploit immunosenescence by using various virulence factors to evade the host’s defenses, leading to severe and often life-threatening infections. This manuscript explores the complex relationship between immunosenescence and bacterial virulence, focusing on the underlying mechanisms that increase vulnerability to bacterial infections in the elderly. Additionally, it discusses how machine learning methods can provide accurate modeling of interactions between the weakened immune system and bacterial virulence mechanisms, guiding the development of personalized interventions. The development of vaccines, novel antibiotics, and antivirulence therapies for multidrug-resistant bacteria, as well as the investigation of potential immune-boosting therapies, are promising strategies in this field. Future research should focus on how machine learning approaches can be integrated with immunological, microbiological, and clinical data to develop personalized interventions that improve outcomes for bacterial infections in the growing elderly population.

Aging is a fundamental biological process characterized by a progressive decline in physiological functions and an increased susceptibility to diseases. Understanding aging at the molecular level is crucial for developing interventions that could delay or reverse its effects. This review explores the integration of machine learning (ML) with multi-omics technologies—including genomics, transcriptomics, epigenomics, proteomics, and metabolomics—in studying the molecular hallmarks of aging to develop personalized medicine interventions. These hallmarks include genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, disabled macroautophagy, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, altered intercellular communication, chronic inflammation, and dysbiosis. Using ML to analyze big and complex datasets helps uncover detailed molecular interactions and pathways that play a role in aging. The advances of ML can facilitate the discovery of biomarkers and therapeutic targets, offering insights into personalized anti-aging strategies. With these developments, the future points toward a better understanding of the aging process, aiming ultimately to promote healthy aging and extend life expectancy.

Sarcopenia, an age-related decline in skeletal muscle mass, strength, and function, is increasingly recognized as a significant condition in the aging population, particularly among those with cardiovascular diseases (CVD). This review provides a comprehensive synthesis of the interplay between sarcopenia and cardiogeriatrics, emphasizing shared mechanisms such as chronic low-grade inflammation (inflammaging), hormonal dysregulation, oxidative stress, and physical inactivity. Despite advancements in diagnostic frameworks, such as the EWGSOP2 and AWGS definitions, variability in criteria and assessment methods continues to challenge standardization. Key diagnostic tools include dual-energy X-ray absorptiometry (DXA) and bioimpedance analysis (BIA) for muscle mass, alongside functional measures such as grip strength and gait speed. The review highlights the bidirectional relationship between sarcopenia and cardiovascular conditions such as heart failure, aortic stenosis, and atherosclerotic cardiovascular disease, which exacerbate each other through complex pathophysiological mechanisms. Emerging therapeutic strategies targeting the mTOR pathway, NAD+ metabolism, and senescence-related processes offer promise in mitigating sarcopenia’s progression. Additionally, integrated interventions combining resistance training, nutritional optimization, and novel anti-aging therapies hold significant potential for improving outcomes. This paper underscores critical gaps in the evidence, including the need for longitudinal studies to establish causality and the validation of advanced therapeutic approaches in clinical settings. Future research should leverage multi-omics technologies and machine learning to identify biomarkers and personalize interventions. Addressing these challenges is essential to reducing sarcopenia’s burden and enhancing the quality of life for elderly individuals with comorbid cardiovascular conditions. This synthesis aims to guide future research and promote effective, individualized management strategies.

Background: As the population ages, the prevalence of surgical interventions in individuals aged 65+ continues to increase. This poses unique challenges due to the higher incidence of comorbidities, polypharmacy, and frailty in the elderly population, which result in high peri-operative risks. Traditional preoperative risk assessment tools often fail to accurately predict post-operative outcomes in the elderly, overlooking the complex interplay of factors that contribute to risk in the elderly. Methods: A literature review was conducted, focusing on the predictive value of CGA for postoperative prognosis and the implementation of perioperative interventions. Results: Evidence shows that CGA is a superior predictive tool compared to traditional models, as it more accurately identifies elderly patients at higher risk of complications such as postoperative delirium, infections, and prolonged hospital stays. CGA includes assessments of frailty, sarcopenia, nutritional status, cognitive function, mental health, and functional status, which are crucial in predicting post-operative outcomes. Studies demonstrate that CGA can also guide personalized perioperative care, including nutritional support, physical training, and mental health interventions, leading to improved surgical outcomes and reduced functional decline. Conclusions: The CGA provides a more holistic approach to perioperative risk assessment in elderly patients, addressing the limitations of traditional tools. CGA can help guide surgical decisions (e.g., curative or palliative) and select the profiles of patients that will benefit from perioperative interventions to improve their prognosis and prevent functional decline.

Background: Cardiometabolic heart failure with preserved ejection fraction (HFpEF) is largely driven by obesity-related factors, including adipokines and bioactive peptides primarily secreted by the adipose tissue, such as leptin, adiponectin, and resistin. These molecules link metabolic dysregulation to cardiovascular dysfunction, influencing HFpEF progression and patient outcomes Methods: A comprehensive literature search was conducted in PubMed up to 20 November 2024, using keywords and MeSH terms, such as “HFpEF”, “adipokines”, “leptin”, “adiponectin”, and “resistin”, yielding 723 results. Boolean operators refined the search, and reference lists of key studies were reviewed. After screening for duplicates and irrelevant studies, 103 articles were included, providing data on adipokines’ roles in HFpEF pathophysiology, biomarkers, and therapeutic implications. Results: Both preclinical and clinical studies have demonstrated that adipokines play a role in modulating cardiovascular function, thereby contributing to the development of cardiometabolic HFpEF. Leptin promotes myocardial hypertrophy, fibrosis, endothelial dysfunction, and inflammation, though contradictory evidence suggests potential cardioprotective roles in subgroups like obese African American women. Adiponectin generally offers protective effects but presents a paradox, where elevated levels may correlate with worse outcomes, which may reflect either a compensatory response to cardiac dysfunction or a maladaptive state characterized by adiponectin resistance. Resistin is associated with increased cardiovascular risk through pro-inflammatory and pro-fibrotic effects, though its role in HFpEF requires further clarification. Other adipokines, like retinol-binding protein 4 and omentin-1, have emerged as potential contributors. Despite growing insights, clinical translation remains limited, underscoring a significant gap between experimental evidence and therapeutic application. Conclusions: Future research should focus on targeted interventions that modulate adipokine pathways to potentially improve HFpEF outcomes. Innovative treatment strategies addressing underlying metabolic disturbances and adipokine dysregulation are essential for advancing the management of this challenging condition.