Statistical techniques for predicting rupture risk in abdominal aortic aneurysms: A contribution based on bootstrap

New Trends of Personalized Medicine in the Management of Abdominal Aortic Aneurysm: A Review

Abdominal aortic aneurysm (AAA) is a significant vascular condition characterized by the dilation of the abdominal aorta, presenting a substantial risk of rupture and associated high mortality rates. Current management strategies primarily rely on aneurysm diameter and growth rates to predict rupture risk and determine the timing of surgical intervention. However, this approach has limitations, as ruptures can occur in smaller AAAs below surgical thresholds, and many large AAAs remain stable without intervention. This review highlights the need for more precise and individualized assessment tools that integrate biomechanical parameters such as wall stress, wall strength, and hemodynamic factors. Advancements in imaging modalities like ultrasound elastography, computed tomography (CT) angiography, and magnetic resonance imaging (MRI), combined with artificial intelligence, offer enhanced capabilities to assess biomechanical indices and predict rupture risk more accurately. Incorporating these technologies can lead to personalized medicine approaches, improving decision-making regarding the timing of interventions. Additionally, emerging treatments focusing on targeted delivery of therapeutics to weakened areas of the aortic wall, such as nanoparticle-based drug delivery, stem cell therapy, and gene editing techniques like CRISPR-Cas9, show promise in strengthening the aortic wall and halting aneurysm progression. By validating advanced screening modalities and developing targeted treatments, the future management of AAA aims to reduce unnecessary surgeries, prevent ruptures, and significantly improve patient outcomes.

Narrative Review of Risk Assessment of Abdominal Aortic Aneurysm Rupture Based on Biomechanics-Related Morphology

CLINICAL IMPACT

Studies have shown that the biomechanical indicators based on multi-scale models are more effective in accurately assessing the rupture risk of AAA. To meet the need for clinical monitoring and rapid decision making, the typical morphological parameters associated with AAA rupture and their relationships with the mechanical environment have been summarized, which provide a reference for clinical preoperative risk assessment of AAA.

The Ratio of the Size of the Abdominal Aortic Aneurysm to That of the Unchanged Aorta as a Risk Factor for Its Rupture

Background: A ruptured abdominal aortic aneurysm is a severe condition associated with high mortality. Currently, the most important criterion used to estimate the risk of its rupture is the size of the aneurysm, but due to patients’ anatomical variability, many aneurysms have a high risk of rupture with a small aneurysm size. We asked ourselves whether individual differences in anatomy could be taken into account when assessing the risk of rupture. Methods: Based on the CT scan image, aneurysm and normal aorta diameters were collected from 186 individuals and compared in patients with ruptured and unruptured aneurysms. To take into account anatomical differences between patients, diameter ratios were calculated by dividing the aneurysm diameter by the diameter of the normal aorta at various heights, and then further comparisons were made. Results: It was found that the calculated ratios differ between patients with ruptured and unruptured aneurysms. This observation is also present in patients with small aneurysms, with its maximal size below the level that indicates the need for surgical treatment. For small aneurysms, the ratios help us to estimate the risk of rupture better than the maximum sac size (AUC: 0.783 vs. 0.650). Conclusions: The calculated ratios appear to be a valuable feature to indicate which of the small aneurysms have a high risk of rupture. The obtained results suggest the need for further confirmation of their usefulness in subsequent groups of patients.

Changes in mental health during the COVID-19 crisis in Romania: A repeated cross-section study based on the measurement of subjective perceptions and experiences

The coronavirus 2019 (COVID-19) pandemic has caused dramatic changes in the daily lives of Romanians, affecting their mental health. The COVID-19 pandemic has evolved at three significant peaks, which sequentially occurred on: April 29, 2020; September 18, 2020; and the third wave registered the highest severity on November 27, 2020. Little is known about the mental health changes during this phase of this pandemic. This study evaluated mental health levels in Romania at the end of the first wave of the pandemic and amidst the third and most severe wave. We administered a two-phase internet-based survey among 543 and 583 participants, respectively, recruited through snowball sampling at a 6-month interval. The IPAT Anxiety Scale measured anxiety, the Beck's Depression Inventory measured depression, and the Dissociative Experiences Scale measured dissociation. We observed no statistically significant differences in the number of participants with clinically relevant scores at either time point. In the first survey, 23.8%, 19.2%, and 32.6% reported being clinically anxious, clinically depressed, and showed clinical dissociation, respectively. Binary logistic regressions indicated that age, education level, and previous traumatic events were significantly associated with clinical levels of anxiety and depression. Moreover, multiple linear regression analysis reported a collective significant effect of gender, age, psychological impact, traumatic events, and dissociation on predicting high levels of anxiety and depression. Romanian adults' mental health status was affected during the COVID-19 pandemic, and it did not change 6 months after the first lockdown.