With the expanding use of endovascular thrombectomy (EVT) for distal and medium vessel occlusions (DMVOs), evaluating how anesthesia type affects clinical outcomes is essential. This meta-analysis compared outcomes between general anesthesia (GA) and non-GA in patients undergoing EVT for DMVOs.

To explore lymphoma survivors' care experiences and needs post-treatment and to determine optimal information and services for a lymphoma survivorship program from the perspectives of both survivors and oncologists.

Intracranial atherosclerotic disease (ICAD) is a major cause of ischemic stroke, particularly in high-risk populations. Endovascular treatment options, including drug-coated balloon (DCB) angioplasty and stent angioplasty (SA), have been explored as alternatives for patients with severe stenosis or refractory symptoms. However, the comparative efficacy and safety of these interventions remain a topic of debate.

IntroductionBlood blister-like aneurysms (BBLAs) are rare, typically found in the anteromedial supraclinoid segment of the internal carotid artery, and are related to high morbidity and mortality rates. Although microsurgery has been traditionally used to manage BBLAs, the Endovascular treatment (EVT) is gaining importance. We aim to compare these two methods using a systematic review and meta-analysis.MethodsA systematic search of PubMed, Embase, and Web of Science databases following PRISMA guidelines was conducted. We pooled odds ratios (OR) with 95% confidence intervals using a random-effects model, and I to assess heterogeneity. Eligible studies compared microsurgery and EVT for BBLAs. Outcome measures included Good and Poor clinical outcomes by Modified Rankin Scale (mRS), Epilepsy, Infection, Intracranial Hemorrhage, Vasospasm, Ischemic Events, Mortality, Operative Rupture, Rebleeding, Recurrence, and Retreatment.ResultsFifteen studies with 770 patients were included (401 microsurgery; 369 EVT). EVT appeared to be protective against Poor Clinical Outcomes (mRS >2), with an OR of 0.43 (95% CI 0.21 to 0.87), and Ischemic Events, having an OR of 0.33 (95% CI 0.18 to 0.61). Microsurgery was related to higher Mortality, with an OR of 2.72 (95% CI 1.46 to 5.06), and Operative Rupture, with 7.72 (95% CI 3.50 to 17.07). EVT also statistically favored the Good Clinical Outcomes analysis, with an OR of 3.13 (95% CI 1.40 to 6.98). Epilepsy, Infection, Intracranial Hemorrhage, and Vasospasm occurrence showed no significant statistical difference.ConclusionDespite microsurgery being traditionally used in BBLAs management, EVT has been shown to be a safer and lower-morbidity option.

Changes to food systems and food environments across the Pacific Islands region have influenced dietary behaviors. While dietary intake is limited, it is believed that fruit and vegetable consumption is low within these populations. Given the benefits of fruit and vegetable consumption, this exploratory study aimed to identify the motivators and facilitators of fruit and vegetable intake in a subset of Tongan adults.

Middle childhood (ages 8-12 years) is a critical period for forming behavioral habits and reducing the risk for the development of skin cancer later in life. During this time, children develop more autonomy and spend more unsupervised time away from their parents. Professional agencies recommend that all children engage in regular sun protection behaviors and avoid the sun during peak daytime hours. Unfortunately, in middle childhood, child sun protection often declines and UV radiation exposure increases. Effective parenting involves balancing ways to encourage the child's increasing independence while providing practical assistance to ensure sun protection is implemented.

Cardiovascular diseases are among the major health problems that are likely to benefit from promising developments in quantum machine learning for medical imaging. The chest X-ray (CXR), a widely used modality, can reveal cardiomegaly, even when performed primarily for a non-cardiological indication. Based on pre-trained DenseNet-121, we designed hybrid classical-quantum (CQ) transfer learning models to detect cardiomegaly in CXRs. Using Qiskit and PennyLane, we integrated a parameterized quantum circuit into a classic network implemented in PyTorch. We mined the CheXpert public repository to create a balanced dataset with 2436 posteroanterior CXRs from different patients distributed between cardiomegaly and the control. Using k-fold cross-validation, the CQ models were trained using a state vector simulator. The normalized global effective dimension allowed us to compare the trainability in the CQ models run on Qiskit. For prediction, ROC AUC scores up to 0.93 and accuracies up to 0.87 were achieved for several CQ models, rivaling the classical-classical (CC) model used as a reference. A trustworthy Grad-CAM++ heatmap with a hot zone covering the heart was visualized more often with the QC option than that with the CC option (94% vs. 61%, < 0.001), which may boost the rate of acceptance by health professionals.