International Journal of Emerging Trends in Health Sciences

Areca Nut Use and Its Association with Health Risk Perception among Youth Population in China

Li Zhiqiang — 2024-12-30

This study aimed to explore the use behaviors of areca nut, associated risk perceptions, and their relationship in the Chinese youth population. A total of Chinese youth aged 18-24 participated in an online survey using a self-administered questionnaire. The analysis revealed that while the overall rate of current areca nut use was low, a higher proportion of young males reported both current and prior use compared to females. The primary motivations for using areca nut included its perceived refreshing effects and stress relief, while curiosity and social sharing were the main reasons for trying it. Participants showed limited awareness of certain health risks, such as its potential to cause gastric inflammation, perforation, and malnutrition, compared to its oral health hazards. Insufficient knowledge of these health risks was identified as a key driver of areca nut use, alongside other factors such as smoking, alcohol consumption, and residing in areas where areca nut production and processing are prevalent. The findings highlight areca nut use as a growing health concern among Chinese youth, with use behaviors closely tied to risk perceptions. Targeted educational efforts to raise awareness about the harms of areca nut are crucial to addressing this issue.

Keywords Areca nut use, Risk perception, Youth health education

Machine learning techniques to predict and manage knee injury in sports medicine

Ravi Kumar — 2024-12-30

The aim of this study is to conduct a complete review of the current state of Machine Learning (ML) in injury prediction and prevention. In recent years, there has been a growing importance in the application of ML techniques to find out and reduce risks associated with injuries, particularly in high-risk industries such as sports, healthcare, and manufacturing. The essential part of our body is the knee, sports persons commonly injuries during play games. Sports injuries result in stress & strain connected with athletic events. Sports wounds can affect soft tissue (ligaments, muscles, cartilage, and tendons). Injuries are common in sports and can have significant physical, psychological, and financial consequences. The aim of our study was therefore to perform a systematic review of Machine learning (ML) techniques that could be used to improve injury prediction and prevention in sports. ML algorithms play a crucial role in extracting accurate information from given images and they also handle the complex pattern of MRI knee-related clarifications. In this paper, discuss a real-life imagery rule, ML design used to recognize meniscus tears, bone marrow edema, and general abnormalities on knee MRI tests accessible. The final evaluation demonstrated the highest accuracy achieved by the support vector machine, closely followed by the KNN model and the RF Tree method, all yielding comparable performance levels.

Keywords: MRI images, SVM, Random Forest, KNN, Automated analysis, ACL Injury, Machine Learning

Alteration of the gut microbiota in patients with nonalcoholic fatty liver disease and obstructive sleep apnea: a multiplied burden

Doina Georgescu — 2024-12-30

Nonalcoholic fatty liver disease (NAFLD), a globally prevalent condition with an increasing trend, is frequently associated with obstructive sleep apnea (OSA). This study investigated the clinical characteristics and gut microbiota alterations in patients with NAFLD and OSA. Comprehensive evaluations included clinical examinations, body mass index (BMI), blood pressure, laboratory tests, fatty liver index (FLI), liver imaging, cardiovascular assessments, polysomnography, and stool analysis for dysbiosis, with next-generation 16S ribosomal RNA sequencing performed in patients with dysbiosis. Patients with OSA exhibited more advanced liver damage, higher BMI and FLI, and increased prevalence of comorbidities such as diabetes, dyslipidemia, metabolic syndrome, atherosclerotic plaques, ischemic heart disease, diastolic heart failure, and pulmonary hypertension. Significant correlations were observed between the severity of nonalcoholic steatohepatitis (NASH) and dysbiosis, as well as between dysbiosis and FLI. Gut microbiota analysis revealed reduced biodiversity, imbalances in Firmicutes/Bacteroidetes ratios, and altered levels of key microbial species such as Faecalibacterium prausnitzii, Akkermansia muciniphila, and Prevotella spp. Patients with NAFLD and OSA exhibited more severe liver damage, increased metabolic and cardiovascular risks, and notable gut microbiota alterations. These findings suggest that gut microbiota assessment may offer valuable insights for tailored therapeutic interventions to improve patient outcomes.

Keywords: Nonalcoholic fatty liver disease; obstructive sleep apnea; gut microbiota alterations.

A rare case of lumbar intramedullary spinal cord metastasis from papillary thyroid carcinoma

Ercan Kaya — 2024-12-30

Intramedullary spinal cord metastasis (ISCM) from papillary thyroid carcinoma (PTC) is an extremely rare and poorly documented condition. This report presents the case of a 55-year-old woman with persistent back pain, in whom an intramedullary mass at the L1 level was identified. Despite no prior history of thyroid disease, pathology revealed the mass to be a metastasis from PTC, which was subsequently confirmed by thyroid ultrasound and biopsy. The patient underwent thyroid surgery and radioiodine treatment, leading to improvement in back pain, although sensory deficits persisted. This case underscores the rarity of spinal metastases as a presentation of PTC and highlights the importance of a multidisciplinary approach, with surgical intervention playing a key role in optimizing outcomes.

Keywords Intramedullary spinal cord metastasis, papillary thyroid carcinoma, spinal metastases, surgical intervention.