Drug-induced sleep endoscopy (DISE) is used for directly visualizing sites of obstruction among patients with obstructive sleep apnea (OSA). Owing to the scarcity of data, there is still no consensus on the anesthetic regimen for conducting pediatric DISE.

This paper presents a 5-year-old patient who underwent DISE using an opioid-sparing regimen with dexmedetomidine and propofol infusion.

Simultaneous dexmedetomidine and propofol infusion is a promising opioid-sparing regimen for pediatric DISE.

Human ; Male ; Child Preschool: 2-5 Yrs Old ; Endoscopy ; Propofol ; Dexmedetomidine ; Sleep Apnea, Obstructive ; Anesthetics ; Apnea ; Consensus ; Paper ; Patients ; Pharmaceutical Preparations ; Research Report ; Sleep ; Sleep Apnea Syndromes ; World Health Organization

Achondroplasia (ACH) is a common inherited skeletal dysplasia (inherited dwarfism) that compromises quality of life across the lifespan. In 2021, vosoritide became the first approved precision therapy for ACH and is now available in more than 40 countries. Compared with prior symptomatic measures, vosoritide has demonstrated favorable efficacy and a reassuring safety profile. Nevertheless, existing international ACH guidelines largely emphasize complication management and symptomatic care, and there is no unified consensus on pharmacologic therapy. To address this gap, an international expert group developed the International Consensus Guidelines for the Implementation and Monitoring of Vosoritide Therapy in Patients with Achondroplasia providing systematic recommendations that span the continuum of care - from initial patient contact and pre-treatment assessment to medication counseling, injection training, and long-term outcome monitoring. These recommendations complement and refine current management and nursing protocols for individuals with ACH and offer practical guidance for clinicians across diverse regions. This article highlights key elements of the guideline to provide evidence-based support and clinical direction for healthcare professionals in China treating children with ACH using vosoritide.
Humans ; Achondroplasia/drug therapy* ; Consensus ; Practice Guidelines as Topic ; Child

Background: A certain percentage of the vaccinated population initially did not want to get vaccinated but changed their minds (from 30% to 70%). By October 2022, World Bank reported that the Philippines had 77.8% COVID-19 vaccination rate. Knowing the factors that changed their decision can help improve the vaccination rate. Objective: This survey aimed to identify the factors that influence positive change in vaccination decisions. Methods: This survey was conducted in the Philippines among Filipinos aged 18-80 years old between March to April 2022. The dependent variable in the study was decision change, a binary variable coded as 1 for a vaccinated person who changed their decision from no to yes and 0 for an unvaccinated person who did not change their decision from yes to no. Results: Age (adjusted odds ratio [aOR] = 0.92, 95% CI = 0.89-0.96) and having a college degree (aOR=11.707, 95% CI=3.23-42.41) are related to changing decisions. Young and college degree holders are likely to change their decisions positively about getting vaccinated. Employer requirement also influences decision change because it affects a person's livelihood. High scores on vaccine confidence (aOR = 1.181, 95% CI = 1.12-1.25) and awareness (aOR = 1.318, 95% CI = 1.08-1.61) are associated with decision change. Conclusion Being young, educated, employed with a requirement to vaccinate, and having high vaccine awareness and confidence are strongly associated with a positive change in the decision to get vaccinated.
Vaccines ; Vaccination ; Philippines ; Awareness ; Covid-19

BACKGROUND

The COVID-19 pandemic disrupted education worldwide, prompting a rapid shift to emergency remote teaching that challenged students’ learning and mental health. Nursing students, in particular, faced heightened pressures due to the suspension or online adaptation of essential clinical experiences, alongside the need to master theoretical and practical competencies. Emerging evidence indicates that such stressors adversely affect students’ emotional and psychological well-being, potentially influencing academic outcomes. Understanding the relationship between mental health and academic performance among nursing students is crucial for developing targeted interventions that support their well-being and professional readiness.

OBJECTIVE

This study analyzed the mental health status and academic performance of graduating nursing students during the challenging period of remote learning amid the pandemic in a government school in Leyte.

METHODS

The study utilized a descriptive correlational design to explore the relationships between mental health status and academic performance among nursing students. A modified self-administered questionnaire was utilized to gather data. Ethical approval from Eastern Visayas Health Research and Development ConsortiumEthics Review with ERC number 2023-024 was secured, and data collection occurred through various methods. Data analysis used SPSS version 24, emphasizing the importance of understanding these relationships in educational settings.

RESULTS

The study assessed the demographic profile, online learning attributes, mental health status, and academic performance of 20 nursing students during the pandemic. All students passed their courses, despite reporting moderate emotional loneliness and irritability, but minimal fear of COVID-19. Significant correlations were found between demographic factors and mental health indicators. The null hypothesis, suggesting no relationship between demographic factors and mental health, is void, as significant associations were identified. Recommendations include enhancing mental health support in nursing education to address these challenges.

CONCLUSION

This study highlights the experiences of 20 nursing students from a government college in Leyte during the COVID-19 pandemic. Predominantly young women from rural, low-income backgrounds, these students faced challenges like poor internet access but successfully completed their academic requirements, showcasing resilience. While they reported low fear of COVID-19, moderate emotional loneliness and irritability indicated underlying mental health issues. The findings stress the need for educational institutions to provide mental health support and address the digital divide to enhance student well-being and success.

Human ; Male ; Female ; Young Adult: 19-24 Yrs Old ; Adult: 25-44 Yrs Old ; Statistics As Topic ; Psychological Well-being ; Indicators And Reagents ; Students, Nursing ; Suspensions ; Academic Performance ; Learning ; Pandemics ; Nursing ; Education, Nursing ; Covid-19 ; Mental Health

BACKGROUND

Stunting remains a major public health issue in Indonesia, particularly in regions like Pandeglang Regency, where prevalence rates are high. Understanding the contributing factors is essential for targeted interventions.

OBJECTIVE

This study aimed to analyze factors associated with stunting among toddlers using a mixed-methods approach.

METHODS

A cross-sectional mixed-methods study was conducted in two health centers in Banten Province from December 2021 to January 2022. Quantitative data were collected using a structured questionnaire and analyzed using chi-square tests (pRESULTS

There is a relationship between maternal knowledge, history of exclusive breastfeeding, history of supplementary feeding, support from health workers, and socio-economic status with the prevalence of stunting. However, the pattern of exclusive breastfeeding and seeking health services in the working areas of Bangkonol Health Center and Kaduhejo Health Center, Pandeglang Regency, is not good enough and needs to be improved. Health workers need to educate mothers with toddlers about patterns of providing complementary feeding, food preparation, and storage, and basic health practices to prevent stunting.

RESULTS

There is a relationship between maternal knowledge, history of exclusive breastfeeding, history of supplementary feeding, support from health workers, and socio-economic status with the prevalence of stunting. However, the pattern of exclusive breastfeeding and seeking health services in the working areas of Bangkonol Health Center and Kaduhejo Health Center, Pandeglang Regency, is not good enough and needs to be improved. Health workers need to educate mothers with toddlers about patterns of providing complementary feeding, food preparation, and storage, and basic health practices to prevent stunting.

Human ; Infant: 1-23 Months ; Child Preschool: 2-5 Yrs Old ; Public Health ; Prevalence ; Methods ; Indonesia ; Health ; Growth Disorders ; Comprehension

BACKGROUND

Generative artificial intelligence (GenAI) is increasingly integrated into healthcare, including occupational therapy (OT), with potential applications in its service delivery and clinical decision-making. While GenAI offers promising educational and clinical support, its generative nature introduces risks related to contextual accuracy, transparency, and ethical use, particularly within supervised clinical training settings where professional judgment is still developing. Empirical research examining GenAI integration in OT clinical training remains limited, especially within the Philippine context.

OBJECTIVE

This is a protocol for a study which aims to explore the perceptions of OT interns in Manila, Philippines, regarding GenAI integration in clinical training, including perceived benefits, challenges, and ethical considerations, guided by Rogers’ Diffusion of Innovations Theory

METHODS

This qualitative study protocol describes an exploratory design that will be used to gather rich and contextualized insights from 24 to 32 OT interns enrolled in universities in Manila with established institutional AI-use policies. Data will be collected through semi-structured online focus group discussions (FGD). Thematic analysis will be used with assistance from atlas.ti. 

EXPECTED RESULTS

The study is expected to generate meaningful themes that describe the perceptions of OT interns regarding the integration of GenAI within supervised clinical training contexts. Results are expected to reflect how interns perceive the role of GenAI in supporting clinical decision-making, as well as its perceived challenges and ethical concerns related to institutional policies, data privacy, reliability, and variability in AI-generated outputs.

Human ; Therapeutics ; Universities ; Volition ; Philippines ; Clinical Decision-making ; Artificial Intelligence

Abstract Intestinal ultrasound (IUS) is increasingly recognized as a vital, non-invasive tool for managing inflammatory bowel disease (IBD) due to its real-time assessment capabilities and patient comfort. However, the lack of standardized training pathways remains a significant barrier to its widespread adoption, particularly in low- and middle-income settings. This editorial evaluates the implementation of a mastery learning-based workshop in Indonesia designed to enhance IUS skills among physicians. The mastery learning framework—incorporating flipped learning, deliberate practice, and real-time feedback led to significant improvements in technical performance with large effect sizes. Despite these gains, only about two-thirds of participants achieved competency in sigmoid colon scanning, and only half met the standard for terminal ileum assessment. This suggests that while short-term intensive workshops are effective for early skill acquisition, they may be insufficient for ensuring consistent proficiency in technically demanding tasks. Mastery learning offers a structured and reproducible approach to gastroenterology procedural training. To translate these initial educational gains into durable clinical expertise, future programs should consider longitudinal curricula that include sustained practice, mentorship, and ongoing assessment.
Intestinal ultrasound ; mastery learning ; Inflammatory bowel disease ; medical education ; competency-based training ; gastroenterology

Urinary tract infections (UTIs) are among the most common bacterial infections worldwide, requiring timely and accurate diagnosis to guide appropriate therapy and reduce antimicrobial resistance. Although urine culture remains the diagnostic gold standard, its prolonged turnaround time and susceptibility to pre-analytical variability limit its clinical efficiency. Recent advances in artificial intelligence (AI) have positioned urinalysis as a promising alternative diagnostic approach, utilizing machine learning and deep learning algorithms for automated analysis and prediction. This review synthesizes current evidence on AI applications in urinalysis for UTI diagnosis, examining computational techniques, diagnostic performance, clinical integration, limitations, and future directions. The literature demonstrates that AI-powered urinalysis can achieve diagnostic accuracy comparable to urine culture, with high sensitivity and specificity while reducing diagnostic time. Integration of AI into clinical workflows has the potential to enhance decision-making, streamline laboratory processes, and support antimicrobial stewardship. However, challenges related to data heterogeneity, algorithm interpretability, validation, and regulatory requirements remain significant barriers to widespread adoption. Overall, AI-driven urinalysis represents a transformative opportunity to complement the existing diagnostic standard and advance more rapid, efficient, and personalized approaches to UTI management.

Human ; Artificial Intelligence ; Urinalysis ; Urinary Tract Infections ; Machine Learning ; Deep Learning

Consensus method is not only a common technical approach to the formulation of the acupuncture-moxibustion guidelines, but also an important way to form the recommended treatment protocols of acupuncture-moxibustion guidelines. Based on the theory of implementation science, the paper explores the influencing factors of consensus-reaching to acupuncture-moxibustion guidelines, and puts forward methodological suggestions on the consensus method performed in the formulation of acupuncture-moxibustion guidelines, so as to advance the rational application of consensus method and enhance the scientificity and transparency of acupuncture-moxibustion guidelines.
Moxibustion/standards* ; Humans ; Acupuncture Therapy/standards* ; Consensus ; Practice Guidelines as Topic

This study aims to develop an abdominal acupoint localization system based on computer vision and convolutional neural networks (CNNs). To address the challenge of abdominal acupoint localization, a multi-task CNNs architecture was constructed and trained to locate the Shenque (CV8) and human body boundaries. Based on the identified Shenque (CV8), the system further deduces key characteristics of four acupoints: Shangwan (CV13), Qugu (CV2), and bilateral Daheng (SP15). An affine transformation matrix is applied to accurately map image coordinates to an acupoint template space, achieving precise localization of abdominal acupoints. Testing has verified that this system can accurately identify and locate abdominal acupoints in images. The development of this localization system provides technical support for TCM remote education, diagnostic assistance, and advanced TCM equipment, such as intelligent acupuncture robots, facilitating the standardization and intelligent advancement of acupuncture.
Acupuncture Points ; Humans ; Deep Learning ; Abdomen/diagnostic imaging* ; Neural Networks, Computer ; Acupuncture Therapy ; Image Processing, Computer-Assisted