Uttaradit Hospital

Purpose The purpose of this study was to design, deploy, and evaluate a universal access–oriented emergency healthcare system that reduces barriers related to age, digital literacy, infrastructure limitations, and organizational fragmentation in rural settings. The research question addressed how a human-centric cyber-physical-human Internet of Things (IoT) platform can support equitable access to emergency healthcare for older adults in low-resource communities. Methods A Smart Information Management System and Emergency Medical Call System (SIMS–EMCS) was developed using a user-centered co-design approach. The platform integrates structured elderly health data management with real-time emergency communication through a widely used social messaging interface. The system was deployed in a rural subdistrict in Thailand and evaluated through real emergency use and controlled drills. Usability and system performance were assessed using a structured questionnaire administered to healthcare personnel, rescue teams, and community volunteers. Results The system achieved a 99.2% end-to-end communication success rate and reduced average emergency response time by 35% compared with conventional phone-based reporting. Usability evaluation yielded a “Good” overall score (mean 4.01 ± 0.65), indicating broad acceptability across users with diverse digital literacy levels. Conclusion The findings demonstrate that effective emergency healthcare access can be achieved without assuming high technical expertise or continuous connectivity, supporting core principles of universal access. SIMS–EMCS provides a replicable, human-centric model for inclusive emergency healthcare delivery in low- and middle-income country contexts.

Red blood cell (RBC) disorders indicate a significant global health burden among pediatric populations. Despite their prevalence, early and accurate diagnosis of pediatric RBC disorders remains a challenge. This is largely due to the complexity of hematological interpretation and limited access to specialized diagnostic expertise in resource-constrained settings. To address this gap, we developed a prototype digital health platform based on a machine learning model for the automated classification of RBC disorders in children using age and complete blood count (CBC) data. This retrospective study analyzed 4183 pediatric cases stratified into normal and abnormal RBC profiles. Five machine learning algorithms were systematically compared: binomial logistic regression, Gaussian naïve Bayes, decision tree, random forest, and adaptive boosting decision tree. All models were trained in age and routine CBC. The adaptive boosting decision tree demonstrated excellent classifier performance with an overall accuracy of 98.81%. With the abnormal class treated as the positive class, the model yielded a sensitivity of 97.85% and a precision of 99.66% for identifying abnormal cases, together with a specificity of 99.69% and a negative predictive value of 98.04% for identifying normal cases. The analysis of feature importance identified age and mean corpuscular volume as the most influential predictors, followed by hemoglobin and hematocrit. The best-performing model was subsequently integrated into the publicly accessible Kid CBC Checker (https://kidcbc.work/medservice/public/index.php), a prototype digital health platform powered by the adaptive boosting decision tree algorithm. This platform offers a reliable digital solution for the screening of pediatric RBC disorders to support evidence-based clinical decision-making for general physicians.

Objective:Adolescent smoking remains a significant public health concern. Effective smoking cessation interventions tailored for adolescents are essential, yet evidence comparing different strategies remains limited. We aimed to compare the effectiveness of various smoking cessation interventions for adolescents using a network meta-analysis (NMA) approach. Study design:Systematic review and network meta-analysis. Methods:We searched PubMed, EMBASE, CENTRAL, CINAHL, and PsycINFO from their inception to February 28, 2024. Randomized controlled trials comparing smoking cessation interventions for adolescents were included if they reported biochemical verification of smoking abstinence. Two pairs of researchers independently conducted the study selection. NMA was performed using a random-effects model in a frequentist framework. The quality of the included studies was assessed using Cochrane's Risk of Bias 2.0 tool. (PROSPERO CRD420251001010). Results:Twelve studies were included. No intervention demonstrated clear superiority over usual care or other comparators. Cognitive behavioral therapy (CBT)-based, CBT combined with nicotine replacement therapy (NRT), and Non-NRT interventions showed higher short-term abstinence (≤6 months) compared with usual care (UC), with relative risks (RRs) and 95% confidence intervals (CIs) of 2.31 (95%CI: 1.59-3.35), 2.44 (95%CI: 1.16-5.16), and 1.57 (95%CI: 1.09-2.28), respectively. However, these findings were based on very low-certainty evidence and were not sustained at longer follow-up. Conclusions:The evidence base for adolescent smoking cessation is limited and heterogeneous. While some interventions may offer short-term benefits, there is no robust evidence of sustained effectiveness beyond six months. High-quality trials are needed to establish effective long-term strategies.

This study aimed to evaluate the impact of Thailand’s hepatitis B virus (HBV) National Program Immunization (NPI), 32 years post-implementation, on infection rates and immunity in various age groups. A cross-sectional study involved 6,068 participants aged 6 months to 80 years from four regions in Thailand. Blood samples were tested for HBsAg, anti-HBs, and anti-HBc using a chemiluminescent immunoassay. Data were compared across age groups and with previous surveys from 2004 to 2014. Individuals born after the implementation of the NPI had significantly lower HBV infection rates (p < 0.0001). No HBsAg was detected in individuals under 20 years old. The prevalence of HBV carriers increased with age, from 0.3% in the 21–30 group to 4.3% in those over 60, with an overall prevalence of 1.7%. Percentages of seroprotected individuals (anti-HBs ≥ 10 mIU/mL) were high in young children but dropped to 19.4% in ages 11–20 and 12.5% in ages 21–30. Anti-HBc was found at very low rates in children but increased significantly after age 30. Thailand’s HBV NPI significantly reduced HBV infection rates, especially in younger populations. This study highlighted the program’s success and guided future elimination efforts to achieve hepatitis elimination goal by 2030.

Hepatitis A virus (HAV) is an RNA virus that causes acute hepatitis and is transmitted via the fecal-oral route. It has historically been highly endemic in Thailand, where most children develop lifelong immunity after infection. Economic development and improved sanitation have reduced HAV transmission, but immunity levels have declined, raising concerns about potential future outbreaks. This study aims to assess the seroprevalence of HAV antibodies in Thailand in 2024, 10 years after the last national survey in 2014, and to evaluate current immunity levels to inform public health strategies. A cross-sectional study was conducted in a population aged 6 months to 80 years across Thailand's geographic regions. A total of 4,312 serum samples were tested for anti-HAV antibodies using the chemiluminescent microparticle immunoassay. The seroprevalence data were compared with findings from previous surveys in 2004 and 2014. The study showed a significant decline in population immunity to HAV, with the age at which 50% of individuals had antibodies increasing from 36 in 2004 to 42 in 2014, and to 47 years in 2024. A majority of the population remained susceptible to HAV, particularly among younger age groups. Thailand has transitioned to low HAV endemicity, with a large proportion of the population lacking immunity. Despite the absence of significant outbreaks in recent decades, the risk of future outbreaks remains, particularly from imported cases. Enhanced surveillance and vaccination strategies are necessary to prevent future HAV transmission and manage public health risks.