Medical Response Research Articles

Wireless Body Sensor Networks for Real-Time Healthcare Monitoring: A Cost-Effective and Energy-Efficient Approach

Background: The continuous and accurate monitoring of physiological signals is critical for timely medical interventions, particularly in the context of chronic disease management and elderly care. The advent of Wireless Body Sensor Networks (WBSN) and Patient Health Monitoring Systems (PHMS) promises to revolutionize healthcare by integrating real-time data collection with advanced processing and communication technologies, enabling proactive medical responses through the Internet of Things (IoT). Methods: In this study, a WBSN-PHMS framework is proposed, leveraging a network of biomedical sensors to continuously monitor vital signs such as temperature and heart rate. The system includes a gateway node that wirelessly transmits sensor data to a cloud-based storage and processing system. Physiological data are processed in real-time using advanced algorithms to detect anomalies and trigger alerts. The health status is modeled using a function g(v,w(v),∅−1(v(w))−∂i(v,∂))g(v, w(v), \varnothing^{-1}(v(w)) - \partial_i(v, \partial))g(v,w(v),∅−1(v(w))−∂i?(v,∂)), which integrates patient-specific factors and real-time physiological states. The processed data are communicated efficiently through IoT platforms, ensuring that healthcare professionals receive timely alerts via mobile applications and specialized dashboards. Results: The WBSN-PHMS demonstrated high accuracy in detecting abnormal temperature and heart rate patterns, achieving detection rates of 98.61% and 99.43%, respectively. Additionally, the system improved overall patient health monitoring by 98.42%, offering a significant advancement in patient safety and healthcare efficiency. The cost-effectiveness of the system was established with a 96.21% improvement, while energy consumption was reduced by 23%, underscoring the sustainability of the technology. Conclusion: The WBSN-PHMS proves to be a reliable and efficient healthcare monitoring system that enhances patient outcomes through real-time data analysis and rapid medical responses. The system's ability to continuously monitor and analyze physiological signals in a non-intrusive manner positions it as a vital tool in modern medical practice, with the potential to revolutionize remote patient care and monitoring.

Medical Technologists: Are They Ready to Play Their Fair Share to Facilitate the Organ Donation and Transplantation Process in India?

Abstract Background: Organ shortage is a global health crisis. Health-care professionals are supposed to be frontrunners in the campaign for organ donation (OD) by being in a good position to liaise with patients and their families for obtaining consent for the OD process. We propose to highlight the current state of awareness, knowledge, attitudes, and practices (KAP) of Medical Technologists, a burgeoning relatively new branch of allied health professionals, in order to assess their readiness for facilitating OD/transplantation process in India. Objective: We aimed to study the current state of awareness, KAP of OD among Medical Technologists. Methods: A cross-sectional, survey-based study utilizing online Google forms for gathering medical technologist responses was conducted. Two surveys (Part A and Part B) were used to collect the requisite data. 146 and 114 participants responded to Part A and Part B, respectively, out of which 99 answered both surveys. Descriptive statistics using Excel and statistical analysis using SPSS version 22 were carried out. Results: Majority of participants were male (61%) within the 20–30 years’ age group, with 82.2% interacting with patients on a daily basis. The mean awareness, knowledge, death, legal, and attitude score were 4.89 ± 1.55 (54.3%), 3.925 ± 1.9514 (43.8%), 2.123 ± 1.328 (42.6%), 1.798 ± 1.00 (59.9%), and 6.11 ± 4.718 (87.3%) (mean ± standard deviation) (% of mean/total score), respectively. Among participants, 23.7% had already donated or signed donor cards, whereas 30.4% of those not yet donated are willing to donate when asked or sometime in the future. Majority of medical technologists showed positive attitudes leaning toward OD and supported further education and awareness. There was no significant difference in scores between donated versus not-donated groups (P > 0.05); however, attitudes scores were significantly higher for the willingness to donate group among current nondonors (P = 0.002). The death score was higher in the postgraduate group (P = 0.045) and knowledge (P = 0.016) and death scores (P = 0.032) were significantly correlated with educational qualification. Furthermore, medical technologists working in different specializations (i.e. areas of work) possessed significant difference in scores (knowledge (P = 0.003), death scores (P = 0.008), legal (P = 0.028), and attitude (P = 0.01) scores) while specifically legal score was significantly different between genders (P = 0.013). Interestingly, the legal score was associated with and moderately correlated with attitude score (P = 0.437). Knowledge score was associated with daily interaction (P = 0.034), death score was associated with area of work (P = 0.021); and legal score was associated with gender (P = 0.003) and area of work (P = 0.043). Conclusion: Since the medical technologist cadre in India can serve as an important bridge between patients and health-care organizations supporting OD; upgrading their knowledge, converting their attitudes into pro-OD practices, and honing their skills through training interventions to facilitate OD definitely needs to be invested in. Such investments in training interventions/courses implemented now can pay rich dividends in the years to come.

A National Disaster Medicine Quality Management Tool in an International Context – A Theoretical Study

Abstract The impact of disasters is changing, with disaster events becoming more complex and often affecting multiple countries simultaneously. Despite this, quality management systems have not yet been established in the field of disaster medicine. The German research project QUARZ-SAND, developed a national disaster medicine quality management system and an online registry. This theoretical study ascertains the current state of quality management in disaster medicine and compares existing initiatives to QUARZ-SAND and highlights advantages and synergies in the pooling of incident data, in view of improving resilience to national and transboundary disaster events. A systematic literature research was conducted on December 18, 2020 in the databases PubMed and LIVIVO. Existing disaster medicine quality management tools were identified and compared with QUARZ-SAND. It was determined that a lot of effort is still needed to get to an internationally accepted common standard and a tool such as a registry for evaluating medical disaster responses. A first step toward the establishment of a registry is the development of a standardized data set.

Variational autoencoders for generative modeling of drug dosing determinants in renal, hepatic, metabolic, and cardiac disease states

AbstractPhysiological determinants of drug dosing (PDODD) are a promising approach for precision dosing. This study investigates the alterations of PDODD in diseases and evaluates a variational autoencoder (VAE) artificial intelligence model for PDODD. The PDODD panel contained 20 biomarkers, and 13 renal, hepatic, diabetes, and cardiac disease status variables. Demographic characteristics, anthropometric measurements (body weight, body surface area, waist circumference), blood (plasma volume, albumin), renal (creatinine, glomerular filtration rate, urine flow, and urine albumin to creatinine ratio), and hepatic (R‐value, hepatic steatosis index, drug‐induced liver injury index), blood cell (systemic inflammation index, red cell, lymphocyte, neutrophils, and platelet counts) biomarkers, and medical questionnaire responses from the National Health and Nutrition Examination Survey (NHANES) were included. The tabular VAE (TVAE) generative model was implemented with the Synthetic Data Vault Python library. The joint distributions of the generated data vs. test data were compared using graphical univariate, bivariate, and multidimensional projection methods and distribution proximity measures. The PDODD biomarkers related to disease progression were altered as expected in renal, hepatic, diabetes, and cardiac diseases. The continuous PDODD panel variables generated by the TVAE satisfactorily approximated the distribution in the test data. The TVAE‐generated distributions of some discrete variables deviated from the test data distribution. The age distribution of TVAE‐generated continuous variables was similar to the test data. The TVAE algorithm demonstrated potential as an AI model for continuous PDODD and could be useful for generating virtual populations for clinical trial simulations.

Future Perspective of Risk Prediction in Aesthetic Surgery: Is Artificial Intelligence Reliable?

Artificial intelligence (AI) techniques are showing significant potential in the medical field. The rapid advancement in artificial intelligence methods suggests their soon-to-be essential role in physicians' practices. In this study, we sought to assess and compare the readability, clarity, and precision of medical knowledge responses provided by 3 large language models (LLMs) and informed consent forms for 14 common aesthetic surgical procedures, as prepared by the American Society of Plastic Surgeons (ASPS). The efficacy, readability, and accuracy of 3 leading LLMs, ChatGPT-4 (OpenAI, San Francisco, CA), Gemini (Google, Mountain View, CA), and Copilot (Microsoft, Redmond, WA), was systematically evaluated with 14 different prompts related to the risks of 14 common aesthetic procedures. Alongside these LLM responses, risk sections from the informed consent forms for these procedures, provided by the ASPS, were also reviewed. The risk factor segments of the combined general and specific operation consent forms were rated highest for medical knowledge accuracy (P < .05). Regarding readability and clarity, the procedure-specific informed consent forms, including LLMs, scored highest scores (P < .05). However, these same forms received the lowest score for medical knowledge accuracy (P < .05). Interestingly, surgeons preferred patient-facing materials created by ChatGPT-4, citing superior accuracy and medical information compared to other AI tools. Physicians prefer patient-facing materials created by ChatGPT-4 over other AI tools due to their precise and comprehensive medical knowledge. Importantly, adherence to the strong recommendation of ASPS for signing both the procedure-specific and the general informed consent forms can avoid potential future complications and ethical concerns, thereby ensuring patients receive adequate information.

Development of AI-generated medical responses using the ChatGPT for cancer patients

Background and objectiveTo develop a healthcare chatbot service (AI-guided bot) that conducts real-time conversations using large language models to provide accurate health information to patients. MethodsTo provide accurate and specialized medical responses, we integrated several cancer practice guidelines. The size of the integrated meta-dataset was 1.17 million tokens. The integrated and classified metadata were extracted, transformed into text, segmented to specific character lengths, and vectorized using the embedding model. The AI-guide bot was implemented using Python 3.9. To enhance the scalability and incorporate the integrated dataset, we combined the AI-guide bot with OpenAI and the LangChain framework. To generate user-friendly conversations, a language model was developed based on Chat-Generative Pretrained Transformer (ChatGPT), an interactive conversational chatbot powered by GPT-3.5. The AI-guide bot was implemented using ChatGPT3.5 from Sep. 2023 to Jan. 2024. ResultsThe AI-guide bot allowed users to select their desired cancer type and language for conversational interactions. The AI-guided bot was designed to expand its capabilities to encompass multiple major cancer types. The performance of the AI-guide bot responses was 90.98 ± 4.02 (obtained by summing up the Likert scores). ConclusionsThe AI-guide bot can provide medical information quickly and accurately to patients with cancer who are concerned about their health.

Endoscopic diagnosis of an obstructive fungal ball in the urethra of a dog

AbstractA 1‐year‐old, male, neutered German shepherd dog was presented for a chronic atraumatic non‐healing fracture of the right accessory carpal bone, stranguria and polyuria/polydipsia. Biochemistry and urinalysis showed azotaemia. Ultrasound and computed tomography of the abdomen both demonstrated bilateral renal infarcts with pyelectasia, bilateral ureteral dilation and bladder distension. Cystoscopy of the bladder identified a fungal ball obstructing the pelvic urethral sphincter, which was adhered to the bladder mucosa in the region of the ureterovesicular junction. The obstruction was traversed endoscopically, but could not be removed transurethrally. The combination of elevated serum galactomannan titres (6.4) and Aspergillus terreus cultured from urine, confirmed a diagnosis of disseminated aspergillosis. The dog was euthanased due to poor quality of life, guarded prognosis and lengthy timeframe before an expected medical response. This is the first case report describing Aspergillus fungal balls in a dog causing partial urethral and bilateral ureteral obstruction, identified using cystoscopy.

Smart solutions in hypertension diagnosis and management: a deep dive into artificial intelligence and modern wearables for blood pressure monitoring.

Hypertension, a widespread cardiovascular issue, presents a major global health challenge. Traditional diagnosis and treatment methods involve periodic blood pressure monitoring and prescribing antihypertensive drugs. Smart technology integration in healthcare offers promising results in optimizing the diagnosis and treatment of various conditions. We investigate its role in improving hypertension diagnosis and treatment effectiveness using machine learning algorithms for early and accurate detection. Intelligent models trained on diverse datasets (encompassing physiological parameters, lifestyle factors, and genetic information) to detect subtle hypertension risk patterns. Adaptive algorithms analyze patient-specific data, optimizing treatment plans based on medication responses and lifestyle habits. This personalized approach ensures effective, minimally invasive interventions tailored to each patient. Wearables and smart sensors provide real-time health insights for proactive treatment adjustments and early complication detection.

An Overview of Local Health Departments' and Medical Reserve Corps' Preparedness and Response Activities during the COVID-19 Pandemic: A Two-Study Summary.

An Overview of Local Health Departments' and Medical Reserve Corps' Preparedness and Response Activities during the COVID-19 Pandemic: A Two-Study Summary.

Enhancing traumatic brain injury emergency care: the impact of grading and zoning nursing management

ABSTRACT Objective This research aimed to evaluate the impact of grading and zoning nursing management on traumatic brain injury (TBI) patients’ emergency treatment outcomes. Methods This randomized controlled trial included 200 TBI patients. They were treated with a conventional care (control group, n = 100) and a novel grading and zoning approach (study group, n = 100), respectively. This innovative model organized care into levels based on urgency and complexity, facilitating targeted medical response and resource allocation. Key metrics compared included demographic profiles, consultation efficiency (time metrics and emergency treatment rates), physiological parameters (HR, RR, MAP, SpO2, RBS), and patient outcomes (hospital and ICU stays, complication rates, and emergency outcomes). Results The study group demonstrated significantly improved consultation efficiency, with reduced times for physician visits, examinations, emergency stays, and specialist referrals (all p < 0.001), alongside a higher emergency treatment rate (93% vs. 79%, p = 0.004), notably better physiological stability, improved HR, RR, MAP, SpO2 and RBS (p < 0.001), shorter hospital and ICU stays, fewer complications, and superior emergency outcomes. Conclusion Grading and zoning nursing management substantially enhances TBI patients’ emergency care efficiency and clinical outcomes, suggesting a viable model for improving emergency treatment protocols.

Gender Matters: A Multidimensional Approach to Optimizing Cardiovascular Health in Women.

Cardiovascular diseases remaina leading cause of mortality among women, yet they are often underestimated and insufficiently addressed. This narrative review delves into the gender disparities in cardiovascular health, underscoring the critical importance of recognizing and addressing the unique challenges women face. The article explores the pathophysiological differences between men and women, highlighting the role of hormonal factors, such as estrogen and menopause, in conferring cardioprotection or increasing risk. It examines the complexities of diagnosis and assessment, including differences in symptom presentation, diagnostic accuracy, and the challenges of interpreting non-invasive testing in women. The review also highlights the need for tailored risk assessment and prevention strategies, incorporating sex-specific conditions and pregnancy-related factors. It emphasizes the importance of lifestyle modifications and interventions, as well as the potential benefits of personalized treatment approaches, considering gender-specific variations in medication responses and cardiac interventions. Furthermore, the article sheds light on the impact of psychosocial and sociocultural factors, such as gender norms, mental health considerations, and access to healthcare, on women's cardiovascular health. It also addresses the significant gaps and challenges in research, including the historical underrepresentation of women in clinical trials and the lack of sex- and gender-sensitive studies. Finally, the review advocates for a multidisciplinary approach, involving patient-centered care, shared decision-making, and collaboration among policymakers, stakeholders, and healthcare systems. This comprehensive strategy aims to enhance awareness, prevention, diagnosis, and treatment of cardiovascular disease in women, ultimately improving health outcomes and reducing the burden of this often overlooked epidemic.

Effectiveness of Biologic Therapy in Controlling Inflammation and Achieving Disease Remission in Patients with Rheumatoid Arthritis: A Systematic Review

Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disorder characterized by joint pain, swelling, and potential systemic complications. The usefulness of biological treatments in reducing inflammation and helping RA patients achieve clinical remission is assessed in this systematic narrative review. Using PubMed, Scopus, and Google Scholar, a thorough literature search was carried out with an emphasis on research published in the last five years. The inclusion criteria were English-language human subject research that contributed significantly to our understanding of biological therapies for RA. Despite concerns over long-term drug withdrawal, TNF-alpha inhibitors, including certolizumab, adalimumab, and infliximab, have shown considerable effectiveness in lowering disease activity and inducing remission. Tocilizumab and other IL inhibitors have shown strong anti-inflammatory properties and increased rates of medication retention. Certain patient profiles have shown success with other biologics, such as rituximab and abatacept, especially those who have not responded to previous therapies. Empirical evidence demonstrates that tofacitinib, a JAK inhibitor, is just as effective as conventional biologics. The study emphasizes how important it is to create individualized treatment programs depending on the medical history and response to the condition. Even with encouraging findings, improving RA care requires ongoing observation of safety profiles and long-term effects. This study offers a thorough synthesis of the available data to help physicians choose the best biologic therapy for patients with RA.

Systematic Review on the Worldwide Disparities in the Frequency and Results of Emergency Medical Services (EMS) and Response to Out-of-Hospital Cardiac Arrest (OHCA).

This systematic analysis aimed to analyze the key patterns and tendencies regarding bystander interventions, emergency medical service (EMS) systems, dispatcher support, regional and temporal differences, and the influence of national efforts on survival rates in out-of-hospital cardiac arrest (OHCA). The studies published between 2010 and 2024 examining outcomes of OHCA, interventions by bystanders, and variables linked to OHCA were included in this research. The inclusion process was done under Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), where publications (n = 24) from various geographical locations, including a wide range of research methodologies, were included for this research. The thematic analysis used for the data analysis shows that bystander cardiopulmonary resuscitation (CPR) enhances the chances of survival. The effectiveness of the EMS system, the assistance offered by dispatchers, and the inclusion of doctors in ambulance services are essential components in the management of OHCA. Regional and temporal variations highlight disparities in resuscitation protocols, emphasizing the need for adaptable approaches. Observations from statewide endeavors emphasize the impact of these activities in fostering a culture of prompt bystander intervention. This systematic review presents a comprehensive analysis of research conducted globally, providing a thorough insight into the variables that influence survival rates in instances of OHCA. The review recognizes the importance of bystander CPR and effective EMS services, while also bringing novel perspectives, such as gender disparities and geographical variations that contribute to the existing body of research. Despite possible variances in the studies and biases, the findings underscore the need for tailored therapies and ongoing research to optimize strategies for controlling OHCA and improving survival rates.

Treatment response for nocturnal enuresis in Taiwanese children: A comparison of medical departments

Purpose: This retrospective study aims to evaluate the medical treatment response, treatment choice, and medication adjustment during a clinical follow-up in Taiwanese children with nocturnal enuresis (NE). Materials and methods: A total of 287 children diagnosed with NE were included in the study. Patients’ characteristics, treatment response, and medication adjustment after the second clinic visit were analyzed. The study also compared treatment options chosen by different medical departments. Results: Of the 287 children analyzed, 56.8% received medical treatment, 68.8% were older than 7 years (P &lt; 0.001), and 45.6% were initially treated with desmopressin. The presence of daytime symptoms did not significantly affect the prescription of medication at the first clinic visit (P = 0.817). However, 76.9% of children with daytime symptoms who were initially treated with desmopressin needed medication adjustment during their second clinic visit (P = 0.01). Urologists were more likely to prescribe medications than other medical departments at the first clinic visit (P &lt; 0.001). Conclusion: Almost half of the Taiwanese children with NE (46%) in this study had a satisfactory treatment response after the initial treatment. Urologists were more likely to use medications as their initial treatment strategy. The limitation included bias from heterogeneous study population and limited information of pretreatment urodynamic or imaging studies. Further education is required for both general public and medical departments to improve the treatment outcomes of children with enuresis.

Computational insights into survival durations and prehospital interventions in accidental cold-water immersion: A comprehensive analysis of fresh and saltwater temperatures

This study examines the complex relationship between scenarios of cold-water immersion, survival durations, and prehospital interventions. It utilizes computational modeling methods to shed light on how different water temperatures affect individuals facing accidental cold-water immersion incidents. The analysis reveals significant variations in survival times based on water temperature. For example, subjects immersed in water at temperatures of 5 °C, 2 °C, and 0 °C had average survival times of 136, 113, and 100 min, respectively, under stable conditions. In flowing water at the same temperatures, survival times decreased to 119, 92, and 81 min, indicating the impact of water movement on cooling rates and survival durations. Likewise, individuals immersed in saltwater at temperatures of 5 °C, 2 °C, 0 °C, and −2 °C showed average survival times of 111, 88, 80, and 66 min, respectively, in static conditions. In flowing saltwater at the same temperatures, survival times decreased to 98, 74, 68, and 57 min, highlighting the influence of water flow on cooling rates and survival durations. A comparison between immersion in pure water and saltwater at 2 °C revealed survival times of 113 and 88 min under stable conditions and 92 and 74 min under dynamic conditions, emphasizing the role of water composition in survival outcomes. The study also challenges the notion that the demise of the Titanic's passengers and crew resulted from hypothermia, asserting instead that severe thermal shock was the primary cause. These numerical findings underscore the importance of considering water temperature, flow dynamics, and prompt medical responses in cold-water emergencies to enhance survival prospects. The study identifies water within the range of 41–43 °C as the most effective active external rewarming fluid for critical hypothermal conditions. By quantifying the impact of these variables on survival times, the study provides data-driven recommendations to improve emergency protocols and outcomes for individuals facing cold-water immersion incidents.

Pharmacogenomic Variation in Antiplatelet and Anticoagulant Medication Response: Data from the Multi-Ethnic New Zealand Study of Acute Coronary Syndromes

Pharmacogenomic Variation in Antiplatelet and Anticoagulant Medication Response: Data from the Multi-Ethnic New Zealand Study of Acute Coronary Syndromes

Evaluating communication capability across diverse groups for disaster medicine: A time-tracking method for functional exercises

Recent experiences in disaster medicine in Japan have shown the importance of preventing post-disaster health deterioration among citizens during the evacuation and recovery phases. The effective involvement of various medical, social welfare, and nursing organizations is necessary to mitigate these health problems. This study explored the effectiveness of a time-tracking evaluation method for functional exercises in analyzing the communication and joint task-processing capabilities of various medical and social welfare organizations in response to a citywide heavy-rain disaster. Each exercise inject was analyzed in advance to create a task-processing chain according to the emergency medical response plan. The actions of the exercise players were then compared with the expected tasks in the processing chain. The exercise created overload for some player groups. The completion rates and average execution times of the tasks were compared across task types and player groups, indicating the potential weaknesses of the current emergency operation plan. Responses of local medical associations to similar exercise injects were compared to analyze the range of diversity in responses and the merits of past exercise participation. Although the results of this time-tracking evaluation need to be carefully interpreted by combining the results regarding the quality of players' exercise actions, this method provides a new perspective for evaluating emergency operation plans through functional exercises.

Multiwell-based G0-PCC assay for radiation biodosimetry.

In cytogenetic biodosimetry, assessing radiation exposure typically requires over 48 hours for cells to reach mitosis, significantly delaying the administration of crucial radiation countermeasures needed within the first 24 hours post-exposure. To improve medical response times, we incorporated the G0-Premature Chromosome Condensation (G0-PCC) technique with the Rapid Automated Biodosimetry Tool-II (RABiT-II), creating a faster alternative for large-scale radiation emergencies. Our findings revealed that using a lower concentration of Calyculin A (Cal A) than recommended effectively increased the yield of highly-condensed G0-PCC cells (hPCC). However, integrating recombinant CDK1/Cyclin B kinase, vital for chromosome condensation, proved challenging due to the properties of these proteins affecting interactions with cellular membranes. Interestingly, Cal A alone was capable of inducing chromosome compaction in some G0 cells even in the absence of mitotic kinases, although these chromosomes displayed atypical morphologies. This suggests that Cal A mechanism for compacting G0 chromatin may differ from condensation driven by mitotic kinases. Additionally, we observed a correlation between radiation dose and extent of hPCC chromosome fragmentation, which allowed us to automate radiation damage quantification using a Convolutional Neural Network (CNN). Our method can address the need for a same-day cytogenetic biodosimetry test in radiation emergency situations.

Advances in pharmacogenomics: optimizing antiepileptic drug therapy for drug-resistant epilepsy

Epilepsy, a complex neurological disorder, is influenced by intricate interactions within cortical, hippocampal, or thalamocortical neuronal networks, presenting a genetically complex condition with non-Mendelian inheritance patterns. This complexity is underscored by the involvement of numerous “susceptibilities” or “modifier” genes, complicating the assessment of risk and therapy outcomes. A critical inquiry in epilepsy treatment involves understanding how genetic diversity impacts treatment strategies and efficacy. Pharmacogenomic advancements have elaborated the connection between genetic variants and antiseizure medication (ASM) safety and response, marking a shift towards precision medicine in epilepsy care. Notably, genetic screening for variants such as HLA-B*1502 and HLA-A*3101 has demonstrated significant efficacy in preventing severe hypersensitivity reactions, including toxic epidermal necrolysis (TEN) and Stevens-Johnson syndrome (SJS), particularly among specific ethnic populations. However, putting pharmacogenomic discoveries into clinical practice faces numerous challenges, including educational, legal, and economic barriers, emphasizing the need for broader acceptance and integration of pharmacogenomic data. This review synthesizes recent studies on pharmacogenomics in epilepsy, highlighting the current advances and prospects for personalizing epilepsy treatment through genetic insights, aiming to enhance ASM safety, reduce adverse effects, and improve treatment outcomes. Through a comprehensive examination of the genetic basis of epilepsy and its influence on pharmacotherapy, this review endeavors to contribute to the evolving landscape of precision medicine in epilepsy care, advocating for a more individualized and effective treatment approach.

The Impact of Development on Antidepressant and Placebo Response in Anxiety Disorders: A Bayesian Hierarchical Meta-Analytic Examination of Randomized Controlled Trials in Children, Adolescents, and Adults.

Background: Understanding how development influences medication and placebo responses in anxiety disorders could inform treatment decisions, including age-specific first- versus second-line psychopharmacological interventions. Objective: To meta-analytically compare the trajectory of selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs), and placebo response in youth and adults with anxiety disorders. Methods: Weekly symptom severity data were extracted from prospective, randomized, parallel-group, placebo-controlled trials of SSRIs and SNRIs in children, adolescents, and adults with anxiety disorders (generalized, separation, and social anxiety disorders as well as panic disorder). Treatment response was modeled for the standardized change in continuous measures of anxiety using a Bayesian hierarchical model. Change in symptom severity was evaluated as a function of time, and post hoc analyses were conducted to determine the sensitivity of these results across sample heterogeneity and alternative functional forms. Results: Data were included from 11 trials of youth (SSRI, κ = 7; SNRI, κ = 4) and 71 studies of adults (SSRI, κ = 46; SNRI, κ = 25). In total, 1067 youth participated in SSRI trials and 1024 in SNRI trials. In total, 10,826 adults participated in SSRI trials (placebo, n = 5367; SSRI n = 5,459) and 6232 in SNRI trials (placebo, n = 3,128; SNRI n = 3,094). A logarithmic model best described the response. Placebo response was similar in youth and adults (mean difference = -1.98 ± 6.21, 95% credible interval [CrI]: -10.2 to 14.2, p = 0.750), and statistically significant improvement from baseline emerged by week 2 in both adults (mean difference: -18.34 + 1.017, 95% CrI: -20.3 to 16.3, p < 0.001) and youth (mean difference: -23.74 + 3.736, 95% CrI: -31.1 to -16.4, p < 0.001). SSRIs produced similar improvements for youth and adults (p = 0.129), but SNRIs produced slower improvement in youth than adults (p = 0.018). Conclusions: Antidepressant-related improvement occurs early in youth and adults with anxiety disorders. SSRI response is similar in adults and youth; however, SNRIs produce greater responses in adults than youth, potentially representing a developmental effect.