A Computed Tomography-Based Fracture Prediction Model With Images of Vertebral Bones and Muscles by Employing Deep Learning: Development and Validation Study.

BACKGROUND: With the progressive increase in aging populations, the use of opportunistic computed tomography (CT) scanning is increasing, which could be a valuable method for acquiring information on both muscles and bones of aging populations. OBJECTIVE: The aim of this study was to develop and externally validate opportunistic CT-based fracture prediction models by using images of vertebral bones and paravertebral muscles. METHODS: The models were developed based on a retrospective longitudinal cohort study of 1214 patients with abdominal CT images between 2010 and 2019. The models were externally validated in 495 patients. The primary outcome of this study was defined as the predictive accuracy for identifying vertebral fracture events within a 5-year follow-up. The image models were developed using an attention convolutional neural network-recurrent neural network model from images of the vertebral bone and paravertebral muscles. RESULTS: The mean ages of the patients in the development and validation sets were 73 years and 68 years, and 69.1% (839/1214) and 78.8% (390/495) of them were females, respectively. The areas under the receiver operator curve (AUROCs) for predicting vertebral fractures were superior in images of the vertebral bone and paravertebral muscles than those in the bone-only images in the external validation cohort (0.827, 95% CI 0.821-0.833 vs 0.815, 95% CI 0.806-0.824, respectively; P<.001). The AUROCs of these image models were higher than those of the fracture risk assessment models (0.810 for major osteoporotic risk, 0.780 for hip fracture risk). For the clinical model using age, sex, BMI, use of steroids, smoking, possible secondary osteoporosis, type 2 diabetes mellitus, HIV, hepatitis C, and renal failure, the AUROC value in the external validation cohort was 0.749 (95% CI 0.736-0.762), which was lower than that of the image model using vertebral bones and muscles (P<.001). CONCLUSIONS: The model using the images of the vertebral bone and paravertebral muscle showed better performance than that using the images of the bone-only or clinical variables. Opportunistic CT screening may contribute to identifying patients with a high fracture risk in the future.

A Deep Learning-Based Rotten Food Recognition App for Older Adults: Development and Usability Study.

BACKGROUND: Older adults are at greater risk of eating rotten fruits and of getting food poisoning because cognitive function declines as they age, making it difficult to distinguish rotten fruits. To address this problem, researchers have developed and evaluated various tools to detect rotten food items in various ways. Nevertheless, little is known about how to create an app to detect rotten food items to support older adults at a risk of health problems from eating rotten food items. OBJECTIVE: This study aimed to (1) create a smartphone app that enables older adults to take a picture of food items with a camera and classifies the fruit as rotten or not rotten for older adults and (2) evaluate the usability of the app and the perceptions of older adults about the app. METHODS: We developed a smartphone app that supports older adults in determining whether the 3 fruits selected for this study (apple, banana, and orange) were fresh enough to eat. We used several residual deep networks to check whether the fruit photos collected were of fresh fruit. We recruited healthy older adults aged over 65 years (n=15, 57.7%, males and n=11, 42.3%, females) as participants. We evaluated the usability of the app and the participants' perceptions about the app through surveys and interviews. We analyzed the survey responses, including an after-scenario questionnaire, as evaluation indicators of the usability of the app and collected qualitative data from the interviewees for in-depth analysis of the survey responses. RESULTS: The participants were satisfied with using an app to determine whether a fruit is fresh by taking a picture of the fruit but are reluctant to use the paid version of the app. The survey results revealed that the participants tended to use the app efficiently to take pictures of fruits and determine their freshness. The qualitative data analysis on app usability and participants' perceptions about the app revealed that they found the app simple and easy to use, they had no difficulty taking pictures, and they found the app interface visually satisfactory. CONCLUSIONS: This study suggests the possibility of developing an app that supports older adults in identifying rotten food items effectively and efficiently. Future work to make the app distinguish the freshness of various food items other than the 3 fruits selected still remains.

Development of a Real-Time Dashboard for Overdose Touchpoints: User-Centered Design Approach.

BACKGROUND: Overdose Fatality Review (OFR) is an important public health tool for shaping overdose prevention strategies in communities. However, OFR teams review only a few cases at a time, which typically represent a small fraction of the total fatalities in their jurisdiction. Such limited review could result in a partial understanding of local overdose patterns, leading to policy recommendations that do not fully address the broader community needs. OBJECTIVE: This study explored the potential to enhance conventional OFRs with a data dashboard, incorporating visualizations of touchpoints-events that precede overdoses-to highlight prevention opportunities. METHODS: We conducted 2 focus groups and a survey of OFR experts to characterize their information needs and design a real-time dashboard that tracks and measures decedents' past interactions with services in Indiana. Experts (N=27) were engaged, yielding insights on essential data features to incorporate and providing feedback to guide the development of visualizations. RESULTS: The findings highlighted the importance of showing decedents' interactions with health services (emergency medical services) and the justice system (incarcerations). Emphasis was also placed on maintaining decedent anonymity, particularly in small communities, and the need for training OFR members in data interpretation. The developed dashboard summarizes key touchpoint metrics, including prevalence, interaction frequency, and time intervals between touchpoints and overdoses, with data viewable at the county and state levels. In an initial evaluation, the dashboard was well received for its comprehensive data coverage and its potential for enhancing OFR recommendations and case selection. CONCLUSIONS: The Indiana touchpoints dashboard is the first to display real-time visualizations that link administrative and overdose mortality data across the state. This resource equips local health officials and OFRs with timely, quantitative, and spatiotemporal insights into overdose risk factors in their communities, facilitating data-driven interventions and policy changes. However, fully integrating the dashboard into OFR practices will likely require training teams in data interpretation and decision-making.

Addressing Hospital Overwhelm During the COVID-19 Pandemic by Using a Primary Health Care-Based Integrated Health System: Modeling Study.

Background: After strict COVID-19-related restrictions were lifted, health systems globally were overwhelmed. Much has been discussed about how health systems could better prepare for future pandemics; however, primary health care (PHC) has been largely ignored. Objective: We aimed to investigate what combined policies PHC could apply to strengthen the health care system via a bottom-up approach, so as to better respond to a public health emergency. Methods: We developed a system dynamics model to replicate Shanghai's response when COVID-19-related restrictions were lifted. We then simulated an alternative PHC-based integrated health system and tested the following three interventions: first contact in PHC with telemedicine services, recommendation to secondary care, and return to PHC for recovery. Results: The simulation results showed that each selected intervention could alleviate hospital overwhelm. Increasing the rate of first contact in PHC with telemedicine increased hospital bed availability by 6% to 12% and reduced the cumulative number of deaths by 35%. More precise recommendations had a limited impact on hospital overwhelm (<1%), but the simulation results showed that underrecommendation (rate: 80%) would result in a 19% increase in cumulative deaths. Increasing the rate of return to PHC from 5% to 20% improved hospital bed availability by 6% to 16% and reduced the cumulative number of deaths by 46%. Moreover, combining all 3 interventions had a multiplier effect; bed availability increased by 683%, and the cumulative number of deaths dropped by 75%. Conclusions: Rather than focusing on the allocation of medical resources in secondary care, we determined that an optimal PHC-based integrated strategy would be to have a 60% rate of first contact in PHC, a 110% recommendation rate, and a 20% rate of return to PHC. This could increase health system resilience during public health emergencies.

Novel Allelic Gene Variations in CmCLAVATA3 (CmCLV3) Were Identified in a Genetic Population of Melon (Cucumis melo L.).

Carpel number (CN) is an important trait affecting the fruit size and shape of melon, which plays a crucial role in determining the overall appearance and market value. A unique non-synonymous single nucleotide polymorphism (SNP) in CmCLAVATA3 (CmCLV3) is responsible for the variation of CN in C. melo ssp. agrestis (hereafter agrestis), but it has been unclear in C. melo ssp. melo (hereafter melo). In this study, one major locus controlling the polymorphism of 5-CN (multi-CN) and 3-CN (normal-CN) in melo was identified using bulked segregant analysis (BSA-seq). This locus was then fine-mapped to an interval of 1.8 Mb on chromosome 12 using a segregating population containing 1451 progeny. CmCLV3 is still present in the candidate region. A new allele of CmCLV3, which contains five other nucleotide polymorphisms, including a non-synonymous SNP in coding sequence (CDS), except the SNP reported in agrestis, was identified in melo. A cis-trans test confirmed that the candidate gene, CmCLV3, contributes to the variation of CNs in melo. The qRT-PCR results indicate that there is no significant difference in the expression level of CmCLV3 in the apical stem between the multi-CN plants and the normal-CN plants. Overall, this study provides a genetic resource for melon fruit development research and molecular breeding. Additionally, it suggests that melo has undergone similar genetic selection but evolved into an independent allele.

User-Centered Framework for Implementation of Technology (UFIT): Development of an Integrated Framework for Designing Clinical Decision Support Tools Packaged With Tailored Implementation Strategies.

BACKGROUND: Electronic health record-based clinical decision support (CDS) tools can facilitate the adoption of evidence into practice. Yet, the impact of CDS beyond single-site implementation is often limited by dissemination and implementation barriers related to site- and user-specific variation in workflows and behaviors. The translation of evidence-based CDS from initial development to implementation in heterogeneous environments requires a framework that assures careful balancing of fidelity to core functional elements with adaptations to ensure compatibility with new contexts. OBJECTIVE: This study aims to develop and apply a framework to guide tailoring and implementing CDS across diverse clinical settings. METHODS: In preparation for a multisite trial implementing CDS for pediatric overweight or obesity in primary care, we developed the User-Centered Framework for Implementation of Technology (UFIT), a framework that integrates principles from user-centered design (UCD), human factors/ergonomics theories, and implementation science to guide both CDS adaptation and tailoring of related implementation strategies. Our transdisciplinary study team conducted semistructured interviews with pediatric primary care clinicians and a diverse group of stakeholders from 3 health systems in the northeastern, midwestern, and southeastern United States to inform and apply the framework for our formative evaluation. RESULTS: We conducted 41 qualitative interviews with primary care clinicians (n=21) and other stakeholders (n=20). Our workflow analysis found 3 primary ways in which clinicians interact with the electronic health record during primary care well-child visits identifying opportunities for decision support. Additionally, we identified differences in practice patterns across contexts necessitating a multiprong design approach to support a variety of workflows, user needs, preferences, and implementation strategies. CONCLUSIONS: UFIT integrates theories and guidance from UCD, human factors/ergonomics, and implementation science to promote fit with local contexts for optimal outcomes. The components of UFIT were used to guide the development of Improving Pediatric Obesity Practice Using Prompts, an integrated package comprising CDS for obesity or overweight treatment with tailored implementation strategies. TRIAL REGISTRATION: ClinicalTrials.gov NCT05627011; https://clinicaltrials.gov/study/NCT05627011.

Tailored Self-Management App to Support Older Adults With Cancer and Multimorbidity: Development and Usability Testing.

BACKGROUND: Globally, cancer predominates in adults aged older than 60 years, and 70% of older adults have ≥1 chronic condition. Cancer self-management interventions can improve symptom management and confidence, but few interventions target the complex needs of older adults with cancer and multimorbidity. Despite growing evidence of digital health tools in cancer care, there is a paucity of theoretically grounded digital self-management supports for older adults. Many apps for older adults have not been co-designed with older adults to ensure that they are tailored to their specific needs, which would increase usability and uptake. OBJECTIVE: We aim to report on the user evaluations of a self- and symptom-management app to support older adults living with cancer and multimorbidity. METHODS: This study used Grey's self-management framework, a design thinking approach, and involved older adults with lived experiences of cancer to design a medium-fidelity app prototype. Older adults with cancer or caregivers were recruited through community organizations or support groups to participate in co-designing or evaluations of the app. Data from interviews were iteratively integrated into the design process and analyzed using descriptive statistics and thematic analyses. RESULTS: In total, 15 older adults and 3 caregivers (n=18) participated in this study: 10 participated (8 older adults and 2 caregivers) in the design of the low-fidelity prototype, and 10 evaluated (9 older adults and 1 caregiver) the medium-fidelity prototype (2 older adults participated in both phases). Participants emphasized the importance of tracking functions to make sense of information across physical symptoms and psychosocial aspects; a clear display; and the organization of notes and reminders to communicate with care providers. Participants also emphasized the importance of medication initiation or cessation reminders to mitigate concerns related to polypharmacy. CONCLUSIONS: This app has the potential to support the complex health care needs of older adults with cancer, creating a "home base" for symptom management and support. The findings from this study will position the researchers to conduct feasibility testing and real-world implementation.

A Novel Electronic Record System for Documentation and Efficient Workflow for Community Health Workers: Development and Usability Study.

BACKGROUND: The COVID-19 pandemic added to the decades of evidence that public health institutions are routinely stretched beyond their capacity. Community health workers (CHWs) can be a crucial extension of public health resources to address health inequities, but systems to document CHW efforts are often fragmented and prone to unneeded redundancy, errors, and inefficiency. OBJECTIVE: We sought to develop a more efficient data collection system for recording the wide range of community-based efforts performed by CHWs. METHODS: The Communities Organizing to Promote Equity (COPE) project is an initiative to address health disparities across Kansas, in part, through the deployment of CHWs. Our team iteratively designed and refined the features of a novel data collection system for CHWs. Pilot tests with CHWs occurred over several months to ensure that the functionality supported their daily use. Following implementation of the database, procedures were set to sustain the collection of feedback from CHWs, community partners, and organizations with similar systems to continually modify the database to meet the needs of users. A continuous quality improvement process was conducted monthly to evaluate CHW performance; feedback was exchanged at team and individual levels regarding the continuous quality improvement results and opportunities for improvement. Further, a 15-item feedback survey was distributed to all 33 COPE CHWs and supervisors for assessing the feasibility of database features, accessibility, and overall satisfaction. RESULTS: At launch, the database had 60 active users in 20 counties. Documented client interactions begin with needs assessments (modified versions of the Arizona Self-sufficiency Matrix and PRAPARE [Protocol for Responding to and Assessing Patient Assets, Risks, and Experiences]) and continue with the longitudinal tracking of progress toward goals. A user-specific automated alerts-based dashboard displays clients needing follow-up and upcoming events. The database contains over 55,000 documented encounters across more than 5079 clients. Available resources from over 2500 community organizations have been documented. Survey data indicated that 84% (27/32) of the respondents considered the overall navigation of the database as very easy. The majority of the respondents indicated they were overall very satisfied (14/32, 44%) or satisfied (15/32, 48%) with the database. Open-ended responses indicated the database features, documentation of community organizations and visual confirmation of consent form and data storage on a Health Insurance Portability and Accountability Act-compliant record system, improved client engagement, enrollment processes, and identification of resources. CONCLUSIONS: Our database extends beyond conventional electronic medical records and provides flexibility for ever-changing needs. The COPE database provides real-world data on CHW accomplishments, thereby improving the uniformity of data collection to enhance monitoring and evaluation. This database can serve as a model for community-based documentation systems and be adapted for use in other community settings.

Promoting a Patient-Centered Understanding of Safety in Acute Mental Health Wards: A User-Centered Design Approach to Develop a Real-Time Digital Monitoring Tool.

BACKGROUND: Acute mental health services report high levels of safety incidents that involve both patients and staff. The potential for patients to be involved in interventions to improve safety within a mental health setting is acknowledged, and there is a need for interventions that proactively seek the patient perspective of safety. Digital technologies may offer opportunities to address this need. OBJECTIVE: This research sought to design and develop a digital real-time monitoring tool (WardSonar) to collect and collate daily information from patients in acute mental health wards about their perceptions of safety. We present the design and development process and underpinning logic model and programme theory. METHODS: The first stage involved a synthesis of the findings from a systematic review and evidence scan, interviews with patients (n=8) and health professionals (n=17), and stakeholder engagement. Cycles of design activities and discussion followed with patients, staff, and stakeholder groups, to design and develop the prototype tool. RESULTS: We drew on patient safety theory and the concepts of contagion and milieu. The data synthesis, design, and development process resulted in three prototype components of the digital monitoring tool (WardSonar): (1) a patient recording interface that asks patients to input their perceptions into a tablet computer, to assess how the ward feels and whether the direction is changing, that is, "getting worse" or "getting better"; (2) a staff dashboard and functionality to interrogate the data at different levels; and (3) a public-facing ward interface. The technology is available as open-source code. CONCLUSIONS: Recent patient safety policy and research priorities encourage innovative approaches to measuring and monitoring safety. We developed a digital real-time monitoring tool to collect information from patients in acute mental health wards about perceived safety, to support staff to respond and intervene to changes in the clinical environment more proactively.

[Forty-three Years of Dedicated Efforts in Advancing Pharmacist Expertise: Aspiring to Become a Pharmacist and Cultivate Pharmacists Proficient in Recommending Prescription Medicines to Doctors].

When I graduated from university, my aim was to become a pharmacist capable of recommending prescription medicines to doctors and teaching others to do the same. To achieve this goal, I developed comprehensive curricula incorporating progressive educational tools such as problem-based learning and small group discussions. Subsequently, the effectiveness of these tools and curricula was evaluated, and the findings of these assessments were published in various peer-reviewed journal articles. Consequently, a body of evidence on the most effective ways to recommend prescription medicines to doctors was gradually established. This paper aims to summarize this comprehensive body of research spanning over 43 years, with the objective of highlighting the valuable insights gained thus far, identifying the best practice techniques, and exploring potential avenues for future research.

User-Friendly Chatbot to Mitigate the Psychological Stress of Older Adults During the COVID-19 Pandemic: Development and Usability Study.

BACKGROUND: To safeguard the most vulnerable individuals during the COVID-19 pandemic, numerous governments enforced measures such as stay-at-home orders, social distancing, and self-isolation. These social restrictions had a particularly negative effect on older adults, as they are more vulnerable and experience increased loneliness, which has various adverse effects, including increasing the risk of mental health problems and mortality. Chatbots can potentially reduce loneliness and provide companionship during a pandemic. However, existing chatbots do not cater to the specific needs of older adult populations. OBJECTIVE: We aimed to develop a user-friendly chatbot tailored to the specific needs of older adults with anxiety or depressive disorders during the COVID-19 pandemic and to examine their perspectives on mental health chatbot use. The primary research objective was to investigate whether chatbots can mitigate the psychological stress of older adults during COVID-19. METHODS: Participants were older adults belonging to two age groups (≥65 years and <65 years) from a psychiatric outpatient department who had been diagnosed with depressive or anxiety disorders by certified psychiatrists according to the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (DSM-5) criteria. The participants were required to use mobile phones, have internet access, and possess literacy skills. The chatbot's content includes monitoring and tracking health data and providing health information. Participants had access to the chatbot for at least 4 weeks. Self-report questionnaires for loneliness, depression, and anxiety were administered before and after chatbot use. The participants also rated their attitudes toward the chatbot. RESULTS: A total of 35 participants (mean age 65.21, SD 7.51 years) were enrolled in the trial, comprising 74% (n=26) female and 26% (n=9) male participants. The participants demonstrated a high utilization rate during the intervention, with over 82% engaging with the chatbot daily. Loneliness significantly improved in the older group ≥65 years. This group also responded positively to the chatbot, as evidenced by changes in University of California Los Angeles Loneliness Scale scores, suggesting that this demographic can derive benefits from chatbot interaction. Conversely, the younger group, <65 years, exhibited no significant changes in loneliness after the intervention. Both the older and younger age groups provided good scores in relation to chatbot design with respect to usability (mean scores of 6.33 and 6.05, respectively) and satisfaction (mean scores of 5.33 and 5.15, respectively), rated on a 7-point Likert scale. CONCLUSIONS: The chatbot interface was found to be user-friendly and demonstrated promising results among participants 65 years and older who were receiving care at psychiatric outpatient clinics and experiencing relatively stable symptoms of depression and anxiety. The chatbot not only provided caring companionship but also showed the potential to alleviate loneliness during the challenging circumstances of a pandemic.

Cross-Modal Sensory Boosting to Improve High-Frequency Hearing Loss: Device Development and Validation.

Background: High-frequency hearing loss is one of the most common problems in the aging population and with those who have a history of exposure to loud noises. This type of hearing loss can be frustrating and disabling, making it difficult to understand speech communication and interact effectively with the world. Objective: This study aimed to examine the impact of spatially unique haptic vibrations representing high-frequency phonemes on the self-perceived ability to understand conversations in everyday situations. Methods: To address high-frequency hearing loss, a multi-motor wristband was developed that uses machine learning to listen for specific high-frequency phonemes. The wristband vibrates in spatially unique locations to represent which phoneme was present in real time. A total of 16 participants with high-frequency hearing loss were recruited and asked to wear the wristband for 6 weeks. The degree of disability associated with hearing loss was measured weekly using the Abbreviated Profile of Hearing Aid Benefit (APHAB). Results: By the end of the 6-week study, the average APHAB benefit score across all participants reached 12.39 points, from a baseline of 40.32 to a final score of 27.93 (SD 13.11; N=16; P=.002, 2-tailed dependent t test). Those without hearing aids showed a 10.78-point larger improvement in average APHAB benefit score at 6 weeks than those with hearing aids (t14=2.14; P=.10, 2-tailed independent t test). The average benefit score across all participants for ease of communication was 15.44 (SD 13.88; N=16; P<.001, 2-tailed dependent t test). The average benefit score across all participants for background noise was 10.88 (SD 17.54; N=16; P=.03, 2-tailed dependent t test). The average benefit score across all participants for reverberation was 10.84 (SD 16.95; N=16; P=.02, 2-tailed dependent t test). Conclusions: These findings show that vibrotactile sensory substitution delivered by a wristband that produces spatially distinguishable vibrations in correspondence with high-frequency phonemes helps individuals with high-frequency hearing loss improve their perceived understanding of verbal communication. Vibrotactile feedback provides benefits whether or not a person wears hearing aids, albeit in slightly different ways. Finally, individuals with the greatest perceived difficulty understanding speech experienced the greatest amount of perceived benefit from vibrotactile feedback.

A Risk Assessment and Planning Tool to Prevent Sudden Unexpected Death in Infancy: Development and Evaluation of The Baby Sleep Planner.

BACKGROUND: Successful national safer sleep campaigns in the United Kingdom have lowered the death rates from sudden unexpected death in infancy (SUDI) over the past 3 decades, but deaths persist in socioeconomically deprived families. The circumstances of current deaths suggest that improvements in support for some families to follow safer sleep advice more consistently could save lives. OBJECTIVE: This study aimed to develop and evaluate a risk assessment and planning tool designed to improve the uptake of safer sleep advice in families with infants at increased risk of SUDI. METHODS: A co-design approach was used to develop the prototype interface of a web-based tool with 2 parts: an individual SUDI risk assessment at birth and a downloadable plan for safety during times of disruption. The advice contained within the tool is concordant with national guidance from the Lullaby Trust, the United Nations International Children's Emergency Fund (UNICEF), and the National Institute for Health and Care Excellence. User testing of the prototype tool was conducted by inviting health visitors, midwives, and family nurses to use it with families eligible for additional support. Qualitative interviews with health professionals and families allowed for iterative changes to the tool and for insights into its function and influence on parental behavior. RESULTS: A total of 22 health professionals were enrolled in the study, of whom 20 (91%) were interviewed. They reported appreciating the functionality of the tool, which allowed them to identify at-risk families for further support. They felt that the tool improved how they communicated about risks with families. They suggested expanding its use to include relevance in the antenatal period and having versions available in languages other than English. They reported using the tool with 58 families; 20 parents gave consent to be interviewed by the research team about their experiences with the tool. Families were positive about the tool, appreciated the trustworthy information, and felt that it was useful and appropriate and that the plans for specific infant sleeps would be of benefit to them and other family members. CONCLUSIONS: Our tool combines risk assessment and safety planning, both of which have the potential to improve the uptake of lifesaving advice. Refinements to the tool based on these findings have ensured that the tool is ready for further evaluation in a larger study before being rolled out to families with infants at increased risk.

Estado nutricional y medidas antropométricas en escolares Zapotecas y no Zapotecas de Oaxaca, México / Nutritional status and anthropometric measurements in Zapotec and non-Zapoteca schoolchildren from Oaxaca, Mexico

Introducción: Los grupos indígenas se enfrentan a la discriminación y exclusión, lo que genera inequidades en el ámbito de la salud. Además, son nutricionalmente vulnerables, lo que afecta su potencial de crecimiento y desarrollo en comparación con población no indígena. Objetivo: comparar el estado nutricional y medidas antropométricas entre escolares zapotecas y no zapotecas de una región de Oaxaca, México. Material y métodos: estudio descriptivo trasversal en una muestra representativa de 477 escolares de 8 a 11 años de un municipio de Oaxaca. Se dividió a la población en zapoteco (Zap+) y no zapoteco (Zap-). Se obtuvo el peso, talla, circunferencia de cintura, circunferencia de brazo y el pliegue tricipital. Se calculó el IMC para la edad, el índice cintura-talla e indicadores del componente graso y muscular del brazo. Se utilizó la prueba chi cuadrada y exacta de Fisher para diferencias proporcionales Resultados: El 51,5% de escolares fue Zap+ y se reportó una alta prevalencia de sobrepeso y obesidad de 33,7%. Las niñas Zap+ presentaron mayor prevalencia de desmedro (p=0,032) y los niños Zap+ presentaron menor % área grasa de brazo (0,004). Entre niños y niñas Zap-, los niños presentaron bajo peso (p=0,040) y musculatura reducida (p=0,003), mientras que las niñas presentaron mayor proporción grasa arriba del promedio (p=<0,001). Los niños Zap- presentaron mayor prevalencia de desmedro en comparación con los Zap+ (p=0,022). Esta diferencia se mantuvo hasta los 11 años (p=0,007). Se observó que las niñas Zap+ de 11 años presentaron una menor musculatura (p=0.001) y mayor riesgo cardiovascular (p=0,032) en comparación con las Zap-. Conclusiones: Se observaron cambios seculares positivos en niños Zap+ reflejados en una mayor talla que las niñas Zap+ y niños Zap-, y una tendencia al aumento del IMC y riesgo cardiovascular en las niñas Zap+ lo cual podría reflejar una posible transición nutricional.(AU)

Introduction: Indigenous groups face discrimination andexclusion, which generates inequities in the field of health. Inaddition, they are nutritionally vulnerable, which affects theirgrowth and development potential compared to the non-in-digenous population. Objective: to compare the nutritional status and anthro-pometric measurements between Zapotec and non-Zapotecschoolchildren from a region of Oaxaca, Mexico. Material and methods: cross-sectional descriptive studyin a sample of 477 schoolchildren aged 8 to 11 from a mu-nicipality in Oaxaca. The population was divided into Zapotec(Zap+) and non-Zapotec (Zap-). Weight, height, waist cir-cumference, arm circumference and triceps fold were meas-ured. Anthropometric indicators and the fatty and muscularcomponent of the arm were calculated. A comparative analy-sis of nutritional status and body composition was performedbetween Zap+ and Zap- using chi square and Fisher’s exacttest. A p value <0.05 was considered significant. Results: 51.5% of schoolchildren were Zap+ and a highprevalence of overweight and obesity of 33.7% was reported.Zap+ girls had a higher prevalence of wasting (p=0.032) andZap+ boys had a lower % arm fat area (0.004). Among Zap-boys and girls, boys had low weight (p=0.040) and reducedmusculature (p=0.003), while girls had a higher proportion offat above average (p=<0.001). Zap- children had a higherprevalence of stunting compared to Zap+ children (p=0.022).It was observed that 11-year-old Zap+ girls had less muscle(p=0.001) and a higher cardiovascular risk (p=0.032) com-pared to Zap- girls. Conclusions: Positive secular changes were observed inZap+ boys, reflected in greater height than Zap- boys, and atrend in increasing BMI and cardiovascular risk in Zap+ girls,which could reflect a possible nutritional transition.(AU)

A Blended Intervention Targeting Emotion Dysregulation in Adults With Attention-Deficit/Hyperactivity Disorder: Development and Feasibility Study.

BACKGROUND: Many adults with attention-deficit/hyperactivity disorder (ADHD) experience difficulties related to emotion regulation. Such difficulties are known to substantially impact quality of life and overall functioning. Yet, there is a lack of treatment interventions specifically designed to address these challenges. OBJECTIVE: This study aimed to describe the development and assess the feasibility, along with the initial clinical outcomes, of a novel blended intervention for adults with ADHD. The blended intervention combines both face-to-face and digital components and is specifically designed to address emotion dysregulation in ADHD. METHODS: This intervention was an 8-week blended intervention combining weekly face-to-face group sessions with a supplementary digital companion app. The intervention is based on elements from dialectic behavioral therapy skills training and positive psychology. To evaluate its feasibility, we performed a 10-week feasibility study with an uncontrolled pre-post study design, including 16 adults with ADHD and co-occurring emotion dysregulation. The feasibility measures encompassed adherence, satisfaction, and perceived credibility of the intervention. Clinical outcomes were evaluated by self-reported symptoms of emotion dysregulation, inattention, hyperactivity-impulsivity, executive function, depression, anxiety, and a measure of quality of life. Paired sample 2-tailed t tests were used to analyze clinical outcomes with a Bonferroni-corrected significance level. RESULTS: Both treatment credibility and treatment satisfaction were rated favorably by the majority of the participants. In particular, the participants emphasized meeting others with ADHD as beneficial. In terms of adherence, 3 participants withdrew before initiating the intervention, while another 4 participants did not complete the intervention. On average, the participants who enrolled in the intervention attended 6.2 of the 8 group sessions and completed 6.7 of the 8 skills training modules in the companion app. In terms of clinical outcomes, there was a reduction in symptoms of emotion dysregulation from before to after the intervention (d=2.0). Significant improvements were also observed in measures of inattention (d=1.1) and hyperactivity-impulsivity (d=0.9). However, no significant improvements were found in the domains of depression, anxiety, quality of life, and executive functioning. CONCLUSIONS: The results are encouraging, both in terms of feasibility and the preliminary clinical results on emotion dysregulation. The blended format, combining digital and face-to-face elements, may also seem to offer some advantages: the group-based format was valued as it facilitated peer interaction, while a rather high completion of modules in the companion app highlights its potential to enhance skills training between the group sessions. Future randomized controlled trials are called for to further evaluate the clinical effectiveness of the intervention. TRIAL REGISTRATION: ClinicalTrials.gov NCT05644028; https://clinicaltrials.gov/study/NCT05644028.

Evaluation of Machine Learning Approaches for Predicting Warfarin Discharge Dose in Cardiac Surgery Patients: Retrospective Algorithm Development and Validation Study.

BACKGROUND: Warfarin dosing in cardiac surgery patients is complicated by a heightened sensitivity to the drug, predisposing patients to adverse events. Predictive algorithms are therefore needed to guide warfarin dosing in cardiac surgery patients. OBJECTIVE: This study aimed to develop and validate an algorithm for predicting the warfarin dose needed to attain a therapeutic international normalized ratio (INR) at the time of discharge in cardiac surgery patients. METHODS: We abstracted variables influencing warfarin dosage from the records of 1031 encounters initiating warfarin between April 1, 2011, and November 29, 2019, at St Michael's Hospital in Toronto, Ontario, Canada. We compared the performance of penalized linear regression, k-nearest neighbors, random forest regression, gradient boosting, multivariate adaptive regression splines, and an ensemble model combining the predictions of the 5 regression models. We developed and validated separate models for predicting the warfarin dose required for achieving a discharge INR of 2.0-3.0 in patients undergoing all forms of cardiac surgery except mechanical mitral valve replacement and a discharge INR of 2.5-3.5 in patients receiving a mechanical mitral valve replacement. For the former, we selected 80% of encounters (n=780) who had initiated warfarin during their hospital admission and had achieved a target INR of 2.0-3.0 at the time of discharge as the training cohort. Following 10-fold cross-validation, model accuracy was evaluated in a test cohort comprised solely of cardiac surgery patients. For patients requiring a target INR of 2.5-3.5 (n=165), we used leave-p-out cross-validation (p=3 observations) to estimate model performance. For each approach, we determined the mean absolute error (MAE) and the proportion of predictions within 20% of the true warfarin dose. We retrospectively evaluated the best-performing algorithm in clinical practice by comparing the proportion of cardiovascular surgery patients discharged with a therapeutic INR before (April 2011 and July 2019) and following (September 2021 and May 2, 2022) its implementation in routine care. RESULTS: Random forest regression was the best-performing model for patients with a target INR of 2.0-3.0, an MAE of 1.13 mg, and 39.5% of predictions of falling within 20% of the actual therapeutic discharge dose. For patients with a target INR of 2.5-3.5, the ensemble model performed best, with an MAE of 1.11 mg and 43.6% of predictions being within 20% of the actual therapeutic discharge dose. The proportion of cardiovascular surgery patients discharged with a therapeutic INR before and following implementation of these algorithms in clinical practice was 47.5% (305/641) and 61.1% (11/18), respectively. CONCLUSIONS: Machine learning algorithms based on routinely available clinical data can help guide initial warfarin dosing in cardiac surgery patients and optimize the postsurgical anticoagulation of these patients.

Internet Tool to Support Self-Assessment and Self-Swabbing of Sore Throat: Development and Feasibility Study.

BACKGROUND: Sore throat is a common problem and a common reason for the overuse of antibiotics. A web-based tool that helps people assess their sore throat, through the use of clinical prediction rules, taking throat swabs or saliva samples, and taking throat photographs, has the potential to improve self-management and help identify those who are the most and least likely to benefit from antibiotics. OBJECTIVE: We aimed to develop a web-based tool to help patients and parents or carers self-assess sore throat symptoms and take throat photographs, swabs, and saliva samples for diagnostic testing. We then explored the acceptability and feasibility of using the tool in adults and children with sore throats. METHODS: We used the Person-Based Approach to develop a web-based tool and then recruited adults and children with sore throats who participated in this study by attending general practices or through social media advertising. Participants self-assessed the presence of FeverPAIN and Centor score criteria and attempted to photograph their throat and take throat swabs and saliva tests. Study processes were observed via video call, and participants were interviewed about their views on using the web-based tool. Self-assessed throat inflammation and pus were compared to clinician evaluation of patients' throat photographs. RESULTS: A total of 45 participants (33 adults and 12 children) were recruited. Of these, 35 (78%) and 32 (71%) participants completed all scoring elements for FeverPAIN and Centor scores, respectively, and most (30/45, 67%) of them reported finding self-assessment relatively easy. No valid response was provided for swollen lymph nodes, throat inflammation, and pus on the throat by 11 (24%), 9 (20%), and 13 (29%) participants respectively. A total of 18 (40%) participants provided a throat photograph of adequate quality for clinical assessment. Patient assessment of inflammation had a sensitivity of 100% (3/3) and specificity of 47% (7/15) compared with the clinician-assessed photographs. For pus on the throat, the sensitivity was 100% (3/3) and the specificity was 71% (10/14). A total of 89% (40/45), 93% (42/45), 89% (40/45), and 80% (30/45) of participants provided analyzable bacterial swabs, viral swabs, saliva sponges, and saliva drool samples, respectively. Participants were generally happy and confident in providing samples, with saliva samples rated as slightly more acceptable than swab samples. CONCLUSIONS: Most adult and parent participants were able to use a web-based intervention to assess the clinical features of throat infections and generate scores using clinical prediction rules. However, some had difficulties assessing clinical signs, such as lymph nodes, throat pus, and inflammation, and scores were assessed as sensitive but not specific. Many participants had problems taking photographs of adequate quality, but most were able to take throat swabs and saliva samples.

Usability and Perception of a Wearable-Integrated Digital Maternity Record App in Germany: User Study.

Background: Although digital maternity records (DMRs) have been evaluated in the past, no previous work investigated usability or acceptance through an observational usability study. Objective: The primary objective was to assess the usability and perception of a DMR smartphone app for pregnant women. The secondary objective was to assess personal preferences and habits related to online information searching, wearable data presentation and interpretation, at-home examination, and sharing data for research purposes during pregnancy. Methods: A DMR smartphone app was developed. Key features such as wearable device integration, study functionalities (eg, questionnaires), and common pregnancy app functionalities (eg, mood tracker) were included. Women who had previously given birth were invited to participate. Participants completed 10 tasks while asked to think aloud. Sessions were conducted via Zoom. Video, audio, and the shared screen were recorded for analysis. Task completion times, task success, errors, and self-reported (free text) feedback were evaluated. Usability was measured through the System Usability Scale (SUS) and User Experience Questionnaire (UEQ). Semistructured interviews were conducted to explore the secondary objective. Results: A total of 11 participants (mean age 34.6, SD 2.2 years) were included in the study. A mean SUS score of 79.09 (SD 18.38) was achieved. The app was rated "above average" in 4 of 6 UEQ categories. Sixteen unique features were requested. We found that 5 of 11 participants would only use wearables during pregnancy if requested to by their physician, while 10 of 11 stated they would share their data for research purposes. Conclusions: Pregnant women rely on their medical caregivers for advice, including on the use of mobile and ubiquitous health technology. Clear benefits must be communicated if issuing wearable devices to pregnant women. Participants that experienced pregnancy complications in the past were overall more open toward the use of wearable devices in pregnancy. Pregnant women have different opinions regarding access to, interpretation of, and reactions to alerts based on wearable data. Future work should investigate personalized concepts covering these aspects.

Autosomal dominant neurodevelopmental disorders associated with KIF1A gene variants in 6 pediatric patients. / å ­ä¾‹KIF1AåŸºå› å˜å¼‚ç›¸å ³å¸¸æŸ“è‰²ä½“æ˜¾æ€§é—ä¼ ç¥žç»å‘è‚²éšœç¢æ‚£å„¿ä¸´åºŠå’Œé—ä¼ å­¦åˆ†æž.

OBJECTIVES: To analyze the clinical and genetic characteristics of children with autosomal dominant neurodevelopmental disorders caused by kinesin family member 1A (KIF1A) gene variation. METHODS: Clinical and genetic testing data of 6 children with KIF1A gene de novo heterozygous variation diagnosed in Shanghai Children's Medical Center Affiliated to Shanghai Jiao Tong University School of Medicine from the year 2018 to 2020 were retrospectively analyzed. Pathogenic variants were identified based on whole exome sequencing, and verified by Sanger sequencing. Moreover, the effect of variants on three-dimensional structure and stability of protein was analyzed by bioinformatics. RESULTS: Among 6 patients there were 4 males and 2 females, and the age of consultation varied from 7 months to 18 years. All cases had varying degrees of motor developmental delay since childhood, and 4 of them had gait abnormalities or fell easily. In addition, 2 children were accompanied by delayed mental development, epilepsy and abnormal eye development. Genetic tests showed that all 6 cases had heterozygous de novo variations of KIF1A gene, including 4 missense mutations c.296C>T (p.T99M), c.761G>A (p.R254Q), c.326G>T (p.G109V), c.745C>G (p.L249V) and one splicing mutation c.798+1G>A, among which the last three variants have not been previously reported. Bioinformatics analysis showed that G109V and L249V may impair their interaction with the neighboring amino acid residues, thereby impacting protein function and reducing protein stability, and were assessed as "likely pathogenic". Meanwhile, c.798+1G>A may damage an alpha helix in the motor domain of the KIF1A protein, and was assessed as "likely pathogenic". CONCLUSIONS: KIF1A-associated neurological diseases are clinically heterogeneous, with motor developmental delay and abnormal gait often being the most common clinical features. The clinical symptoms in T99M carriers are more severe, while those in R254Q carriers are relatively mild.

Effect of environmental level of methomyl on hatching, morphology, immunity and development related genes expression in zebrafish (Danio rerio) embryo.

The extensive use of carbamate pesticides has led to a range of environmental and health problems, such as surface and groundwater contamination, and endocrine disorders in organisms. In this study, we focused on examining the effects of toxic exposure to the carbamate pesticide methomyl on the hatching, morphology, immunity and developmental gene expression levels in zebrafish embryos. Four concentrations of methomyl (0, 2, 20, and 200 µg/L) were administered to zebrafish embryos for a period of 96 h. The study found that exposure to methomyl accelerated the hatching process of zebrafish embryos, with the strongest effect recorded at the concentration of 2 µg/L. Methomyl exposure also trigged significantly reductions in heart rate and caused abnormalities in larvae morphology, and it also stimulated the synthesis and release of several inflammatory factors such as IL-1ß, IL-6, TNF-α and INF-α, lowered the IgM contents, ultimately enhancing inflammatory response and interfering with immune function. All of these showed the significant effects on exposure time, concentration and their interaction (Time × Concentration). Furthermore, the body length of zebrafish exposed to methomyl for 96 h was significantly shorter, particularly at higher concentrations (200 µg/L). Methomyl also affected the expression levels of genes associated with development (down-regulated igf1, bmp2b, vasa, dazl and piwi genes), demonstrating strong developmental toxicity and disruption of the endocrine system, with the most observed at the concentration of 200 µg/L and 96 h exposure to methomyl. The results of this study provide valuable reference information on the potential damage of methomyl concentrations in the environment on fish embryo development, while also supplementing present research on the immunotoxicity of methomyl.