Search

Objective: The objective of this study is to assess the perceptions of Indigenous medical students on postgraduate admissions through an Indigenous admissions pathway (IAP), and to determine what factors may influence Indigenous medical students’ choice of residency training program. Methods: We distributed a survey to self-identified Indigenous students at settler Canadian medical schools. The survey questioned the students’ acceptability of an IAP, and what factors would influence application through an IAP. Analysis included descriptive statistics and thematic analysis of open-ended questions. Results: Thirty-six participants responded to the survey. Location and proximity to family or support system were the most important factors in choosing a residency program. Participants identified mentorship from Indigenous physicians and community involvement as being important features of a residency program that has an IAP. Eighty-one percent of participants felt the availability of an IAP would influence their choice of residency program. Fear of judgement or stigma, concern about entrance requirements, and program logistics were identified as barriers to applying to residency through an IAP. All participants believed that an IAP would have a positive influence on the healthcare system more broadly. Conclusions: An IAP appears to be an acceptable residency application format to Indigenous students but cannot exist in isolation. It is important for programs to consider the needs and safety of Indigenous trainees within residency programs.

Abstract Background Meaningful performance measurement requires indicators to be scientifically robust and strategically focused. For many circumpolar states, indicators aligned with national strategies may ignore the priorities of northern, remote, or Indigenous populations. The aim of this project was to identify contextually appropriate performance indicators for maternity care in circumpolar regions. Methods Fourteen maternity care and health systems experts participated in a modified Delphi consensus process. The list of proposed indicators was derived from a previously published scoping review. Fourteen participants rated each proposed indicator according to importance, circumpolar relevance, validity, and reliability and suggested additional indicators for consideration. Results Consensus was achieved after two rounds, as measured by a Cronbach’s alpha of 0.87. Eleven indicators, many of which represented physical health outcomes, were ranked highly on all four criteria. Twenty-nine additional indicators, largely focused on social determinants of health, health care responsiveness, and accessibility, were identified for further research. Travel for care, cultural safety and upstream structural determinants of health were identified as important themes. Conclusions This study identified the important gaps between current performance measurement strategies and the context and values that permeate maternal-child health in circumpolar regions. The indicators identified in this study provide an important foundation for ongoing work. We recommend that future work encompass an appreciation for the intersectoral nature of social, structural, and colonial determinants of maternal-child health in circumpolar regions.

This symposium report provides a brief overview of the six programmes and studies on parental education and maternal health services within the circumpolar region presented in the symposium “parental education” at the 17th International Congress of Circumpolar Health in Copenhagen, Denmark, August 2018.

Background: In circumpolar regions, harsh climates and scattered populations have prompted the centralization of care and reduction of local maternity services. The resulting practice of routine evacuation for birth from smaller towns to larger urban centres points to a potential conflict between the necessity to ensure patient safety and the importance of delivering services that are responsive to the health needs and values of populations served. Objective: To identify recommended performance/quality indicators for use in circumpolar maternity care systems. Methods: We searched Scopus, Ebscohost databases (including Academic Search Complete and CINAHL), the Global Health Database, High North Research Documents, and online grey literature. Articles were included if they focused on maternal health indicators in the population of interest (Indigenous women, women receiving care in circumpolar or remote regions). Articles were excluded if they were not related to pregnancy, birth or the immediate post-partum or neonatal periods. Two reviewers independently reviewed articles for inclusion and extracted relevant data. Results: Twenty-six documents were included. Twelve were government documents, seven were review articles or indicator compilations, four were indicator sets recommended by academics or non-governmental organizations and three were research papers. We extracted and categorized 81 unique health indicators. The majority of indicators reflected health systems processes and outcomes during the antenatal and intra-partum periods. Only two governmental indicator sets explicitly considered the needs of Indigenous peoples. Conclusions: This review demonstrates that, although most circumpolar health systems engage in performance reporting for maternity care, efforts to capture local priorities and values are limited in most regions. Future work in this area should involve northern stakeholders in the process of indicator selection and development.

Abstract Background The emergence of COVID-19 precipitated containment policies (e.g., lockdowns, school closures, etc.). These policies disrupted healthcare, potentially eroding gains for Sustainable Development Goals including for neonatal mortality. Our analysis aimed to evaluate indirect effects of COVID-19 containment policies on neonatal admissions and mortality in 67 neonatal units across Kenya, Malawi, Nigeria, and Tanzania between January 2019 and December 2021. Methods The Oxford Stringency Index was applied to quantify COVID-19 policy stringency over time for Kenya, Malawi, Nigeria, and Tanzania. Stringency increased markedly between March and April 2020 for these four countries (although less so in Tanzania), therefore defining the point of interruption. We used March as the primary interruption month, with April for sensitivity analysis. Additional sensitivity analysis excluded data for March and April 2020, modelled the index as a continuous exposure, and examined models for each country. To evaluate changes in neonatal admissions and mortality based on this interruption period, a mixed effects segmented regression was applied. The unit of analysis was the neonatal unit (n = 67), with a total of 266,741 neonatal admissions (January 2019 to December 2021). Results Admission to neonatal units decreased by 15% overall from February to March 2020, with half of the 67 neonatal units showing a decline in admissions. Of the 34 neonatal units with a decline in admissions, 19 (28%) had a significant decrease of ≥ 20%. The month-to-month decrease in admissions was approximately 2% on average from March 2020 to December 2021. Despite the decline in admissions, we found no significant changes in overall inpatient neonatal mortality. The three sensitivity analyses provided consistent findings. Conclusion COVID-19 containment measures had an impact on neonatal admissions, but no significant change in overall inpatient neonatal mortality was detected. Additional qualitative research in these facilities has explored possible reasons. Strengthening healthcare systems to endure unexpected events, such as pandemics, is critical in continuing progress towards achieving Sustainable Development Goals, including reducing neonatal deaths to less than 12 per 1000 live births by 2030.

There are substantial challenges in studying human transgenerational epigenetic outcomes resulting from environmental conditions. The task requires specialized methods and tools that incorporate specific knowledge of multigenerational relationship combinations of probands and their ancestors, phenotype data for individuals, environmental information of ancestors and their descendants, which can span historical to present datasets, and informative environmental data that chronologically aligns with ancestors and descendants over space and time. As a result, there are few epidemiologic studies of potential transgenerational effects in human populations, thus limiting the knowledge of ancestral environmental conditions and the potential impacts we face with modern human health outcomes. In an effort to overcome some of the challenges in studying human transgenerational effects, we present two transgenerational study designs: transgenerational space-time cluster detection and transgenerational case-control study design. Like other epidemiological methods, these methods determine whether there are statistical associations between phenotypic outcomes (e.g., adverse health outcomes) among probands and the shared environments and environmental factors facing their ancestors. When the ancestor is a paternal grandparent, a statistically significant association provides some evidence that a transgenerational inheritable factor may be involved. Such results may generate useful hypotheses that can be explored using epigenomic data to establish conclusive evidence of transgenerational heritable effects. Both methods are proband-centric: They are designed around the phenotype of interest in the proband generation for case selection and family pedigree creation. In the examples provided, we incorporate at least three generations of paternal lineage in both methods to observe a potential transgenerational effect.

Abstract Background Service readiness tools are important for assessing hospital capacity to provide quality small and sick newborn care (SSNC). Lack of summary scoring approaches for SSNC service readiness means we are unable to track national targets such as the Every Newborn Action Plan targets. Methods A health facility assessment (HFA) tool was co-designed by Newborn Essential Solutions and Technologies (NEST360) and UNICEF with four African governments. Data were collected in 68 NEST360-implementing neonatal units in Kenya, Malawi, Nigeria, and Tanzania (September 2019-March 2021). Two summary scoring approaches were developed: a) standards-based, including items for SSNC service readiness by health system building block (HSBB), and scored on availability and functionality, and b) level-2 + , scoring items on readiness to provide WHO level-2 + clinical interventions. For each scoring approach, scores were aggregated and summarised as a percentage and equally weighted to obtain an overall score by hospital, HSBB, and clinical intervention. Results Of 1508 HFA items, 1043 (69%) were included in standards-based and 309 (20%) in level-2 + scoring. Sixty-eight neonatal units across four countries had median standards-based scores of 51% [IQR 48–57%] at baseline, with variation by country: 62% [IQR 59–66%] in Kenya, 49% [IQR 46–51%] in Malawi, 50% [IQR 42–58%] in Nigeria, and 55% [IQR 53–62%] in Tanzania. The lowest scoring was family-centred care [27%, IQR 18–40%] with governance highest scoring [76%, IQR 71–82%]. For level-2 + scores, the overall median score was 41% [IQR 35–51%] with variation by country: 50% [IQR 44–53%] in Kenya, 41% [IQR 35–50%] in Malawi, 33% [IQR 27–37%] in Nigeria, and 41% [IQR 32–52%] in Tanzania. Readiness to provide antibiotics by culture report was the highest-scoring intervention [58%, IQR 50–75%] and neonatal encephalopathy management was the lowest-scoring [21%, IQR 8–42%]. In both methods, overall scores were low ( 75%. Discussion Two scoring approaches reveal gaps in SSNC readiness with no neonatal units achieving high scores (> 75%). Government-led quality improvement teams can use these summary scores to identify areas for health systems change. Future analyses could determine which items are most directly linked with quality SSNC and newborn outcomes.

Abstract Background Each year an estimated 2.3 million newborns die in the first 28 days of life. Most of these deaths are preventable, and high-quality neonatal care is fundamental for surviving and thriving. Service readiness is used to assess the capacity of hospitals to provide care, but current health facility assessment (HFA) tools do not fully evaluate inpatient small and sick newborn care (SSNC). Methods Health systems ingredients for SSNC were identified from international guidelines, notably World Health Organization (WHO), and other standards for SSNC. Existing global and national service readiness tools were identified and mapped against this ingredients list. A novel HFA tool was co-designed according to a priori considerations determined by policymakers from four African governments, including that the HFA be completed in one day and assess readiness across the health system. The tool was reviewed by > 150 global experts, and refined and operationalised in 64 hospitals in Kenya, Malawi, Nigeria, and Tanzania between September 2019 and March 2021. Results Eight hundred and sixty-six key health systems ingredients for service readiness for inpatient SSNC were identified and mapped against four global and eight national tools measuring SSNC service readiness. Tools revealed major content gaps particularly for devices and consumables, care guidelines, and facility infrastructure, with a mean of 13.2% (n = 866, range 2.2–34.4%) of ingredients included. Two tools covered 32.7% and 34.4% (n = 866) of ingredients and were used as inputs for the new HFA tool, which included ten modules organised by adapted WHO health system building blocks, including: infrastructure, pharmacy and laboratory, medical devices and supplies, biomedical technician workshop, human resources, information systems, leadership and governance, family-centred care, and infection prevention and control. This HFA tool can be conducted at a hospital by seven assessors in one day and has been used in 64 hospitals in Kenya, Malawi, Nigeria, and Tanzania. Conclusion This HFA tool is available open-access to adapt for use to comprehensively measure service readiness for level-2 SSNC, including respiratory support. The resulting facility-level data enable comparable tracking for Every Newborn Action Plan coverage target four within and between countries, identifying facility and national-level health systems gaps for action.

Abstract Anal cancer incidence is significantly higher in people living with HIV as HIV increases the oncogenic potential of human papillomavirus. The incidence of anal cancer in the United States has recently increased, with diagnosis and treatment hampered by high loss-to-follow-up rates. Novel methods for the automated, real-time diagnosis of AIN 2+ could enable "see and treat" strategies, reducing loss-to-follow-up rates. A previous retrospective study demonstrated that the accuracy of a high-resolution microendoscope (HRME) coupled with a deep learning model was comparable to expert clinical impression for diagnosis of AIN 2+ (sensitivity 0.92 [P = 0.68] and specificity 0.60 [P = 0.48]). However, motion artifacts and noise led to many images failing quality control (17%). Here, we present a high frame rate HRME (HF-HRME) with improved image quality, deployed in the clinic alongside a deep learning model and evaluated prospectively for detection of AIN 2+ in real-time. The HF-HRME reduced the fraction of images failing quality control to 4.6% by employing a high frame rate camera that enhances contrast and limits motion artifacts. The HF-HRME outperformed the previous HRME (P

Abstract Background Small and sick newborn care (SSNC) is critical for national neonatal mortality reduction targets by 2030. Investment cases could inform implementation planning and enable coordinated resource mobilisation. We outline development of an investment case for Tanzania to estimate additional financing for scaling up SSNC to 80% of districts as part of health sector strategies to meet the country’s targets. Methods We followed five steps: (1) reviewed national targets, policies and guidelines; (2) modelled potential health benefits by increased coverage of SSNC using the Lives Saved Tool; (3) estimated setup and running costs using the Neonatal Device Planning and Costing Tool, applying two scenarios: (A) all new neonatal units and devices with optimal staffing, and (B) half new and half modifying, upgrading, or adding resources to existing neonatal units; (4) calculated budget impact and return on investment (ROI) and (5) identified potential financing opportunities. Results Neonatal mortality rate was forecast to fall from 20 to 13 per 1000 live births with scale-up of SSNC, superseding the government 2025 target of 15, and close to the 2030 Sustainable Development Goal 3.2 target of

Abstract Cervical cancer is a leading cause of death for women in low-resource settings despite being preventable through human papillomavirus (HPV) vaccination, early detection, and treatment of precancerous lesions. The World Health Organization recommends high-risk HPV (hrHPV) as the preferred cervical cancer screening strategy, which is difficult to implement in low-resource settings due to high costs, reliance on centralized laboratory infrastructure, and long sample-to-answer times. To help meet the need for rapid, low-cost, and decentralized cervical cancer screening, we developed tailed primer isothermal amplification and lateral flow detection assays for HPV16, HPV18, and HPV45 DNA. We translated these assays into a self-contained cartridge to achieve multiplexed detection of three hrHPV genotypes in a disposable cartridge. The developed test achieves clinically relevant limits of detection of 50–500 copies per reaction with extracted genomic DNA from HPV-positive cells. Finally, we performed sample-to-answer testing with direct lysates of HPV-negative and HPV-positive cell lines and demonstrated consistent detection of HPV16, HPV18, and HPV45 with 5000–50,000 cells/mL in

Abstract Background Millions of newborns die annually from preventable causes, with the highest rates occurring in Africa. Reducing neonatal mortality requires investment to scale hospital care, which includes providing hospitals with appropriate technology to care for small and sick newborns. Expensive medical devices designed for high-resource settings often fail to withstand conditions in low-resource hospitals, including humidity, dust, frequent user turnover, complex maintenance, lack of stable power, or difficulty sourcing expensive consumables. Rigorous evaluation protocols are needed to identify effective, affordable, rugged, and easy-to-use medical devices appropriate for quality hospital-based newborn care in low-resource hospitals. Methods We developed an evidence-based technology review process to identify medical devices suitable for small and sick newborn care in low-resource hospitals. The eight-step process consists of: identifying devices needed for effective newborn care; defining Target Product Profiles (TPPs); identifying commercially-available products that may meet TPPs; conducting desk research to evaluate technologies against TPPs; performing technical performance verification testing under laboratory conditions; verifying technical performance after exposure to heat, humidity, dust, and power loss; performing usability evaluations with nurses, and qualifying devices that pass all steps. Devices were purchased, installed, and monitored in newborn wards across Kenya, Malawi, Nigeria, and Tanzania. Results Of 271 devices considered, only 45 (16.6%) met corresponding TPPs based on desk research. Thirty-nine were purchased and evaluated in the laboratory; five (12.8%) failed to meet TPPs. Thirty-four products passing laboratory evaluation underwent short-term environmental testing; only one (2.9%) device failed. Thirty-seven products underwent usability testing with 127 clinicians; surprisingly, 14 (37.8%) failed to meet TPPs. Twenty-three products passed all evaluations, and 2457 devices were installed across 65 newborn wards in Kenya, Malawi, Nigeria, and Tanzania. Continuous device monitoring reported minimal device failures, with failed devices typically returned to service within two days, resulting in an average uptime (service days divided by days installed) of 99%. Conclusion An evidence-based device selection process can improve procurement of effective, affordable, rugged, usable newborn care devices for low-resource hospitals, and feedback to manufacturers can improve device quality. Similar processes could be adapted beyond newborn care to identify medical devices suitable for implementation in any low-resource setting.

Abstract Background Every Newborn Action Plan (ENAP) coverage target 4 necessitates national scale-up of Level-2 Small and Sick Newborn Care (SSNC) (with Continuous Positive Airway Pressure (CPAP)) in 80% of districts by 2025. Routine neonatal inpatient data is important for improving quality of care, targeting equity gaps, and enabling data-driven decision-making at individual, district, and national-levels. Existing neonatal inpatient datasets vary in purpose, size, definitions, and collection processes. We describe the co-design and operationalisation of a core inpatient dataset for use to track outcomes and improve quality of care for small and sick newborns in high-mortality settings. Methods A three-step systematic framework was used to review, co-design, and operationalise this novel neonatal inpatient dataset in four countries (Malawi, Kenya, Tanzania, and Nigeria) implementing with the Newborn Essential Solutions and Technologies (NEST360) Alliance. Existing global and national datasets were identified, and variables were mapped according to categories. A priori considerations for variable inclusion were determined by clinicians and policymakers from the four African governments by facilitated group discussions. These included prioritising clinical care and newborn outcomes data, a parsimonious variable list, and electronic data entry. The tool was designed and refined by > 40 implementers and policymakers during a multi-stakeholder workshop and online interactions. Results Identified national and international datasets (n = 6) contained a median of 89 (IQR:61–154) variables, with many relating to research-specific initiatives. Maternal antenatal/intrapartum history was the largest variable category (21, 23.3%). The Neonatal Inpatient Dataset (NID) includes 60 core variables organised in six categories: (1) birth details/maternal history; (2) admission details/identifiers; (3) clinical complications/observations; (4) interventions/investigations; (5) discharge outcomes; and (6) diagnosis/cause-of-death. Categories were informed through the mapping process. The NID has been implemented at 69 neonatal units in four African countries and links to a facility-level quality improvement (QI) dashboard used in real-time by facility staff. Conclusion The NEST360 NID is a novel, parsimonious tool for use in routine information systems to inform inpatient SSNC quality. Available on the NEST360/United Nations Children's Fund (UNICEF) Implementation Toolkit for SSNC, this adaptable tool enables facility and country-level comparisons to accelerate progress toward ENAP targets. Additional linked modules could include neonatal at-risk follow-up, retinopathy of prematurity, and Level-3 intensive care.

Abstract Background Medical devices are critical to providing high-quality, hospital-based newborn care, yet many of these devices are unavailable in low- and middle-income countries (LMIC) and are not designed to be suitable for these settings. Target Product Profiles (TPPs) are often utilised at an early stage in the medical device development process to enable user-defined performance characteristics for a given setting. TPPs can also be applied to assess the profile and match of existing devices for a given context. Methods We developed initial TPPs for 15 newborn product categories for LMIC settings. A Delphi-like process was used to develop the TPPs. Respondents completed an online survey where they scored their level of agreement with each of the proposed performance characteristics for each of the 15 devices. Characteristics with 75% agreement. Areas of disagreement were voted on by 69 participants at an in-person consensus meeting, with consensus achieved for 648 (97%) performance characteristics. Only 20 (3%) performance characteristics did not achieve consensus, most (15/20) relating to quality management systems. UNICEF published the 15 TPPs in April 2020, accompanied by a report detailing the online survey results and consensus meeting discussion, which has been viewed 7,039 times (as of January 2023). Conclusions These 15 TPPs can inform developers and enable implementers to select neonatal care products for LMIC. Over 2,400 medical devices and diagnostics meeting these TPPs have been installed in 65 hospitals in Nigeria, Tanzania, Kenya, and Malawi through the NEST360 Alliance. Twenty-three medical devices identified and qualified by NEST360 meet nearly all performance characteristics across 11 of the 15 TPPs. Eight of the 23 qualified medical devices are available in the UNICEF Supply Catalogue. Some developers have adjusted their technologies to meet these TPPs. There is potential to adapt the TPP process beyond newborn care.

Abstract Background High-quality neonatal care requires sufficient functional medical devices, furniture, fixtures, and use by trained healthcare workers, however there is lack of publicly available tools for quantification and costing. This paper describes development and use of a planning and costing tool regarding furniture, fixtures and devices to support scale-up of WHO level-2 neonatal care, for national and global newborn survival targets. Methods We followed a systematic process. First, we reviewed planning and costing tools of relevance. Second, we co-designed a new tool to estimate furniture and device set-up costs for a default 40-bed level-2 neonatal unit, incorporating input from multi-disciplinary experts and newborn care guidelines. Furniture and device lists were based off WHO guidelines/norms, UNICEF and national manuals/guides. Due to lack of evidence-based quantification, ratios were based on operational manuals, multi-country facility assessment data, and expert opinion. Default unit costs were from government procurement agency costs in Kenya, Nigeria, and Tanzania. Third, we refined the tool by national use in Tanzania. Results The tool adapts activity-based costing (ABC) to estimate quantities and costs to equip a level-2 neonatal unit based on three components: (1) furniture/fixtures (18 default but editable items); (2) neonatal medical devices (16 product categories with minimum specifications for use in low-resource settings); (3) user training at device installation. The tool was used in Tanzania to generate procurement lists and cost estimates for level-2 scale-up in 171 hospitals (146 District and 25 Regional Referral). Total incremental cost of all new furniture and equipment acquisition, installation, and user training were US$93,000 per District hospital (level-2 care) and US$346,000 per Regional Referral hospital. Estimated cost per capita for whole-country district coverage was US$0.23, representing 0.57% increase in government health expenditure per capita and additional 0.35% for all Regional Referral hospitals. Conclusion Given 2.3 million neonatal deaths and potential impact of level-2 newborn care, rational and efficient planning of devices linked to systems change is foundational. In future iterations, we aim to include consumables, spare parts, and maintenance cost options. More rigorous implementation research data are crucial to formulating evidence-based ratios for devices numbers per baby. Use of this tool could help overcome gaps in devices numbers, advance efficiency and quality of neonatal care.

BackgroundDigital weight management interventions (DWMIs) have the potential to support existing specialist weight management services (SWMS) in the National Health Service (NHS) to increase access to treatment for people living with obesity and type 2 diabetes. At present, there is limited real-world evidence and long-term outcomes on the potential effectiveness of DWMIs to support such services. ObjectiveThis study aimed to examine real-world data to evaluate the impact of Second Nature’s 12-month DWMI for patients living with obesity with or without type 2 diabetes, referred from NHS primary care services, on sustained weight loss over a 2-year period. MethodsRetrospective data were extracted in August 2023 for participants who participated in the program between January 1, 2017, and January 8, 2021. Eligible participants were adults with a BMI ≥35 kg/m2, with or without type 2 diabetes. The primary outcomes were weight change in kilograms and percentage weight change at 2 years. Secondary outcomes were weight loss at 1 year, program engagement, and the proportion of participants who achieved >5% and >10% weight loss. Differences in weight loss between baseline and the 1- and 2-year follow-up points were compared using paired 2-tailed t tests. Linear regression models were used to examine whether participants’ ethnicity, indices of multiple deprivation, presence of type 2 diabetes, or program engagement were associated with weight loss at 1 year or 2 years. ResultsA total of 1130 participants with a mean baseline BMI of 46.3 (SD 31.6) kg/m2 were included in the analysis. Of these participants, 65% (740/1130) were female (mean age 49.9, SD 12.0 years), 18.1% (205/339) were from Black, Asian, mixed, or other ethnicities, and 78.2% (884/1130) had type 2 diabetes. A total of 281 (24.9%) participants recorded weight readings at 2 years from baseline, with a mean weight loss of 13.8 kg (SD 14.2 kg; P

Esophageal carcinoma is the sixth-leading cause of cancer death worldwide. A precursor to esophageal adenocarcinoma (EAC) is Barrett’s Esophagus (BE). Early-stage diagnosis and treatment of esophageal neoplasia (Barrett’s with high-grade dysplasia/intramucosal cancer) increase the five-year survival rate from 10% to 98%. BE is a global challenge; however, current endoscopes for early BE detection are costly and require extensive infrastructure for patient examination and sedation. We describe the design and evaluation of the first prototype of ScanCap, a high-resolution optical endoscopy system with a reusable, low-cost tethered capsule, designed to provide high-definition, blue-green illumination imaging for the early detection of BE in unsedated patients. The tethered capsule (12.8 mm diameter, 35.5 mm length) contains a color camera and rotating mirror and is designed to be swallowed; images are collected as the capsule is retracted manually via the tether. The tether provides electrical power and illumination at wavelengths of 415 nm and 565 nm and transmits data from the camera to a tablet. The ScanCap prototype capsule was used to image the oral mucosa in normal volunteers and ex vivo esophageal resections; images were compared to those obtained using an Olympus CV-180 endoscope. Images of superficial capillaries in intact oral mucosa were clearly visible in ScanCap images. Diagnostically relevant features of BE, including irregular Z-lines, distorted mucosa, and dilated vasculature, were clearly visible in ScanCap images of ex vivo esophageal specimens.

BackgroundDigital weight management interventions have the potential to increase access to novel pharmacotherapy for people living with obesity. At present, there is limited real-world evidence on the effectiveness, feasibility, and acceptability of this type of intervention. ObjectiveThis retrospective service evaluation examines real-world data to evaluate the preliminary impact of Second Nature’s 24-month, remotely delivered, semaglutide-supported weight management intervention for adults living with obesity at 12 weeks. MethodsRetrospective data were extracted in October 2023 for participants who started the intervention between June 8, 2023, and July 22, 2023. The primary outcomes were weight change (kg) and percentage of weight change at 12 weeks. The secondary outcomes were the proportion of participants who achieved ≥5% and ≥10% weight loss and the feasibility and acceptability of this type of intervention. Descriptive statistics were used to evaluate the baseline characteristics, retention, engagement, prevalence of side effects, and weight change. A paired 2-tailed t test was used to determine the significance of weight change. Content analysis was used to analyze the free-text questionnaire responses. ResultsA total of 113 participants with a mean baseline BMI of 38.4 kg/m2 (SD 7.3) were included in the analysis (n=102, 90.4% women, mean age 46.6, SD 11.1 years). Over 12 weeks, 23% (n=26) of participants withdrew from the intervention. A total of 70.8% (n=80) of participants provided weight data at 12 weeks. The average weight loss observed over this 12-week period was 6.5 (SD 4.4) kg (P

Because of their close relationship with humans, non-human apes (chimpanzees, bonobos, gorillas, orangutans, and gibbons, including siamangs) are of great scientific interest. The goal of understanding their complex behavior would be greatly advanced by the ability to perform video-based pose tracking. Tracking, however, requires high-quality annotated datasets of ape photographs. Here we present OpenApePose, a new public dataset of 71,868 photographs, annotated with 16 body landmarks of six ape species in naturalistic contexts. We show that a standard deep net (HRNet-W48) trained on ape photos can reliably track out-of-sample ape photos better than networks trained on monkeys (specifically, the OpenMonkeyPose dataset) and on humans (COCO) can. This trained network can track apes almost as well as the other networks can track their respective taxa, and models trained without one of the six ape species can track the held-out species better than the monkey and human models can. Ultimately, the results of our analyses highlight the importance of large, specialized databases for animal tracking systems and confirm the utility of our new ape database.

# Background Cervical cancer remains the leading cause of cancer-related death among Nepalese women. To this effect, Cancer Care Nepal established an international collaboration to implement a 'training of trainers' (TOT) program to expand the reach of cervical cancer prevention techniques. # Methods The Nepal cervical cancer prevention program began with an in-person TOT session in Kathmandu in November 2019. Due to the COVID-19 pandemic, two additional TOT courses were held in October and November 2021 with virtual support, didactic lectures from international faculty, and a hands-on component by Nepalese faculty. The Nepalese providers underwent training in these courses and then held further training in five collaborating centers across Nepal. Participants completed pre- and post-course knowledge assessments. The trainings were supplemented by the creation of a new Project ECHO® (Extension for Community Healthcare Outcomes) telementoring hub at Cancer Care Nepal. A capstone refresher course was held in November 2022. # Results 42 participants attended the initial TOT course in 2019. The two follow-up TOT courses held in October/November 2021 were two days long and included providers from five participating regions in Nepal. The courses included virtual didactic sessions followed by hands-on stations led by the Nepalese faculty who had participated in the 2019 TOT course. The stations included: visual inspection with acetic acid (VIA), colposcopy, thermal ablation, and loop electrosurgical excision procedure (LEEP). There were 41 participants in the October/November TOT courses. The trainers who received the TOT education then conducted local courses of similar content in each of the five regions for 152 local providers. Participants had improved mean knowledge scores after the training (0.70, 95% CI=0.67-0.72) in comparison to prior to training (0.50, 95% CI=0.47-0.53), p\

Abstract Background Transgenerational epigenetic risks associated with complex health outcomes, such as autism spectrum disorder (ASD), have attracted increasing attention. Transgenerational environmental risk exposures with potential for epigenetic effects can be effectively identified using space-time clustering. Specifically applied to ancestors of individuals with disease outcomes, space-time clustering characterized for vulnerable developmental stages of growth can provide a measure of relative risk for disease outcomes in descendants. Objectives (1) Identify space-time clusters of ancestors with a descendent with a clinical ASD diagnosis and matched controls. (2) Identify developmental windows of ancestors with the highest relative risk for ASD in descendants. (3) Identify how the relative risk may vary through the maternal or paternal line. Methods Family pedigrees linked to residential locations of ASD cases in Utah have been used to identify space-time clusters of ancestors. Control family pedigrees of none-cases based on age and sex have been matched to cases 2:1. The data have been categorized by maternal or paternal lineage at birth, childhood, and adolescence. A total of 3957 children, both parents, and maternal and paternal grandparents were identified. Bernoulli space-time binomial relative risk (RR) scan statistic was used to identify clusters. Monte Carlo simulation was used for statistical significance testing. Results Twenty statistically significant clusters were identified. Thirteen increased RR (> 1.0) space-time clusters were identified from the maternal and paternal lines at a p-value

Advancing digitalization is reaching the realm of lightweight construction and structural–mechanical components. Through the synergistic combination of distributed sensors and intelligent evaluation algorithms, traditional structures evolve into smart sensing systems. In this context, Structural Health Monitoring (SHM) plays a key role in managing potential risks to human safety and environmental integrity due to structural failures by providing analysis, localization, and records of the structure’s loading and damaging conditions. The establishment of networks between sensors and data-processing units via Internet of Things (IoT) technologies is an elementary prerequisite for the integration of SHM into smart sensing systems. However, this integrating of SHM faces significant restrictions due to scalability challenges of smart sensing systems and IoT-specific issues, including communication security and interoperability. To address the issue, this paper presents a comprehensive methodological framework aimed at facilitating the scalable integration of objects ranging from components via systems to clusters into SHM systems. Furthermore, we detail a prototypical implementation of the conceptually developed framework, demonstrating a structural component and its corresponding Digital Twin. Here, real-time capable deformation and strain-based monitoring of the structure are achieved, showcasing the practical applicability of the proposed framework.

The Digital Twin is one of the major technology trends of the last decade. During the course of its rapid expansion into various fields of application, many definitions of the Digital Twin emerged, tailored to its respective applications. Taxonomies can cluster the diversity and define application-specific archetypes. This paper presents a systematic characterization of the Digital Twin in the context of structural mechanics and lightweight design. While the importance of a shared understanding and the development of holistic solutions for implementing Digital Twins in various application areas is widely recognized, a general framework for implementing Digital Twins in structural mechanics has not yet been established. In this paper, we systematically characterize Digital Twins and develop a framework for their application in structural mechanics, enabling the digital design and monitoring of structures for improved performance and maintenance strategies. The key contributions include collecting and clustering design and operational requirements and deriving two central archetypes: structure-designing and structure-monitoring Digital Twins. The primary goal is to reduce the complexity of conceptualizing Digital Twins of structures by providing a preliminary framework and reconsidering the Digital Twins of structures as a holistic system throughout the product life cycle. Overall, in this paper, we take a systematic approach to enhancing the conceptualization and implementation of Digital Twins in structural mechanics.

Abstract Background Yoga is becoming an increasingly popular holistic approach in the West to manage long-term health conditions. This study presents the evaluation of a pilot yoga intervention, Yoga4Health, that was developed for the NHS to be socially prescribed to patients at risk of developing specific health conditions (risk factors for cardiovascular disease, pre-diabetes, anxiety/depression or experiencing social isolation). The aim of this qualitative study was to explore service users’ experiences of Yoga4Health and the acceptability of the programme. Methods Qualitative data were collected from three sources: 1. Open-ended questions on questionnaires completed by services users at three different time-points (baseline, post intervention and 3 months); 2. Interviews and focus groups with a subset of participants (n = 22); 3. interviews with yoga teachers delivering Yoga4Health (n = 7). Each data source was analysed thematically, then findings were combined. Results Of participants completing baseline questionnaires (n = 240), 82.5% were female, 50% White, with a mean age of 53 (range 23–82) years. Baseline questionnaires revealed key motivations to attend Yoga4Health were to improve psychological and physical health, and believing Yoga4Health would be accessible for people with their health condition. Post-intervention, participants reported a range of benefits across psychological, physical and social domains from Yoga4Health. Increased confidence in self-management of health was also reported, and a number of participants described making positive lifestyle changes after attending the programme. Unanticipated benefits of yoga emerged for participants, such as enjoyment and social connectedness, which facilitated ongoing attendance and practice. Also key to facilitating practice (during and after the intervention) were suitability of the classes for those with health conditions, practising with a group and qualities of the yoga teacher. Home practice was supported by course materials (manual, videos), as well as the teaching of techniques for everyday application that offered immediate benefits, such as breathing practices. Follow-up questionnaires revealed a key challenge was continuation of practice once the intervention had finished, with the structure of a class important in supporting practice. Conclusions Yoga4Health was a highly acceptable intervention to services users, which brought a range of biopsychosocial improvements, suggesting yoga is an appropriate intervention to offer on social prescription.

Cervical cancer is the leading cause of death among women in Nepal. The American Society of Clinical Oncology (ASCO) and The University of Texas MD Anderson Cancer Center collaborated with international and local experts to hold a cervical cancer prevention course in Nepal in November 2019. The course included didactic lectures and a hands-on workshop. The didactic lectures included the epidemiology of cervical cancer globally and locally, cervical cancer screening guidelines, human papillomavirus vaccination, colposcopy and visual inspection with acetic acid (VIA), cervical dysplasia, and cervical cancer treatment. The hands-on workshop consisted of four stations: (1) VIA; (2) colposcopy, cervical biopsy, and endocervical curettage; (3) thermal ablation; and (4) loop electrosurgical excision procedure (LEEP). A train-the-trainer model short course was held by the international faculty to assist six local faculty to become familiar with the instruments, procedures, and models used in the hands-on training stations. Forty-two people (84% gynecologist, 8% radiation oncologist, and 8% other) attended the course. Following the course, the international faculty visited the regional hospitals for additional educational activities. Increased knowledge in cervical cancer screening guidelines and ability in performing VIA, colposcopy and cervical biopsy, thermal ablation, and LEEP were reported by 89%, 84%, 84%, 87%, and 84% of participants, respectively, from the postcourse on-site evaluations. From the 6-month follow-up survey, all respondents reported that they had made practice changes based on what they learned in the course and had implemented or tried to implement the cervical cancer screening guidelines presented at the course. In conclusion, the course evaluations suggested an improvement in participants' ability to perform cervical cancer screening and diagnostic procedures and reported the changes in practices after training.

Optical endoscopy is the primary diagnostic and therapeutic tool for management of gastrointestinal (GI) malignancies. Most GI neoplasms arise from precancerous lesions; thus, technical innovations to improve detection and diagnosis of precancerous lesions and early cancers play a pivotal role in improving outcomes. Over the last few decades, the field of GI endoscopy has witnessed enormous and focused efforts to develop and translate accurate, user‐friendly, and minimally invasive optical imaging modalities. From a technical point of view, a wide range of novel optical techniques is now available to probe different aspects of light–tissue interaction at macroscopic and microscopic scales, complementing white light endoscopy. Most of these new modalities have been successfully validated and translated to routine clinical practice. Herein, we provide a technical review of the current status of existing and promising new optical endoscopic imaging technologies for GI cancer screening and surveillance. We summarize the underlying principles of light–tissue interaction, the imaging performance at different scales, and highlight what is known about clinical applicability and effectiveness. Furthermore, we discuss recent discovery and translation of novel molecular probes that have shown promise to augment endoscopists' ability to diagnose GI lesions with high specificity. We also review and discuss the role and potential clinical integration of artificial intelligence‐based algorithms to provide decision support in real time. Finally, we provide perspectives on future technology development and its potential to transform endoscopic GI cancer detection and diagnosis.

Purpose We aimed to explore participants' experiences of mental health during an acceptance and commitment therapy (ACT)-based guided self-help intervention to support weight management in adults with overweight or obesity during the COVID-19 pandemic (SWiM-C: Supporting Weight Management during COVID-19). Methods We conducted semi-structured telephone interviews with twenty participants and used reflexive thematic analysis to identify patterns of meaning across the dataset relevant to mental health. Results Four themes were conceptualized: i) Mental health changes associated with SWiM-C, ii) External factors negatively impacted mental health and intervention engagement, iii) Use and impact of coping responses, and iv) Intervention preferences based on psychological needs. Conclusions Findings suggest that participants were exposed to multiple factors, both related to and external to the intervention, that negatively impact their mental health, yet ACT-based aspects of the SWiM-C intervention appeared to support participants to adaptively manage the decline in their mental health. The findings can be used to inform the development of future weight management interventions, such as through intervention personalization and the inclusion of more strategies that target emotional regulation. Trial registration: ISRCTN 12107048, https://www.isrctn.com/ISRCTN12107048