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The argument made here is that childism advances a new critical theory for understanding what is involved in social empowerment. Like feminism, decolonialism, and other critical perspectives, its aim is to reimagine human relations not just for one particular group but for all as members of shared social systems. Childism is first examined as a response to the normative problem of historical adultism or patriarchy, the empowerment of adulthood by disempowering childhood. Then it is formulated as a critical theory of its own based on new conceptions of the political subject, public expression, and political empowerment (or, respectively, the ontological, epistemological, and political dimensions of social life). These are illustrated in relation to questions of voting rights, climate activism, free speech, and work. The result is a theory of social empowerment that calls for the active inclusion of all persons in systems of power specifically in their deeply interdependent lived experiences of difference.

This article is a conceptual co-exploration of the relationship between philosophy and childism. It draws upon a colloquium in December 2021 at the Childism Institute at Rutgers University. Nine co-authors lay out and interweave scholarly imaginations to collectively explore the concept of childism in critical philosophical depth. Through diverse entry points, the co-authors bring a wide range of theoretical perspectives to this task, some engaging the term childism explicitly in their work, others approaching it anew. The result is an extended conversation about the possibilities for deconstructing ingrained historical adultism and reconstructing social norms and structures in response to what is marginalized in the experiences of children. Our own conclusion, having initiated this dialogue, is that we have learned to think about childism with greater plurality, that is, as childisms.

One day in my middle age deep asleep beside my wife, I heard a grinding, thunder, Moses smiting rock, bone-shaking, loosening some unnamed certainty I'd taken for granted. I opened [...]

Abstract Background Despite the detrimental impact of abnormal glucose metabolism on cardiovascular prognosis after myocardial infarction (MI), diabetes is both underdiagnosed and undertreated. We investigated associations between structured diabetes care routines in cardiac rehabilitation (CR) and detection and treatment of diabetes at one-year post-MI. Methods Center-level data was derived from the Perfect-CR survey, which evaluated work routines applied at Swedish CR centers (n = 76). Work routines involving diabetes care included: (1) routine assessment of fasting glucose and/or HbA1c, (2) routine use of oral glucose tolerance test (OGTT), (3) having regular case rounds with diabetologists, and (4) whether glucose-lowering medication was adjusted by CR physicians. Patient-level data was obtained from the national MI registry SWEDEHEART (n = 7601, 76% male, mean age 62.6 years) and included all post-MI patients irrespective of diabetes diagnosis. Using mixed-effects regression we estimated differences between patients exposed versus. not exposed to the four above-mentioned diabetes care routines. Outcomes were newly detected diabetes and the proportion of patients receiving oral glucose-lowering medication at one-year post-MI. Results Routine assessment of fasting glucose/HbA1c was performed at 63.2% (n = 48) of the centers, while 38.2% (n = 29) reported using OGTT for detecting glucose abnormalities. Glucose-lowering medication adjusted by CR physicians (n = 13, 17.1%) or regular case rounds with diabetologists (n = 7, 9.2%) were less frequently reported. In total, 4.0% of all patients (n = 304) were diagnosed with diabetes during follow-up and 17.9% (n = 1361) were on oral glucose-lowering treatment one-year post-MI. Routine use of OGTT was associated with a higher rate of newly detected diabetes at one-year (risk ratio [95% confidence interval]: 1.62 [1.26, 1.98], p = 0.0007). At one-year a higher proportion of patients were receiving oral glucose-lowering medication at centers using OGTT (1.22 [1.07, 1.37], p = 0.0046) and where such medication was adjusted by CR physicians (1.31 [1.06, 1.56], p = 0.0155). Compared to having none of the structured diabetes care routines, the more routines implemented the higher the rate of newly detected diabetes (from 0 routines: 2.7% to 4 routines: 6.3%; p for trend = 0.0014). Conclusions Having structured routines for diabetes care implemented within CR can improve detection and treatment of diabetes post-MI. A cluster-randomized trial is warranted to ascertain causality.

The last two decades have witnessed a significant growth in the volume of academic work exploring the final statements of inmates executed in the United States of America. While this has done much to advance academic understanding of final statements, comparably little attention has been paid to the not-insignificant number of inmates who decline to speak prior to their execution. The article presents the results of a regression analysis of a 574-case data set covering all executions conducted in Texas between December 1982 and April 2022. Despite including a range of variables, analysis identified only a single significant result: the presence of victims' family and/or close friends. The significance of this finding for existing scholarship and practice is discussed, alongside possible directions for future research.

Abstract Background Understanding biodiversity patterns is a central topic in biogeography and ecology, and it is essential for conservation planning and policy development. Diversity estimates that consider the evolutionary relationships among species, such as phylogenetic diversity and phylogenetic endemicity indices, provide valuable insights into the functional diversity and evolutionary uniqueness of biological communities. These estimates are crucial for informed decision-making and effective global biodiversity management. However, the current methodologies used to generate these metrics encounter challenges in terms of efficiency, accuracy, and data integration. Results We introduce PhyloNext, a flexible and data-intensive computational pipeline designed for phylogenetic diversity and endemicity analysis. The pipeline integrates GBIF occurrence data and OpenTree phylogenies with the Biodiverse software. PhyloNext is free, open-source, and provided as Docker and Singularity containers for effortless setup. To enhance user accessibility, a user-friendly, web-based graphical user interface has been developed, facilitating easy and efficient navigation for exploring and executing the pipeline. PhyloNext streamlines the process of conducting phylogenetic diversity analyses, improving efficiency, accuracy, and reproducibility. The automated workflow allows for periodic reanalysis using updated input data, ensuring that conservation strategies remain relevant and informed by the latest available data. Conclusions PhyloNext provides researchers, conservationists, and policymakers with a powerful tool to facilitate a broader understanding of biodiversity patterns, supporting more effective conservation planning and policy development. This new pipeline simplifies the creation of reproducible and easily updatable phylogenetic diversity analyses. Additionally, it promotes increased interoperability and integration with other biodiversity databases and analytical tools.

Background Cost of illness studies are important tools to summarise the burden of disease for individuals, the healthcare system and society. The lack of standardised methods for reporting costs for cystic fibrosis (CF) makes it difficult to quantify the total socioeconomic burden. In this study, we aimed to comprehensively report the socioeconomic burden of CF in Canada.Methods The total cost of CF in Canada was calculated by triangulating information from three sources (Canadian CF Registry, customised Burden of Disease survey and publicly available information). A prevalence-based, bottom-up, human capital approach was applied, and costs were categorised into four perspectives (ie, healthcare system, individual/caregiver, variable (ie, medicines) and society) and three domains (ie, direct, indirect and intangible). All costs were converted into 2021 Canadian dollars (CAD) and adjusted for inflation. The cost of cystic fibrosis transmembrane conductance regulator (CFTR) modulator therapies was excluded.Results The total socioeconomic burden of CF in Canada in 2021 across the four perspectives was $C414 million. Direct costs accounted for two-thirds of the total costs, with medications comprising half of all direct costs. Out-of-pocket costs to individuals and caregivers represented 18.7% of all direct costs. Indirect costs representing absenteeism accounted for one-third of the total cost.Conclusion This comprehensive cost of illness study for CF represents a community-oriented approach describing the socioeconomic burden of living with CF and serves as a benchmark for future studies.

Internet-based cognitive behavioral therapy (iCBT) offers a scalable, cost-effective, accessible, and low-threshold form of psychotherapy. Recent advancements explored the use of conversational agents such as chatbots and voice assistants to enhance the delivery of iCBT. These agents can deliver iCBT-based exercises, recognize and track emotional states, assess therapy progress, convey empathy, and potentially predict long-term therapy outcome. However, existing systems predominantly utilize categorical approaches for emotional modeling, which can oversimplify the complexity of human emotional states. To address this, we developed a transformer-based model for dimensional text-based emotion recognition, fine-tuned with a novel, comprehensive dimensional emotion dataset comprising 75,503 samples. This model significantly outperforms existing state-of-the-art models in detecting the dimensions of valence, arousal, and dominance, achieving a Pearson correlation coefficient of r = 0.90, r = 0.77, and r = 0.64, respectively. Furthermore, a feasibility study involving 20 participants confirmed the model’s technical effectiveness and its usability, acceptance, and empathic understanding in a conversational agent-based iCBT setting, marking a substantial improvement in personalized and effective therapy experiences.

Abstract Background When the COVID pandemic hit the world, there was need for applied guides and training materials to support frontline health care staff to manage patients effectively and safely and to educate themselves and communities. This article reports on the development and piloting of such a set of materials in Sierra Leone, which were based on international evidence but adapted to the local context. Reflecting on this experience, including community and health system barriers and enablers, is important to prepare for future regional shocks. Methods This study, in Bombali district in 2020, piloted user-friendly COVID guides for frontline health workers (the intervention), which was evaluated using facility checklists (pre and post training), routine data analysis and 32 key informant interviews. Results Key informants at district, hospital and community health centre levels identified gains from the training and desk guides, including improved diagnosis, triaging, infection prevention and management of patients. They also reported greater confidence to share messages on protection with colleagues and community members, which was needed to encourage continued use of essential services during the pandemic. However, important barriers were also revealed, including the lack of testing facilities, which reduced the sense of urgency, as few cases were identified. Actions based on the Ebola experience, such as setting up testing and isolation centres, which the community avoided, were not appropriate to COVID. Stigma and fear were important factors, although these were reduced with outreach activities. Supplies of essential medicines and personal protective equipment were also lacking. Conclusion This pilot study demonstrated the relevance and importance of guides adapted to the context, which were able to improve the confidence of health staff to manage their own and the community’s fears in the face of a new pandemic and improve their skills. Previous epidemics, particularly Ebola, complicated this by both creating structures that could be revitalised but also assumptions and behaviours that were not adapted to the new disease. Our study documents positive adaptations and resilience by health staff but also chronic system weaknesses (particularly for medicines, supplies and equipment) which must be urgently addressed before the next shock arrives.

Abstract Background High salt intake is a major risk factor for hypertension, which in turn contributes to cardiovascular diseases, the major cause of death from non communicable diseases (NCDs). Research is limited on social mobilisation interventions to tackle NCDs, including in fragile health settings such as Sierra Leone. Methods Participatory action research methods were used to develop a social mobilisation intervention for salt reduction in Bombali District, Sierra Leone. A team of 20 local stakeholders were recruited to develop and deliver the intervention. Stakeholder workshop reports and interviews were used to record outcomes, enablers, and barriers to the intervention. Focus group discussions were used to observe knowledge, attitudes, and behaviours of community members pre- and post- the intervention. Results Stakeholders showed enthusiasm and were well engaged in the social mobilisation process around salt reduction. They developed radio jingles, radio show talks, organised community awareness raising meetings, school sensitisation outreaches, and door to door engagements. Stakeholders reported benefiting personally through developing their own skills and confidence in communication and felt positive about their role in educating their community. The interventions led to reported increased awareness of risks of high salt intake and NCDs, resulting in a reduction of salt use in the community, leading to perceived health gains. However, salt reduction was also met with some resistance due to social factors. Local community structures were also reactivated to work on the interventions and connect the community to the local health facility, which saw an increase in patients having their blood pressure checked. The comparison villages also experienced an increase in awareness and perceived reductions in salt intake behaviours. This was as messages had cascaded via the radio and initial focus group discussions. The social mobilisation stakeholders also agreed on future activities that could continue at no or low cost. Conclusion Social mobilisation interventions can provide low-cost strategies to tackle NCDs in fragile settings such as Sierra Leone through the utilisation of community structures. However, more research is required to ascertain the key enablers for replicability and if such successes can be sustained over a longer follow up period.

Objective: Interactive patient education, referred to as Heart School (HS), is an important part of cardiac rehabilitation (CR) after myocardial infarction (MI), which has been associated with improved outcomes. Little is known about HS attendance among foreign-born patients. The aims were to assess; 1) HS attendance in foreign-born versus native-born patients, 2) the association between the provision of professional interpreters and HS attendance, and 3) secondary prevention goal attainment after MI based on HS attendance. Methods: The provision of professional interpreters during post-MI follow-up was assessed by a questionnaire sent to all 78 Swedish CR sites. Patient-specific data was retrieved from the SWEDEHEART registry. The association between the provision of professional interpreters and HS attendance was estimated with logistic regression models. HS attendance and attainment of secondary prevention goals by country of birth were investigated. Results: In total, 8377 patients

Abstract SARS‐CoV‐2 acute respiratory distress syndrome (ARDS) induces uncontrolled lung inflammation and coagulopathy with high mortality. Anti‐viral drugs and monoclonal antibodies reduce early COVID‐19 severity, but treatments for late‐stage immuno‐thrombotic syndromes and long COVID are limited. Serine protease inhibitors (SERPINS) regulate activated proteases. The myxoma virus‐derived Serp‐1 protein is a secreted immunomodulatory serpin that targets activated thrombotic, thrombolytic, and complement proteases as a self‐defense strategy to combat clearance. Serp‐1 is effective in multiple animal models of inflammatory lung disease and vasculitis. Here, we describe systemic treatment with purified PEGylated Serp‐1 as a therapy for immuno‐coagulopathic complications during ARDS. Treatment with PEGSerp‐1 in two mouse‐adapted SARS‐CoV‐2 models in C57Bl/6 and BALB/c mice reduced lung and heart inflammation, with improved outcomes. PEGSerp‐1 significantly reduced M1 macrophages in the lung and heart by modifying urokinase‐type plasminogen activator receptor (uPAR), thrombotic proteases, and complement membrane attack complex (MAC). Sequential changes in gene expression for uPAR and serpins (complement and plasminogen inhibitors) were observed. PEGSerp‐1 is a highly effective immune‐modulator with therapeutic potential for severe viral ARDS, immuno‐coagulopathic responses, and Long COVID.

Purpose Depression and anxiety afflict millions worldwide causing considerable disability. MULTI-PSYCH is a longitudinal cohort of genotyped and phenotyped individuals with depression or anxiety disorders who have undergone highly structured internet-based cognitive-behaviour therapy (ICBT). The overarching purpose of MULTI-PSYCH is to improve risk stratification, outcome prediction and secondary preventive interventions. MULTI-PSYCH is a precision medicine initiative that combines clinical, genetic and nationwide register data.Participants MULTI-PSYCH includes 2668 clinically well-characterised adults with major depressive disorder (MDD) (n=1300), social anxiety disorder (n=640) or panic disorder (n=728) assessed before, during and after 12 weeks of ICBT at the internet psychiatry clinic in Stockholm, Sweden. All patients have been blood sampled and genotyped. Clinical and genetic data have been linked to several Swedish registers containing a wide range of variables from patient birth up to 10 years after the end of ICBT. These variable types include perinatal complications, school grades, psychiatric and somatic comorbidity, dispensed medications, medical interventions and diagnoses, healthcare and social benefits, demographics, income and more. Long-term follow-up data will be collected through 2029.Findings to date Initial uses of MULTI-PSYCH include the discovery of an association between PRS for autism spectrum disorder and response to ICBT, the development of a machine learning model for baseline prediction of remission status after ICBT in MDD and data contributions to genome wide association studies for ICBT outcome. Other projects have been launched or are in the planning phase.Future plans The MULTI-PSYCH cohort provides a unique infrastructure to study not only predictors or short-term treatment outcomes, but also longer term medical and socioeconomic outcomes in patients treated with ICBT for depression or anxiety. MULTI-PSYCH is well positioned for research collaboration.

Generating biomass-at-age indices for fisheries stock assessments with acoustic data collected by uncrewed surface vessels (USVs) has been hampered by the need to resolve acoustic backscatter with contemporaneous biological (e.g., age) composition data. To address this limitation, Pacific hake (Merluccius productus; “hake”) acoustic data were gathered from a USV survey (in 2019) and acoustic-trawl survey (ATS; 2019 and eight previous years), and biological data were gathered from fishery-dependent and non-target (i.e., not specifically targeting hake) fishery-independent sources (2019 and eight previous years). To overcome the lack of contemporaneous biological sampling in the USV survey, age class compositions were estimated from a generalized linear mixed spatio-temporal model (STM) fit to the fishery-dependent and non-target fishery-independent data. The validity of the STM age composition estimation procedure was assessed by comparing estimates to age compositions from the ATS in each year. Hake biomass-at-age was estimated from all combinations of acoustics (USV or ATS in 2019, ATS only in other years) and age composition information (STM or ATS in all years). Across the survey area, proportional age class compositions derived from the best STM differed from ATS observations by 0.09 on average in 2019 (median relative error (MRE): 19.45%) and 0.14 across all years (MRE: 79.03%). In data-rich areas (i.e., areas with regular fishery operations), proportional age class compositions from the STM differed from ATS observations by 0.03 on average in 2019 (MRE: 11.46%) and 0.09 across years (MRE: 54.96%). On average, total biomass estimates derived using STM age compositions differed from ATS age composition-based estimates by approximately 7% across the study period (~ 3% in 2019) given the same source of acoustic data. When biomass estimates from different sources of acoustic data (USV or ATS) were compared given the same source of age composition data, differences were nearly ten-fold greater (22% or 27%, depending on if ATS or STM age compositions were used). STMs fit to non-contemporaneous data may provide suitable information for assigning population structure to acoustic backscatter in data-rich areas, but advancements in acoustic data processing (e.g., automated echo classification) may be needed to generate viable USV-based estimates of biomass-at-age.

This paper introduces a novel approach to measure deformations in geomaterials using the recently developed ‘Smart Pebble’ sensors. Smart Pebbles were included in triaxial test specimens of unbound aggregates stabilized with geogrids. The sensors are equipped with an aggregate particle/position tracking algorithm that can manage uncertainty arising due to signal noise and random walk effects. Two Smart Pebbles were placed in each test specimen, one at specimen’s mid-height, where a geogrid was installed in the mechanically stabilized specimen, and one towards the top of the specimen. Even with simple raw data processing, the trends on linear vertical acceleration indicated the ability of Smart Pebbles to assess the geomaterial configuration and applied stress states. Employing a Kalman filter-based algorithm, the Smart Pebble position coordinates were tracked during testing. The specimen’s resilient deformations were simultaneously recorded. bender element shear wave transducer pairs were also installed on the specimens to further validate the Smart Pebble small-strain responses. The results indicate a close agreement between the BE sensors and Smart Pebbles estimates towards local stiffness enhancement quantification in the geogrid specimen. The study findings confirm the viability of using the Smart Pebbles in describing the resilient behavior of an aggregate material under repeated loading.

Measurement(s) Corrections and impact Technology Type(s) Data comparisons Factor Type(s) taxon name Sample Characteristic - Organism Fabaceae Sample Characteristic - Environment global

Abstract This study applied supervised machine learning with multi-modal data to predict remission of major depressive disorder (MDD) after psychotherapy. Genotyped adult patients (n = 894, 65.5% women, age 18–75 years) diagnosed with mild-to-moderate MDD and treated with guided Internet-based Cognitive Behaviour Therapy (ICBT) at the Internet Psychiatry Clinic in Stockholm were included (2008–2016). Predictor types were demographic, clinical, process (e.g., time to complete online questionnaires), and genetic (polygenic risk scores). Outcome was remission status post ICBT (cut-off ≤10 on MADRS-S). Data were split into train (60%) and validation (40%) given ICBT start date. Predictor selection employed human expertise followed by recursive feature elimination. Model derivation was internally validated through cross-validation. The final random forest model was externally validated against a (i) null, (ii) logit, (iii) XGBoost, and (iv) blended meta-ensemble model on the hold-out validation set. Feature selection retained 45 predictors representing all four predictor types. With unseen validation data, the final random forest model proved reasonably accurate at classifying post ICBT remission (Accuracy 0.656 [0.604, 0.705], P vs null model = 0.004; AUC 0.687 [0.631, 0.743]), slightly better vs logit (bootstrap D = 1.730, P = 0.084) but not vs XGBoost (D = 0.463, P = 0.643). Transparency analysis showed model usage of all predictor types at both the group and individual patient level. A new, multi-modal classifier for predicting MDD remission status after ICBT treatment in routine psychiatric care was derived and empirically validated. The multi-modal approach to predicting remission may inform tailored treatment, and deserves further investigation to attain clinical usefulness.

Connectivity between inferred spawning areas and potential settlement areas of the petrale sole (Eopsetta jordani) was explored in the California Current System (CCS) using an individual-based model (IBM) coupled with the ROMS hydrodynamic model for the period 1988-2008. The IBM modeled pelagic early life stages, including egg and larval development, growth, natural mortality and settlement into benthos. Eggs were released within discrete spawning grounds identified from the winter fishery logbook data. Potential settlement areas were defined based on bathymetrical criteria and juvenile (2-year old) distribution from a groundfish bottom trawl survey. The influence of cross-shelf and alongshore advection on the transport and connectivity between spawning and benthic settlement areas was explored by identifying the location of juveniles (22 mm length) among the potential settlement areas. The most important spawning regions varied over time with between 4 and 19% of spawned individuals successfully settling, mostly ranging from off northern Washington to northern Oregon. The strong influence of northward alongshore transport resulted in transboundary transport of pelagic life stages from U.S. spawning grounds to inner shelf settlement areas in Canadian waters, with 33.9-70.4% (average 49.7 ± 9.6) of annual successful juveniles settling in Canada. Interannual variability in juvenile settlement success suggests that mesoscale (100-200 km) oceanographic structures play a major role defining pelagic juvenile transport trajectories. While, in some years, the presence of coastal cyclonic eddies can retain juveniles off Oregon, the strong northward transport supplies a large number of juveniles to Moresby and Vancouver island, clearly showing that petrale sole off the west coast of North America are a transboundary stock with important settlement areas off the coast of British Columbia, thus extension of this study into Canadian waters is particularly relevant.

Background: Despite reported tuberculosis (TB) treatment success rate of 86%, TB remains a leading cause of death in Ethiopia. We investigated patient and provider-specific factors associated with unfavorable treatment outcomes in Ethiopian health facilities providing TB care. Methods: Data on characteristics and treatment outcomes of patients registered for TB treatment at 15 public health facilities (4 hospitals and 11 health centres) were collected from clinic registers. Proportions of unfavorable outcomes (defined as deaths, loss-to-follow-up [LTFU] and treatment failure), were compared across facilities using multivariable logistic regression, with separate analyses for death and LTFU. Results: Among 3359 patients (53.5 % male, median age 28 years, 19.6 % HIV-positive), 296 (8.8 %) had unfavorable treatment outcome. Proportions of unfavorable outcomes across facilities ranged from 2.0 % to 21.1 % (median 8.3 %). Median proportions of death and LTFU among facilities were 3.3 % (range 0–10.9 %) and 2.6 % (range 0.6 %-19.2 %), respectively. Three facilities had significantly higher rates of LTFU, whereas two facilities had higher rates of death. The two facilities with full-time TB-nurses had higher proportions of successful outcomes (95.2 % vs 90.1 %, adjusted odds ratio 2.27, p

IntroductionUnderstanding how abundance, productivity and distribution of individual species may respond to climate change is a critical first step towards anticipating alterations in marine ecosystem structure and function, as well as developing strategies to adapt to the full range of potential changes.MethodsThis study applies the NOAA (National Oceanic and Atmospheric Administration) Fisheries Climate Vulnerability Assessment method to 64 federally-managed species in the California Current Large Marine Ecosystem to assess their vulnerability to climate change, where vulnerability is a function of a species’ exposure to environmental change and its biological sensitivity to a set of environmental conditions, which includes components of its resiliency and adaptive capacity to respond to these new conditions.ResultsOverall, two-thirds of the species were judged to have Moderate or greater vulnerability to climate change, and only one species was anticipated to have a positive response. Species classified as Highly or Very Highly vulnerable share one or more characteristics including: 1) having complex life histories that utilize a wide range of freshwater and marine habitats; 2) having habitat specialization, particularly for areas that are likely to experience increased hypoxia; 3) having long lifespans and low population growth rates; and/or 4) being of high commercial value combined with impacts from non-climate stressors such as anthropogenic habitat degradation. Species with Low or Moderate vulnerability are either habitat generalists, occupy deep-water habitats or are highly mobile and likely to shift their ranges.DiscussionAs climate-related changes intensify, this work provides key information for both scientists and managers as they address the long-term sustainability of fisheries in the region. This information can inform near-term advice for prioritizing species-level data collection and research on climate impacts, help managers to determine when and where a precautionary approach might be warranted, in harvest or other management decisions, and help identify habitats or life history stages that might be especially effective to protect or restore.

ABSTRACT The immune control of tuberculosis (TB) infection could be influenced by pregnancy. To elucidate this, we longitudinally characterized Mycobacterium tuberculosis (Mtb)-specific and nonspecific immune responses in women during pregnancy and postpartum. HIV-uninfected women without past or current active TB, and with blood samples available from the 1st/2nd trimester, 3rd trimester, and 9 months postpartum, were identified at Ethiopian antenatal care clinics. Twenty-two TB+ women and 10 TB− women, defined according to Mtb-stimulated interferon-γ levels (≥0.35 and

Objective We investigated prolonged COVID-19 symptom duration, defined as lasting 28 days or longer, among people with systemic autoimmune rheumatic diseases (SARDs).Methods We analysed data from the COVID-19 Global Rheumatology Alliance Vaccine Survey (2 April 2021–15 October 2021) to identify people with SARDs reporting test-confirmed COVID-19. Participants reported COVID-19 severity and symptom duration, sociodemographics and clinical characteristics. We reported the proportion experiencing prolonged symptom duration and investigated associations with baseline characteristics using logistic regression.Results We identified 441 respondents with SARDs and COVID-19 (mean age 48.2 years, 83.7% female, 39.5% rheumatoid arthritis). The median COVID-19 symptom duration was 15 days (IQR 7, 25). Overall, 107 (24.2%) respondents had prolonged symptom duration (≥28 days); 42/429 (9.8%) reported symptoms lasting ≥90 days. Factors associated with higher odds of prolonged symptom duration included: hospitalisation for COVID-19 vs not hospitalised and mild acute symptoms (age-adjusted OR (aOR) 6.49, 95% CI 3.03 to 14.1), comorbidity count (aOR 1.11 per comorbidity, 95% CI 1.02 to 1.21) and osteoarthritis (aOR 2.11, 95% CI 1.01 to 4.27). COVID-19 onset in 2021 vs June 2020 or earlier was associated with lower odds of prolonged symptom duration (aOR 0.42, 95% CI 0.21 to 0.81).Conclusion Most people with SARDs had complete symptom resolution by day 15 after COVID-19 onset. However, about 1 in 4 experienced COVID-19 symptom duration 28 days or longer; 1 in 10 experienced symptoms 90 days or longer. Future studies are needed to investigate the possible relationships between immunomodulating medications, SARD type/flare, vaccine doses and novel viral variants with prolonged COVID-19 symptoms and other postacute sequelae of COVID-19 among people with SARDs.

Performing Markov chain Monte Carlo parameter estimation on complex mathematical models can quickly lead to endless searching through highly multimodal parameter spaces. For computationally complex models, one rarely has prior knowledge of the optimal proposal distribution. In such cases, the Markov chain can become trapped near a suboptimal mode, lowering the computational efficiency of the method. With these challenges in mind, we present a novel MCMC kernel which incorporates both mixing and adaptation. The method is flexible and robust enough to handle parameter spaces that are highly multimodal. Other advantages include not having to locate a near-optimal mode with a different method beforehand, as well as requiring minimal computational and storage overhead from standard Metropolis. Additionally, it can be applied in any stochastic optimization context which uses a Gaussian kernel. We provide results from several benchmark problems, comparing the kernel's performance in both optimization and MCMC cases. For the former, we incorporate the kernel into a simulated annealing method and real-coded genetic algorithm. For the latter, we incorporate it into the standard Metropolis and adaptive Metropolis methods.

Objective To pilot the use of a scalable innovative mobile health (mHealth) non-communicable diseases (NCDs) training application for nurses at the primary care level.Design Mixed methods pilot of mHealth training on NCD care for nurses at primary healthcare (PHC) facilities. We provide a descriptive analysis of mHealth training test scores, with trend analysis of blood pressure (BP) control using paired t-test for quantitative data and thematic analysis for qualitative data.Setting PHC facilities in rural and urban communities in Cross River State, south eastern Nigeria. NCDs were not part of routine training previously. As in most low-and-middle-income settings, funding for scale-up using conventional classroom in-service training for NCDs is not available in Nigeria, and onsite supervision poses challenges.Participants Twenty-four health workers in 19 PHC facilities.Intervention A self-paced mHealth training module on an NCD desk guide was adapted to be applicable within the Nigerian context in collaboration with the Federal Ministry of Health. The training which focused on hypertension, diabetes and sickle cell disease was delivered via Android tablet devices, supplemented by quarterly onsite supervision and group support via WhatsApp. The training was evaluated with pre/post-course tests, structured observations and focus group discussions. This was an implementation pilot assessing the feasibility and potential effectiveness of mHealth training on NCD in primary care delivery.Results Nurses who received mHealth training recorded a statistically significant difference (p

Background: Large variation exists for out-of-hospital-cardiac-arrest (OHCA) prehospital care, but less is known about variations in post-arrest care. We sought to evaluate variation in post-arrest care in Texas as well as factors associated with higher performing hospitals. Methods: We analyzed data in Texas Cardiac Arrest Registry to Enhance Survival (TX-CARES), including all adult, non-traumatic OHCAs from 1/1/2014 through 12/31/ 2020 that survived to hospital admission. We first evaluated variability in provisions of post-arrest care and outcomes. We then stratified hospitals into quartiles based on their rate of survival and evaluated the association between improving quartiles and care. Lastly, we evaluated for outliers in post-arrest care and outcomes using a mixed-effect regression model. Results: We analyzed 7,842 OHCAs admitted to 146 hospitals. We identified large variations in post-arrest care, including targeted temperature management (TTM) (IQR 7.0–51.1%), left heart catheterization (LHC) (IQ 0–25%), and percutaneous coronary intervention (PCI) (IQR 0–10.3%). Higher performing hospital quartiles were associated with higher rates of TTM (aOR 1.42, 95% CI 1.36–1.49), LHC (aOR 2.07, 95% CI 1.92–2.23), and PCI (aOR 2.02, 95% CI 1.81–2.25); but lower rates of bystander CPR (aOR 0.90, 95% CI 0.87–0.94). We identified numerous performance outlier hospitals; 39 for TTM, 34 for PCI, 9 for survival to discharge, and 24 for survival with good neurologic function. Conclusions: Post-arrest care varied widely across Texas hospitals. Hospitals with higher rates of survival to discharge had increased rates of TTM, LHC, and PCI but not bystander CPR.

Air pollution poses a threat to human health, with pregnant women and their developing fetuses being particularly vulnerable. A high dual burden of ambient and indoor air pollution exposure has been identified in Ethiopia, but studies investigating their effects on adverse birth outcomes are currently lacking. This study explores the association between ambient air pollution (NOX and NO2) and indoor air pollution (cooking fuel type) and fetal and neonatal death in Adama, Ethiopia. A prospective cohort of mothers and their babies was used, into which pregnant women were recruited at their first antenatal visit (n = 2085) from November 2015 to February 2018. Previously developed land-use regression models were utilized to assess ambient concentrations of NOX and NO2 at the residential address, whereas data on cooking fuel type was derived from questionnaires. Birth outcome data was obtained from self-reported questionnaire responses during the participant's postnatal visit or by phone if an in-person meeting was not possible. Binary logistic regression was employed to assess associations within the final study population (n = 1616) using both univariate and multivariate models; the latter of which adjusted for age, education, parity, and HIV status. Odds ratios (OR) and their corresponding 95% confidence intervals (CI) were reported. Within the cohort, 69 instances of fetal death (n = 16 miscarriages; n = 53 stillbirths) and 16 cases of neonatal death were identified. The findings suggest a tendency towards an association between ambient NOX and NO2 exposure during pregnancy and an increased risk of fetal death overall as well as stillbirth, specifically. However, statistical significance was not observed. Results for indoor air pollution and neonatal death were inconclusive. As limited evidence on the effects of exposure to ambient air pollution on adverse birth outcomes exists in Sub-Saharan Africa and Ethiopia, additional studies with larger study populations should be conducted.