Search

Background: Hip fracture and multimorbidity represent significant health challenges for older people. Despite evidence that orthogeriatric co-management improves hip fracture management and patients' health outcomes, there is little evidence to understand its effectiveness for patients with multimorbidity. The study aimed to assess the effect of the orthogeriatric co-management care model on older hip fracture patients with multimorbidity. Methods: This study was a post-hoc analysis of a recently completed trial. Patients were admitted to three urban hospitals and three suburban hospitals in Beijing, with diagnosed hip fracture. One urban hospital (intervention group) implemented the orthogeriatric co-management, while other hospitals (control group) continued orthopedics-led usual care. All enrolled patients were followed-up for three times within one year. Study outcome was patients' one-year cumulative adverse events, including re-operation, complication and death. Logistic regression models were used to compare the differences between the intervention and control groups, with adjustment for all potential confounders. Result: A total of 2,071 patients with hip fracture (1,110 intervention, 961 control) were included. More than half of the patients had multimorbidity. Hypertension and diabetes were the leading disease cluster, while hypertension was the most prevalent disease condition across all observed disease clusters. Older hip fracture patients with multimorbidity in the intervention group saw a significantly reduced risk of adverse events compared to the control group (Odds Ratio = 0.59, 95% Confidence Interval: 0.48 to 0.73). Conclusion: Multimorbidity is common among older hip fracture patients. Orthogeriatric co-management provides better outcomes for patients with multimorbidity, in reducing the risk of adverse events after a hip fracture. Clinical trial registration information: The study was a post-hoc analysis using data from a non-randomized controlled trial. Registry name: Services Mapping Among Older Adults With Hip Fracture (HiFit) ClinicalTrials.gov ID: NCT03184896 URL: https://clinicaltrials.gov/study/NCT03184896 [ABSTRACT FROM AUTHOR]

Background: Substantial inequalities in the overall prevalence and patterns of multimorbidity have been widely reported, but the causal mechanisms are complex and not well understood. This study aimed to identify common patterns of multimorbidity in Serbia and assess their relationship with air pollutant concentrations and water quality indicators. Methods: This ecological study was conducted on a nationally representative sample of the Serbian population. Data were obtained from the European Health Interview (EHIS) Survey, a periodic study designed to assess population health using widely recognized standardized instruments. The study included 13,069 participants aged 15 and older, randomly selected through a multistage stratified sampling design. Multimorbidity was defined as having two or more self-reported diagnoses of chronic non-communicable diseases. Latent class analysis (LCA) was performed to identify clusters of multimorbidity. Concentrations of particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3), as well as water quality indicators, were obtained from the Serbian Environmental Protection Agency. Results: The overall prevalence of multimorbidity was 33.4% [32.6%—34.2%]. Six latent classes of multimorbidity were identified: Healthy, Multicondition, Cardiovascular, Metabolic syndrome, Respiratory, and Musculoskeletal. Annual increases in PM10 and SO2 concentrations, as well as daily increases in O3 concentrations, significantly raised the odds of having multimorbidity (OR = 1.02, 95% CI 1.02–1.03; OR = 1.01, 95% CI 1.00–1.02 and OR = 1.03, 95% CI 1.02–1.03, respectively). A pattern of increased risk was observed with rising levels of water contamination. Exposure to physico-chemical, microbiological and combined contamination was associated with a 3.92%, 5.17% and 5.54% higher probability, respectively, of having multiple chronic conditions. There was strong evidence that air pollutants, as well as chemical and microbial water contamination, were significantly associated with higher odds of the most common clusters of multimorbidity identified by LCA. Conclusion: There is compelling evidence of an association between multimorbidity and environmental pollution, suggesting that exposure to air pollutants and water contaminants may contribute to disease accumulation and help explain geographically and socioeconomically patterned inequalities. These findings underscore the need for extensive studies that simultaneously measure both multimorbidity and pollution to explore their complex interrelationships. [ABSTRACT FROM AUTHOR]

Background: Family history of Parkinson's disease (PD) is a common finding in PD patients. However, a few studies have systematically examined this aspect. Objectives: We investigated the family history of PD patients, comparing demographic and clinical features between familial PD (fPD) and sporadic PD (sPD). Methods: A cross‐sectional study enrolling 2035 PD patients was conducted in 28 Italian centers. Clinical data and family history up to the third degree of kinship were collected. Results: Family history of PD was determined in 21.9% of patients. fPD patients had earlier age at onset than sporadic patients. No relevant differences in the prevalence of motor and nonmotor symptoms were detected. Family history of mood disorders resulted more prevalently in the fPD group. Conclusions: fPD was found to recur more frequently than previously reported. Family history collection beyond the core family is essential to discover disease clusters and identify novel risk factors for PD. [ABSTRACT FROM AUTHOR]

Vaccination is one of the most impactful public health interventions globally. To ensure equitable access to vaccines for all children, the World Health Organization (WHO) launched the Expanded Programme on Immunization (EPI) in 1974 as a guiding framework for member states. The EPI has saved over 50 million lives in the WHO African Region over its 50-year history. Despite current progress, most countries in the WHO African Region are still not on track to achieve the targets of the Immunization Agenda 2030. Research has been identified as an important tool for enhancing immunization performance and it's included as part of the strategic priorities of the IA2030. During a recently concluded immunization programme managers' meeting of East and Southern African countries, held from 25 to 27 June 2024, a discussion was held on vaccine and immunization-related research. We provide insights into suggested research priorities by immunization managers for the WHO African Region. Dedicated national and regional research agendas for vaccine and immunization research may need to be strengthened. Additionally, most countries will need capacity building for developing national research priority agendas within their national immunization programmes, ensuring that the needs, concerns, and contextual issues of the population are considered. While most of the suggested research priorities focused primarily on potential implementation research, other topics included the impact of vaccination and vaccine safety. Overall, there is need for broader stakeholder consultations to ensure that research prioritization is comprehensive to inform all the programme pillars in immunization. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has spread through pre-existing fault lines in societies, deepening structural barriers faced by precarious workers, low-income populations, and racialized communities in lower income sub-city units. Many studies have quantified the magnitude of inequalities in COVID-19 distribution within cities, but few have taken an international comparative approach to draw inferences on the ways urban epidemics are shaped by social determinants of health. Methods: Guided by critical epidemiology, this study quantifies sub-city unit-level COVID-19 inequalities across eight of the largest metropolitan areas of Latin America and Canada. Leveraging new open-data sources, we use concentration indices to quantify income- and vulnerability-related inequalities in incidence, test positivity, and deaths over the first 125 weeks of the pandemic between January 2020 and May 2022. Results: Our findings demonstrate that incidence, deaths, and test positivity are all less concentrated in low-income sub-city units than would be expected, with incidence ranging concentration in lower income neighbourhoods in Toronto (CI = -0.07) to concentration in higher income neighbourhoods in Mexico City (CI = 0.33). Drawing on relevant studies and evaluations of data reliability, we conclude that the best available public surveillance data for the largest cities in Latin America are likely not reliable measures of the true COVID-19 disease burden. We also identify recurring trends in the evolution of inequalities across most cities, concluding that higher income sub-city units were frequent early epicentres of COVID-19 transmission across the Latin America and Canada. Conclusions: Just as critical epidemiology points to individuals biologically embodying the material and social conditions in which we live, it may be just as useful to think of cities reifying their material and social inequities in the form of sub-city unit-level infectious disease inequities. By shifting away from a typical vulnerability-based social determinants of health frame, policymakers could act to redress and reduce externalities stemming from sub-city unit-level income inequality through redistributive and equity-promoting policies to shift the centre of gravity of urban health inequalities before the next infectious disease epidemic occurs. [ABSTRACT FROM AUTHOR]

Background: Foodborne infections such as listeriosis caused by the bacterium Listeria monocytogenes represent a significant public health concern, particularly when outbreaks affect many individuals over prolonged time. Systematic collection of pathogen isolates from infected patients, whole genome sequencing (WGS) and phylogenetic analyses allow recognition and termination of outbreaks after source identification and risk profiling of abundant lineages. Methods: We here present a multi-dimensional analysis of > 1800 genome sequences from clinical L. monocytogenes isolates collected in Germany between 2018 and 2021. Different WGS-based subtyping methods were used to determine the population structure with its main phylogenetic sublineages as well as for identification of disease clusters. Clinical frequencies of materno-foetal and brain infections and in vitro infection experiments were used for risk profiling of the most abundant sublineages. These sublineages and large disease clusters were further characterised in terms of their genetic and epidemiological properties. Results: The collected isolates covered 62% of all notified cases and belonged to 188 infection clusters. Forty-two percent of these clusters were active for > 12 months, 60% generated cases cross-regionally, including 11 multinational clusters. Thirty-seven percent of the clusters were caused by sequence type (ST) ST6, ST8 and ST1 clones. ST1 was identified as hyper- and ST8, ST14, ST29 as well as ST155 as hypovirulent, while ST6 had average virulence potential. Inactivating mutations were found in several virulence and house-keeping genes, particularly in hypovirulent STs. Conclusions: Our work presents an in-depth analysis of the genomic characteristics of L. monocytogenes isolates that cause disease in Germany. It supports prioritisation of disease clusters for epidemiological investigations and reinforces the need to analyse the mechanisms underlying hyper- and hypovirulence. [ABSTRACT FROM AUTHOR]

The article "Spatial clustering of dengue cases during the 2024 epidemic in Brazil" published in the Journal of Travel Medicine explores the spatial distribution of dengue cases in Brazil during the severe 2024 epidemic. The study reveals significant spatial heterogeneity in dengue incidence rates, with clusters primarily in the South and Southeast regions. Lower coverage rates of primary healthcare and family health teams were associated with higher dengue incidence, highlighting the importance of robust healthcare systems in controlling vector-borne diseases. The findings emphasize the need for targeted public health interventions, including enhanced vector control, infrastructure improvements, community health education, and strategic vaccine distribution, to reduce the burden of dengue in Brazil. [Extracted from the article]

Objective: Despite generating huge employment opportunities and profitable business, fishing is considered a dangerous occupation due to challenging weather conditions and exposure to unhealthy occupational factors and lifestyles, which contribute to various health issues. However, few studies have examined the health status of shrimp cultivators. Consequently, this study aims to estimate the age group-wise burden of non-communicable diseases (NCDs) among shrimp cultivators. Methods: Simple random sampling was employed for collecting data. The sample size was 357 shrimp cultivators. Disability-adjusted life years (DALY) and relative risk (RR) methods were used to measure the burden of NCDs among shrimp cultivators. This study reported the burden of NCDs per 100,000 shrimp cultivators. Results: The top five prevalence of NCDs per 100,000 shrimp cultivators were mental disorders (85,434), musculoskeletal diseases (26,325), digestive diseases (9,803), diabetes (5,882), and cardiovascular diseases (4,481). DALY per 100,000 shrimp cultivators was 33,407.59, while at the national level, it was 24,775.99 per 100,000 people across all age groups. The RR of NCDs among shrimp cultivators in terms of DALY was 1.35, indicating a 0.35 times higher burden of NCDs among shrimp cultivators than at the national level. The largest RR of NCDs was found among shrimp cultivators aged 15–49 years (1.85), followed by 50–69 years (1.09). The highest percentage changes in the burden of NCDs among shrimp cultivators, resulting from changes in the methods of estimating DALY, was observed in the age group of 70 years and above (−48.36%) followed by 15–49 years (−46.08%) and 50–69 years (−40.33%) when compared to the baseline method of estimating DALY without utilizing age weightage and discount rate. Conclusions: Focus should be given to improving the lifestyle and occupational factors of shrimp cultivators to mitigate the burden of NCDs. [ABSTRACT FROM AUTHOR]

Environmental exposure is associated with increased incidence of respiratory and cardiovascular diseases and reduced fertility. Exposure to air pollution can influence gene expression through epigenetic mechanisms. In this study, we analysed gene-specific CpG methylation in spermatozoa of city policemen occupationally exposed to air pollution in two Czech cities differing by sources and composition of the air pollution. In Prague, the pollution is mainly formed by NO2 from heavy traffic. Ostrava is a hotspot of industrial air pollution with high concentrations of particular matter (PM) and benzo[a]pyrene (B[a]P). We performed genome-wide methylation sequencing using the SureSelectXT Human Methyl-Seq system (Agilent Technologies) and next-generation sequencing to reveal differentially methylated CpG sites and regions. We identified differential methylation in the region chr5:662169 – 663376 annotated to genes CEP72 and TPPP. The region was then analysed in sperm DNA from 117 policemen using targeted methylation sequencing, which proved its hypermethylation in sperm of Ostrava policemen. [ABSTRACT FROM AUTHOR]

In various fields, including medical science, datasets characterized by uncertainty are generated. Conventional clustering algorithms, designed for deterministic data, often prove inadequate when applied to uncertain data, posing significant challenges. Recent advancements have introduced clustering algorithms based on a possible world model, specifically designed to handle uncertainty, showing promising outcomes. However, these algorithms face two primary issues. First, they treat all possible worlds equally, neglecting the relative importance of each world. Second, they employ time-consuming and inefficient post-processing techniques for world selection. This research aims to create clusters of observed symptoms in patients, enabling the exploration of intricate relationships between symptoms. However, the symptoms dataset presents unique challenges, as it entails uncertainty and exhibits overlapping symptoms across multiple diseases, rendering the formation of mutually exclusive clusters impractical. Conventional similarity measures, assuming mutually exclusive clusters, fail to address these challenges effectively. Furthermore, the categorical nature of the symptoms dataset further complicates the analysis, as most similarity measures are optimized for numerical datasets. To overcome these scientific obstacles, this research proposes an innovative clustering algorithm that considers the precise weight of each symptom in every disease, facilitating the generation of overlapping clusters that accurately depict the associations between symptoms in the context of various diseases. [ABSTRACT FROM AUTHOR]

Background/Objectives: The ongoing avian influenza (H5N1) outbreak, one of the most widespread and persistent in recent history, has significantly impacted public health and the poultry and dairy cattle industries. This review covers lessons from past outbreaks, risk factors for transmission, molecular epidemiology, clinical features, surveillance strategies, and socioeconomic impacts. Since 1997, H5N1 has infected over 900 individuals globally, with a fatality rate exceeding 50%. Key factors influencing infection rates include demographic, socioeconomic, environmental, and ecological variables. The virus's potential for sustained human-to-human transmission remains a concern. The current outbreak, marked by new viral clades, has complicated containment efforts. Methods: This review discusses how to integrate technological advances, such as mathematical modeling and artificial intelligence (AI), to improve forecasting, hotspot detection, and early warning systems. Results: We provide inventories of data sources, covering both conventional and unconventional data streams, as well as those of mathematical and AI models, which can be vital for comprehensive surveillance and outbreak responses. Conclusion: In conclusion, integrating AI, mathematical models, and technological innovations into a One-Health approach is essential for improving surveillance, forecasting, and response strategies to mitigate the impacts of the ongoing avian influenza outbreak. Strengthening international collaboration and biosecurity measures will be pivotal in controlling future outbreaks and protecting both human and animal populations from this evolving global threat. [ABSTRACT FROM AUTHOR]

Abstract Background Substantial inequalities in the overall prevalence and patterns of multimorbidity have been widely reported, but the causal mechanisms are complex and not well understood. This study aimed to identify common patterns of multimorbidity in Serbia and assess their relationship with air pollutant concentrations and water quality indicators. Methods This ecological study was conducted on a nationally representative sample of the Serbian population. Data were obtained from the European Health Interview (EHIS) Survey, a periodic study designed to assess population health using widely recognized standardized instruments. The study included 13,069 participants aged 15 and older, randomly selected through a multistage stratified sampling design. Multimorbidity was defined as having two or more self-reported diagnoses of chronic non-communicable diseases. Latent class analysis (LCA) was performed to identify clusters of multimorbidity. Concentrations of particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3), as well as water quality indicators, were obtained from the Serbian Environmental Protection Agency. Results The overall prevalence of multimorbidity was 33.4% [32.6%—34.2%]. Six latent classes of multimorbidity were identified: Healthy, Multicondition, Cardiovascular, Metabolic syndrome, Respiratory, and Musculoskeletal. Annual increases in PM10 and SO2 concentrations, as well as daily increases in O3 concentrations, significantly raised the odds of having multimorbidity (OR = 1.02, 95% CI 1.02–1.03; OR = 1.01, 95% CI 1.00–1.02 and OR = 1.03, 95% CI 1.02–1.03, respectively). A pattern of increased risk was observed with rising levels of water contamination. Exposure to physico-chemical, microbiological and combined contamination was associated with a 3.92%, 5.17% and 5.54% higher probability, respectively, of having multiple chronic conditions. There was strong evidence that air pollutants, as well as chemical and microbial water contamination, were significantly associated with higher odds of the most common clusters of multimorbidity identified by LCA. Conclusion There is compelling evidence of an association between multimorbidity and environmental pollution, suggesting that exposure to air pollutants and water contaminants may contribute to disease accumulation and help explain geographically and socioeconomically patterned inequalities. These findings underscore the need for extensive studies that simultaneously measure both multimorbidity and pollution to explore their complex interrelationships.

We evaluated the spatiotemporal clustering of rapid diagnostic test−positive cholera cases in Uvira, eastern Democratic Republic of the Congo. We detected spatiotemporal clusters that consistently overlapped with major rivers, and we outlined the extent of zones of increased risk that are compatible with the radii currently used for targeted interventions.

Background: Out-of-pocket healthcare expenditure (OOPHE) without adequate social protection often translates to inequitable financial burden and utilization of services. Recent publications highlighted Cambodia's progress towards Universal Health Coverage (UHC) with reduced incidence of catastrophic health expenditure (CHE) and improvements in its distribution. However, departing from standard CHE measurement methods suggests a different storyline on trends and inequality in the country. Objective: This study revisits the distribution and impact of OOPHE and its financial burden from 2009–19, employing alternative socio-economic and economic shock metrics. It also identifies determinants of the financial burden and evaluates inequality-contributing and -mitigating factors from 2014–19, including coping mechanisms, free healthcare, and OOPHE financing sources. Methods: Data from the Cambodian Socio-Economic Surveys of 2009, 2014, and 2019 were utilized. An alternative measure to CHE is proposed: Excessive financial burden (EFB). A household was considered under EFB when its OOPHE surpassed 10% or 25% of total consumption, excluding healthcare costs. A polychoric wealth index was used to rank households and measure EFB inequality using the Erreygers Concentration Index. Inequality shifts from 2014–19 were decomposed using the Recentered Influence Function regression followed by the Oaxaca-Blinder method. Determinants of financial burden levels were assessed through zero-inflated ordered logit regression. Results: Between 2009–19, EFB incidence increased from 10.95% to 17.92% at the 10% threshold, and from 4.41% to 7.29% at the 25% threshold. EFB was systematically concentrated among the poorest households, with inequality sharply rising over time, and nearly a quarter of the poorest households facing EFB at the 10% threshold. The main determinants of financial burden were geographic location, household size, age and education of household head, social health protection coverage, disease prevalence, hospitalization, and coping strategies. Urbanization, biased disease burdens, and preventive care were key in explaining the evolution of inequality. Conclusion: More efforts are needed to expand social protection, but monitoring those through standard measures such as CHE has masked inequality and the burden of the poor. The financial burden across the population has risen and become more unequal over the past decade despite expansion and improvements in social health protection schemes. Health Equity funds have, to some extent, mitigated inequality over time. However, their slow expansion and the reduced reliance on coping strategies to finance OOPHE could not outbalance inequality. Key messages: • The healthcare financial burden and its inequality have sharply increased between 2009–19; disproportionally impacting socio-economically disadvantaged households even with Health Equity Funds offering some mitigation since their national expansion. Urbanization, demographic shifts, and changing disease patterns are key factors in understanding these trends. • Standard methods for measuring catastrophic healthcare expenditure underestimate the financing burden on less-wealthy households by inflating their consumption and shifting their socio-economic rank. • The mitigating effect of out-of-pocket spending exemptions and preventive healthcare on both inequality and the overall financial burden of the population suggests a way forward towards UHC for the Cambodian healthcare system. [ABSTRACT FROM AUTHOR]

The spatial distribution of disease cases can provide important insights into disease spread and its potential risk factors. Identifying disease clusters correctly can help us discover new risk factors and inform interventions to control and prevent the spread of disease as quickly as possible. In this study, we propose a novel scan method, the Prefiltered Component‐based Greedy (PreCoG) scan method, which efficiently and accurately detects irregularly shaped clusters using a prefiltered component‐based algorithm. The PreCoG scan method's flexibility allows it to perform well in detecting both regularly and irregularly‐shaped clusters. Additionally, it is fast to apply while providing high power, sensitivity, and positive predictive value for the detected clusters compared to other scan methods. To confirm the effectiveness of the PreCoG method, we compare its performance to many other scan methods. Additionally, we have implemented this method in the smerc R package to make it publicly available to other researchers. Our proposed PreCoG scan method presents a unique and innovative process for detecting disease clusters and can improve the accuracy of disease surveillance systems. [ABSTRACT FROM AUTHOR]

Social determinants of health are known to underly excessive burden from infectious diseases. However, it is unclear if social determinants are strong enough drivers to cause repeated infectious disease clusters in the same location. When infectious diseases are known to co-occur, such as in the co-occurrence of HIV and TB, it is also unknown how much social determinants of health can shift or intensify the co-occurrence. We collected available data on COVID-19, HIV, influenza, and TB by county in the United States from 2019–2022. We applied the Kulldorff scan statistic to examine the relative risk of each disease by year depending on the data available. Additional analyses using the percent of the county that is below the US poverty level as a covariate were conducted to examine how much clustering is associated with poverty levels. There were three counties identified at the centers of clusters in both the adjusted and unadjusted analysis. In the poverty-adjusted analysis, we found a general shift of infectious disease burden from urban to rural clusters. [ABSTRACT FROM AUTHOR]

Aims: Although tick‐borne disease (TBD) incidence has increased in the United States (U.S.) in the past decade, new evidence suggests that notifiable diseases surveillance records may not accurately reflect the true magnitude of TBD diagnoses. Furthermore, while regional electronic health records (EHR) are readily accessible their potential use as a more stable and consistent source of TBD diagnoses data has remained largely unexplored. Methods and Results: In this study, we used EHR from a database of more than 100 hospitals, healthcare networks, and insurance providers in Indiana, U.S., to better understand incidence, spatio‐temporal and demographic distribution of TBD Diagnoses from 2009–2018. Our results revealed that in Indiana, from 2009 to 2018, there were 5173 unique TBD Diagnoses across three diagnoses categories: Lyme disease (72.5%, n = 3751), Rickettsioses (12.0%, n = 623) and Other TBD Diagnoses (15.4%, n = 799). Using EHR, the average yearly Lyme disease diagnoses was more than double the cases obtained using notifiable disease surveillance data for the same period. Patients with a TBD Diagnoses were generally older (ages 45–59) and less racially diverse (96.3% white). Rickettsiosis diagnoses were reported more among male patients (55.2%), while Lyme disease diagnoses were higher among female patients (57.1%). Temporal data illustrated higher frequencies of diagnoses from May to July. Hot spot analysis identified a Lyme disease hot spot in northwest Indiana, while hotspots of Rickettsiosis and Other TBD Diagnoses category were identified in southwest Indiana. Extrapolated to the Indiana population, chi‐squared (χ2) tests of independence revealed that the observed distribution of TBD diagnoses in our data was significantly different from the expected distribution in the Indiana population‐based race, gender and age groups. Conclusions: Our study findings demonstrate that in Indiana, EHR provide a stable data source for elucidating TBD disease burden and for monitoring spatio‐temporal trends in TBD diagnoses. [ABSTRACT FROM AUTHOR]

BACKGROUND: Ultrasound has a long history as a diagnostic and therapeutic tool. Low-intensity pulsed ultrasound (LIPUS), whose intensity is below 300 mW/cm2, has been widely used in orthopedic rehabilitation treatment. However, the detailed bioeffects and underlying mechanisms of LIPUS treatment need to be explored. OBJECTIVE: To make a comprehensive view of the field, bibliometric and visualization analysis was used to reveal the global research trends of LIPUS in orthopedics and rehabilitation treatment between 1994 and 2023. METHODS: All literature data on LIPUS were retrieved from the Web of Science Core Collection database. VOSviewer and CiteSpace were applied for the bibliometric and visualization analysis. RESULTS: A total of 760 publications were included. The distribution of publications generally showed an unstable rising trend. China had the highest number of publications (28.0%), and Chong Qing Medical University was the organization with the highest number of publications (5.8%). Ultrasound in Medicine and Biology had the highest number of publications (8.8%), while BMJ-British Medical Journal had the highest impact factor among the retrieved journals. Ling Qin from the Chinese University of Hong Kong was the most active researcher. Our overlay visualization map showed that the keywords such as pain, knee osteoarthritis, apoptosis, chondrocytes, cartilage, and autophagy, which link to osteoarthritis, have becoming the new research trends and hotspots. CONCLUSION: LIPUS is a popular and increasingly important area of orthopedic rehabilitation, and collaboration of authors from different countries should be further strengthened. Predictably, clinical application of LIPUS on chronic inflammation-related diseases and regenerative medicine, and in-depth biological mechanisms are the orientations of LIPUS in orthopedic rehabilitation treatment. [ABSTRACT FROM AUTHOR]

The development and change patterns as well as the disease course management of multiple ground-glass nodules (GGNs) in the lungs are currently hotspots and difficulties in clinical lung cancer research. Understanding the latest advancements in the natural history of multiple GGNs is crucial for grasping the disease variation patterns and formulating management strategies. Meanwhile, utilizing advanced methods such as intelligent follow-up management platforms makes the long-term standardized management of GGNs possible. Therefore, this article provides an overview of the latest research advancements on the natural history of multiple GGNs and new experience in GGNs management. [ABSTRACT FROM AUTHOR]

Background Leptospirosis is an endemic zoonosis in tropical areas that is mainly related to rural activities; nevertheless, human leptospirosis (HL) outbreaks differ among regions. In Colombia, HL notifications are mandatory. Our objective was to determine the spatiotemporal distribution of HL in Colombia during 2007–2018 and its relationship with the main hydroclimatic variables. Methods We determined the estimated incidence and lethality of HL according to department and year. The Bayesian spatiotemporal analysis of an autoregressive model (STAR) model included HL cases and hydroclimatic factors (average temperature, rainfall and relative humidity) for quarterly periods. Results During the study period, 10 586 HL cases were registered (estimated incidence: 1.75 cases x 105) and 243 deaths by HL (lethality 2.3%). The STAR model found association of HL risk with temperature (RR:6.80; 95% CI 3.57 to 12.48) and space. Quindío and three other Amazonian departments (Guainía, Guaviare and Putumayo) had a positive relationship with a significant number of HL cases, adjusted for quarterly precipitation and humidity. Conclusion Spatial analysis showed a high risk of HL in departments of the western Andean Colombian regions. By contrast, in the spatiotemporal model, a higher HL risk was associated with temperature and departments of the North Colombian Amazon regions and Quindío in the Colombian Andean region. [ABSTRACT FROM AUTHOR]

Nurses play key roles in dealing with pandemics yet are often conceived solely as "technical" experts without political agency. This study conducts the first global comparative analysis of COVID-19-related protests of nurses and other frontline health workers, with a focus on the first 18 months of the pandemic. We draw on quantitative and qualitative data on nurses' protests and protest drivers. Results show that such protests were widespread: We identify 3515 events in 90 countries, with several regional hotspots existing. The most common reasons for protests were poor working conditions and insufficient workplace safety, followed by wider social issues like poverty and racism. For most of the time period under consideration, protests demanding access to vaccinations (a rarely explored phenomenon) were more widespread than anti-vaccination events. Protest frequency was highest in countries with high COVID-19-related mortality rates, high levels of human development, and strong social movements at the onset of the pandemic. Recognising the key role of nurses as political actors would help to improve health policies and to maintain a capable healthcare workforce, particularly during acute crises like pandemics. [ABSTRACT FROM AUTHOR]

Background: Ideally, health services and interventions to improve dental health should be tailored to local target populations. But this is not the standard. Little is known about risk clusters in dental health care and their evaluation based on small-scale, spatial data, particularly among under-represented groups in health surveys. Our study aims to investigate the incidence rates of major oral diseases among privately insured and self-paying individuals in Germany, explore the spatial clustering of these diseases, and evaluate the influence of social determinants on oral disease risk clusters using advanced data analysis techniques, i.e. machine learning. Methods: A retrospective cohort study was performed to calculate the age- and sex-standardized incidence rate of oral diseases in a study population of privately insured and self-pay patients in Germany who received dental treatment between 2016 and 2021. This was based on anonymized claims data from BFS health finance, Bertelsmann, Dortmund, Germany. The disease history of individuals was recorded and aggregated at the ZIP code 5 level (n = 8871). Results: Statistically significant, spatially compact clusters and relative risks (RR) of incidence rates were identified. By linking disease and socioeconomic databases on the ZIP-5 level, local risk models for each disease were estimated based on spatial-neighborhood variables using different machine learning models. We found that dental diseases were spatially clustered among privately insured and self-payer patients in Germany. Incidence rates within clusters were significantly elevated compared to incidence rates outside clusters. The relative risks (RR) for a new dental disease in primary risk clusters were min = 1.3 (irreversible pulpitis; 95%-CI = 1.3–1.3) and max = 2.7 (periodontitis; 95%-CI = 2.6–2.8), depending on the disease. Despite some similarity in the importance of variables from machine learning models across different clusters, each cluster is unique and must be treated as such when addressing oral public health threats. Conclusions: Our study analyzed the incidence of major oral diseases in Germany and employed spatial methods to identify and characterize high-risk clusters for targeted interventions. We found that private claims data, combined with a network-based, data-driven approach, can effectively pinpoint areas and factors relevant to oral healthcare, including socioeconomic determinants like income and occupational status. The methodology presented here enables the identification of disease clusters of greatest demand, which would allow implementing more targeted approaches and improve access to quality care where they can have the most impact. [ABSTRACT FROM AUTHOR]

The categorization of human diseases is mainly based on the affected organ system and phenotypic characteristics. This is limiting the view to the pathological manifestations, while it neglects mechanistic relationships that are crucial to develop therapeutic strategies. This work aims to advance the understanding of diseases and their relatedness beyond traditional phenotypic views. Hence, the similarity among 502 diseases is mapped using six different data dimensions encompassing molecular, clinical, and pharmacological information retrieved from public sources. Multiple distance measures and multi‐view clustering are used to assess the patterns of disease relatedness. The integration of all six dimensions into a consensus map of disease relationships reveals a divergent disease view from the International Classification of Diseases (ICD), emphasizing novel insights offered by a multi‐view disease map. Disease features such as genes, pathways, and chemicals that are enriched in distinct disease groups are identified. Finally, an evaluation of the top similar diseases of three candidate diseases common in the Western population shows concordance with known epidemiological associations and reveals rare features shared between Type 2 diabetes (T2D) and Alzheimer's disease. A revision of disease relationships holds promise for facilitating the reconstruction of comorbidity patterns, repurposing drugs, and advancing drug discovery in the future. [ABSTRACT FROM AUTHOR]

Background: ET, one of the most prevalent neurological disorders, presents a significant challenge in terms of disability. Despite the growing focus on ET in recent years, comprehensive bibliometric analysis has been lacking. Methods: This study delves into essential tremor research covering the period from 2013 to 2023, utilizing the Web of Science (WOS) database. Employing CiteSpace for quantitative analysis, it examines an array of metrics including annual publication trends, contributions from countries and institutions, authorship patterns, key terminologies, and patterns of reference co-citation. The primary objective is to use CiteSpace for a detailed visual exploration of the literature over the last decade, pinpointing the evolving landscape and key areas of focus in essential tremor research, and thus providing a foundation for future investigative endeavors. Results: There were 2,224 literary works included in all. The amount of published works has been steadily rising in recent years. Of them, the majority originate from the United States, Louis, Elan D. is the publisher of the most publications (161 articles), and Movement Disorders is the journal that receives the most citations. The key words contribution and co-cited literatures suggest that the main research hotspots in recent years are the physiological and pathological mechanism of essential tremor, the determination of optimal targets for deep brain stimulation (DBS) and surgery transcranial magnetic resonance-guided focused ultrasound (MRgFUS) in the surgical management of essential tremor and the innovative research of botulinum toxin administration method. [ABSTRACT FROM AUTHOR]

Caribbean coral reefs are currently facing a rapid decline caused by a plethora of threats including disease outbreaks. Octocorals appear to be unaffected by the majority of diseases impacting scleractinian corals, including stony coral tissue loss disease (SCTLD) that emerged in 2014 and resulted in a mass mortality of scleractinian coral populations inhabiting Florida, the USA, and Caribbean reefs. Although the Caribbean Sea is considered a disease hot spot, few investigations into the mechanism(s) responsible for the resistance of octocorals have been conducted. In response, the capacity for octocoral-derived extracts and natural products to inhibit strains of Vibrio coralliilyticus, pathogenic bacteria that can cause bleaching and disease in stony corals and can co-occur in SCTLD infections, was explored. Extracts obtained from each of the four octocoral species studied demonstrated antimicrobial activity against V. coralliilyticus. Bioassay-guided fractionations of crude extracts from Antillogorgia americana were employed to identify the antimicrobial compounds, revealing the presence of secosterols in the most bioactive fractions. These results suggest that octocoral species may utilize chemical defenses to protect themselves against infection by strains of a known coral pathogen and contribute to the body of knowledge regarding the success of octocorals on Caribbean reefs. [ABSTRACT FROM AUTHOR]

Background Healthcare seeking behavior (HSB) and community perception on cholera can influence its management. We conducted a cross-sectional survey to generate evidence on cholera associated HSB and disease perception in populations living in cholera hotspots in Ethiopia. Methods A total of 870 randomly selected households (HHs) in Shashemene Town (ST) and Shashemene Woreda (SW) participated in our survey in January 2022. Results Predominant HHs (91.0%; 792/870) responded "primary health center" as the nearest healthcare facility (HCF). Around 57.4% (247/430) of ST HHs traveled <30 minutes to the nearest HCF. In SW, 60.2% (265/440) of HHs travelled over 30 minutes and 25.9% (114/440) over 4 km. Two-thirds of all HHs paid

Background Cholera is a public health priority in Ethiopia. The Ethiopian National Cholera Plan elaborates a multi-year scheme of oral cholera vaccine (OCV) use. Aligned with this, a preemptive OCV campaign was conducted under our Ethiopia Cholera Control and Prevention project. Here, we present the OCV vaccination outcomes. Method Cholera high-priority hotspots in the Oromia Region, Shashemene Town (ST) and Shashemene Woreda (SW), were selected. Four kebelles (Abosto, Alelu, Arada, and Awasho) in ST and 4 clusters (Faji Gole, Harabate, Toga, and Chabi) in SW were study sites with OCV areas nested within. A total of 40 000 and 60 000 people in ST and SW, respectively, were targeted for a 2-dose OCV (Euvichol-Plus) campaign in 11–15 May (first round [R1]) and 27–31 May (second round [R2]) 2022. Daily administrative OCV coverage and a coverage survey in 277 randomly selected households were conducted. Results The administrative OCV coverage was high: 102.0% for R1 and 100.5% for R2 in ST and 99.1% (R1) and 100.0% (R1) in SW. The coverage survey showed 78.0% (95% confidence interval [CI]: 73.1–82.9) of household members with 2-dose OCV and 16.8% (95% CI: 12.4–21.3) with no OCV in ST; and 83.1% (95% CI: 79.6–86.5) with 2-dose OCV and 11.8% (95% CI: 8.8–14.8) with no OCV in SW. The 2-dose coverages in 1–4-, 5–14-, and ≥15-year age groups were 88.3% (95% CI: 70.6–96.1), 88.9% (95% CI: 82.1–95.7), and 71.3% (95% CI: 64.2–78.3), respectively, in ST and 78.2% (95% CI: 68.8–87.7), 91.0% (95% CI: 86.6–95.3), and 78.7% (95% CI: 73.2–84.1) in SW. Conclusions High 2-dose OCV coverage was achieved. Cholera surveillance is needed to assess the vaccine impact and effectiveness. [ABSTRACT FROM AUTHOR]

From 2020 to 2023, South Dakota witnessed a substantial increase in cases of congenital syphilis (CS), with the highest rates identified in rural and Native American (NA) communities. Here, we discuss 3 severe cases of CS in premature infants born to NA individuals and communities in South Dakota with poor access to prenatal care. The infants in these 3 cases presented with varying clinical conditions, including respiratory failure, persistent pulmonary hypertension of the newborn, severe direct hyperbilirubinemia, feeding intolerance, and necrotizing enterocolitis. Lack of prenatal care and other systemic health disparities likely contributed to the increased disease burden. For NA communities, rurality, limited resources, systemic racism, historical trauma, and lack of trust in medical institutions likely contribute to inadequate prenatal care. All 3 of these cases also occurred in pregnant people with a present or history of substance use disorders, which may have led to further hesitancy to seek care because of fear of prosecution. To combat the rising number of syphilis and CS cases, we advocate for new and continued outreach that provides education about and testing for sexually transmitted diseases to NA and rural populations, increased care coordination, the integration of point-of-care testing and treatment strategies in lower resource centers, and legislative allocation of additional resources to engage pregnant people with or at risk for substance use disorders. [ABSTRACT FROM AUTHOR]

"Eliminate rheumatic fever (RF) and minimize the burden of rheumatic heart disease by 2025" is the goal of World Heart Federation (WHF). The most important step to achieve the goal of WHF is the implementation of the prevention and control of RF in India. The program can be implemented with minimal fund allocation from government making use of the existing manpower in the government and private health sector and schools with the concurrence of National Health Mission, Ministry of Health and Family Welfare, Ministry of Public Education and under the guidance of Cardiological Society of India, National Rheumatic Heart Consortium, Rheumatic Heart Club India, Association of Physicians of India, Indian Academy of Pediatrics, and Association of Otolaryngologists of India. By the successful implementation of this program, the children of 5--15 years in India can be protected from RF. India eradicated smallpox in 1980 and Polio 2012. With this program, we can start our efforts to eliminate RF by 2025. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Malaria, a pervasive infectious disease, remains a critical health concern worldwide, particularly in regions with high transmission rates. This study investigates demographic patterns and prognostic factors influencing outcomes in malaria patients presenting to the emergency department (ED). MATERIAL AND METHODS: This retrospective cross-sectional study, conducted at ED of South coastal India, from September 1, 2017, to September 1, 2022, analysed data from approximately 12,000 annual visits. Mortality predictors were assessed in malaria-positive patients, including Shock Index (SI), Modified Early Warning Score (MEWS), Sequential Organ Failure Assessment (SOFA), Malaria Severity Index (MSA), Malaria Prognostic Score (MPS), Coma Acidosis Malaria (CAM) score, Respiratory and Bicarbonate-based CAM score (R-CAM and B-CAM), Glasgow Coma Scale (GCS), and GCRBS Score. RESULT: Analysis of 114 severe malaria cases revealed higher mortality (21.1%) among older rural patients. Non-survivors exhibited elevated pulse rates (139.83 ± 7.43), lower blood pressure (systolic: 62.58 ± 28.27, diastolic: 47.33 ± 20.73), and impaired consciousness (GCS: 6.63 ± 1.69). GCRBS, MSA, and SOFA scores demonstrated exceptional predictive accuracy (AUC = 1.00). CONCLUSIONS: Identifying crucial mortality predictors like MSA, MPS, CAM, and GCRBS scores in malaria patients can optimize ED management protocols effectively. [ABSTRACT FROM AUTHOR]

The article "Mayaro fever in Brazil from 2014 to 2024" published in the Journal of Travel Medicine discusses the epidemiology of Mayaro virus infection in Brazil over a ten-year period. The study reveals that Mayaro fever cases are concentrated in the states of Pará, Amazonas, and Goiás, with fluctuations in incidence rates influenced by environmental, climatic, and human factors. The research highlights the importance of enhanced public health infrastructure, diagnostics, surveillance, and case reporting to effectively manage and mitigate the spread of the disease in high-risk areas. [Extracted from the article]

Background: Social Frailty is a significant public health concern affecting the elderly, particularly with the global population aging rapidly. Older adults with social frailty are at significantly higher risk of adverse outcomes such as disability, cognitive impairment, depression, and even death. In recent years, there have been more and more studies on social frailty, but no bibliometrics has been used to analyze and understand the general situation in this field. Therefore, by using CiteSpace, VOSviewer, and Bilioshiny software programs, this study aims to analyze the general situation of the research on social frailties of the older adults and determine the research trends and hot spots. Methods: A bibliometric analysis was conducted by searching relevant literature on the social frailty of the older adults from 2003 to 2022 in the Web of Science core database, using visualization software to map publication volume, country and author cooperation networks, keyword co-occurrences, and word emergence. Results: We analyzed 415 articles from 2003 to 2022. Brazil has the highest number of articles in the field of social frailty of the older adults, and the United States has the highest number of cooperative publications. Andrew MK, from Canada, is the most published and co-cited author, with primary research interests in geriatric assessment, epidemiology, and public health. "Social Vulnerability," "Health," "Frailty," "Mortality," and "Older Adult" are among the research hotspots in this field. "Dementia," "Alzheimer's disease," "Population," and "Covid-19" are emerging research trends in social frailty among the older adults. Conclusion: This scientometric study maps the research hotspots and trends for the past 20 years in social frailty among the older adults. Our findings will enable researchers to better understand trends in this field and find suitable directions and partners for future research. [ABSTRACT FROM AUTHOR]

Diversification at the plot level, through the use of intercropping (mixtures of crops), is an alternative to the conventional system of intensive agriculture, based on monospecific, usually single-variety canopies. Intercropping has been shown to provide benefits in terms of disease control. However, competition phenomena and the heterogeneity of the associated crops raise new ecological questions, particularly with regard to the dynamics and evolution of parasite populations. No study has assessed the potential impact of these associations on the dynamics of pathogenic species complexes. Changes in the nutritional status of plants and therefore in their physiological susceptibility to infection within intercropping systems could contribute to an increased diversity of ecological niches and thus affect the composition of the parasitic complex and its spatiotemporal dynamics. In this review, focusing on foliar diseases of fungal origin, and after outlining some elements of the biology and epidemiology of these fungal diseases, we will (i) describe the mechanisms that contribute to the composition of disease clusters and that drive interactions, but we will also review the strategies that these foliar diseases have adopted to deal with these co-infections; (ii) define how intercropping can lead to changes in epidemic dynamics, in particular by presenting the mechanisms that have a direct and indirect effect on disease evolution; and (iii) present the approach that should be adopted to properly study intercropping correctly in a multi-infection situation. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is a degenerative illness of the central nervous system that is irreversible and is characterized by gradual behavioral impairment and cognitive dysfunction. Researches on exosomes in AD have gradually gained the attention of scholars in recent years. However, the literatures in this research area do not yet have a comprehensive visualization analysis. The aim of this work is to use bibliometrics to identify the knowledge constructs and investigate the research frontiers and hotspots related to exosomes in AD. Methods: From January 2003 until June 2023, we searched the Web of Science Core Collection for literature on exosomes in AD. We found 585 papers total. The bibliometric study was completed using VOSviewer, the R package "bibliometrix," and CiteSpace. The analysis covered nations, institutions, authors, journals, and keywords. Results: Following 2019, the articles on exosomes in AD increased significantly year by year. The vast majority of publications came from China and the US. The University of California System, the National Institutes of Health, and the NIH National Institute on Aging in the US were the primary research institutions. Goetzl Edward J. was frequently co-cited, while Kapogiannis Dimitrios was the most prolific author in this discipline with the greatest number of articles. Lee Mijung et al. have been prominent in the last two years in exosomes in AD. The Journal of Alzheimer's Disease was the most widely read publication, and Alzheimers & Dementia had the highest impact factor. The Journal of Biological Chemistry, Proceedings of the National Academy of Sciences of the United States of America, and Journal of Alzheimer's Disease were the three journals with more than 1,000 citations. The primary emphasis of this field was Alzheimer's disease, exosomes, and extracellular vesicles; since 2017, the number of phrases pertaining to the role of exosomes in AD pathogenesis has increased annually. "Identification of preclinical Alzheimer's disease by a profile of pathogenic proteins in neurally derived blood exosomes: a case-control study" was the reference with the greatest citing power, indicating the future steered direction in this field. Conclusion: Using bibliometrics, we have compiled the research progress and tendencies on exosomes in Alzheimer's disease for the first time. This helps determine the objectives and paths for future study. [ABSTRACT FROM AUTHOR]

Multimorbidity, also known as multiple long-term conditions, leads to higher healthcare utilisation, including hospitalisation, readmission, and polypharmacy, as well as a financial burden to families, society, and nations. Despite some progress, the economic burden of multimorbidity remains poorly understood. This paper outlines a protocol for a systematic review that aims to identify and synthesise comprehensive evidence on the economic burden of multimorbidity, considering various definitions and measurements of multimorbidity, including their implications for future cost-of-illness analyses. The review will include studies involving people of all ages with multimorbidity without any restriction on location and setting. Cost-of-illness studies or studies that examined economic burden including model-based studies will be included, and economic evaluation studies will be excluded. Databases including Scopus (that includes PubMed/MEDLINE), Web of Science, CINAHL Plus, PsycINFO, NHS EED (including the HTA database), and the Cost-Effectiveness Analysis Registry, will be searched until March 2024. The risk of bias within included studies will be independently assessed by two authors using appropriate checklists. A narrative synthesis of the main characteristics and results, by definitions and measurements of multimorbidity, will be conducted. The total economic burden of multimorbidity will be reported as mean annual costs per patient and disaggregated based on counts of diseases, disease clusters, and weighted indices. The results of this review will provide valuable insights for researchers into the key cost components and areas that require further investigation in order to improve the rigour of future studies on the economic burden of multimorbidity. Additionally, these findings will broaden our understanding of the economic impact of multimorbidity, inform us about the costs of inaction, and guide decision-making regarding resource allocation and cost-effective interventions. The systematic review's results will be submitted to a peer-reviewed journal, presented at conferences, and shared via an online webinar for discussion. [ABSTRACT FROM AUTHOR]

Background: Identifying clusters of co-occurring diseases may help characterise distinct phenotypes of Multiple Long-Term Conditions (MLTC). Understanding the associations of disease clusters with health-related outcomes requires a strategy to assign clusters to people, but it is unclear how the performance of strategies compare. Aims: First, to compare the performance of methods of assigning disease clusters to people at explaining mortality, emergency department attendances and hospital admissions over one year. Second, to identify the extent of variation in the associations with each outcome between and within clusters. Methods: We conducted a cohort study of primary care electronic health records in England, including adults with MLTC. Seven strategies were tested to assign patients to fifteen disease clusters representing 212 LTCs, identified from our previous work. We tested the performance of each strategy at explaining associations with the three outcomes over 1 year using logistic regression and compared to a strategy using the individual LTCs. Results: 6,286,233 patients with MLTC were included. Of the seven strategies tested, a strategy assigning the count of conditions within each cluster performed best at explaining all three outcomes but was inferior to using information on the individual LTCs. There was a larger range of effect sizes for the individual LTCs within the same cluster than there was between the clusters. Conclusion: Strategies of assigning clusters of co-occurring diseases to people were less effective at explaining health-related outcomes than a person's individual diseases. Furthermore, clusters did not represent consistent relationships of the LTCs within them, which might limit their application in clinical research. [ABSTRACT FROM AUTHOR]

Wound healing is a complicated and multistage biological process for the repair of damaged/injured tissues, which requires intelligent designs to provide comprehensive and convenient treatment. Peptide‐based wound dressings have received extensive attention for further development and application due to their excellent biocompatibility and multifunctionality. However, the current lack of intuitive analysis of the development trend and research hotspots of peptides applied in wound healing, as well as detailed elaboration of possible research hotspots, restricted obtaining a comprehensive understanding and development in this field. The present study analysed publications from the Web of Science (WOS) Core Collection database and visualized the hotspots and current trends of peptide research in wound healing. Data between January 1st, 2003, and December 31st, 2022, were collected and subjected to a bibliometric analysis. The countries, institutions, co‐authorship, co‐citation reference, and co‐occurrence of keywords in this subject were examined using VOSviewer and CiteSpace. We provided an intuitive, timely, and logical overview of the development prospects and challenges of peptide application in wound healing and some solutions to the major obstacles, which will help researchers gain insights into the investigation of this promising field. [ABSTRACT FROM AUTHOR]

Abstract Background Infliximab is currently recommended as a third-line treatment for refractory sarcoidosis. Data in function of clinical phenotype are currently lacking. We evaluated patients’ characteristics and responses to infliximab according to their GenPhenReSa cluster. Methods We evaluated clinical and biological characteristics of patients diagnosed with sarcoidosis who received infliximab between September 2008 and April 2019 at our centre. Results Fifty-five patients (median disease duration, 87 months) received infliximab: 48 (87%) as a second- or third-line treatment, and 7 (13%) as a first-line treatment. After a median duration of 12 months, 24 (45%) and 14 (25%) patients achieved complete and partial responses, respectively, together with a significant decrease in the number of affected organs and tapering of steroid doses. All patients with neurosarcoidosis (OR 17), 90% in group 2 (ocular-cardiac-cutaneous-CNS, OR 7.4), and approximately two-thirds of those in groups 1 (abdominal organs), 4 (pulmonary-lympho-nodal), and 5 (extrapulmonary), achieved a response, whereas patients in group 3 (musculoskeletal-cutaneous) had a treatment-failure OR of 9. Infliximab could be stopped after complete remission was achieved in 7 patients: 4 relapsed after a median of 6 months. Overall, 36% of patients experienced serious adverse events, mainly infections, which led to treatment cessation in 29% of patients and caused two deaths. Conclusions Other than patients with musculoskeletal-cutaneous involvement (group 3), infliximab led to a good response for patients with CNS (group 2) and liver (group 1) organ-predominant sarcoidosis. However, it led to serious infections and merely suspended sarcoidosis, so further research on factors predictive of relapse is needed.

In cardiac cells, the expression of the cardiac voltage-gated Na+ channel (NaV1.5) is reciprocally regulated with the inward rectifying K+ channel (KIR2.1). These channels can form macromolecular complexes that pre-assemble early during forward trafficking (transport to the cell membrane). In this study, we present in silico 3D models of NaV1.5-KIR2.1, generated by rigid-body protein-protein docking programs and deep learning-based AlphaFold-Multimer software. Modeling revealed that the two channels could physically interact with each other along the entire transmembrane region. Structural mapping of diseaseassociated mutations revealed a hotspot at this interface with several traffickingdeficient variants in close proximity. Thus, examining the role of disease-causing variants is important not only in isolated channels but also in the context of macromolecular complexes. These findings may contribute to a better understanding of the life-threatening cardiovascular diseases underlying KIR2.1 and NaV1.5 malfunctions. [ABSTRACT FROM AUTHOR]

Dengue is a wide spectrum of diseases creating menace in the community. This vector-born disease alone has a significant impact on global public health and the economy. Resources need to be mobilized to tackle the situation. The present article focused on the novice concept of "Seven-Plus-One models" as an approach to dengue prevention with vector management through community participation. A multidisciplinary approach along with exemplifying effective methods of inspectorial coordination and community participation is much required. The implementation of the Seven-Plus-One model has a positive impact on reducing dengue cases, indicating acceptance and effectiveness of the concept among the public. Dengue morbidity rate can be reduced through early detection and mobilizing the community for active participation in dengue prevention and control. [ABSTRACT FROM AUTHOR]

Simple Summary: In cancer, hotspots are those mutations emerging recurrently in tumors. Hotspots are highly likely to be functional because tumors tend to keep those mutations that provide physiological advantages. However, few hotspots have been studied, mainly because it is costly and time-consuming. Here, we systematically test more than 1400 hotspots for their association with patient survival and provide the results, including more than 300 significant associations, accessible on the web. This would help prioritize hotspots that are likely functional and affect patient survival, accelerating our knowledge of cancer and improving patient care. Background: Cofactors, biomarkers, and the mutational status of genes such as TP53, EGFR, IDH1/2, or PIK3CA have been used for patient stratification. However, many genes exhibit recurrent mutational positions known as hotspots, specifically linked to varying degrees of survival outcomes. Nevertheless, few hotspots have been analyzed (e.g., TP53 and EGFR). Thus, many other genes and hotspots remain unexplored. Methods: We systematically screened over 1400 hotspots across 33 TCGA cancer types. We compared the patients carrying a hotspot against (i) all cases, (ii) gene-mutated cases, (iii) other mutated hotspots, or (iv) specific hotspots. Due to the limited number of samples in hotspots and the inherent group imbalance, besides Cox models and the log-rank test, we employed VALORATE to estimate their association with survival precisely. Results: We screened 1469 hotspots in 6451 comparisons, where 314 were associated with survival. Many are discussed and linked to the current literature. Our findings demonstrate associations between known hotspots and survival while also revealing more potential hotspots. To enhance accessibility and promote further investigation, all the Kaplan–Meier curves, the log-rank tests, Cox statistics, and VALORATE-estimated null distributions are accessible on our website. Conclusions: Our analysis revealed both known and putatively novel hotspots associated with survival, which can be used as biomarkers. Our web resource is a valuable tool for cancer research. [ABSTRACT FROM AUTHOR]

Background: Families in high‐risk communities for COVID‐19 transmission experienced a disproportionate burden during the pandemic. This study assessed these families' needs, changes in children's well‐being, and perceptions related to the pandemic. Methods: Four online surveys were administered January 2021 to September 2021 to parents of students, enrolled in parochial, kindergarten‐eighth grade schools in Chicago neighborhoods with higher COVID‐19 incidence rates by ZIP code, compared to the city average, and higher resource need. Results: The response rate was 69.1% (n = 186 of 269) in the baseline survey; and other surveys were at 1 (n = 151), 3 (n = 145), and 5 months (n = 154). Of the sample, 83% of parents identified as Hispanic/Latinx with a mean age of 38.3 years (SD: 8.5). Approximately a quarter of parents reported difficulty paying cable and internet bills (26%) and paying utilities (25%). Parents reported children as happy (94% and 95%, p =.59) and hopeful (96% and 95%, p =.74) at 1‐month (February to May 2021) and 5‐month surveys (June to September 2021). Parents also reported fewer children were irritable (29% vs 19%, p =.03), felt lonely (17% vs 10%, p =.03), and felt isolated (28% vs 9%, p <.001) between those survey waves. The majority (67%) of parents felt that their child had no difficulty wearing a mask in public. Conclusions: In this longitudinal study, Chicago parents rated children's well‐being highly and reported a decrease in negative emotions over time. The areas of need identified may be particularly relevant for outreach and providing resources to Hispanic/Latino families in future emergencies or global health threats. [ABSTRACT FROM AUTHOR]

Aims: In Canada, enteric diseases pose substantial health and economic burdens. The distribution of these diseases is uneven across both geography and time and understanding these patterns is therefore important for the prevention of future outbreaks. We evaluated temporal, spatial and space–time clustering of laboratory‐confirmed cases of Campylobacter spp. (n = 28,728), non‐typhoidal Salmonella spp. (n = 22,640), Shiga toxin‐producing Escherichia coli (STEC; n = 1340), Yersinia spp. (n = 1674) and Listeria monocytogenes (n = 471) infections, reported between 2010 and 2017 inclusive in Ontario, the most populous province in Canada (population ~ 13,500,000 in 2016). Methods and Results: For each enteric pathogen, we calculated the mean incidence rates (IRs) for Ontario's 35 public health unit (PHU) areas and visualized them using choropleth maps. We identified temporal, spatial and space–time high infection rate clusters using retrospective Poisson scan statistics. Campylobacter and Salmonella infections had the highest IRs, while Listeria infections had the lowest. Campylobacter, Salmonella, STEC and Listeria mostly clustered temporally in the spring/summer and sometimes extended into fall, while Yersinia showed a less clear seasonal pattern. The IR visualizations and spatial and space–time scan statistics showed geographic heterogeneity of infection rates with high infection rate clusters detected mainly in PHUs across the southwestern and central‐western regions of Ontario for Campylobacter, Salmonella and STEC infections, and mainly in PHUs located in the central‐eastern regions for Yersinia and Listeria. A high proportion of cases in some of the significant Salmonella, STEC and Listeria infection clusters were linked to disease outbreaks. Conclusions: Results from this study will inform heightened public health surveillance, and prevention and control programmes, in populations and regions of high infection rates. Further research is needed to determine the pathogen‐specific socioeconomic, environmental and agricultural risk factors that may be related to the temporal and spatial disease patterns we observed in our study. [ABSTRACT FROM AUTHOR]

Background: Neuroticism is a psychological personality trait that has a significant impact on public health and is also a potential predisposing factor for adverse disease outcomes; however, comprehensive studies of the subsequently developed conditions are lacking. The starting point of disease trajectory in terms of genetic variation remains unclear. Method: Our study included 344,609 adult participants from the UK Biobank cohort who were virtually followed up from January 1, 1997. Neuroticism levels were assessed using 12 items from the Eysenck Personality Questionnaire. We performed a phenome‐wide association analysis of neuroticism and subsequent diseases. Binomial tests and logistic regression models were used to test the temporal directionality and association between disease pairs to construct disease trajectories. We also investigated the association between polygenic risk scores (PRSs) for five psychiatric traits and high neuroticism. Results: The risk for 59 diseases was significantly associated with high neuroticism. Depression, anxiety, irritable bowel syndrome, migraine, spondylosis, and sleep disorders were the most likely to develop, with hazard ratios of 6.13, 3.66, 2.28, 1.74, 1.74, and 1.71, respectively. The disease trajectory network revealed two major disease clusters: cardiometabolic and chronic inflammatory diseases. Medium/high genetic risk groups stratified by the PRSs of four psychiatric traits were associated with an elevated risk of high neuroticism. We further identified eight complete phenotypic trajectory clusters of medium or high genetic risk for psychotic, anxiety‐, depression‐, and stress‐related disorders. Conclusion: Neuroticism plays an important role in the development of somatic and mental disorders. The full picture of disease trajectories from the genetic risk of psychiatric traits and neuroticism in early life to a series of diseases later provides evidence for future research to explore the etiological mechanisms and precision management. [ABSTRACT FROM AUTHOR]

In this research, we conducted hierarchical multiple regression and complex sample general linear model (CSGLM) to expand knowledge on factors contributing to mental distress, particularly from a geographic perspective. Based on the Getis-Ord G* hot-spot analysis, geographic distribution of both FMD and insufficient sleep showed several contiguous hotspots in southeast regions. Moreover, in the hierarchical regression, even after accounting for potential covariates and multicollinearity, a significant association between FMD and insufficient sleep was found, explaining that mental distress increases with increasing insufficient sleep (R2 = 0.835). In the CSGLM, a R2 value of 0.782 indicated that the CSGLM procedure provided concrete evidence that FMD was significantly related to sleep insufficiency even after taking complex sample designs and weighting adjustments in the BRFSS into account. This geographic association between FMD and insufficient sleep based on cross-county study has not been reported before in the literature. These findings suggest a need for further investigation on geographic disparity on mental distress and insufficient sleep and have novel implications in our understanding of the etiology of mental distress. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic brought diagnostics into the spotlight in an unprecedented way not only for case management but also for population health, surveillance, and monitoring. The industry saw notable levels of investment and accelerated research which sparked a wave of innovation. Simple non-invasive sampling methods such as nasal swabs have become widely used in settings ranging from tertiary hospitals to the community. Self-testing has also been adopted as standard practice using not only conventional lateral flow tests but novel and affordable point-of-care molecular diagnostics. The use of new technologies, including artificial intelligence-based diagnostics, have rapidly expanded in the clinical setting. The capacity for next-generation sequencing and acceptance of digital health has significantly increased. However, 4 years after the pandemic started, the market for SARS-CoV-2 tests is saturated, and developers may benefit from leveraging their innovations for other diseases; tuberculosis (TB) is a worthwhile portfolio expansion for diagnostics developers given the extremely high disease burden, supportive environment from not-for-profit initiatives and governments, and the urgent need to overcome the long-standing dearth of innovation in the TB diagnostics field. In exchange, the current challenges in TB detection may be resolved by adopting enhanced swab-based molecular methods, instrument-based, higher sensitivity antigen detection technologies, and/or artificial intelligence-based digital health technologies developed for COVID-19. The aim of this article is to review how such innovative approaches for COVID-19 diagnosis can be applied to TB to have a comparable impact. [ABSTRACT FROM AUTHOR]

Purpose: Human Borna disease virus (BoDV-1) encephalitis is an emerging disease in Germany. This study investigates the spectrum of human BoDV-1 infection, characterizes anti-BoDV-1-antibodies and kinetics, and compares laboratory test performances. Methods: Three hundred four encephalitis cases, 308 nation-wide neuropsychiatric conditions, 127 well-defined psychiatric cases from Borna disease-endemic areas, and 20 persons with contact to BoDV-1 encephalitis patients or animals were tested for BoDV-1 infections by serology and PCR. Results: BoDV-1 infections were only found in encephalitis patients with residence in, or recent travel to, virus-endemic areas. Antibodies were detected as early as 12 days after symptom onset. Serum antibody levels correlated with disease duration. Serology was ordered after 50% of the disease duration had elapsed, reflecting low awareness. BoDV-1-antibodies were of IgG1 subclass, and the epitope on BoDV-1 antigens was determined. Specificity of the indirect immunofluorescence antibody test (IFAT) and lineblot (LB) from serum and cerebrospinal fluid (CSF), as well as PCR testing from CSF, was 100%. Sensitivity, depending on first or all samples, reached 75–86% in serum and 92–94% in CSF for the IFAT, and 33–57% in serum and 18–24% in CSF for the LB. Sensitivity for PCR in CSF was 25–67%. Positive predictive values were 100% each, while negative predictive values were 99% (IFAT), 91–97% (LB), and 90% (PCR). Conclusions: There is no hint that BoDV-1 causes other diseases than encephalitis in humans. Awareness has to be increased in virus-endemic areas. Tests are robust but lack sensitivity. Detection of IgG1 against specific peptides may facilitate diagnosis. Screening of healthy individuals is likely not beneficial. [ABSTRACT FROM AUTHOR]