Research shows completing a placement year is associated with improved academic and employment outcomes. For Biomedical science courses, pathology placements allow completion of the Institute of Biomedical Science (IBMS) registration training portfolio and obtaining Health and Care Professions Council (HCPC) registration post-graduation. This study sought to identify the barriers biomedical science students across the West Midlands region of England face when completing a placement year, to identify strategies which promote inclusivity to overcome these barriers. Level 5 and Level 6 students from Aston, Coventry, Keele and Wolverhampton universities were invited to complete a questionnaire which included a mixture of Likert scale and free-text responses. A range of questions assessed student perceptions on the importance of placement opportunities, as well as identifying factors which were important when pursuing a placement year. Likert scale data was analysed quantitatively, and a Mann Whitney U or Kruskal Wallis test were used to infer significance, whereas free text responses were analysed using thematic analysis. A total of 107 students completed the questionnaire. Students who declared a disability were less likely to undertake an unpaid placement compared to their peers (p = 0.013). Of those students who declared caring responsibilities, 33.3% chose not to apply for a placement year compared to 18.2% of those who did not have caring responsibilities (p = 0.020). Participants reported that funding was important when deciding whether to pursue a placement (88.8%). Thematic analysis revealed several recurring themes deterring student placement applications, including financial support and placement availability within their geographical area. Students valued the importance of professional recognition following the placement and the development of technical and transferable skills. Many of the barriers are fuelled by financial constraints which deter students from applying to placement positions. Despite the need to increase the Biomedical Scientist workforce, the strategies to increase training opportunities are not well established. Equity in placement funding from centralised sources is key to ensuring Biomedical Scientists can excel in their professional careers. Through availability of funding, marginalised populations will have the same opportunities as their peers therefore producing more employable graduates to meet pathology workforce demands.
The final year Professional Development for Biomedical Scientists module at Aston University strives to create competent practitioners upon graduation. Recent research identified that 93% of NHS pathology employers within the United Kingdom, do not believe that new Biomedical Scientist graduates possess the skills required for a Band 5 interview. Additionally, 73% of these employers believed students were not fully prepared for the NHS interview process. Therefore, Aston University redeveloped an existing mock interview component to align directly with NHS interview processes. This research aimed to evaluate the effectiveness of the redesigned "Job interview" assessment upon student understanding of their own transferable skills and readiness for future laboratory employment. Researchers evaluated the effectiveness of the assessment through a mixed-method approach survey. The survey was launched to students following their completion of the Medical Laboratory Assistant video interview, using the interview software Interview360. The survey sought to identify if after the interview assessment students felt they could demonstrate with examples, using the STAR technique, several key skills sought by employers. Data was collected from both the 2023-2024 and 2024-2025 final year Biomedical Science cohort. Collected data has been overwhelmingly positive, with 97% of students agreeing that they "understand the types of questions they would be asked in an NHS interview" (p < 0.0001). In terms of the key skills sought for by employers, 93% of respondents agreed or strongly agreed that they felt they could communicate within a specific situation example their understanding of "Basic equipment skills" (p < 0.0001) and their "understanding of laboratory results" (p < 0.0001). Whilst 99% of respondents agreed or strongly agreed that they could demonstrate their "understanding of laboratory health and safety" (p < 0.0001). Furthermore, respondents reported that the job interview assessment assisted them to demonstrate their transferable skills, including teamwork (81.6%) and organisational skills (71.05%). Student responses identify a positive change to their job interview skills and understanding of the NHS interview process. Here, researchers present the re-modelled graded job interview assessment with the NHS aligned mark scheme, along with four pre-assessment workshops as a process to embed employability into the Biomedical Science curriculum.
Accurate interpretation of loss-of-function (LOF) variants in MODY genes is essential for diagnosis but remains challenging, particularly for variants that are predicted to escape nonsense-mediated decay (NMD). We aimed to systematically evaluate the pathogenicity of LOF variants, stratified by NMD-triggering and NMD-escape status, across all known MODY genes. We analysed ultra-rare LOF variants (minor allele frequency <1 in 10,000) in 5171 individuals of European ancestry with suspected MODY, compared with 155,501 population-based control individuals from UK Biobank. LOF variants in ABCC8, GCK, HNF1A, HNF4A, HNF1B, INS, KCNJ11, NEUROD1, PDX1 and RFX6 were classified as NMD-triggering or NMD-escape. We tested for gene-level enrichment in cases vs controls. For novel associations, we performed replication in additional MODY patients, assessed familial co-segregation, and undertook in silico protein modelling. LOF variants were significantly enriched in all MODY genes except ABCC8 and KCNJ11. Both NMD-triggering and NMD-escape variants were enriched in GCK, HNF1A and HNF4A, consistent with haploinsufficiency (all p<10-3). HNF1B and RFX6 showed enrichment only for NMD-triggering variants, while NEUROD1 and PDX1 were enriched only for NMD-escape variants. A novel finding was the significant enrichment of only NMD-escape LOF variants in INS (OR=181, p<10-5). Including replication in additional MODY patients, we identified eight families with 17 affected individuals carrying INS variants. These variants co-segregated with diabetes (logarithm of the odds score=3), included one de novo case, and were absent from >800,000 population control individuals. Individuals presented with diabetes at a median age of 19 years, had median BMI of 22.9 kg/m2, were negative for islet autoantibodies, and had low type 1 diabetes genetic risk scores. Compared with INS missense MODY, diagnosis occurred approximately 10 years later in individuals with NMD-escape LOF variants. Protein modelling suggested that INS NMD-escape variants produce aberrant proinsulin molecules with unpaired B-chain cysteines, leading to milder misfolding. The pathogenicity of LOF variants in MODY genes depends on gene context and NMD status. Heterozygous NMD-escape LOF variants in INS are a novel cause of MODY. These findings provide systematic gene-level evidence to inform variant interpretation guidelines and improve the accuracy of MODY diagnosis in clinical practice.
Lower respiratory infections (LRIs) remain the world's leading infectious cause of death. This analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 provides global, regional, and national estimates of LRI incidence, mortality, and disability-adjusted life-years (DALYs), with attribution to 26 pathogens, including 11 newly modelled pathogens, across 204 countries and territories from 1990 to 2023. With new data and revised modelling techniques, these estimates serve as an update and expansion to GBD 2021. Through these estimates, we also aimed to assess progress towards the 2025 Global Action Plan for the Prevention and Control of Pneumonia and Diarrhoea (GAPPD) target for pneumonia mortality in children younger than 5 years. Mortality from LRIs, defined as physician-diagnosed pneumonia or bronchiolitis, was estimated using the Cause of Death Ensemble model with data from vital registration, verbal autopsy, surveillance, and minimally invasive tissue sampling. The Bayesian meta-regression tool DisMod-MR 2.1 was used to model overall morbidity due to LRIs. DALYs were calculated as the sum of years of life lost (YLLs) and years lived with disability (YLDs) for all locations, years, age groups, and sexes. We modelled pathogen-specific case-fatality ratios (CFRs) for each age group and location using splined binomial regression to create internally consistent estimates of incidence and mortality proportions attributable to viral, fungal, parasitic, and bacterial pathogens. Progress was assessed towards the GAPPD target of less than three deaths from pneumonia per 1000 livebirths, which is roughly equivalent to a mortality rate of less than 60 deaths per 100 000 children younger than 5 years. In 2023, LRIs were responsible for 2·50 million (95% uncertainty interval [UI] 2·24-2·81) deaths and 98·7 million (87·7-112) DALYs, with children younger than 5 years and adults aged 70 years and older carrying the highest burden. LRI mortality in children younger than 5 years fell by 33·4% (10·4-47·4) since 2010, with a global mortality rate of 94·8 (75·6-116·4) per 100 000 person-years in 2023. Among adults aged 70 years and older, the burden remained substantial with only marginal declines since 2010. A mortality rate of less than 60 deaths per 100 000 for children younger than 5 years was met by 129 of the 204 modelled countries in 2023. At a super-regional level, sub-Saharan Africa had an aggregate mortality rate in children younger than 5 years (hereafter referred to as under-5 mortality rate) furthest from the GAPPD target. Streptococcus pneumoniae continued to account for the largest number of LRI deaths globally (634 000 [95% UI 565 000-721 000] deaths or 25·3% [24·5-26·1] of all LRI deaths), followed by Staphylococcus aureus (271 000 [243 000-298 000] deaths or 10·9% [10·3-11·3]), and Klebsiella pneumoniae (228 000 [204 000-261 000] deaths or 9·1% [8·8-9·5]). Among pathogens newly modelled in this study, non-tuberculous mycobacteria (responsible for 177 000 [95% UI 155 000-201 000] deaths) and Aspergillus spp (responsible for 67 800 [59 900-75 900] deaths) emerged as important contributors. Altogether, the 11 newly modelled pathogens accounted for approximately 22% of LRI deaths. This comprehensive analysis underscores both the gains achieved through vaccination and the challenges that remain in controlling the LRI burden globally. Furthermore, it demonstrates persistent disparities in disease burden, with the highest mortality rates concentrated in countries in sub-Saharan Africa. Globally, as well as in these high-burden locations, the under-5 LRI mortality rate remains well above the GAPPD target. Progress towards this target requires equitable access to vaccines and preventive therapies-including newer interventions such as respiratory syncytial virus monoclonal antibodies-and health systems capable of early diagnosis and treatment. Expanding surveillance of emerging pathogens, strengthening adult immunisation programmes, and combating vaccine hesitancy are also crucial. As the global population ages, the dual challenge of sustaining gains in child survival while addressing the rising vulnerability in older adults will shape future pneumonia control strategies. Gates Foundation.
Widening participation among the clinical laboratory scientific workforce is essential to meet future needs of healthcare systems. The advantages of more diversity in this clinically pivotal workforce include better decision making, improved diagnostics and a wider pool of appropriately trained applicants for new and advanced posts. This review summarises a sustainable "trickle up approach" to increase diversity and widen participation at all levels of the career pathway for clinical laboratory scientists with a focus on socioeconomically disadvantaged and minoritised scientists. Issues of access to appropriate degrees are present years in advance of university application and can be addressed through meaningful outreach programmes from universities and professional bodies. Interventions to broaden degree entry access including foundation routes have proven efficacy, whereas the role of degree apprenticeships in widening participation appears to be minimal, currently. There is a higher proportion of ethnic minorities, particularly black students, who don't complete their degree programme or attain lower awards than colleagues. Contributory factors include curriculum design along with psychosocial deficiencies in delivery. Decolonising and making biomedical science curricula and delivery more inclusive have proven effective in reducing these risks. Furthermore, socioeconomically disadvantaged students face a new challenge from generative artificial intelligence tools, where those that can pay get access to more powerful tools, creating a new gap, unless these tools are used judiciously and free at point of use. A graduate is required to complete training in a clinical laboratory to gain HCPC or equivalent registration, these places are competitive, and often unpaid. This appears to be a key barrier to widening participation, with a majority of graduates not pursuing careers as Biomedical Scientists. A state and financially supported training programme is required to broaden involvement at and post-registration. There is a paucity of information regarding the makeup of the workforce at promotional grades. However, an analysis of postgraduate study and research avenues reveals challenges for those from minoritised backgrounds and working mothers. These can be addressed through diversity in academic institutions and tailored, personalised approaches to research for working mothers to maximise participation at management and clinical leadership roles in the diagnostic laboratory.
Violence against women and against children are human rights violations with lasting harms to survivors and societies at large. Intimate partner violence (IPV) and sexual violence against children (SVAC) are two major forms of such abuse. Despite their wide-reaching effects on individual and community health, these risk factors have not been adequately prioritised as key drivers of global health burden. Comprehensive x§and reliable estimates of the comparative health burden of IPV and SVAC are urgently needed to inform investments in prevention and support for survivors at both national and global levels. We estimated the prevalence and attributable burden of IPV among females and SVAC among males and females for 204 countries and territories, by age and sex, from 1990 to 2023, as part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2023. We searched several global databases for data on self-reported exposure to IPV and SVAC and undertook a systematic review to identify the health outcomes associated with each of these risk factors. We modelled IPV and SVAC prevalence using spatiotemporal Gaussian process regression, applying data adjustments to account for measurement heterogeneity. We employed burden-of-proof methodology to estimate relative risks for outcomes associated with IPV and SVAC. These estimates informed the calculation of population attributable fractions, which were then used to quantify disability-adjusted life-years (DALYs) attributable to each risk factor. Globally, in 2023, we estimated that 608 million (95% uncertainty interval 518-724) females aged 15 years and older had ever been exposed to IPV, and 1·01 billion (0·764-1·48) individuals aged 15 years and older had experienced sexual violence during childhood. 18·5 million (8·74-30·0) DALYs were attributed to IPV among females and 32·2 million (16·4-52·5) DALYs were attributed to SVAC among males and females in 2023. IPV and SVAC were among the top contributors to the global disease burden in 2023, particularly among females aged 15-49 years, ranking as the fourth and fifth leading risk factors, respectively, for DALYs in this group. Among the eight health outcomes found to be associated with IPV, anxiety disorders and major depressive disorder were the leading causes of IPV-attributed DALYs, accounting for 5·43 million (-1·25 to 14·6) and 3·96 million (1·71 to 6·92) DALYs in 2023, respectively. SVAC was associated with 14 health outcomes, including mental health disorder, substance use disorder, and chronic and infectious disease outcomes. Self-harm and schizophrenia were the leading causes of SVAC-attributed burden, with SVAC accounting for 6·71 million (2·00 to 12·7) DALYs due to self-harm and 4·15 million (-1·92 to 13·1) DALYs due to schizophrenia in 2023. IPV and SVAC are substantial contributors to global health burden, and their health consequences span a variety of individual health outcomes. Importantly, mental health disorders account for the greatest share of disease burden among survivors. Investing in prevention of these avoidable risk factors has the potential to avert millions of DALYs and considerable premature mortality each year. Our findings represent strong evidence for global and national leaders to elevate IPV and SVAC among public health priorities. Sustained investments are needed to prevent IPV and SVAC and to implement interventions focused on supporting the complex social and health needs of survivors. Gates Foundation.
The G protein-coupled receptor 68 (GPR68) detects variations in extracellular pH, and has potential roles in homeostasis and responses to ischaemia and inflammation within different organs, including the gastrointestinal tract. However, in the human colon the distribution of GPR68 remains unclear. We examined the localization and density of GPR68 within the ascending (AC) and descending (DC) human colon from younger and older adults. Macroscopically normal AC and DC were obtained from patients undergoing lower bowel cancer resection (aged 22-91 years; grouped into younger (≤60 years) and older (≥67 years) populations). Immunolabelling was performed using formalin-fixed, paraffin-embedded sections and antibodies against GPR68, protein gene product 9.5 (PGP9.5) and calretinin to identify the presence and density of GPR68-immunoreactive (IR) expressing cells. Ageing did not change the density of total PGP9.5-IR enteric neuronal fibres in the AC or DC. For the myenteric plexus (MP) of both age groups, the densities of calretinin-IR neurons were similar in both the AC (younger: 1.2 ± 0.3 × 10-3; older: 0.9 ± 0.2 × 10-3 per mm2 plexus) and DC (1.4 ± 0.2 × 10-3; 1.3 ± 0.3 × 10-3 per mm2 plexus), but reduced in the mucosa of older adults for both AC (respectively, 9.8 ± 0.5 vs. 3.2 ± 0.1/pixel) and DC (11.5 ± 0.9 vs. 7.4 ± 0.3/pixel). Similar reduction of calretinin-IR enteric neurons was found in the SMP of AC but not clearly in the DC in the older adults. GPR68 was widely expressed in the mucosa, circular muscle and myenteric plexus of both the AC and DC. The density of GPR68-IR in the muscle and myenteric plexus was similar in both age groups, but smaller in the mucosa of older adults for both AC and DC. GPR68 is widely distributed within the enteric nervous system of the human colon, with potential roles for GPR68 suggested in the muscle and MP, and in the functions of calretinin-IR neurons within the mucosa. Further, the concomitant loss of GPR68 and calretinin-IR neurons in the mucosa of older adults suggests selective vulnerability of mucosal sensory and homeostatic mechanisms of the ageing colon.
The same dataset can be analysed in different justifiable ways to answer the same research question, potentially challenging the robustness of empirical science1-3. In this crowd initiative, we investigated the degree to which research findings in the social and behavioural sciences are contingent on analysts' choices. We examined a stratified random sample of 100 studies published between 2009 and 2018, in which, for one claim per study, at least five reanalysts independently reanalysed the original data. The statistical appropriateness of the reanalyses was assessed in peer evaluations, and the robustness indicators were inspected along a range of research characteristics and study designs. We found that 34% of the independent reanalyses yielded the same result (within a tolerance region of ±0.05 Cohen's d) as the original report; with a four times broader tolerance region, this indicator increased to 57%. Of the reanalyses conducted, 74% reached the same conclusion as the original investigation, 24% yielded no effects or inconclusive results and 2% reported the opposite effect. This exploratory study indicates that the common single-path analyses in social and behavioural research should not be simply assumed to be robust to alternative analyses4. Therefore, we recommend the development and use of practices to explore and communicate this neglected source of uncertainty.
The primary analysis of the SELECT randomized clinical trial suggests that semaglutide reduced the rates of cardiovascular (CV) death, myocardial infarction, and stroke in patients with established CV disease (CVD) and overweight or obesity without diabetes. However, the effect of semaglutide on hospitalizations in this population remains unknown. To determine the impact of semaglutide on total hospital admissions and duration of hospital stay. The SELECT trial included patients aged 45 years or older with established CVD and a body mass index (BMI, calculated as weight in kilograms divided by height in meters squared) of 27 or higher without diabetes at 804 clinical settings across North America, South America, Europe, Asia, Africa, and Australia. Patients were randomized from October 2018 to March 2021. This prespecified exploratory analysis was conducted from February 2024 to September 2025. Once-weekly subcutaneous semaglutide, 2.4 mg, or placebo. The total number of hospital admissions and days in hospital between the semaglutide and placebo groups. A total of 17 604 patients (median [IQR] age, 61.0 [55.0-68.0] years; 4872 female patients [27.7%]; median [IQR] BMI, 32.1 [29.7-35.7]) were followed up for a median (IQR) period of 41.8 (33.0-47.0) months. There were 11 287 hospital admissions. The number of total hospitalizations was lower in the semaglutide group vs placebo for any indication (18.3 vs 20.4 admissions per 100 patient-years; mean ratio [MR], 0.90; 95% CI, 0.85-0.95; P < .001) and for serious adverse events (15.2 vs 17.1 admissions per 100 patient-years; MR, 0.89; 95% CI, 0.84-0.94; P < .001). The number of days hospitalized for any indication per 100 patient-years was lower in the semaglutide group vs placebo (157.2 vs 176.2 days; rate ratio [RR], 0.89; 95% CI, 0.82-0.98; P = .01), as well as hospitalizations for serious adverse events (137.6 vs 153.9 days; RR, 0.89; 95% CI, 0.81-0.98; P = .02). No heterogeneity was observed for the reduction of hospital admissions with semaglutide in selected subgroups, including BMI, age, and sex. In this prespecified exploratory analysis of the SELECT randomized clinical trial, the trial cohort had a high rate of hospital admissions. Treatment with once-weekly semaglutide was associated with significant reductions in hospital admissions and overall time spent in hospital, extending its benefits beyond CV risk reduction. ClinicalTrials.gov Identifier: NCT03574597.
Cardiometabolic diseases (CMD) which include cardiovascular disease (CVD), diabetes, hypertension, and other metabolic syndromes represent a significant global health burden. Three quarters of global CVD deaths occur in low-and-middle-income countries (LMICs) and CMD account for approximately 35 percent of deaths in the Sub-Saharan Africa (SSA) region. The COVID-19 Pandemic significantly accelerated the transformation of the landscape in the management of patients with multiple long-term conditions, prompting innovation in healthcare delivery and highlighting the importance of more integrated and adaptable healthcare approaches. Addressing CMD requires a multifaceted approach involving both individual-level interventions, health system approaches, community-based approaches, and broader population-wide strategies for prevention. This study aimed to develop and pilot a person-centred model of health care for CMD management, integrating key principles from the Chronic Care Model (CCM) and Collaborative Care Model (CoCM) to assess feasibility and potential scalability in LMICs. The development of the CREATE intervention took a mixed method approach utilizing both qualitative and quantitative methodologies, including a systematic review, qualitative synthesis, and needs assessment including the delivery of workshops with local stakeholders and people living with CMD in Ghana, Kenya and Mozambique. A CoCCM with the following components was developed as the CREATE intervention: 1) Self-Management support, 2) Decision support (which included health care provider training), 3) Community linkages, 4) Organisation of health care, 5) Clinical information system, and 6) Delivery system design (streamlining the referral pathway). The CREATE intervention was informed by a systematic review, needs assessment, and six stakeholder workshops across three LMICs, identifying barriers such as limited primary care infrastructure, lack of referral systems, and gaps in self-management education. This is the first CoCCM model for Multiple Long-term Conditions (MLTC) to be developed for SSA. The intervention is currently being tested as part of a feasibility study in Kenya, Ghana and Mozambique. The CREATE intervention has the potential for adaptability to local context, however there is need for more rigorous research to evaluate the model effectiveness in relation to improving patient outcomes.
Information on childhood cancer burden is crucial for effective cancer policy planning. Unfortunately, observed paediatric cancer data are not available in every country, and previous global burden estimates have not discretely reported several common cancers of childhood. We aimed to inform efforts to address childhood cancer burden globally by analysing results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023, which now include nine additional cancer causes compared with previous GBD analyses. GBD 2023 data sources for cancer estimation included population-based cancer registries, vital registration systems, and verbal autopsies. For childhood cancers (defined as those occurring at ages 0-19 years), mortality was estimated using cancer-specific ensemble models and incidence was estimated using mortality estimates and modelled mortality-to-incidence ratios (MIRs). Years of life lost (YLLs) were estimated by multiplying age-specific cancer deaths by the standard life expectancy at the age of death. Prevalence was estimated using survival estimates modelled from MIRs and multiplied by sequelae-specific disability weights to estimate years lived with disability (YLDs). Disability-adjusted life-years (DALYs) were estimated as the sum of YLLs and YLDs. Estimates are presented globally and by geographical and resource groupings, and all estimates are presented with 95% uncertainty intervals (UIs). Globally, in 2023, there were an estimated 377 000 incident childhood cancer cases (95% UI 288 000-489 000), 144 000 deaths (131 000-162 000), and 11·7 million (10·7-13·2) DALYs due to childhood cancer. Deaths due to childhood cancer decreased by 27·0% (15·5-36·1) globally, from 197 000 (173 000-218 000) in 1990, but increased in the WHO African region by 55·6% (25·5-92·4), from 31 500 (24 900-38 500) to 49 000 (42 600-58 200) between 1990 and 2023. In 2023, age-standardised YLLs due to childhood cancer were inversely correlated with country-level Socio-demographic Index. Childhood cancer was the eighth-leading cause of childhood deaths and the ninth-leading cause of DALYs among all cancers in 2023. The percentage of DALYs due to uncategorised childhood cancers was reduced from 26·5% (26·5-26·5) in GBD 2017 to 10·5% (8·1-13·1) with the addition of the nine new cancer causes. Target cancers for the WHO Global Initiative for Childhood Cancer (GICC) comprised 47·3% (42·2-52·0) of global childhood cancer deaths in 2023. Global childhood cancer burden remains a substantial contributor to global childhood disease and cancer burden and is disproportionately weighted towards resource-limited settings. The estimation of additional cancer types relevant in childhood provides a step towards alignment with WHO GICC targets. Efforts to decrease global childhood cancer burden should focus on addressing the inequities in burden worldwide and support comprehensive improvements along the childhood cancer diagnosis and care continuum. St Jude Children's Research Hospital, Gates Foundation, and St Baldrick's Foundation.
People with mental disorders have an increased risk of diabetes, yet conflicting evidence exists regarding the quality of diabetes care they receive. To address this evidence gap, we conducted a systematic review and meta-analysis to assess and compare diabetes quality of care in people with diabetes with mental disorders versus people with diabetes without mental disorders. In this systematic review and random-effects meta-analysis, we searched Scopus, Embase, MEDLINE, and PsycINFO for cohort and case-control studies published between database inception and Feb 8, 2025. We estimated summary odds ratios (ORs) for diabetes quality of care indicators in individuals with any mental disorder versus without mental disorders to investigate the association between the presence of a mental disorder and diabetes quality of care indicators, including overall diabetes monitoring and treatment. Studies were excluded if it was not possible to generate pooled quantitative data. The primary outcome was a binary composite measure of diabetes quality of care, meaning the percentage of people receiving any diabetes monitoring and treatment (ie, urine albumin-creatinine ratio test, HbA1c test, blood pressure measured, foot surveillance, serum creatinine test, serum cholesterol test, BMI recorded, smoking status recorded, retinal monitoring). Secondary outcomes were study-specific diabetes quality of care individual indicators matched to the nine NICE diabetes monitoring indicators and specific diabetes interventions and anti-diabetes medications. We analysed primary and secondary outcomes according to any mental disorder and to specific diagnostic subgroups. Study quality was evaluated using the Newcastle-Ottawa Scale (NOS). Data from 49 studies (42 cohort and seven case-control) were included, comprising 5 503 712 individuals with diabetes, of whom 838 366 (15·2%) had a diagnosed mental disorder (defined using ICD-9 or ICD-10 criteria in 40 studies). Sex was reported in 35 of 49 studies, comprising 4 250 666 individuals, 1 956 506 (46·0%) of whom were female and 2 294 160 (54·0%) were male. The mean age was 61·4 years (SD 8·7; range 47-82 years). 38 studies reported on various mental disorders, 21 on mood disorders spectrum, 21 on major depressive disorder, 20 on schizophrenia, 11 on bipolar disorder, 11 on substance use disorder spectrum, including alcohol use disorder, six on dementia, five on anxiety disorder spectrum, and one on personality disorder spectrum. Most studies were high quality and spanned Asia, North America, Europe, and Australasia. Significant negative associations were observed between having any mental disorder and the likelihood of receiving any recommended diabetes monitoring (29 studies, OR=0·81 [95% CI 0·70-0·94], p=0·0049). Negative associations were also observed for HbA1c measurement (24 studies, 0·81 [0·68-0·97], p=0·024), retinal screening (21 studies, 0·77 [0·63-0·95], p=0·013), lipid and cholesterol measurement (20 studies, 0·83 [0·69-0·99], p=0·043), foot examination (11 studies, 0·85 [0·76-0·95], p=0·0044), and renal investigation (16 studies, 0·78 [0·63-0·96], p=0·022). A significant positive association was found between any mental disorder and recorded smoking status (two studies, 1·09 [1·02-1·17]; p=0·0076). Any mental disorder was significantly associated with higher odds of receiving insulin (ten studies, 1·52 [95% CI 1·16-1·99]; p=0·0022), but negatively associated with treatment with a GLP-1 receptor agonist (two studies, 0·26 [0·13-0·49]; p<0·0001). There was no evidence of publication bias. Mental disorders are negatively associated with receiving adequate diabetes monitoring and GLP-1 agonist therapy. Addressing these disparities has the potential to address the increased mortality associated with mental disorders. None.
The readability of public-facing vaccine-related information is an important aspect of health literacy particularly regarding vaccine uptake. The aims of this study were to analyse the readability of such written literature and to provide recommendations, for improvement. Readability of vaccine-related information (ntotal = 240) from publicly available sources (n = 20 per category), including PubMed Abstracts, Expert Review of Vaccines (ERV) and Cochrane Reviews (CR), paired plain language and scientific abstracts, public health materials, clinical trial summaries and vaccine patient information leaflets, were assessed using the Flesch Reading Ease (FRE), Flesch-Kincaid Grade Level (FKGL), SMOG and Gunning Fog readability metrics using the readability software tool readable.com. Vaccine-related information for all sources had poor readability across all readability metrics with 90.8% and 94.6% not reaching the target FKGL (≤8) (mean 12 ± 3.2 sd) and FRE (≥60) (mean 34 ± 17 sd). Plain language summaries had improved readability, but did not reach reference targets. Scientific abstract and plain language scores for the CR were FRE (mean 25 ± 7.2 sd; median 25) versus (mean 37 ± 8.6 sd; median 36) p < 0.0001), respectively and for ERV FRE the scientific abstract (mean 18 ± 11 sd; median 17) versus the plain language score (mean 26 ± 11 sd; median 28) p = 0.002), respectively, indicating an improvement in readability scores for plain language summaries but again not reaching reference targets. The readability of public-facing vaccination materials is currently not optimum. The readability can be improved through the employment of readability calculators and ensuring, where possible, the use of mono-syllable words and less than fourteen words per sentence. The preparation of public-facing materials with improved readability scores will help aid in the promotion of health literacy and in turn promote vaccination uptake.
Quantification of the calcific burden is valuable in percutaneous coronary intervention (PCI) planning and in research to assess its changes after pharmacotherapies targeting plaque progression. In intravascular ultrasound (IVUS) images this analysis is currently performed manually and time consuming. To overcome these limitations, we introduce a deep-learning (DL) method for seamless detection of the calcific tissue. IVUS images from 197 vessels were analysed by an expert who identified the presence of calcium, and these estimations were used to train a DL model for fast detection of calcific deposits. The output of the model was tested in a set of 30 vessels against the estimations of the two experts. Comparison was performed at a frame-, lesion- and segment level. In total 26,211 frames were included in the training and 5,138 in the test set. The estimations of the DL method for the presence of calcium were similar to the experts (kappa 0.842 and 0.848, p < 0.001), while the correlation between the DL approach and the two experts for the arc of calcium (0.946 and 0.947, p < 0.001) and calcific area (0.745 and 0.706, p < 0.001) were high. Lesion- (0.971 and 0.990, p < 0.001) and segment-level analysis (0.980 and 0.981, p < 0.001) demonstrated a high correlation between the method and the two experts for calcific burden. The proposed DL method is able to accurately detect the calcific tissue and quantify its burden. These features render it useful in research and are expected to facilitate its application in the clinical workflows to guide PCI.
The poor solubility and permeability of Biopharmaceutics Classification System (BCS) Class IV drugs pose major challenges to achieving sufficient oral bioavailability and therapeutic efficacy. Improving drug dissolution is a key strategy to enhance bioavailability, which in turn can enable more effective targeting of drugs to their site of action. To address this, we formulated cefdinir, a model BCS Class IV compound, using three amorphisation strategies; solid dispersions, mesoporous silica dispersions, and co-amorphous systems to assess the impact of formulation on stability and dissolution. Formulations were prepared via spray drying and solvent immersion using different drug-to-polymer ratios, with miscibility predicted using Flory-Huggins theory. The amorphous nature of each system was confirmed using differential scanning calorimetry (DSC), polarised light microscopy (PLM), and powder X-ray diffraction (PXRD). Dissolution studies revealed significantly enhanced drug release from all formulations compared to crystalline cefdinir. Among them, solid dispersion and co-amorphous systems exhibited the greatest improvement in dissolution rates, attributed to their ability to maintain supersaturation and inhibit crystallisation via kinetic stabilisation. These systems also showed better physical stability under non-sink aqueous conditions. However, mesoporous silica dispersions demonstrated superior long-term stability, retaining over 95% drug content and preserving their amorphous structure across three storage conditions (25 °C/0% RH, 40 °C/0% RH, and 40 °C/75% RH) for 6 months. This was attributed to the confinement of the drug within silica pores and the absence of hygroscopic excipients. Overall, this study highlights the distinct advantages of each approach, emphasising the importance of balancing dissolution enhancement with solid-state stability, and supports the use of theoretical modelling to guide rational formulation design for poorly soluble drugs to improve oral bioavailability and enable more targeted therapeutic outcomes.
Diagnosing cardiac amyloidosis (CA) on echocardiography can be challenging due to the imaging overlap between CA and more prevalent causes of a hypertrophic phenotype. This study sought to (1) evaluate the performance of artificial-intelligence (AI) derived measurements incorporated into the established multiparametric echocardiographic scoring system to detect CA; (2) develop and validate an AI-based deep-learning model for video-based detection of CA on echocardiography. The study population comprised 5776 patients (CA, 2756; controls, 3020). The training data set included patients from the UK National Amyloidosis Center and Taiwan MacKay Memorial Hospital (CA, 2241; controls, 2130). External test data sets were obtained from the US Duke University Health System (CA, 334; left ventricular hypertrophy controls, 668) and Japan National Cerebral and Cardiovascular Center (CA, 181; left ventricular hypertrophy controls, 222). The multiparametric echocardiographic score computed using AI-derived measurements achieved an accuracy of 79.5% (sensitivity, 75.4%; specificity, 81.5%) in the United States cohort and 79.7% (sensitivity, 81.6%; specificity, 78.1%) in the Japan cohort. The deep-learning model demonstrated accuracies of 96.2% (sensitivity, 96.8%; specificity, 95.7%) and 95.8% (sensitivity, 97.3%; specificity, 94.3%) in the internal validation and internal test sets, respectively. External validation of the deep-learning model showed accuracies of 87.5% (sensitivity, 86.6%; specificity, 87.9%) in the United States and 88.4% (sensitivity, 92.3%; specificity, 85.3%) in the Japanese cohort. Subgroup analysis demonstrated that the deep-learning model showed robust discrimination of CA from other hypertrophic phenocopies: CA versus hypertension (area under the curve [AUC], 0.92 [95% CI, 0.91-0.94]), CA versus hypertrophic cardiomyopathy (AUC, 0.91 [95% CI, 0.87-0.94]), CA versus aortic stenosis (AUC, 0.93 [95% CI, 0.90-0.95]), CA versus chronic kidney disease (AUC, 0.93 [95% CI, 0.91-0.95]). The deep-learning model was able to classify a greater proportion of patients compared with the AI-derived multiparametric echocardiographic score and achieved superior diagnostic accuracy (AUC, 0.93 [95% CI, 0.91-0.95] versus AUC, 0.88 [95% CI, 0.85-0.90]; P<0.001). Both the multiparametric echocardiographic score computed from AI-derived measurements and the fully automated deep-learning model can accurately identify patients with CA in globally diverse cohorts, with the deep-learning model providing superior performance.
Heart failure (HF) remains a significant burden following transcatheter aortic valve replacement, adversely impacting survival and quality of life. Identification of patients who may benefit from closer monitoring or adjunctive medical therapy to reduce the risk of HF is an unmet need. The objective of this study was to develop and internally validate a clinical prediction model to determine the 1-year risk of HF hospitalization or death after transcatheter aortic valve replacement. Using the Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapy Registry, we analyzed patients who underwent successful transcatheter aortic valve replacement for aortic stenosis and survived to discharge between 2016 and 2019. Covariates were selected based on expert opinion and prior literature. A hierarchical cumulative odds regression model was used to predict a composite outcome of (1) all-cause death, (2) ≥2 HF readmissions, or (3) 1 HF readmission at 1 year. Among 78 384 patients (median age, 82 years; 45.6% female), 17.4% experienced the composite outcome, including death (10.9%), ≥2 HF readmissions (1.6%), and 1 HF readmission (4.9%). The model demonstrated good discrimination (C statistic, 0.753 derivation and 0.747 validation) and excellent calibration. Among 1-year survivors, performance in predicting HF readmission as an isolated outcome was similar (C statistic, 0.753). A simplified model, including the top 12 variables from the full model, maintained comparable performance (C statistics, 0.74-0.75). This prediction model effectively stratifies post-transcatheter aortic valve replacement patients by risk of death or HF readmission, supporting its use to guide clinical surveillance and clinical trial enrollment for adjunctive medical therapies aimed at mitigating this risk.
Meningitis remains the leading infectious cause of neurological disabilities globally, disproportionately affecting children younger than 5 years and populations in the African meningitis belt. Whereas previous global estimates focused on ten pathogen categories, this study presents the most comprehensive analysis to date, assessing the meningitis burden attributable to 17 causative pathogens based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 framework. GBD is a systematic, scientific effort aimed at quantifying the comparative magnitude of health loss caused by diseases, injuries, and risk factors across age groups, sexes, and geographical locations over time. We estimated meningitis mortality using the Cause of Death Ensemble model (CODEm) and morbidity using DisMod-MR 2.1, incorporating data from vital registration, verbal autopsy, surveillance, hospital data, and systematic reviews. Aetiology-specific estimates were generated with pathogen-linked case-fatality ratios and splined binomial regression models. Risk factor attribution was based on established risk-outcome pairs and population attributable fractions. In 2023, there were 259 000 (95% uncertainty interval 202 000-335 000) global deaths and 2·54 million (2·20-2·93) incident cases of meningitis. Children younger than 5 years accounted for more than a third of deaths (86 600 [53 300-149 000]). Streptococcus pneumoniae, Neisseria meningitidis, non-polio enteroviruses, and other viruses were the leading causes of death, while non-polio enteroviruses caused the most cases. The four WHO-defined preventable meningitis pathogens of interest (S pneumoniae, N meningitidis, Haemophilus influenzae, and Group B streptococcus) contributed to 98 700 deaths (77 000-127 000) and 594 000 cases (514 000-686 000). Low birthweight, short gestation, and household air pollution were the top risk factors for meningitis-related mortality. Although mortality and incidence have declined significantly since 1990, progress is insufficient to meet WHO 2030 targets. Despite marked progress in reducing bacterial meningitis via global vaccination campaigns, a substantial meningitis burden persists, attributable both to common pathogens such as S pneumoniae and N meningitidis and to emerging non-bacterial pathogens such as Candida spp and drug-resistant fungi. Achieving WHO goals will require sustained investment in surveillance, vaccination, maternal screening, and health-system strengthening, especially in high-burden settings. Gates Foundation, Wellcome Trust, and UK Department of Health and Social Care.
Oral epithelial dysplasia (OED) is the precursor to oral squamous cell carcinoma, but histologic grading alone lacks reproducibility and prognostic power. This study evaluates whether pattern-based p53 and p16 immunohistochemistry (IHC) can serve as alternative markers to genomic loss of heterozygosity (LOH) testing in predicting OED progression. From a previously characterized LOH cohort, 64 patients were assessed with IHC for p53 and p16 using defined abnormal staining patterns (overexpression, cytoplasmic, or null). Abnormal p53 expression occurred in 19% of cases, with 93% specificity, and was significantly associated with reduced progression-free survival (PFS; 8-year PFS, 25% vs. 74%; P = 0.0011). Abnormal p16 expression was observed in 56% of cases with 95% sensitivity and was significantly associated with 8-year PFS (42% vs. 96%; P < 0.0001). Combined p53/p16-abnormal IHCs identified 95% of the progressing lesions and yielded superior risk discrimination (log-rank P < 0.0001), particularly at the 3-year follow-up mark. Concordance analysis revealed moderate agreement between p16 IHC and 9p LOH (κ = 0.39) and fair agreement between p53 IHC and 17p LOH (κ = 0.21), indicating that IHC and LOH detect related but distinct molecular disruptions. Chronologic evaluation of serial biopsies supported a sequential model in which p16 alteration precedes p53 alteration during malignant progression. Taken together, these findings highlight the potential of a pattern-based approach with combined p53/p16 IHC as a feasible, scalable, and clinically accessible tool to guide surveillance intensity and timely clinical intervention, thereby reducing progression risks. In this study, we demonstrate that p53/p16 pattern-based IHC provides a practical and sensitive tool for predicting progression in OED. Its clinical accessibility may facilitate early detection of high-risk lesions, optimizing triage, surveillance, and preventative treatment strategies to reduce the incidence of high-grade lesions or oral cancer.
Urbanization often correlates with reduced diversity in human gut microbiota, with notable variations observed between the gut microbiota among the Indigenous communities in rural villages and urban citizens residing in modern settings. Although research has been conducted on the gut microbiota of healthy adults in Malaysia, there has been no study characterising the gut microbiota of Sarawak's Indigenous communities to date. This study aims to fill this gap by examining the gut microbiota profile of the Sarawak Indigenous groups (specifically Orang Ulu subethnic groups Kayan and Kenyah), comparing them with semi-urbanized Selangor Indigenous communities from Peninsular Malaysia (represented by Proto Malay subtribe Temuan) and Urban communities from Kuala Lumpur. We conducted a cross-sectional study and collected stool samples from 86 Indigenous participants from Sarawak and compared them with published data from 45 Malaysian Indigenous participants from Selangor and 18 Urban citizens living in Kuala Lumpur City. DNA was extracted from the stool samples, and subsequently, the V4 hypervariable region of the 16S rRNA gene was sequenced. The raw sequence data were analyzed using the Quantitative Insights into Microbial Ecology 2 (QIIME2) bioinformatics platform. Analysis revealed that the Sarawak Indigenous community exhibited the highest gut microbial diversity, followed by the Peninsular Indigenous and Urban groups. The Prevotella/Bacteroides (P/B) ratio revealed that the Sarawak Indigenous community showed the highest presence of Prevotella at 88.3%, while Kuala Lumpur Urban residents had a predominantly Bacteroides composition at 61%. The Selangor Indigenous community also exhibited a Prevotella-dominant profile at 75.5%. VANISH microbes (Prevotella, Faecalibacterium, and Succinivibrio) were identified as dominant genera in the Sarawak Indigenous gut microbiota, contrasting with the BIoSSUM microbe (Bacteroidaceae) found in the Kuala Lumpur cohort. This study sheds light on the distinct gut microbiota composition of Sarawak's Indigenous community, which has not been previously explored. It highlights the impact of urbanization on gut microbiota composition during lifestyle transitions.