Research on automated mental health assessment tools has been growing in recent years, often aiming to address the subjectivity and bias that existed in the current clinical practice of the psychiatric evaluation process. Despite the substantial health and economic ramifications, the potential unfairness of those automated tools was understudied and required more attention. In this work, we systematically evaluated the fairness level in a multimodal remote mental health dataset and an assessment system, where we compared the fairness level in race, gender, education level, and age. Demographic parity ratio (DPR) and equalized odds ratio (EOR) of classifiers using different modalities were compared, along with the F1 scores in different demographic groups. Post-training classifier threshold optimization was employed to mitigate the unfairness. No statistically significant unfairness was found in the composition of the dataset. Varying degrees of unfairness were identified among modalities, with no single modality consistently demonstrating better fairness across all demographic variables. Post-training mitigation effectively improved both DPR and EOR metrics at the expense of a decrease in F1 scores. Addressing and mitigating unfairness in these automated tools are essential steps in fostering trust among clinicians, gaining deeper insights into their use cases, and facilitating their appropriate utilization.
Background: Both tirzepatide and semaglutide have been shown to reduce weight for patients with overweight or obesity in randomized controlled trials (RCTs). While tirzepatide appears to provide greater weight loss than semaglutide in this population, head-to-head RCTs are not yet available. Accordingly, we sought to compare on-treatment weight loss in a real- world setting for adults with overweight or obesity initiated on tirzepatide or semaglutide. Methods: Adults with overweight or obesity first dispensed semaglutide or tirzepatide be- tween May 2022 and September 2023 were identified from Truveta Data, a large electronic health record (EHR) dataset linked with comprehensive pharmacy dispensing data. The study cohort was restricted to patients with no prior GLP-1 RA use, who initiated a formulation of semaglutide or tirzepatide labelled for type 2 diabetes mellitus (T2D) (a proxy for dose), received regular care in the previous year, had a GLP-1 RA prescription written in the 60 days prior to initiation, and had an available baseline weight. On treatment weight changes in a propensity score matched population were compared for outcomes of time to 5%, 10%, and 15% weight loss, and percentage change in weight by 3, 6, and 12 months. For all outcomes, we conducted subgroup analyses stratified by T2D (on-label users) and sensitivity analyses using inverse probability of treatment weighting. Results: A total of 41,223 patients met our cohort definition (semaglutide: 32,030; tirzepatide: 9,193). Propensity score matching produced an analytic cohort of 18,386 patients with good balance on all baseline covariates. At treatment initiation, the mean(SD) age was 52.0 (12.9) years, 70.5% of patients were female, 51.7% had T2D, and mean(SD) weight was 110 (25.7) kg. A larger proportion of patients on tirzepatide, compared to semaglutide, achieved weight reductions [≥]5% (81.8% vs. 64.6%), [≥]10% (62.1% vs. 38.0%), and [≥]15% (42.3% vs 19.3%) within 1 year on treatment, yielding hazard ratios of 1.76 (1.68 - 1.85) for 5%, 2.42 (2.25 - 2.59) for 10%, and 3.04 (2.73 - 3.38) for 15% weight loss. Patients on tirzepatide experienced larger changes in percentage of body weight lost at 3 months on treatment (difference [95% CI]) (-2.3% [-2.5% , -2.2%]), 6 months on treatment (-4.3% [-4.6%, -3.9%]) , and 12 months on treatment (-7.2% [-8.3% , -6.2%]). Hazards for all gastrointestinal (GI) adverse events were similar between groups. Conclusion: In a real-world population of US adults with overweight or obesity initiated on tirzepatide or semaglutide formulations labelled for T2D, patients on tirzepatide were signifi- cantly more likely to achieve 5%, 10% and 15% weight loss and experience larger reductions in weight at 3, 6, and 12 months. Findings were robust to analytic choice and consistent among populations stratified by T2D. Future work is needed to understand whether these findings result in a differential impact on other outcomes, including rates of adverse cardiovascular events.
Background Ethnicity is known to be an important correlate of health outcomes, particularly during the COVID-19 pandemic, where some ethnic groups were shown to be at higher risk of infection and adverse outcomes. The recording of patients' ethnic groups in primary care can support research and efforts to achieve equity in service provision and outcomes; however the coding of ethnicity is known to present complex challenges. We therefore set out to describe ethnicity coding in detail with a view to supporting the use of this data in a wide range of settings, as part of wider efforts to robustly describe and define methods of using administrative data. Methods We describe the completeness and consistency of primary care ethnicity recording in the OpenSAFELY-TPP database, containing linked primary care and hospital records in >25 million patients in England. We also compared the ethnic breakdown in OpenSAFELY-TPP with that of the 2021 UK census. Results 78.2% of patients registered in OpenSAFELY-TPP on 1 January 2022 had their ethnicity recorded in primary care records, rising to 92.5% when supplemented with hospital data. The completeness of ethnicity recording was higher for women than for men. The rate of primary care ethnicity recording ranged from 77% in the South East of England to 82.2% in the West Midlands. Ethnicity recording rates were higher in patients with chronic or other serious health conditions. For each of the five broad ethnicity groups, primary care recorded ethnicity was within 2.9 percentage points of the population rate as recorded in the 2021 Census for England as a whole. For patients with multiple ethnicity records, 98.7% of the latest recorded ethnicities matched the most frequently coded ethnicity. Patients whose latest recorded ethnicity was categorised as Other were most likely to have a discordant ethnicity recording (32.2%). Conclusions Primary care ethnicity data in OpenSAFELY is present for over three quarters of all patients, and combined with data from other sources can achieve a high level of completeness. The overall distribution of ethnicities across all English OpenSAFELY-TPP practices was similar to the 2021 Census, with some regional variation. This report identifies the best available codelist for use in OpenSAFELY and similar electronic health record data.
Synthetic data has recently risen as a new precious item in the computational pathologist's toolbox, supporting several tasks such as helping with data scarcity or augmenting training set in deep learning. Nonetheless, the use of such novel resources requires a carefully planned construction and evaluation, to avoid pitfalls such as the generation of clinically meaningless artifacts. As the major outcome described in the current manuscript, a novel full stack pipeline is introduced for the generation and evaluation of synthetic pathology data powered by a diffusion model. The workflow features, as characterizing elements, a new multifaceted evaluation strategy with an embedded explainability procedure effectively tackling two critical aspects of the use of synthetic data in health-related domains. An ensemble-like strategy is adopted for the evaluation of the produced data, with the threefold aim of assessing the similarity of real and synthetic data through a set of well-established metrics, evaluating the practical usability of the generated images in deep learning models complemented by explainable AI methods, and validating their histopathological realism through a dedicated questionnaire answered by three professional pathologists. The pipeline is demonstrated on the public GTEx dataset of 650 WSIs, including five different tissues, conditioning the training step of the underlying diffusion model. An equal number of tiles from each of these five tissues are then generated. Finally, the reliability of the generated data is assessed using the proposed evaluation pipeline, with encouraging results. We show that each of these evaluation steps are necessary as they provide complementary information on the generated data's quality. Overall, all the aforementioned features characterize the proposed workflow as a fully-fledged solution for generative AI in digital pathology representing a potentially useful tool for the digital pathology community in their transition towards digitalization and data-driven modeling.
Background: Autism spectrum disorder (ASD) is a prevalent and heterogeneous neurodevelopmental disorder. Risk is attributed to genetic and prenatal environmental factors, though the environmental agents are incompletely characterized. Methods: In Early Autism Risk Longitudinal Investigation (EARLI) and Markers of Autism Risk in Babies Learning Early Signs (MARBLES), two pregnancy cohorts with high likelihood of ASD, maternal urinary metals concentrations at two time points during pregnancy were measured using inductively coupled plasma mass spectrometry. At age three, clinicians assessed ASD with DSM-5 criteria. Using multivariable log binomial regression, we examined each metal for association with ASD status, adjusting for gestational age at urine sampling, child sex, maternal age, and maternal education, and meta-analyzed across the two cohorts. Results: In EARLI (n=170) 17.6% of children were diagnosed with ASD, and an additional 43.5% were classified as having other non-neurotypical development (Non-TD). In MARBLES (n=156), 22.7% were diagnosed with ASD, while an additional 11.5% had Non-TD. In earlier pregnancy metals measures, having cadmium concentration over the level of detection was associated with 1.78 (1.19, 2.67) times higher risk of ASD, and 1.43 (1.06, 1.92) times higher risk of Non-TD. A doubling of early pregnancy cesium concentration was marginally associated with 1.81 (0.95, 3.42) times higher risk of ASD, and 1.58 (0.95, 2.63) times higher risk of Non-TD. Conclusion: Exposure in utero to elevated levels of cadmium and cesium, as measured in maternal urine collected during pregnancy, was associated with increased risk of developing ASD.
Introduction: Adherence to infection prevention and control guidelines is critical to improving the quality of hospital care based on their efficacy in reducing the occurrence of infections that compromise patients' outcomes. However, the impact of predictors on IPC compliance among healthcare workers has not been adequately reported. Objectives: This study aims to demonstrate the utility of the Ordinal Logistic regression model in identifying the impact of personal and organizational characteristics on health workers' level of compliance with infection prevention and control at the University of Port Harcourt Teaching Hospital. Methods: A cross-sectional study design using a self-administered questionnaire was adopted. A sample of 235 respondents was chosen using a proportionate stratified random sampling method. We analyzed data using descriptive statistics and the ordinal Logistic regression model. Result: The study result shows that IPC compliance among Health workers in UPTH is high, 77%. Predictors of compliance were found to be age group 35-45years (AOR= 7.679, CI= 1.214 -48.577), training (AOR=0.401, CI: 0.189, 0.849), knowledge, (AOR= 0.45, CI: 0.207, 0.978), management support (AOR=0.45, CI 0.16, 0.968) as they were found to be statistically significant with the level of compliance with infection prevention and control. Conclusion. There is relatively high Compliance with Infection Prevention and Control; this can be further improved through improved management commitment and increased surveillance of health workers. Keywords: Infection control, Compliance, Healthcare-Associated infection, Health workers, Ordinal Logistic Regression.
Impaired glucose homeostasis leads to many complications, with coronary artery disease (CAD) being a major contributor to healthcare costs. However, current CAD screening methods lack efficacy. Here, we predicted CAD using easy-to-measure indices, including continuous glucose monitoring (CGM)-derived indices. We found that CGM-derived indices, particularly ADRR and AC_Var, exhibited stronger predictive capabilities for CAD compared to commonly used diabetes diagnostic indices such as fasting blood glucose (FBG), hemoglobin A1C (HbA1c), and plasma glucose level at 120 min during oral glucose tolerance tests (PG120). Factor analysis identified three distinct components underlying glucose dynamics - value, variability, and autocorrelation - each independently associated with CAD. Remarkably, ADRR was influenced by the first two components, and AC_Var was influenced by the third component. FBG, HbA1c, and PG120 were influenced only by the value component, making them insufficient for CAD prediction. CGM-derived indices reflecting the three components can outperform traditional diabetes diagnostic methods in CAD prediction.
Introduction Visceral adiposity is emerging as a key driver of cardio-metabolic risk factors and cardiovascular disease (CVD), but its relationship with cardiac structure and function is not well characterized across sexes. Using the Canadian Alliance for Healthy Heart and Minds (CAHHM), a large population-based cohort study, we sought to determine the association of visceral adipose tissue (VAT) on subclinical left ventricular (LV) remodeling in males and females. Methods As part of the CAHHM study, 6522 participants free of clinical CVD (mean age: 57.4 [8.8 SD] years; 3,671 females, 56%) underwent magnetic resonance imaging (MRI) in which LV parameters and VAT volume were measured. Information about demographic factors, CV risk factors, and anthropometric measurements were obtained. Subclinical cardiac remodelling was defined as altered LV concentricity, represented by increased LV mass-to-volume ratio (LVMV). Results Males had a higher VAT volume (80.8 mL; 95% CI: 74.6 t 86.9) compared to females (64.7 mL; 95% CI: 58.5 to 70.8), adjusted for age and height. Among both males and females, VAT was significantly associated with subclinical cardiac remodeling (increased LVMV), independent of other CV risk factors. In multiple regression models adjusted for cardiovascular risk factors, age, and height, every 1 sex-specific standard deviation increase in VAT corresponded to an increase of 0.037 g/mL in LVMV (95% CI: 0.032 to 0.041; p<0.001), which was consistent across both sexes. Notably, a 1 standard deviation increase in VAT is associated with a LVMV that is 20 times higher than what is observed with natural aging alone (0.0020 g/mL rise in LVMV (95% CI 0.0016 to 0.0025), and 1.5 times higher than the impact of an integrated measure of CV risk factors (0.024 g/mL; 95% CI: 0.020 to 0.028). Conclusion VAT significantly influences subclinical cardiac remodeling in both males and females, independent of other cardiovascular risk factors and age. Further research to understand the pathways by which VAT contributes to accelerated cardiac aging is needed.
Pulmonary hypertension (PH) is a pathological condition that affects approximately 1% of the population. The prognosis for many patients is poor, even after treatment. Our knowledge about the pathophysiological mechanisms that cause or are involved in the progression of PH is incomplete. Additionally, the mechanism of action of many drugs used to treat pulmonary hypertension, including sotatercept, requires elucidation. Using our graph-powered knowledge mining software Lifelike in combination with a very small patient metabolite data set, we demonstrate how we derive detailed mechanistic hypotheses on the mechanisms of PH pathophysiology and clinical drugs. In PH patients, the concentration of hypoxanthine, 12(S)-HETE, glutamic acid, and sphingosine 1 phosphate is significantly higher, while the concentration of L-arginine and L-histidine is lower than in healthy controls. Using the graph-based data analysis, gene ontology, and semantic association capabilities of Lifelike, led us to connect the differentially expressed metabolites with G-protein signaling and SRC. Then, we associated SRC with IL6 signaling. Subsequently, we found associations that connect SRC, and IL6 to Activin and BMP signaling. Lastly, we analyzed the mechanisms of action of several existing and novel pharmacological treatments for PH. Lifelike elucidated the interplay between G-protein, interleukin 6, activin, and BMP signaling. Those pathways regulate hallmark pathophysiological processes of PH, including vasoconstriction, endothelial barrier function, cell proliferation, and apoptosis. The results highlight the importance of SRC, ERK1, AKT, and MLC activity in PH. The molecular pathways affected by existing and novel treatments for PH also converge on these molecules. Importantly, sotatercept affects SRC, ERK1, AKT, and MLC simultaneously. The present study shows the power of mining knowledge graphs using Lifelike's diverse set of data analytics functionalities for developing knowledge-driven hypotheses on PH pathophysiological and drug mechanisms and their interactions. We believe that Lifelike and our presented approach will be valuable for future mechanistic studies of PH, other diseases, and drugs.
Importance: Earlier research on COVID-19 vaccines identified a range of adverse reactions related to proinflammatory actions that can lead to an excessive immune response and sustained inflammation. However, no study has been conducted on the association between inflammatory musculoskeletal disorders and COVID-19 vaccines. Objective: To investigate the incidence rates of inflammatory musculoskeletal disorders following COVID-19 vaccination and to compare them with those of unvaccinated individuals. Design, Setting, and Participants: This retrospective nationwide cohort study used data from the Korean National Health Insurance Service (NHIS) database, involving 2,218,715 individuals. Data were collected from January 1, 2021, to 12 weeks after the second dose of vaccine for vaccinated individuals and 12 weeks after September 30, 2021, for unvaccinated individuals. Exposures: Status was categorized as unvaccinated and vaccinated with mRNA vaccine, viral vector vaccine, and mixing and matching. Main Outcomes and Measures: The primary outcome was the occurrence of inflammatory musculoskeletal disorders that were selected as plantar fasciitis (ICD code, M72.2), rotator cuff syndrome (M75.1), adhesive capsulitis (M75.0), herniated intervertebral disc (HIVD) (M50.2/M51.2), spondylosis (M47.9), bursitis (M71.9), Achilles tendinitis (M76.6), and de-Quervain tenosynovitis (M65.4). Multivariate logistic regression analysis was used to determine the risk factors of musculoskeletal disorders after adjusting for potential confounders. Results: Among the 2,218,715 individuals, 1,882,640 (84.9%) received two doses of the COVID-19 vaccine, and 336,075 (15.1%) did not. At 12 weeks after vaccination, the incidences of plantar fasciitis (0.14-0.17%), rotator cuff syndrome (0.29-0.42%), adhesive capsulitis (0.29-0.47%), HIVD (0.18-0.23%), spondylosis (0.14-0.23%), bursitis (0.02-0.03%), Achilles tendinitis (0.0-0.05%), and de-Quervain tenosynovitis (0.04-0.05%) were higher in all three vaccinated groups (mRNA, cDNA, and mixing and matching vaccines) when compared to the unvaccinated group. All COVID-19 vaccines were identified as significant risk factors for each inflammatory musculoskeletal disorder (odds ratio, 1.404-3.730), except for mixing and matching vaccines for de-Quervain tenosynovitis. Conclusions and Relevance: This cohort study found that individuals who received any COVID-19 vaccine were more likely to be diagnosed with inflammatory musculoskeletal disorders than those who did not. This information will be useful in clarifying the adverse reactions to COVID-19 vaccines and informing people about their potential for inflammatory musculoskeletal disorders after vaccination.
Background When clinicians need to administer a vasopressor infusion, they are faced with the choice of administration via either peripheral intravenous catheter (PIVC) or central venous catheter (CVC). Vasopressor infusions have traditionally been administered via central venous catheters (CVC) rather than Peripheral Intra Venous Catheters (PIVC), primarily due to concerns of extravasation and resultant tissue injury. This practice is not guided by contemporary RCT evidence. Observational data suggests safety of vasopressor infusion via PIVC. To address this evidence gap, we have designed the "Vasopressors Infused via Peripheral or Central Access" (VIPCA) randomised controlled trial (RCT). Methods The VIPCA trial is a single-centre, feasibility, parallel-group RC. Eligible critically ill patients requiring a vasopressor infusion will be identified by emergency department (ED) or intensive care unit (ICU) staff and randomised to receive vasopressor infusion via either PIVC or CVC. Primary outcome is feasibility, a composite of recruitment rate, proportion of eligible patients randomised, protocol fidelity, retention and missing data. Primary clinical outcome is days alive and out of hospital up to day-30. Secondary outcomes will include safety and other clinical outcomes, and process and cost measures. Specific aspects of safety related to vasopressor infusions such as extravasation, leakage, device failure, tissue injury and infection will be assessed. Discussion VIPCA is a feasibility RCT whose outcomes will inform the feasibility and design of a multicentre Phase-3 trial comparing routes of vasopressor delivery. The exploratory economic analysis will provide input data for the full health economic analysis which will accompany any future Phase-3 RCT.
Objective: To examine the incidence rate and risk of non-fatal irAEs, including gynecological, hematological, dermatological, ophthalmological, otologic, and dental problems following the COVID-19 vaccination. Methods: We conducted a population-based cohort study from the National Health Insurance Service (NHIS) database in Seoul, South Korea. The non-fatal irAEs included gynecological, hematological, dermatological, ophthalmological, ear, and periodontal problems as reported by the Vaccine Adverse Event Reporting Center. The cumulative incidence rate per 10,000 population, Odds ratio, and Hazard ratio (HR) with 95% Confidence Interval (CI) were measured to assess the non-fatal irAEs after COVID-19 vaccination. Results: The cIR of non-fatal irAEs for three months was significantly higher in vaccinated subjects than in non-vaccinated subjects, except for endometriosis. The vaccination significantly increased the risks of all the non-fatal irAEs except for visual impairment. The risk of inner ear disease showed the highest HRs (HR [95% CI] = 2.368 [2.153-2.604]) among the non-fatal irAEs following COVID-19 vaccination. Among the vaccinated subjects, heterologous vaccination was associated with the increased risk of most of the non-fatal irAEs. Conclusions: The three-month risks of incidental non-fatal irAEs are substantially higher in the COVID-19 vaccinated subjects than in non-vaccinated controls. Our findings suggested that vaccinated subjects with predisposition are potentially vulnerable to the occurrence of diverse irAEs although the COVID-19 vaccines may not be fatal.
Adverse hematologic events have been reported after COVID-19 vaccination. The objective of this study was to investigate whether hematologic abnormalities develop after COVID-19 vaccination. Retrospective cohort analyses of data from the Korean National Health Insurance Service (KNHIS) database were conducted from July 2022 to August 2023. We randomly selected data of half of those living in Seoul City as of January 1, 2021 with their diagnostic records up to December 31, 2021. The included participants were vaccinated and nonvaccinated persons aged 20 years or older (n= 4,203,887). Hematologic abnormalities after COVID-19 vaccination were identified as nutritional anemia, hemolytic anemia, aplastic anemia, coagulation defects, and neutropenia using International Classification of Diseases, Tenth Revision codes after index date. Incidence rates of hematologic abnormalities in the vaccination group 3 months after vaccination were significantly higher than those in the nonvaccinated group: 14.79 vs. 9.59 (P<.001) for nutritional anemia, 7.83 vs. 5.00 (P<.001) for aplastic anemia, and 4.85 vs. 1.85 (P<.001) for coagulation defects. COVID-19 mRNA vaccine was associated with higher development of nutritional anemia (odds ratio [OR], 1.230 [95% CI, 1.129-1.339], P<.001) and aplastic anemia (OR, 1.242 [95% CI, 1.110-1.390], P<.001) than the viral vector vaccine. The risk of coagulation defects was increased (OR, 1.986 [95% CI, 1.523-2.589], P<.001) after vaccination, and there was no risk difference between mRNA vaccine and viral vector vaccine (OR, 1.075 [95% CI, 0.936-1.233], P=.306). In conclusions, COVID-19 vaccination increased the risk of hematologic abnormalities. When administering the COVID-19 vaccine, careful observation will be necessary after vaccination.
Objectives. We evaluated Nanopore sequencing for influenza surveillance. Methods. Influenza A and B PCR-positive samples from hospital patients in Oxfordshire, UK, and a UK-wide population survey from winter 2022-23 underwent Nanopore sequencing following targeted rt-PCR amplification. Results. From 941 infections, successful sequencing was achieved in 292/388(75%) available Oxfordshire samples: 231(79%) A/H3N2, 53(18%) A/H1N1, and 8(3%) B/Victoria and in 53/113(47%) UK-wide samples. Sequencing was more successful at lower Ct values. Most same-sample replicate sequences had identical haemagglutinin segments (124/141;88%); a subset of samples also Illumina sequenced were very similar to Nanopore sequences. Comparison of Oxfordshire and UK-wide sequences showed frequent inter-regional transmission. Infections were closely-related to 2022-23 vaccine strains. Only one sample had a neuraminidase inhibitor resistance mutation. 849/941(90%) Oxfordshire infections were community-acquired. 63/88(72%) potentially healthcare-associated cases shared a hospital ward with [≥]1 known infectious case. 33 epidemiologically-plausible transmission links had sequencing data for both source and recipient: 8 were within [≤]5 SNPs, of these, 5(63%) involved potential sources that were also hospital-acquired. Conclusions. Nanopore influenza sequencing was reproducible and antiviral resistance rare. Inter-regional transmission was common; most infections were genomically similar. Hospital-acquired infections are likely an important source of nosocomial transmission and should be prioritised for infection prevention and control.
Objective To evaluate Phenotype Execution and Modelling Architecture (PhEMA), to express sharable phenotypes using Clinical Query Language (CQL) and intensional SNOMED CT Fast Healthcare Interoperability Resources (FHIR) valuesets, for exemplar chronic disease, sociodemographic risk factor and surveillance phenotypes. Method We curated three phenotypes: Type 2 diabetes (T2DM), excessive alcohol use and incident influenza-like illness (ILI) using CQL to define clinical and administrative logic. We defined our phenotypes with valuesets, using SNOMED's hierarchy and expression constraint language (ECL), and CQL, combining valuesets and adding temporal elements where needed. We compared the count of cases found using PhEMA with our existing approach using convenience datasets. Results The T2DM phenotype could be defined as two intensionally defined SNOMED valuesets and a CQL script. It increased the prevalence from 7.2% to 7.3%. Excess alcohol phenotype was defined by valuesets that added qualitative clinical terms to the quantitative conceptual definitions we currently use; this change increased prevalence by 58%, from 1.2% to 1.9%. We created an ILI valueset with SNOMED concepts, adding a temporal element using CQL to differentiate new episodes. This increased the weekly incidence in our convenience sample (weeks 26 to 38) from 0.95 cases to 1.11 cases per 100,000 people. Conclusions Phenotypes for surveillance and research can be described fully and comprehensibly using CQL and intensional FHIR valuesets. Our use case phenotypes identified a greater number of cases, whilst anticipated from excessive alcohol this was not for our other variable. This may have been due to our use of SNOMED CT hierarchy.
We tested the performance of Chat Generative Pre-trained Transformer (ChatGPT) in the role of a trainee clinician (Specialist Registrar or Resident) undergoing direct assessment by a human supervising specialist clinician (Consultant or Attending). The session consisted of a hospital ward round scenario presented to three versions of ChatGPT, namely OpenAI ChatGPT-3.5, Bing ChatGPT-4 and OpenAI ChatGPT-4. A specific test of memory and context was included via an end-of-teaching educator feedback exercise. Only OpenAI ChatGPT-4 provided responses comparable to the standard a trainee might offer during progress towards completion of training and specialist accreditation. Bing ChatGPT-4 responded with several clinically dubious statements, often in a repetitive and detached way, and was unable to retain awareness of the purpose of the session and the identities of participants.
Background Multimorbidity, defined as two or more chronic conditions in an individual, is increasing in prevalence and is associated with polypharmacy. Polypharmacy can lead to increased out-of-pocket payments for prescription medicines. This, in turn, can be associated with cost-related non-adherence and impoverishment. Healthcare in Denmark is mostly free at the point-of-use; prescription medicines are one of the only exceptions. Objective To examine the association between multimorbidity and annual out-of-pocket prescription medicine expenditure for adults in Denmark. Methods A population-based register study was conducted. The study population included all adults residing in Denmark in 2020. Frequencies and descriptive statistics were used and regression analyses were conducted to assess the association between multimorbidity and annual out-of-pocket prescription medicine expenditure, while controlling for demographic and socioeconomic covariates. Results Overall, 1,212,033 (24.2%) individuals had multimorbidity. Individuals with five or more conditions spent, on average, 320 euro in out-of-pocket prescription medicines expenditure compared to 187 euro for those with two conditions and 44 euro for those with no conditions. Amongst those with any out-of-pocket prescription medicine expenditure, having multimorbidity was associated with 2-4 times greater out-of-pocket prescription medicine expenditure than those with zero conditions. Amongst those in the quantile with the highest expenditure, those with five or more conditions spent 408 euro more than those with no conditions, and those with two conditions spent 185 euro more than those with no conditions. Conclusions For adults in Denmark, multimorbidity was associated with significantly higher out-of-pocket prescription medicine expenditure, even after controlling for demographic and socioeconomic covariates. This is similar to patterns in other countries and likely affects those with lowest income the most, given the known socioeconomic patterning of multimorbidity and raises concerns about cost related non-adherence. Potential protective mechanisms could include subsidies for certain vulnerable patient groups (e.g. those with severe mental illness) and low-income groups.
Background: Sleep apnea (SA) has been linked to an increased risk of dementia in numerous observational studies; whether this is driven by neurodegenerative, vascular or other mechanisms is not clear. We sought to examine the bidirectional causal relationships between SA, Alzheimer's disease (AD), coronary artery disease (CAD), and ischemic stroke using Mendelian randomization (MR). Methods: Using summary statistics from four recent, large genome-wide association studies of SA (n=523,366), AD (n=64,437), CAD (n=1,165,690), and stroke (n=1,308,460), we conducted bidirectional two-sample MR analyses. Our primary analytic method was fixed-effects inverse variance weighted MR; diagnostics tests and sensitivity analyses were conducted to verify the robustness of the results. Results: We identified a significant causal effect of SA on the risk of CAD (odds ratio (ORIVW) =1.35 per log-odds increase in SA liability, 95% confidence interval (CI) =1.25-1.47) and stroke (ORIVW=1.13, 95% CI =1.01-1.25). These associations were somewhat attenuated after excluding single-nucleotide polymorphisms associated with body mass index (BMI) (ORIVW=1.26, 95% CI =1.15-1.39 for CAD risk; ORIVW=1.08, 95% CI =0.96-1.22 for stroke risk). SA was not causally associated with a higher risk of AD (ORIVW=1.14, 95% CI =0.91-1.43). We did not find causal effects of AD, CAD, or stroke on risk of SA. Conclusions: These results suggest that SA increased the risk of CAD, and the identified causal association with stroke risk may be confounded by BMI. Moreover, no causal effect of SA on AD risk was found. Future studies are warranted to investigate cardiovascular pathways between sleep disorders, including SA, and dementia.
Epigenetic clocks, an estimate of biological age based on DNA methylation (DNAmAge) are gaining prominence as potential markers of brain ageing. However, consensus is lacking as the repertoire of DNAmAges expands, particularly concerning their ability to predict age-related cognitive changes. In our cohort of 785 elderly, we examined 11 DNAmAges, evaluating their associations with brain ageing in cross-sectional and longitudinal settings. Our results highlighted DNAmAges as strong predictors of cognitive change compared to baseline cognition, albeit varying performance across cognitive domains. DunedinPACE excelled in predicting baseline cognition, while Zhang's clocks and principal component-based PhenoAge (PCPheno) performed best in predicting cognitive decline. DNAmAges elucidated substantial cognitive variability, matching or surpassing the predictive power of vascular risk factors and ApoE4 genotypes. Notably, in ApoE4 carriers, Zhang's clock and PCPheno exhibited significantly larger effects, explaining over five times the variability in memory decline compared to non-carriers.
Importance: Evidence regarding audiovestibular adverse events post COVID-19 vaccination to date has been inconclusive regarding a potential etiological association. This study used a multi-data source approach to assess incidence of these events following COVID-19 vaccination. Objective: To determine if there was an increase in audiovestibular adverse events following COVID-19 vaccination in South-eastern Australia during January 2021-March 2023. Design: Retrospective observational analysis of spontaneous reports of audiovestibular events to a statewide vaccine safety surveillance service, SAEFVIC, as well as accompanying self-controlled case series (SCCS) analysis using general practice data collected via the POpulation Level Analysis and Reporting (POLAR) tool with permission from Primary Health Networks (PHNs) as the de-identified dataset owners in Victoria and New South Wales. Setting: Victoria and New South Wales (NSW), Australia. Participants: Victorians who spontaneously reported an audiovestibular-related symptom or diagnosis to SAEFVIC, and people in Victoria and NSW who presented to a POLAR GP registered practice with a new audiovestibular diagnosis. Exposures: COVID-19 vaccination with adenovirus vector, mRNA or protein-subunit vaccine. Outcomes and Measures: In SAEFVIC, audiovestibular events of interest were ascertained through searching key words in the vaccine safety database. Reporting rates were calculated and compared per 100,000 COVID-19 vaccine doses administered and recorded in the Australian Immunisation Register (AIR). Audiovestibular presentations of interest were isolated from the general practice dataset aggregated by POLAR, by searching for relevant SNOMED CT codes. Similarly, relative incidence (RI) was calculated for all COVID-19 vaccine types. Results: This study demonstrates an increase in general practice presentations of vertigo following mRNA vaccines (RI= 1.40 P <.001), and tinnitus following both the adenovirus vector and mRNA vaccines (RI= 2.25 ,P <.001 and 1.53 ,P <.001 respectively). There was no increase in hearing loss following any COVID-19 vaccinations. Conclusions and Relevance: This is the first study that demonstrates an increase in audiovestibular presentations following COVID-19 vaccination, in particular, vertigo and tinnitus.Healthcare providers and vaccinees should be alert to potential audiovestibular complaints after COVID-19 vaccination. Our analysis highlights the importance of using large real-world datasets to gather reliable evidence for public health decision making.