Beta blockers are associated with lower all-cause mortality among HFpEF patients.

BACKGROUND: The evidence regarding beta blocker (BB) benefit in heart failure with preserved ejection fraction (HFpEF) remains inconclusive, leading to consideration of BB withdrawal in this population. OBJECTIVES: In this study, we retrospectively analyzed the association of BB on all-cause mortality in HFpEF patients. METHODS: This is a single-center retrospective cohort study of 20,206 patients with left ventricular ejection fraction (EF) ≥ 50% who were hospitalized with decompensated HF between January 2011 and March 2020. Survival is reported at 30 days, 1 year, and 3 years. A secondary analysis comparing mortality for patients on BB with additional indications including hypertension (HTN), coronary artery disease (CAD), and atrial fibrillation (AF) was completed. Mortality was compared between patients on BB and additional therapies of spironolactone or angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (ACEi/ARBs). RESULTS: BB showed lower all-cause mortality at 30 days, 1 year, and 3 years (p < 0.0001). This association with lower all-cause mortality was validated by a supplementary propensity score-matched analysis. At 3 years, there was significant mortality reduction with addition of BB to either spironolactone (p = 0.0359) or ACEi/ARBs (p < 0.0001). CONCLUSION: In a large single-center retrospective registry, BB use was associated with lower mortality in HFpEF patients with a recent decompensated HF hospitalization. The mortality benefit persisted in those treated with spironolactone or ACEi/ARBs, and in those with AF. This provocative data further highlights the uncertainty of the benefit of BB use in this cohort and calls for re-consideration of BB withdrawal, especially in those tolerating it well, without conclusive, large, and randomized trials showing lack of benefit or harm.

Citizen science mitigates the lack of distributional data on Nigerian birds.

Citizen science projects are expanding globally, with the African continent, particularly Nigeria, registering significant growth. Here, we document and analyse novel operations of the Nigerian Bird Atlas Project (NIBAP), 2015-2022. This project has employed the use of ornithologists, mainly trained at the A. P. Leventis Ornithological Research Institute (APLORI) located in Jos, Nigeria, and its 28 bird clubs established across Nigeria to enlist 827 bird enthusiasts that contribute regular and near real-time data about bird distribution and relative abundance in the country. Interestingly, NiBAP has recorded about 75% of the bird species known from Nigeria in only about 50% of Nigeria's total surface area, including 39 nationally threatened species. The Common Bulbul Pycnonotus barbatus, Laughing Dove Spilopelia senegalensis, and Grey-backed Camaroptera Camaroptera brevicaudata were the most commonly recorded species, while Amurum Forest Reserve, Rennajj Fish Farm, and Obudu Cattle Ranch were the most surveyed sites during the period. Thus, our approach reveals how to increase involvement of nature enthusiasts, ornithologists, and a regional research institute to build local capacity and contribute rich information necessary to alleviate the lack of distributional data about Afrotropical avifauna. We strongly recommend our approach to boost other citizen science projects across Africa and beyond to address the huge lack of biodiversity data, create public awareness, and foster conservation education.

Canopy2: tumor phylogeny inference by bulk DNA and single-cell RNA sequencing.

Tumors are comprised of a mixture of distinct cell populations that differ in terms of genetic makeup and function. Such heterogeneity plays a role in the development of drug resistance and the ineffectiveness of targeted cancer therapies. Insight into this complexity can be obtained through the construction of a phylogenetic tree, which illustrates the evolutionary lineage of tumor cells as they acquire mutations over time. We propose Canopy2, a Bayesian framework that uses single nucleotide variants derived from bulk DNA and single-cell RNA sequencing to infer tumor phylogeny and conduct mutational profiling of tumor subpopulations. Canopy2 uses Markov chain Monte Carlo methods to sample from a joint probability distribution involving a mixture of binomial and beta-binomial distributions, specifically chosen to account for the sparsity and stochasticity of the single-cell data. Canopy2 demystifies the sources of zeros in the single-cell data and separates zeros categorized as non-cancerous (cells without mutations), stochastic (mutations not expressed due to bursting), and technical (expressed mutations not picked up by sequencing). Simulations demonstrate that Canopy2 consistently outperforms competing methods and reconstructs the clonal tree with high fidelity, even in situations involving low sequencing depth, poor single-cell yield, and highly-advanced and polyclonal tumors. We further assess the performance of Canopy2 through application to breast cancer and glioblastoma data, benchmarking against existing methods. Canopy2 is an open-source R package available at https://github.com/annweideman/canopy2.

Bayesian design of clinical trials using the scale transformed power prior.

There are many Bayesian design methods allowing for the incorporation of historical data for sample size determination (SSD) in situations where the outcome in the historical data is the same as the outcome of a new study. However, there is a dearth of methods supporting the incorporation of data from a previously completed clinical trial that investigated the same or similar treatment as the new trial but had a primary outcome that is different. We propose a simulation-based Bayesian SSD framework using the partial-borrowing scale transformed power prior (straPP). The partial-borrowing straPP is developed by applying a novel scale transformation to a traditional power prior on the parameters from the historical data model to make the information better align with the new data model. The scale transformation is based on the assumption that the standardized parameters (i.e., parameters multiplied by the square roots of their respective Fisher information matrices) are equal. To illustrate the method, we present results from simulation studies that use real data from a previously completed clinical trial to design a new clinical trial with a primary time-to-event endpoint.

Bayesian joint modeling of multivariate longitudinal and survival outcomes using Gaussian copulas.

There is an increasing interest in the use of joint models for the analysis of longitudinal and survival data. While random effects models have been extensively studied, these models can be hard to implement and the fixed effect regression parameters must be interpreted conditional on the random effects. Copulas provide a useful alternative framework for joint modeling. One advantage of using copulas is that practitioners can directly specify marginal models for the outcomes of interest. We develop a joint model using a Gaussian copula to characterize the association between multivariate longitudinal and survival outcomes. Rather than using an unstructured correlation matrix in the copula model to characterize dependence structure as is common, we propose a novel decomposition that allows practitioners to impose structure (e.g., auto-regressive) which provides efficiency gains in small to moderate sample sizes and reduces computational complexity. We develop a Markov chain Monte Carlo model fitting procedure for estimation. We illustrate the method's value using a simulation study and present a real data analysis of longitudinal quality of life and disease-free survival data from an International Breast Cancer Study Group trial.

Clinical Outcomes Associated With Diltiazem Use in Heart Failure With Reduced Ejection Fraction After Implementation of a Clinical Support System.

BACKGROUND: Despite atrial fibrillation guideline recommendations, many patients with heart failure with reduced ejection fraction (EF) continue to receive IV diltiazem for acute rate control. OBJECTIVE: Our institution recently implemented a clinical decision support system (CDSS)-based tool that recommends against the use of diltiazem in patients with an EF ≤ 40%. The objective of this study was to evaluate outcomes of adherence to the aforementioned CDSS-based tool. METHODS: This multi-hospital, retrospective study assessed patients who triggered the CDSS alert and compared those who did and did not discontinue diltiazem. The primary outcome was the occurrence of clinical deterioration. The primary endpoint was compared utilizing a Fisher's Exact Test, and a multivariate logistic regression model was developed to confirm the results of the primary analysis. RESULTS: A total of 246 patients were included in this study with 146 patients in the nonadherent group (received diltiazem) and 100 patients in the adherent group (did not receive diltiazem). There was a higher proportion of patients experiencing clinical deterioration in the alert nonadherence group (33% vs 21%, P = 0.044), including increased utilization of inotropes and vasopressors, and higher rate of transfer to ICU. CONCLUSION AND RELEVANCE: In patients with heart failure with reduced EF, diltiazem use after nonadherence to a CDSS alert resulted in an increased risk of clinical deterioration. This study highlights the need for improved provider adherence to diltiazem clinical decision support systems.

Efficient computation of high-dimensional penalized generalized linear mixed models by latent factor modeling of the random effects.

Modern biomedical datasets are increasingly high-dimensional and exhibit complex correlation structures. Generalized linear mixed models (GLMMs) have long been employed to account for such dependencies. However, proper specification of the fixed and random effects in GLMMs is increasingly difficult in high dimensions, and computational complexity grows with increasing dimension of the random effects. We present a novel reformulation of the GLMM using a factor model decomposition of the random effects, enabling scalable computation of GLMMs in high dimensions by reducing the latent space from a large number of random effects to a smaller set of latent factors. We also extend our prior work to estimate model parameters using a modified Monte Carlo Expectation Conditional Minimization algorithm, allowing us to perform variable selection on both the fixed and random effects simultaneously. We show through simulation that through this factor model decomposition, our method can fit high-dimensional penalized GLMMs faster than comparable methods and more easily scale to larger dimensions not previously seen in existing approaches.

Safety signal detection with control of latent factors.

Postmarket drug safety database like vaccine adverse event reporting system (VAERS) collect thousands of spontaneous reports annually, with each report recording occurrences of any adverse events (AEs) and use of vaccines. We hope to identify signal vaccine-AE pairs, for which certain vaccines are statistically associated with certain adverse events (AE), using such data. Thus, the outcomes of interest are multiple AEs, which are binary outcomes and could be correlated because they might share certain latent factors; and the primary covariates are vaccines. Appropriately accounting for the complex correlation among AEs could improve the sensitivity and specificity of identifying signal vaccine-AE pairs. We propose a two-step approach in which we first estimate the shared latent factors among AEs using a working multivariate logistic regression model, and then use univariate logistic regression model to examine the vaccine-AE associations after controlling for the latent factors. Our simulation studies show that this approach outperforms current approaches in terms of sensitivity and specificity. We apply our approach in analyzing VAERS data and report our findings.

Balloon Rises Above: REBOA at Zone 1 May Be Superior to Resuscitative Thoracotomy.

BACKGROUND: The use of Zone 1 REBOA for life-threatening trauma has increased dramatically. STUDY DESIGN: The Aortic Occlusion for Resuscitation in Trauma and Acute Care Surgery database was queried for blunt and penetrating trauma between 2013 and 2021. Outcomes were examined both for mechanisms of injury combined and separately and for combinations of abdominal injury with and without traumatic brain injury and chest injuries (Abbreviated Injury Scale [AIS] score >2). RESULTS: A total of 531 patients underwent REBOA (408 with blunt injury and 123 with penetrating injury) and 1,603 (595 with blunt injury and 1,008 with penetrating injury) underwent resuscitative thoracotomy (RT). Mean age was 38.5 ± 16 years and mean injury severity score was 34.5 ± 21; 57.7% had chest AIS score of more than 2, 21.8% had head AIS score of more than 2, and 37.3% had abdominal AIS score of more than 2. Admission Glasgow Coma Scale was 4.9 + 4, and systolic blood pressure at aortic occlusion (AO) was 22 + 40 mmHg. No differences in outcomes in REBOA or RT patients were identified between institutions (p > 0.5). After inverse probability weighting, Glasgow Coma Scale, age, injury severity score, systolic blood pressure at AO, CPR at AO, and blood product transfusion, REBOA was superior to RT in both blunt (odds ratio [OR] 4.7, 95% CI 1.9 to 11.7) and penetrating (OR 4.9, 95% CI 1.7 to 14) injuries, across all spectrums of injury (p < 0.01). Overall mortality was significantly higher for AO more than 90 minutes compared with less than 30 minutes in blunt (OR 4.6, 95% CI 1.5 to 15) and penetrating (OR 5.4, 95% CI 1.1 to 25) injuries. Duration of AO more than 60 minutes was significantly associated with mortality after penetrating abdominal injury (OR 5.1, 95% CI 1.1 to 22) and abdomen and head (OR 5.3, 95% CI 1.6 to 18). CONCLUSIONS: In-hospital survival is higher for patients undergoing REBOA than RT for all injury patterns. Complete AO by REBOA or RT should be limited to less than 30 minutes. Neither hospital and procedure volume nor trauma verification level impacts outcomes for REBOA or RT.

Evaluating Clinical Outcomes of Laparoscopic Subtotal and Total Cholecystectomy for Complicated Acute Cholecystitis: A Systematic Review and Meta-Analysis.

INTRODUCTION: This systematic review and meta-analysis aimed to compare clinical outcomes in patients with complicated acute cholecystitis undergoing laparoscopic total vs subtotal cholecystectomy. METHODS: This systematic review and meta-analysis was conducted according to PRISMA guidelines and queried PubMed, Embase, ProQuest, Google Scholar, and Cochrane databases from inception to May 2023. The primary outcome was complication rates including common bile duct injury, wound infection, reoperation, bile leak, retained stones, and subhepatic collection, whereas secondary outcomes were in-hospital mortality and hospital length of stay. RESULTS: A total of 7 studies with 135,233 cases were included for meta-analysis. Patients who underwent laparoscopic total cholecystectomy had a significantly lower risk of postoperative bile leaks (RR: .15; 95% CI: .03, .80) and subhepatic fluid collection (RR: 0.19; 95% CI: .06, .63) and were 2.94 times less likely to die compared to those who underwent subtotal cholecystectomy (RR .34; 95% CI: .15, .77). Patients who underwent subtotal cholecystectomy had significantly longer hospital length of stay (mean difference 1.0 days; 95% CI: .5 days, 1.4 days). CONCLUSIONS: In adult patients presenting with complicated cholecystitis, management with laparoscopic subtotal cholecystectomy presents a unique complication profile with increased risk of postoperative bile leak and subhepatic fluid collection, in-hospital mortality, and longer hospital length-of-stay when used as an alternative approach to laparoscopic total cholecystectomy. Further research into the most appropriate clinical scenarios and patient populations for the use of the subtotal cholecystectomy approach may prove useful in improving its associated outcomes.

A scoping review of models of care for the management of older trauma patients.

INTRODUCTION: The number of older people hospitalised with major trauma is rapidly increasing. New models of care have emerged, such as co-management, and trauma centres dedicated to delivering geriatric trauma care. The aim of this scoping review was to explore in-hospital models of care for older adults who experience physical trauma. PATIENTS AND METHODS: The search was conducted in accordance with the PRISMA- SC (preferred reporting items for systematic reviews and meta-analyses extension for scoping reviews) reporting guidelines. The National Heart Lung, and Blood Institute (NIH) study quality assessment tool was used to evaluate risk of bias in before and after non-randomised experimental studies. RESULTS: Of 2127 records returned from the database search, 43 papers were included. We identified five types of care models investigated in the reviewed studies: centralised trauma management, consultation services, co-management, patient care protocols, and alert and triage systems. The majority of patients were admitted under a specialised trauma service, intervention teams were for the most part multidisciplinary, and follow-up of patients post-discharge was seldom reported. Consultation services more often had advanced care and discharge planning as treatment objectives. In contrast, patient care protocol and alert systems commonly had management of anticoagulation as a treatment objective. Overall, the impact of the five models of care on patient outcomes was mixed. DISCUSSION: Given the variability in patient characteristics and capabilities of health services, models of care need to be matched to the local profile of older trauma patients. However, some standards should be incorporated into a care model, including identifying goals of care, medication review and follow up post-discharge.

Medicolegal pitfalls when assessing decision-making capacity in people with cognitive impairment.

BACKGROUND: The global population of older adults will double over the next three decades, and one in 10 will have dementia. OBJECTIVE: This article examines medicolegal pitfalls when assessing the decision-making capacity of cognitively impaired patients. DISCUSSION: Be aware of the pitfalls while completing the five steps of the assessment. Step 1, the request for a capacity assessment, alerts the clinician that this is more than an administrative form-filling task and that the consultation is not therapeutic. Step 2, initiation of the consultation, requires being prepared for a new diagnosis of dementia, explicitly obtaining consent and understanding the expectations of all involved. Step 3, the clinical assessment, requires avoiding assumptions about the patient and the law, completing tests of cognition, including executive function, and ensuring a detailed understanding of the matter requiring a decision. Step 4, the formulation of opinion and documentation, requires documenting and addressing the legal questions about function and impairment. Step 5, review and reflect assuming somebody will contest the opinion.

A population-based cross-sectional study examining homicides among community-dwelling older adults in Victoria, Australia: A study protocol.

BACKGROUND: There is a need for both descriptive and analytical evidence on the factors associated with older adult homicide. The current landscape is insufficient because most published research is confined to the United States, and contains insufficient data about the homicide context. This study protocol describes the proposed method for examining the characteristics and factors associated with older adult homicide in the Australian state of Victoria, using data generated for the criminal and coronial investigation into these deaths stored in the Victorian Homicide Register (VHR). Outcomes will support practitioners, policy makers and other key stakeholders to strengthen prevention strategies to reduce the risk of future homicides among older Victorians. METHODS: This study will comprise a single-jurisdiction population-based cross-sectional design to analyse consecutive cases of homicide among community-dwelling older adults in Victoria, Australia for the period 2001 to 2015. All homicides of adults aged 18 years and older, and where the Coroner's investigation is completed at data extraction will be included. Variables will be selected in accordance with elements of the social-ecological model (i.e., individual, interpersonal, incident, and community). This will include: socio-demographic characteristics; presence of mental or physical illness; deceased-offender relationship; nature of any abuse between the deceased and offender; incident location and weapon used; the presence of alcohol or drugs; and criminal justice outcomes. Homicide rates per 100,000 population will be calculated for older adults (aged 65 years and older) and younger adults (aged 18-64 years), and compared as rate ratios using Poisson regression. Descriptive statistics and cross-tabulation will be generated for factors associated with homicide for older compared to younger adults. Homicide typologies based on deceased-offender relationship and motive will be explored within group and family homicides will be compared between older and younger adults.

Bayesian bi-level variable selection for genome-wide survival study.

Mild cognitive impairment (MCI) is a clinical syndrome characterized by the onset and evolution of cognitive impairments, often considered a transitional stage to Alzheimer's disease (AD). The genetic traits of MCI patients who experience a rapid progression to AD can enhance early diagnosis capabilities and facilitate drug discovery for AD. While a genome-wide association study (GWAS) is a standard tool for identifying single nucleotide polymorphisms (SNPs) related to a disease, it fails to detect SNPs with small effect sizes due to stringent control for multiple testing. Additionally, the method does not consider the group structures of SNPs, such as genes or linkage disequilibrium blocks, which can provide valuable insights into the genetic architecture. To address the limitations, we propose a Bayesian bi-level variable selection method that detects SNPs associated with time of conversion from MCI to AD. Our approach integrates group inclusion indicators into an accelerated failure time model to identify important SNP groups. Additionally, we employ data augmentation techniques to impute censored time values using a predictive posterior. We adapt Dirichlet-Laplace shrinkage priors to incorporate the group structure for SNP-level variable selection. In the simulation study, our method outperformed other competing methods regarding variable selection. The analysis of Alzheimer's Disease Neuroimaging Initiative (ADNI) data revealed several genes directly or indirectly related to AD, whereas a classical GWAS did not identify any significant SNPs.

Bayesian joint models for multi-regional clinical trials.

In recent years, multi-regional clinical trials (MRCTs) have increased in popularity in the pharmaceutical industry due to their ability to accelerate the global drug development process. To address potential challenges with MRCTs, the International Council for Harmonisation released the E17 guidance document which suggests the use of statistical methods that utilize information borrowing across regions if regional sample sizes are small. We develop an approach that allows for information borrowing via Bayesian model averaging in the context of a joint analysis of survival and longitudinal data from MRCTs. In this novel application of joint models to MRCTs, we use Laplace's method to integrate over subject-specific random effects and to approximate posterior distributions for region-specific treatment effects on the time-to-event outcome. Through simulation studies, we demonstrate that the joint modeling approach can result in an increased rejection rate when testing the global treatment effect compared with methods that analyze survival data alone. We then apply the proposed approach to data from a cardiovascular outcomes MRCT.

A qualitative descriptive study exploring clinicians' perspectives of the management of older trauma care in rural Australia.

BACKGROUND: For older trauma patients who sustain trauma in rural areas, the risk of adverse outcomes associated with advancing age, is compounded by the challenges encountered in rural healthcare such as geographic isolation, lack of resources, and accessibility. Little is known of the experience and challenges faced by rural clinicians who manage trauma in older adults. An understanding of stakeholders' views is paramount to the effective development and implementation of a trauma system inclusive of rural communities. The aim of this descriptive qualitative study was to explore the perspectives of clinicians who provide care to older trauma patients in rural settings. METHOD: We conducted semi-structured interviews of health professionals (medical doctors, nurses, paramedics, and allied health professionals) who provide care to older trauma patients in rural Queensland, Australia. A thematic analysis consisting of both inductive and deductive coding approaches, was used to identify and develop themes from interviews. RESULTS: Fifteen participants took part in the interviews. Three key themes were identified: enablers of trauma care, barriers, and changes to improve trauma care of older people. The resilience of rural residents, and breadth of experience of rural clinicians were strengths identified by participants. The perceived systemic lack of resources, both material and in the workforce, and fragmentation of the health system across the state were barriers to the provision of trauma care to older rural patients. Some changes proposed by participants included tailored education programs that would be taught in rural centres, a dedicated case coordinator for older trauma patients from rural areas, and a centralised system designed to streamline the management of older trauma patients coming from rural regions. CONCLUSIONS: Rural clinicians are important stakeholders who should be included in discussions on adapting trauma guidelines to the rural setting. In this study, participants formulated pertinent and concrete recommendations that should be weighed against the current evidence, and tested in rural centres.

LESA: Longitudinal Elastic Shape Analysis of Brain Subcortical Structures.

Over the past 30 years, magnetic resonance imaging has become a ubiquitous tool for accurately visualizing the change and development of the brain's subcortical structures (e.g., hippocampus). Although subcortical structures act as information hubs of the nervous system, their quantification is still in its infancy due to many challenges in shape extraction, representation, and modeling. Here, we develop a simple and efficient framework of longitudinal elastic shape analysis (LESA) for subcortical structures. Integrating ideas from elastic shape analysis of static surfaces and statistical modeling of sparse longitudinal data, LESA provides a set of tools for systematically quantifying changes of longitudinal subcortical surface shapes from raw structure MRI data. The key novelties of LESA include: (i) it can efficiently represent complex subcortical structures using a small number of basis functions and (ii) it can accurately delineate the spatiotemporal shape changes of the human subcortical structures. We applied LESA to analyze three longitudinal neuroimaging data sets and showcase its wide applications in estimating continuous shape trajectories, building life-span growth patterns, and comparing shape differences among different groups. In particular, with the Alzheimer's Disease Neuroimaging Initiative (ADNI) data, we found that the Alzheimer's Disease (AD) can significantly speed the shape change of ventricle and hippocampus from 60 to 75 years old compared with normal aging.

The epidemiology of homicide among older adults: retrospective analysis using data from the Victorian Homicide Register.

Older adult homicide is unique and under-researched, requiring immediate attention due to the rapidly ageing population. The current study aims to contribute to the description of homicide at the individual, interpersonal, incident and community levels. This research comprised a whole of state jurisdiction population-based retrospective analysis of homicide deaths of older adults aged 65 years and older reported to the Coroner between 2001 and 2015. Descriptive statistical analyses were conducted to compare older adult homicides by sex and the deceased-offender relationship. There were 59 homicide incidents involving 23 female and 36 male deceased (median age=72 years) and 16 female and 41 male offenders (median age=41 years). Individual factors included the following: Deceased frequently had a recorded physical illness (66%), and over one-third were born overseas (37%) or had recent contact with general practitioners and human services (36%). Offenders frequently had a history of illicit drug or alcohol use (63%), diagnosed mental illness (63%) and historical exposure to violence (61%). Interpersonal factors included the following: The deceased-offender relationship tended to be intimate or familial (63%). Incidents factors included the following: incident predominantly occurred in the victim's home (73%), involving the use of a sharp object (36%), bodily force (31%) or blunt force (20%). The older adult homicide is characterised by poor health in the victim, mental illness, substance abuse or a history of conflict in the either the victim or the offender, familial deceased-offender relationship and the home as the incident location. The results identify future prevention opportunities in clinical and human services settings.