abscessus causing native aortic valve endocarditis post stenting.

Native valve endocarditis owing to is extremely rare and only a few cases have been reported in the literature. We present a case of a 44-year old male patient, a coronary artery disease (CAD) case with a stent in situ with pyrexia of unknown origin (PUO). He started becoming febrile following placement of stent and continued to remain febrile for duration of five months before coming to our centre.

Bridging the gap: building and sustaining recovery capital in the transition from prison to recovery residences.

The transition from jail to community is a high-risk time for individuals experiencing substance use disorders (SUD), with elevated risks of overdose and other substance-related harms, as well as high recidivism rates and re-incarceration. Gains made from successful treatment in prison are often lost in this transition. The current paper evaluates this process for one justice programme, Chesterfield HARP, a Therapeutic Community based in the Chesterfield County jail that continues supporting former inmates through their release by examining engagement and retention rates and changes in recovery capital among incarcerated individuals before incarceration and after transition to recovery housing in the community.

A self-efficacy enhancement alcohol reduction intervention for men on-remand in prison: the APPRAISE feasibility pilot RCT.

Background: As many as 70% of remand prisoners have admitted to being under the influence of alcohol when committing the crime leading to their imprisonment. Providing support and advice regarding alcohol consumption can be effective in some groups of people. There is little evidence regarding this for men on remand in prison.

Modeling Recovery Housing Retention and Program Outcomes by Justice Involvement among Residents in Virginia, USA: An Observational Study.

Living in recovery housing can improve addiction recovery and desistance outcomes. This study examined whether retention in recovery housing and types of discharge outcomes (completed, "neutral," and "negative" outcomes) differed for clients with recent criminal legal system (CLS) involvement. Using data from 101 recovery residences certified by the Virginia Association of Recovery Residences based on 1,978 individuals completing the REC-CAP assessment, competing risk analyses (cumulative incidence function, restricted mean survival time, and restricted mean time lost) followed by the marginalization of effects were implemented to examine program outcomes at final discharge.

Broadening Eligibility Criteria and Diversity among Patients for Cancer Clinical Trials.

Background: Certain populations have been historically underrepresented in clinical trials. Broadening eligibility criteria is one approach to inclusive clinical research and achieving enrollment goals. How broadened trial eligibility criteria affect the diversity of eligible participants is unknown.

Perinatal exposure to PFOS and sustained high-fat diet promote neurodevelopmental disorders via genomic reprogramming of pathways associated with neuromotor development.

Perfluorooctanesulfonic acid (PFOS) is a neurotoxic widespread organic contaminant which affects several brain functions including memory, motor coordination and social activity. PFOS has the ability to traverse the placenta and the blood brain barrier (BBB) and cause weight gain in female mice. It's also known that obesity and consumption of a high fat diet have negative effects on the brain, impairs cognition and increases the risk for the development of dementia.

Kinase-impaired BTK mutations are susceptible to clinical-stage BTK and IKZF1/3 degrader NX-2127.

Increasing use of covalent and noncovalent inhibitors of Bruton's tyrosine kinase (BTK) has elucidated a series of acquired drug-resistant BTK mutations in patients with B cell malignancies. Here we identify inhibitor resistance mutations in BTK with distinct enzymatic activities, including some that impair BTK enzymatic activity while imparting novel protein-protein interactions that sustain B cell receptor (BCR) signaling. Furthermore, we describe a clinical-stage BTK and IKZF1/3 degrader, NX-2127, that can bind and proteasomally degrade each mutant BTK proteoform, resulting in potent blockade of BCR signaling.

Assessing a pilot scheme of intensive support and assertive linkage in levels of engagement, retention, and recovery capital for people in recovery housing using quasi-experimental methods.

Introduction: Strong and ever-growing evidence highlights the effectiveness of recovery housing in supporting and sustaining substance use disorder (SUD) recovery, especially when augmented by intensive support that includes assertive linkages to community services. This study aims to evaluate a pilot intensive recovery support (IRS) intervention for individuals (n = 175) entering certified Level II and III recovery residences. These individuals met at least three out of five conditions (no health insurance; no driving license; substance use in the last 14 days; current unemployment; possession of less than $75 capital).

A systematic approach towards missing lab data in electronic health records: A case study in non-small cell lung cancer and multiple myeloma.

Real-world data derived from electronic health records often exhibit high levels of missingness in variables, such as laboratory results, presenting a challenge for statistical analyses. We developed a systematic workflow for gathering evidence of different missingness mechanisms and performing subsequent statistical analyses. We quantify evidence for missing completely at random (MCAR) or missing at random (MAR), mechanisms using Hotelling's multivariate t-test, and random forest classifiers, respectively.

Postprediction Inference for Clinical Characteristics Extracted With Machine Learning on Electronic Health Records.

Purpose: Real-world data (RWD) derived from electronic health records (EHRs) are often used to understand population-level relationships between patient characteristics and cancer outcomes. Machine learning (ML) methods enable researchers to extract characteristics from unstructured clinical notes, and represent a more cost-effective and scalable approach than manual expert abstraction. These extracted data are then used in epidemiologic or statistical models as if they were abstracted observations.

Replication of Real-World Evidence in Oncology Using Electronic Health Record Data Extracted by Machine Learning.

Meaningful real-world evidence (RWE) generation requires unstructured data found in electronic health records (EHRs) which are often missing from administrative claims; however, obtaining relevant data from unstructured EHR sources is resource-intensive. In response, researchers are using natural language processing (NLP) with machine learning (ML) techniques (i.e.

Targeted Therapy Development in Acute Myeloid Leukemia.

Therapeutic developments targeting acute myeloid leukemia (AML) have been in the pipeline for five decades and have recently resulted in the approval of multiple targeted therapies. However, there remains an unmet need for molecular treatments that can deliver long-term remissions and cure for this heterogeneous disease. Previously, a wide range of small molecule drugs were developed to target sub-types of AML, mainly in the relapsed and refractory setting; however, drug resistance has derailed the long-term efficacy of these as monotherapies.

EUS-Guided hepaticogastrostomy in a pregnant patient with Roux-en-Y hepaticojejunostomy anatomy.

Video 1EUS-Guided hepaticogastrostomy in a pregnant patient with Roux-en-Y hepaticojejunostomy anatomy.

The growth of recovery capital in clients of recovery residences in Florida, USA: a quantitative pilot study of changes in REC-CAP profile scores.

Background: There is a growing evidence base around predictors of retention and completion in a range of recovery residence models, particularly Oxford Houses and Sober Living Houses, and recovery housing is recognized as a clearly evidenced area of recovery intervention. The aim of the study was to quantitatively assess recovery capital in a sample of recovery residence clients.

Method: The study used a repeated measures self-completion of a standardized recovery capital instrument (REC-CAP) for clients retained across various houses within one Level 2 recovery residence provider whose program was based on a 12-step approach.

Estimating survival parameters under conditionally independent left truncation.

Databases derived from electronic health records (EHRs) are commonly subject to left truncation, a type of selection bias that occurs when patients need to survive long enough to satisfy certain entry criteria. Standard methods to adjust for left truncation bias rely on an assumption of marginal independence between entry and survival times, which may not always be satisfied in practice. In this work, we examine how a weaker assumption of conditional independence can result in unbiased estimation of common statistical parameters.

Selective prediction-set models with coverage rate guarantees.

The current approach to using machine learning (ML) algorithms in healthcare is to either require clinician oversight for every use case or use their predictions without any human oversight. We explore a middle ground that lets ML algorithms abstain from making a prediction to simultaneously improve their reliability and reduce the burden placed on human experts. To this end, we present a general penalized loss minimization framework for training selective prediction-set (SPS) models, which choose to either output a prediction set or abstain.

Bayesian additional evidence for decision making under small sample uncertainty.

Background: Statistical inference based on small datasets, commonly found in precision oncology, is subject to low power and high uncertainty. In these settings, drawing strong conclusions about future research utility is difficult when using standard inferential measures. It is therefore important to better quantify the uncertainty associated with both significant and non-significant results based on small sample sizes.

A Small Area Estimation Method for Investigating the Relationship between Public Perception of Drug Problems with Neighborhood Prognostics: Trends in London between 2012 and 2019.

The correlation of the public's perception of drug problems with neighborhood characteristics has rarely been studied. The aim of this study was to investigate factors that correlate with public perceptions in London boroughs using the Mayor's Office for Policing and Crime (MOPAC) Public Attitude Survey between 2012 and 2019. A subject-specific random effect deploying a Generalized Linear Mixed Model (GLMM) using an Adaptive Gaussian Quadrature method with 10 integration points was applied.

Multimodal Mapping of the Tumor and Peripheral Blood Immune Landscape in Human Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDA) is characterized by an immune-suppressive tumor microenvironment that renders it largely refractory to immunotherapy. We implemented a multimodal analysis approach to elucidate the immune landscape in PDA. Using a combination of CyTOF, single-cell RNA sequencing, and multiplex immunohistochemistry on patient tumors, matched blood, and non-malignant samples, we uncovered a complex network of immune-suppressive cellular interactions.

Maximizing success in single-session EUS-directed transgastric ERCP: a retrospective cohort study to identify predictive factors of stent migration.

Background And Aims: EUS-directed transgastric ERCP (the EDGE procedure) is a simplified method of performing ERCP in Roux-en-Y gastric bypass patients. The EDGE procedure involves placement of a lumen-apposing metal stent (LAMS) into the excluded stomach to serve as a conduit for passage of the duodenoscope for pancreatobiliary intervention. Originally a multistep process, urgent indications for ERCP have led to the development of single-session EDGE (SS-EDGE) with LAMS placement and ERCP performed in the same session.