Reinforced Borrowing Framework: Leveraging Auxiliary Data for Individualized Inference.

Increasingly during the past decade, researchers have sought to leverage auxiliary data for enhancing individualized inference. Many existing methods, such as multisource exchangeability models (MEM), have been developed to borrow information from multiple supplemental sources to support parameter inference in a primary source. MEM and its alternatives decide how much information to borrow based on the exchangeability of the primary and supplemental sources, where exchangeability is defined as equality of the target parameter.

A proposed method for identifying Interfacility transfers in Medicare claims data.

Objective: To develop a method of consistently identifying interfacility transfers (IFTs) in Medicare Claims using patients with ST-Elevation Myocardial Infarction (STEMI) as an example.

Data Sources/study Setting: 100% Medicare inpatient and outpatient Standard Analytic Files and 5% Carrier Files, 2011-2020.

Study Design: Observational, cross-sectional comparison of patient characteristics between proposed and existing methods.

Symptom Descriptors in Individuals Living With Undiagnosed Lower Extremity Peripheral Artery Disease.

Objective: Most individuals with lower extremity peripheral artery disease (PAD) experience symptoms other than claudication and live with undiagnosed PAD yet no tools exist to detect atypical PAD symptoms. The purpose of this study was to identify discriminating PAD symptom descriptors from a community-based sample of patients with no current diagnosis of PAD.

Methods: Symptoms descriptors were obtained in a sample of 22 participants with persistent lower extremity symptoms pre/post exercise.

Potential impact of blood cholesterol guidelines on statin treatment in the U.S. population using interrupted time series analysis.

Background: The 2013 ACC/AHA Guideline was a paradigm shift in lipid management and identified the four statin-benefit groups. Many have studied the guideline's potential impact, but few have investigated its potential long-term impact on MACE. Furthermore, most studies also ignored the confounding effect from the earlier release of generic atorvastatin in Dec 2011.

Repurposing non-pharmacological interventions for Alzheimer's disease through link prediction on biomedical literature.

Non-pharmaceutical interventions (NPI) have great potential to improve cognitive function but limited investigation to discover NPI repurposing for Alzheimer's Disease (AD). This is the first study to develop an innovative framework to extract and represent NPI information from biomedical literature in a knowledge graph (KG), and train link prediction models to repurpose novel NPIs for AD prevention. We constructed a comprehensive KG, called ADInt, by extracting NPI information from biomedical literature.

Logistic burdens of cancer care: A qualitative study.

Cancer treatment often creates logistic conflicts with everyday life priorities; however, these challenges and how they are subjectively experienced have been largely unaddressed in cancer care. Our goal was to describe time and logistic requirements of cancer care and whether and how they interfered with daily life and well-being. We conducted interviews with 20 adults receiving cancer-directed treatment at a single academic cancer center.

Effect of a Multicomponent Food Pantry Intervention in Client Subgroups.

Nutrition promotion programs may have varying effects and influence health disparities. SuperShelf promotes healthy choices in food pantries through inventory changes and nudge implementation (e.g.

Machine Learning Identifies Higher Survival Profile In Extracorporeal Cardiopulmonary Resuscitation.

Objectives: Extracorporeal cardiopulmonary resuscitation (ECPR) has been shown to improve neurologically favorable survival in patients with refractory out-of-hospital cardiac arrest (OHCA) caused by shockable rhythms. Further refinement of patient selection is needed to focus this resource-intensive therapy on those patients likely to benefit. This study sought to create a selection model using machine learning (ML) tools for refractory cardiac arrest patients undergoing ECPR.

Unsupervised Machine Learning of the Combined Danish and Norwegian Knee Ligament Registers: Identification of 5 Distinct Patient Groups With Differing ACL Revision Rates.

Background: Most clinical machine learning applications use a supervised learning approach using labeled variables. In contrast, unsupervised learning enables pattern detection without a prespecified outcome.

Purpose/hypothesis: The purpose of this study was to apply unsupervised learning to the combined Danish and Norwegian knee ligament register (KLR) with the goal of detecting distinct subgroups.

Kidney Outcomes with Sodium-Glucose Cotransporter-2 Inhibitor Initiation after AKI among Veterans with Diabetic Kidney Disease.

Key Points: Post-AKI sodium–glucose cotransporter-2 inhibitor use was associated with a reduced risk for progression of CKD and for recurrent AKI among veterans with diabetic kidney disease even after accounting for recovery from the index AKI. A minority of Veterans with diabetic kidney disease received a sodium–glucose cotransporter-2 inhibitor after having had AKI during the study period.

Background: The effect of sodium–glucose cotransporter-2 inhibitor (SGLT2i) on kidney function after AKI is unknown.

Decision rules for personalized statin treatment prescriptions over multi-objectives.

In our previous study, we demonstrated the feasibility of producing a proactive statin prescription strategy - a personalized statin treatment plan (PSTP) - using neural networks with big data. However, its non-transparency limited result interpretations and clinical usability. To improve the transparency of our previous approach with minimal compromise to the maximal statin treatment benefit-to-risk ratio, this study proposed a five-step pipeline approach called the decision rules for statin treatment (DRST).

External validation of the Norwegian anterior cruciate ligament reconstruction revision prediction model using patients from the STABILITY 1 Trial.

Purpose: A machine learning-based anterior cruciate ligament (ACL) revision prediction model has been developed using Norwegian Knee Ligament Register (NKLR) data, but lacks external validation outside Scandinavia. This study aimed to assess the external validity of the NKLR model (https://swastvedt.shinyapps.

Associations Between Psychosocial Needs, Carbohydrate-Counting Behavior, and App Satisfaction: A Randomized Crossover App Trial on 92 Adults With Diabetes.

To examine whether psychosocial needs in diabetes care are associated with carbohydrate counting and if carbohydrate counting is associated with satisfaction with diabetes applications' usability, a randomized crossover trial of 92 adults with type 1 or 2 diabetes requiring insulin therapy tested two top-rated diabetes applications, mySugr and OnTrack Diabetes. Survey responses on demographics, psychosocial needs (perceived competence, autonomy, and connectivity), carbohydrate-counting frequency, and application satisfaction were modeled using mixed-effect linear regressions to test associations. Participants ranged between 19 and 74 years old (mean, 54 years) and predominantly had type 2 diabetes (70%).

Personalized statin treatment plan using counterfactual approach with multi-objective optimization over benefits and risks.

Background: Statins are a class of drugs that lower cholesterol levels in the blood by inhibiting an enzyme called 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase. High cholesterol levels can lead to plaque buildup in the arteries, which can cause Atherosclerotic Cardiovascular Disease(ASCVD). Statins can reduce the risk of ASCVD events by about 25-35% but they might be associated with symptoms such as muscle pain, liver damage, or diabetes.

A Cluster-Randomized Evaluation of the SuperShelf Intervention in Choice-Based Food Pantries.

Background: Interventions in food pantry settings have the potential to improve health among clients at risk of diet-related disease.

Purpose: This study evaluates whether a cluster-randomized, behavioral intervention in food pantries resulted in improved client outcomes.

Methods: Sixteen Minnesota food pantries were randomized to an intervention (n = 8) or control condition (n = 8).

Myocardial extracellular volume fraction is positively associated with activated monocyte subsets among cART-treated persons living with HIV in South Africa.

Background: Despite treatment with combination antiretroviral therapy (cART), persons living with HIV (PLWH) are at higher risk of cardiac structural abnormalities that may presage clinical heart failure, including myocardial fibrosis. This study assessed whether circulating cellular and soluble protein markers of immune activation cross-sectionally associate with myocardial fibrosis among cART-treated PLWH in South Africa.

Methods: Participants were enrolled in Khayelitsha township near Cape Town, SA.

An intersectional framework for counterfactual fairness in risk prediction.

Along with the increasing availability of health data has come the rise of data-driven models to inform decision making and policy. These models have the potential to benefit both patients and health care providers but can also exacerbate health inequities. Existing "algorithmic fairness" methods for measuring and correcting model bias fall short of what is needed for health policy in two key ways.

Human Milk Feeding and Direct Breastfeeding Improve Outcomes for Infants With Single Ventricle Congenital Heart Disease: Propensity Score-Matched Analysis of the NPC-QIC Registry.

Background Infants with single ventricle congenital heart disease undergo 3 staged surgeries/interventions, with risk for morbidity and mortality. We estimated the effect of human milk (HM) and direct breastfeeding on outcomes including necrotizing enterocolitis, infection-related complications, length of stay, and mortality. Methods and Results We analyzed the National Pediatric Cardiology Quality Improvement Collaborative (NPC-QIC) registry (2016-2021), examining HM/breastfeeding groups during stage 1 and stage 2 palliations.

Early results of a natural experiment evaluating the effects of a local minimum wage policy on the diet-related health of low-wage workers, 2018-2020.

Objective: The current study presents results of a midpoint analysis of an ongoing natural experiment evaluating the diet-related effects of the Minneapolis Minimum Wage Ordinance, which incrementally increases the minimum wage to $15/h.

Design: A difference-in-difference (DiD) analysis of measures collected among low-wage workers in two U.S.

Renin-Angiotensin-Aldosterone System Blockade after AKI with or without Recovery among US Veterans with Diabetic Kidney Disease.

Significance Statement: Among patients with CKD, optimal use of angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers after AKI is uncertain. Despite these medications' ability to reduce risk of mortality and other adverse outcomes, there is concern that ACEi/ARB use may delay recovery of kidney function or precipitate recurrent AKI. Prior studies have provided conflicting data regarding the optimal timing of these medications after AKI and have not addressed the role of kidney recovery in determining appropriate timing.

Cases and context: Mask-related behaviors among U.S. trail visitors during the COVID-19 pandemic.

The challenge of simultaneously providing outdoor recreation opportunities while protecting the public from SARS-CoV-2 virus and COVID-19 transmission, as well as future pandemics, remains foremost on managers' minds. Safe spaces and cultures are paramount for managers and visitors alike. Recommended protective measures against COVID-19 included physically distancing 1.

Predicting physical distancing on recreational trails during COVID-19.

Unlabelled: The emergence of Coronavirus 19 led to societal and behavioral changes, including intensified use of many public parks and trails for mental respite and leisure time physical activity. As visitors sought stress-relief in the great outdoors, they also encountered stressful situations as they navigated risk exposure. Recommendations to physically distance between parties was a key component to reduce risk, but compliance is unknown in the outdoor arena.

Effects of personalized exercise prescriptions and social media delivered through mobile health on cancer survivors' physical activity and quality of life.

Purpose: This study aimed to examine the effects of a multi-component mobile health intervention (wearable, apps, and social media) on cancer survivors' (CS') physical activity (PA), quality of life, and PA determinants compared to exercise prescription only, social media only, and attention control conditions.

Methods: A total of 126 CS (age = 60.37 ± 7.