"When she goes out, she feels better:" co-designing a Green Activity Program with Hispanic/Latino people living with memory challenges and care partners.

Purpose: Utilizing a participatory approach, we sought to co-design a 12-week Green Activity Program (GAP) with Hispanic/Latino individuals living with memory challenges and their care partners, local outdoor professionals, and healthcare providers. Methods: Participants were recruited via convenience and snowball sampling in the Bronx, New York with Hispanic/Latino persons living with memory challenges and care partners, outdoor activity professionals, and interdisciplinary healthcare providers/dementia experts. Co-design occurred iteratively with 5 focus groups and 4 individual interviews lasting 30-90 min and focused on program and research design. Sessions were recorded and transcribed. Utilizing directed content analysis data was coded using a priori codes program design and research design. Results: 21 participants completed co-design activities: (n = 8 outdoor activity professionals, n = 6 Hispanic/Latino persons living with memory challenges and care partners, and n = 7 interdisciplinary healthcare providers/dementia experts). Participant preferences for program design were captured by subcodes session duration (30-90 min), frequency (4-8 sessions), and delivery modes (in-person and phone). Participants' preferred nature activities included group exercise and outdoor crafts [crocheting], outcomes of social participation, connectedness to nature, decreased loneliness, and stewardship were identified. Preferred language for recruiting and describing the program were "memory challenges," "Hispanic/Latino," and "wellbeing." Referral pathways were identified including community-based organizations and primary care. Conclusion: Co-design was a successful form of engagement for people living with memory challenges that enabled participants to help design key elements of the GAP and research design. Our processes, findings, and recommendations for tailoring co-design to engage Hispanic/Latino people living with memory challenges can inform the development of other programs for this population.

Composite Burkitt Lymphoma and Classical Hodgkin Lymphoma in an Human Immunodeficiency Virus (HIV)-Positive Patient.

Lymphoma, a term encompassing tumor masses in the lymph nodes, is often classified into Hodgkin and non-Hodgkin lymphomas, each with distinct subtypes. We present the unique case of an HIV-positive patient diagnosed with Burkitt lymphoma and classical Hodgkin lymphoma simultaneously as a composite lymphoma. Over the course of five years, a variety of dose-adjusted chemotherapy regimens were used that ultimately proved highly effective. The successful management of this rare case reinforces the significance of considering unexpected combinations of neoplastic processes during diagnosis and treatment planning.

Genome-wide association studies of lifetime and frequency cannabis use in 131,895 individuals.

Cannabis is one of the most widely used drugs globally. Decriminalization of cannabis is further increasing cannabis consumption. We performed genome-wide association studies (GWASs) of lifetime (N=131,895) and frequency (N=73,374) of cannabis use. Lifetime cannabis use GWAS identified two loci, one near CADM2 (rs11922956, p=2.40E-11) and another near GRM3 (rs12673181, p=6.90E-09). Frequency of use GWAS identified one locus near CADM2 (rs4856591, p=8.10E-09; r2 =0.76 with rs11922956). Both traits were heritable and genetically correlated with previous GWASs of lifetime use and cannabis use disorder (CUD), as well as other substance use and cognitive traits. Polygenic scores (PGSs) for lifetime and frequency of cannabis use associated cannabis use phenotypes in AllofUs participants. Phenome-wide association study of lifetime cannabis use PGS in a hospital cohort replicated associations with substance use and mood disorders, and uncovered associations with celiac and infectious diseases. This work demonstrates the value of GWASs of CUD transition risk factors.

Ionizing Radiation-Induced Oxidative Stress in Computed Tomography-Effect of Vitamin C on Prevention of DNA Damage: PREVIR-C Randomized Controlled Trial Study Protocol.

Exposure to ionizing radiation (IR) is inevitable in various X-ray imaging examinations, with computed tomography (CT) being a major contributor to increased human radiation exposure. Ionizing radiation may cause structural damage to macromolecules, particularly DNA, mostly through an indirect pathway in diagnostic imaging. The indirect pathway primarily involves the generation of reactive oxygen species (ROS) due to water radiolysis induced by IR, leading to DNA damage, including double-strand breaks (DSB), which are highly cytotoxic. Antioxidants, substances that prevent oxidative damage, are proposed as potential radioprotective agents. This Study Protocol article presents the rationale for selecting vitamin C as a preventive measure against CT-associated IR-induced DNA damage, to be investigated in a randomized placebo-controlled trial, with a full in vivo design, using an oral easy-to-use schedule administration in the outpatient setting, for the single CT examination with the highest total global IR dose burden (contrast-enhanced abdomen and pelvis CT). The study also aims to explore the mediating role of oxidative stress, and it has been written in adherence to the Standard Protocol Items recommendations.

Rare and common variants associated with alcohol consumption identify a conserved molecular network.

BACKGROUND: Genome-wide association studies (GWAS) have identified hundreds of common variants associated with alcohol consumption. In contrast, genetic studies of alcohol consumption that use rare variants are still in their early stages. No prior studies of alcohol consumption have examined whether common and rare variants implicate the same genes and molecular networks, leaving open the possibility that the two approaches might identify distinct biology. METHODS: To address this knowledge gap, we used publicly available alcohol consumption GWAS summary statistics (GSCAN, N = 666,978) and whole exome sequencing data (Genebass, N = 393,099) to identify a set of common and rare variants for alcohol consumption. We used gene-based analysis to implicate genes from common and rare variant analyses, which we then propagated onto a shared molecular network using a network colocalization procedure. RESULTS: Gene-based analysis of each dataset implicated 294 (common variants) and 35 (rare variants) genes, including ethanol metabolizing genes ADH1B and ADH1C, which were identified by both analyses, and ANKRD12, GIGYF1, KIF21B, and STK31, which were identified in only the rare variant analysis, but have been associated with other neuropsychiatric traits. Network colocalization revealed significant network overlap between the genes identified via common and rare variants. The shared network identified gene families that function in alcohol metabolism, including ADH, ALDH, CYP, and UGT. Seventy-one of the genes in the shared network were previously implicated in neuropsychiatric or substance use disorders but not alcohol-related behaviors (e.g. EXOC2, EPM2A, and CACNG4). Differential gene expression analysis showed enrichment in the liver and several brain regions. CONCLUSIONS: Genes implicated by network colocalization identify shared biology relevant to alcohol consumption, which also underlie neuropsychiatric traits and substance use disorders that are comorbid with alcohol use, providing a more holistic understanding of two disparate sources of genetic information.

A Cost-effective, High-throughput, Highly Accurate Genotyping Method for Outbred Populations.

Affordable sequencing and genotyping methods are essential for large scale genome-wide association studies. While genotyping microarrays and reference panels for imputation are available for human subjects, non-human model systems often lack such options. Our lab previously demonstrated an efficient and cost-effective method to genotype heterogeneous stock rats using double-digest genotyping-by-sequencing. However, low-coverage whole-genome sequencing offers an alternative method that has several advantages. Here, we describe a cost-effective, high-throughput, high-accuracy genotyping method for N/NIH heterogeneous stock rats that can use a combination of sequencing data previously generated by double-digest genotyping-by-sequencing and more recently generated by low-coverage whole-genome-sequencing data. Using double-digest genotyping-by-sequencing data from 5,745 heterogeneous stock rats (mean 0.21x coverage) and low-coverage whole-genome-sequencing data from 8,760 heterogeneous stock rats (mean 0.27x coverage), we can impute 7.32 million bi-allelic single-nucleotide polymorphisms with a concordance rate >99.76% compared to high-coverage (mean 33.26x coverage) whole-genome sequencing data for a subset of the same individuals. Our results demonstrate the feasibility of using sequencing data from double-digest genotyping-by-sequencing or low-coverage whole-genome-sequencing for accurate genotyping, and demonstrate techniques that may also be useful for other genetic studies in non-human subjects. Article Summary: Heterogeneous stock rats were derived by interbreeding eight inbred founders in 1984, and have been maintained as an outbred population for more than 100 generations. Heterogeneous stock rats offer a high degree of genetic and phenotypic diversity, and have been extensively used for genetic studies. Here, we describe a cost-effective and high-throughput genotyping method for heterogeneous stock rats. We applied the method to 15,552 heterogeneous stock rats. The resulting genotypes were highly accurate. These techniques may be useful for genetic studies in other non-human subjects.

Diagnosis and Treatment of Low-Grade Marginal Zone B-cell Lymphoma With Psychiatric Overlap.

This case report delineates the intricate interplay between psychiatric and oncological pathology in a 72-year-old male diagnosed with low-grade marginal zone B-cell lymphoma and severe psychiatric disturbances, including catatonia. The presentation of severe psychiatric symptoms initially obscured the underlying lymphoma, delaying diagnosis and complicating clinical management. Notably, the lymphoma itself may have precipitated or exacerbated the psychiatric condition, underscoring the potential for oncological diseases to manifest with rapidly progressive dementia and catatonia. A multidisciplinary approach was employed, utilizing electroconvulsive therapy (ECT) for rapid resolution of catatonia, which facilitated significant mental health improvements and clearer delineation of the oncological underpinnings. Concurrently, the patient was treated with rituximab, targeting the lymphoma. This case highlights the critical need for a comprehensive evaluation in patients presenting with psychiatric symptoms, particularly in the elderly, to uncover potential medical causes and illustrates the efficacy of ECT in managing psychiatric conditions that may overshadow or complicate concurrent medical issues.

Variable effect of the post-partum menstrual cycle on aldosterone and renin in women with recent preeclampsia.

The purpose of the present study is to identify the impact of the postpartum menstrual cycle on aldosterone, renin, and their ratio of women with and without a preeclamptic pregnancy in the past. To this end, we analysed the data from 59 women with a history of preeclampsia and 39 healthy parous controls. Five to seven months post-partum, we measured aldosterone, renin, and the aldosterone-to-renin ratio during both the follicular and the luteal phase of the menstrual cycle. All measurements were taken in the supine position in the morning. Patients had maintained a standardized sodium diet in the week prior to the measurements. Our results show that in both post-partum women with recent preeclampsia and controls, average levels of renin and aldosterone are significantly elevated in the luteal phase as compared to the follicular phase. The aldosterone-to-renin ratio does not differ between the two phases in either group. Compared to controls, women with recent preeclampsia have significantly lower levels of renin, aldosterone, and aldosterone-to-renin ratio in the follicular phase. This remained consistent in the luteal phase, except for renin. A close correlation existed between the luteal and follicular aldosterone-to-renin ratio in the control group but not in the preeclampsia group. We conclude that both renin and aldosterone are significantly affected by the menstrual cycle whereas the resulting aldosterone-to-renin ratio is not. Post-partum women with recent preeclampsia tend to have lower values for aldosterone and the aldosterone-to-renin ratio than controls.

Unraveling Complexity: A Case of Possible Overlapping Between Mixed Connective Tissue Disease and Systemic Lupus Erythematosus With Renal Involvement.

Autoimmune diseases, a term encompassing conditions where the immune system targets its own cells, consist of various pathologies, two of which are systemic lupus erythematosus (SLE) and mixed connective tissue disorder (MCTD). We present the unique case of an anti-ribonucleoprotein (RNP)-positive patient exhibiting renal pathology consistent with lupus nephritis and an additional collapsing variant of focal segmental glomerulonephropathy, who initially presented to the emergency department with signs and symptoms of pneumonia and portal vein thrombosis that were subsequently treated. Conflicting accounts of her autoimmune history led to an extensive workup during her stay, which yielded a tentative diagnosis of SLE vs. MCTD during her current hospitalization for pneumonia. The diagnostic labs revealed conflicting serological markers, with delayed anti-Smith positive results favoring lupus due to its high specificity. A subsequent renal biopsy showed complex renal involvement, suggesting SLE, despite initial positive anti-RNP antibodies known to be protective against renal pathology and classic for MCTD. Complicating matters further, the renal biopsy findings extended beyond common SLE pathology, including additional focal segmental glomerulonephritis (FSGS) involvement. Despite this uncertainty, the patient was treated as if solely having SLE, and immunosuppressives that could have been utilized for the possible MCTD component were avoided due to minimal signs of inflammation/immune response and normal kidney function. This case highlights the difficulty in accurately classifying lupus and MCTD, emphasizing the need for precise diagnosis for tailored patient care. Ongoing research is crucial to refine diagnostic criteria and improve patient outcomes.

Genome-wide association study for age-related hearing loss in CFW mice.

Age-related hearing impairment is the most common cause of hearing loss and is one of the most prevalent conditions affecting the elderly globally. It is influenced by a combination of environmental and genetic factors. The mouse and human inner ears are functionally and genetically homologous. Investigating the genetic basis of age-related hearing loss (ARHL) in an outbred mouse model may lead to a better understanding of the molecular mechanisms of this condition. We used Carworth Farms White (CFW) outbred mice, because they are genetically diverse and exhibit variation in the onset and severity of ARHL. The goal of this study was to identify genetic loci involved in regulating ARHL. Hearing at a range of frequencies was measured using Auditory Brainstem Response (ABR) thresholds in 946 male and female CFW mice at the age of 1, 6, and 10 months. We obtained genotypes at 4.18 million single nucleotide polymorphisms (SNP) using low-coverage (mean coverage 0.27x) whole-genome sequencing followed by imputation using STITCH. To determine the accuracy of the genotypes we sequenced 8 samples at >30x coverage and used calls from those samples to estimate the discordance rate, which was 0.45%. We performed genetic analysis for the ABR thresholds for each frequency at each age, and for the time of onset of deafness for each frequency. The SNP heritability ranged from 0 to 42% for different traits. Genome-wide association analysis identified several regions associated with ARHL that contained potential candidate genes, including Dnah11, Rapgef5, Cpne4, Prkag2, and Nek11. We confirmed, using functional study, that Prkag2 deficiency causes age-related hearing loss at high frequency in mice; this makes Prkag2 a candidate gene for further studies. This work helps to identify genetic risk factors for ARHL and to define novel therapeutic targets for the treatment and prevention of ARHL.

Genome-wide association studies of coffee intake in UK/US participants of European ancestry uncover cohort-specific genetic associations.

Coffee is one of the most widely consumed beverages. We performed a genome-wide association study (GWAS) of coffee intake in US-based 23andMe participants (N = 130,153) and identified 7 significant loci, with many replicating in three multi-ancestral cohorts. We examined genetic correlations and performed a phenome-wide association study across hundreds of biomarkers, health, and lifestyle traits, then compared our results to the largest available GWAS of coffee intake from the UK Biobank (UKB; N = 334,659). We observed consistent positive genetic correlations with substance use and obesity in both cohorts. Other genetic correlations were discrepant, including positive genetic correlations between coffee intake and psychiatric illnesses, pain, and gastrointestinal traits in 23andMe that were absent or negative in the UKB, and genetic correlations with cognition that were negative in 23andMe but positive in the UKB. Phenome-wide association study using polygenic scores of coffee intake derived from 23andMe or UKB summary statistics also revealed consistent associations with increased odds of obesity- and red blood cell-related traits, but all other associations were cohort-specific. Our study shows that the genetics of coffee intake associate with substance use and obesity across cohorts, but also that GWAS performed in different populations could capture cultural differences in the relationship between behavior and genetics.

Plant Waste-Based Bioadditive as an Antioxidant Agent and Rheological Modifier of Bitumen.

In recent times, circular economy initiatives in addition to the need for sustainable biomaterials have brought about several attempts at the eco-friendly, eco-sustainable and cost-effective production of asphalt pavements. It is an increasingly common practice in the asphalt industry to improve road pavement performance using additives to enhance the physico-chemical properties of bitumen, which performs the role of the binder in the asphalt mix. This paper evaluated the potential of a bio-based additive derived from olive leaf residue as a modifier and antioxidant agent for bitumen. Samples of neat, aged and doped aged bitumen were analyzed. In this study, the two bio-based additives were characterized in terms of phenol, chlorophyll, lignin and cellulose content, which was correlated with the mechanical properties of the tested samples. The mechanical properties of the neat, modified, aged and unaged samples were evaluated via Dynamic Shear Rheology. The bio-based additives proved to be promising and can improve the properties of bitumen binder and the performance of asphalt pavements in general.

Multimodal analysis of RNA sequencing data powers discovery of complex trait genetics.

Transcriptome data is commonly used to understand genome function via quantitative trait loci (QTL) mapping and to identify the molecular mechanisms driving genome wide association study (GWAS) signals through colocalization analysis and transcriptome-wide association studies (TWAS). While RNA sequencing (RNA-seq) has the potential to reveal many modalities of transcriptional regulation, such as various splicing phenotypes, such studies are often limited to gene expression due to the complexity of extracting and analyzing multiple RNA phenotypes. Here, we present Pantry (Pan-transcriptomic phenotyping), a framework to efficiently generate diverse RNA phenotypes from RNA-seq data and perform downstream integrative analyses with genetic data. Pantry currently generates phenotypes from six modalities of transcriptional regulation (gene expression, isoform ratios, splice junction usage, alternative TSS/polyA usage, and RNA stability) and integrates them with genetic data via QTL mapping, TWAS, and colocalization testing. We applied Pantry to Geuvadis and GTEx data, and found that 4,768 of the genes with no identified expression QTL in Geuvadis had QTLs in at least one other transcriptional modality, resulting in a 66% increase in genes over expression QTL mapping. We further found that QTLs exhibit modality-specific functional properties that are further reinforced by joint analysis of different RNA modalities. We also show that generalizing TWAS to multiple RNA modalities (xTWAS) approximately doubles the discovery of unique gene-trait associations, and enhances identification of regulatory mechanisms underlying GWAS signal in 42% of previously associated gene-trait pairs. We provide the Pantry code, RNA phenotypes from all Geuvadis and GTEx samples, and xQTL and xTWAS results on the web.

Genome-wide association study reveals multiple loci for nociception and opioid consumption behaviors associated with heroin vulnerability in outbred rats.

The increased prevalence of opioid use disorder (OUD) makes it imperative to disentangle the biological mechanisms contributing to individual differences in OUD vulnerability. OUD shows strong heritability, however genetic variants contributing toward vulnerability remain poorly defined. We performed a genome-wide association study using over 850 male and female heterogeneous stock (HS) rats to identify genes underlying behaviors associated with OUD such as nociception, as well as heroin-taking, extinction and seeking behaviors. By using an animal model of OUD, we were able to identify genetic variants associated with distinct OUD behaviors while maintaining a uniform environment, an experimental design not easily achieved in humans. Furthermore, we used a novel non-linear network-based clustering approach to characterize rats based on OUD vulnerability to assess genetic variants associated with OUD susceptibility. Our findings confirm the heritability of several OUD-like behaviors, including OUD susceptibility. Additionally, several genetic variants associated with nociceptive threshold prior to heroin experience, heroin consumption, escalation of intake, and motivation to obtain heroin were identified. Tom1 , a microglial component, was implicated for nociception. Several genes involved in dopaminergic signaling, neuroplasticity and substance use disorders, including Brwd1 , Pcp4, Phb1l2 and Mmp15 were implicated for the heroin traits. Additionally, an OUD vulnerable phenotype was associated with genetic variants for consumption and break point, suggesting a specific genetic contribution for OUD-like traits contributing to vulnerability. Together, these findings identify novel genetic markers related to the susceptibility to OUD-relevant behaviors in HS rats.

Associations of between- and within-day patterns of physical activity accumulation with arterial stiffness and indices of microvascular health-Evidence from The Maastricht study.

While physical activity (PA) is understood to promote vascular health, little is known about whether the daily and weekly patterns of PA accumulation associate with vascular health. Accelerometer-derived (activPAL3) 6- or 7-day stepping was analyzed for 6430 participants in The Maastricht Study (50.4% women; 22.4% Type 2 diabetes mellitus (T2DM)). Multivariable regression models examined associations between stepping metrics (average step count, and time spent slower and faster paced stepping) with arterial stiffness (measured as carotid-femoral pulse wave velocity (cfPWV)), and several indices of microvascular health (heat-induced skin hyperemia, retinal vessel reactivity and diameter), adjusting for confounders and moderators. PA pattern metrics were added to the regression models to identify associations with vascular health beyond that of stepping metrics. Analyses were stratified by T2DM status if an interaction effect was present. Average step count and time spent faster paced stepping was associated with better vascular health, and the association was stronger in those with compared to those without T2DM. In fully adjusted models a higher step count inter-daily stability was associated with a higher (worse) cfPWV in those without T2DM (std ß = 0.04, p = 0.007) and retinal venular diameter in the whole cohort (std ß = 0.07, p = 0.002). A higher within-day variability in faster paced stepping was associated with a lower (worse) heat-induced skin hyperemia in those with T2DM (std ß = -0.31, p = 0.008). Above and beyond PA volume, the daily and weekly patterns in which PA was accumulated were additionally associated with improved macro- and microvascular health, which may have implications for the prevention of vascular disease.

Construction of the Digital Health Equity-Focused Implementation Research Conceptual Model - Bridging the Divide Between Equity-focused Digital Health and Implementation Research.

Digital health implementations and investments continue to expand. As the reliance on digital health increases, it is imperative to implement technologies with inclusive and accessible approaches. A conceptual model can be used to guide equity-focused digital health implementations to improve suitability and uptake in diverse populations. The objective of this study is expand an implementation model with recommendations on the equitable implementation of new digital health technologies. The Digital Health Equity-Focused Implementation Research (DH-EquIR) conceptual model was developed based on a rigorous review of digital health implementation and health equity literature. The Equity-Focused Implementation Research for Health Programs (EquIR) model was used as a starting point and merged with digital equity and digital health implementation models. Existing theoretical frameworks and models were appraised as well as individual equity-sensitive implementation studies. Patient and program-related concepts related to digital equity, digital health implementation, and assessment of social/digital determinants of health were included. Sixty-two articles were analyzed to inform the adaption of the EquIR model for digital health. These articles included digital health equity models and frameworks, digital health implementation models and frameworks, research articles, guidelines, and concept analyses. Concepts were organized into EquIR conceptual groupings, including population health status, planning the program, designing the program, implementing the program, and equity-focused implementation outcomes. The adapted DH-EquIR conceptual model diagram was created as well as detailed tables displaying related equity concepts, evidence gaps in source articles, and analysis of existing equity-related models and tools. The DH-EquIR model serves to guide digital health developers and implementation specialists to promote the inclusion of health-equity planning in every phase of implementation. In addition, it can assist researchers and product developers to avoid repeating the mistakes that have led to inequities in the implementation of digital health across populations.

Predicting Risk of Alzheimer's Diseases and Related Dementias with AI Foundation Model on Electronic Health Records.

Early identification of Alzheimer's disease (AD) and AD-related dementias (ADRD) has high clinical significance, both because of the potential to slow decline through initiating FDA-approved therapies and managing modifiable risk factors, and to help persons living with dementia and their families to plan before cognitive loss makes doing so challenging. However, substantial racial and ethnic disparities in early diagnosis currently lead to additional inequities in care, urging accurate and inclusive risk assessment programs. In this study, we trained an artificial intelligence foundation model to represent the electronic health records (EHR) data with a vast cohort of 1.2 million patients within a large health system. Building upon this foundation EHR model, we developed a predictive Transformer model, named TRADE, capable of identifying risks for AD/ADRD and mild cognitive impairment (MCI), by analyzing the past sequential visit records. Amongst individuals 65 and older, our model was able to generate risk predictions for various future timeframes. On the held-out validation set, our model achieved an area under the receiver operating characteristic (AUROC) of 0.772 (95% CI: 0.770, 0.773) for identifying the AD/ADRD/MCI risks in 1 year, and AUROC of 0.735 (95% CI: 0.734, 0.736) in 5 years. The positive predictive values (PPV) in 5 years among individuals with top 1% and 5% highest estimated risks were 39.2% and 27.8%, respectively. These results demonstrate significant improvements upon the current EHR-based AD/ADRD/MCI risk assessment models, paving the way for better prognosis and management of AD/ADRD/MCI at scale.

Multi-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes.

Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviours and although strides have been made using genome-wide association studies to identify risk variants, most variants identified have been for nicotine consumption, rather than TUD. Here we leveraged four US biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records) in 653,790 individuals (495,005 European, 114,420 African American and 44,365 Latin American) and data from UK Biobank (ncombined = 898,680). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviours in children and hundreds of medical outcomes, including HIV infection, heart disease and pain. This work furthers our biological understanding of TUD and establishes electronic health records as a source of phenotypic information for studying the genetics of TUD.

Race and Ethnicity Are Related to Undesirable Home Health Care Outcomes in Seriously Ill Older Adults.

OBJECTIVES: Medicare Home Health Care (HHC) services are integral to the care of homebound seriously ill older adults requiring ongoing specialized medical care. Although disparities in health outcomes are well documented in inpatient and primary care, disparities experienced by historically marginalized racial and ethnic groups underrepresented in HHC are understudied. This study aimed to examine the relationship between individual characteristics and differences in HHC health outcomes for seriously ill older adults. DESIGN: Secondary data analysis, repeated measure. SETTING AND PARTICIPANTS: Seriously ill older adults who received HHC in 2016 in the HHC Outcome and Assessment Information Set (OASIS). METHODS: Start of care and discharge data from the 2016 HCC OASIS were used to examine the relationship between individual characteristics and differences in HHC health outcomes identified by the Centers for Medicare and Medicaid Services as key indicators of quality in HHC, including dyspnea, pain frequency, cognitive functioning, and presence of unhealed pressure ulcer stage II or higher. A generalized ordered logit model with partial proportional odds was used for the ordinal categorical outcomes and a logistic regression was used for the binary dependent variable. RESULTS: Findings indicated that of 227,402 seriously ill individuals with an HHC episode in 2016, those from underrepresented racial and ethnic groups had between 14% and 57% higher odds of worse health outcomes compared with non-Hispanic white patients with the exception of pain frequency. CONCLUSIONS AND IMPLICATIONS: For people living with serious illness, there are significant differences in Medicare HHC health outcomes when comparing underrepresented racial or ethnic beneficiaries with white counterparts. More research is needed to understand how health care processes such as referral patterns or time to care initiation, and structural factors such as HHC agency quality and neighborhood social deprivation are related to health differences observed in the population.

A Preliminary Validation of an Optimal Cutpoint in Total Number of Patient-Reported Symptoms in Head and Neck Cancer for Effective Alignment of Clinical Resources with Patients' Symptom Burden.

Background: Patients with head and neck cancer (HNC) often experience high symptom burden leading to lower quality of life (QoL). Objective: This study aims to conceptually model optimal cutpoint by examining where total number of patient-reported symptoms exceeds patients' coping capacity, leading to a decline in QoL in patients with HNC. Methods: Secondary data analysis of 105 individuals with HNC enrolled in a clinical usefulness study of the NYU Electronic Patient Visit Assessment (ePVA)©, a digital patient-reported symptom measure. Patients completed ePVA and European Organization for Research and Treatment of Cancer (EORTC©) QLQ-C30 v3.0. The total number of patient-reported symptoms was the sum of symptoms as identified by the ePVA questionnaire. Analysis of variance (ANOVA) was used to define optimal cutpoint. Results: Study participants had a mean age of 61.5, were primarily male (67.6%), and had Stage IV HNC (53.3%). The cutpoint of 10 symptoms was associated with significant decline of QoL (F= 44.8, P<.0001), dividing the population into categories of low symptom burden (< 10 symptoms) and high symptom burden (≥ 10 symptoms). Analyses of EORTC© function subscales supported the validity of 10 symptoms as the optimal cutpoint (Physical: F=28.3, P<.0001; Role: F=21.6, P<.0001; Emotional: F=9.5, P=.003; Social: F=33.1, P<.0001). Conclusions: In HNC, defining optimal cutpoints in the total number of patient-reported symptoms is feasible. Implications for Practice: Cutpoints in the total number of patient-reported symptoms may identify patients experiencing a high symptom burden from HNC. Foundational: Using optimal cutpoints of the total number of patient-reported symptoms may help effectively align clinical resources with patients' symptom burden.