Abstract Background This study aims to assess the impact of healthy lifestyle on prostate cancer (PCa) risk in a diverse population. Methods Data for 281,923 men from the Million Veteran Program ...(MVP), a nationwide, health system–based cohort study, were analyzed. Self‐reported information at enrollment included smoking status, exercise, diet, family history of PCa, and race/ethnicity. Body mass index (BMI) was obtained from clinical records. Genetic risk was assessed via a validated polygenic score. Cox proportional hazards models were used to assess associations with PCa outcomes. Results After accounting for ancestry, family history, and genetic risk, smoking was associated with an increased risk of metastatic PCa (hazard ratio HR, 1.83; 95% confidence interval CI, 1.64–2.02; p < 10 −16 ) and fatal PCa (HR, 2.73; 95% CI, 2.36–3.25; p < 10 −16 ). Exercise was associated with a reduced risk of fatal PCa (HR, 0.86; 95% CI, 0.76–0.98; p = .03). Higher BMI was associated with a slightly reduced risk of fatal PCa, and diet score was not independently associated with any end point. Association with exercise was strongest among those who had nonmetastatic PCa at MVP enrollment. Absolute reductions in the risk of fatal PCa via lifestyle factors were greatest among men of African ancestry (1.7% for nonsmokers vs. 6.1% for smokers) or high genetic risk (1.4% for nonsmokers vs. 4.3% for smokers). Conclusions Healthy lifestyle is minimally related to the overall risk of developing PCa but is associated with a substantially reduced risk of dying from PCa. In multivariable analyses, both exercise and not smoking remain independently associated with reduced metastatic and fatal PCa.
In this Million Veteran Program study, exercise and not smoking are shown to be minimally related to the overall risk of developing prostate cancer but are associated with a substantially reduced risk of dying from prostate cancer.
Porous, resorbable biomaterials can serve as temporary scaffolds that support cell infiltration, tissue formation, and remodeling of nonhealing skin wounds. Synthetic biomaterials are less expensive ...to manufacture than biologic dressings and can achieve a broader range of physiochemical properties, but opportunities remain to tailor these materials for ideal host immune and regenerative responses. Polyesters are a well-established class of synthetic biomaterials; however, acidic degradation products released by their hydrolysis can cause poorly controlled autocatalytic degradation. Here, we systemically explored reactive oxygen species (ROS)-degradable polythioketal (PTK) urethane (UR) foams with varied hydrophilicity for skin wound healing. The most hydrophilic PTK-UR variant, with seven ethylene glycol (EG7) repeats flanking each side of a thioketal bond, exhibited the highest ROS reactivity and promoted optimal tissue infiltration, extracellular matrix (ECM) deposition, and reepithelialization in porcine skin wounds. EG7 induced lower foreign body response, greater recruitment of regenerative immune cell populations, and resolution of type 1 inflammation compared to more hydrophobic PTK-UR scaffolds. Porcine wounds treated with EG7 PTK-UR foams had greater ECM production, vascularization, and resolution of proinflammatory immune cells compared to polyester UR foam-based NovoSorb Biodegradable Temporizing Matrix (BTM)-treated wounds and greater early vascular perfusion and similar wound resurfacing relative to clinical gold standard Integra Bilayer Wound Matrix (BWM). In a porcine ischemic flap excisional wound model, EG7 PTK-UR treatment led to higher wound healing scores driven by lower inflammation and higher reepithelialization compared to NovoSorb BTM. PTK-UR foams warrant further investigation as synthetic biomaterials for wound healing applications.
The role of obesity-associated insulin resistance (IR) in airflow limitation in asthma is uncertain.
Using data in the Severe Asthma Research Program 3 (SARP-3), we evaluated relationships between ...homeostatic measure of IR (HOMA-IR), lung function (cross-sectional and longitudinal analyses), and treatment responses to bronchodilators and corticosteroids.
HOMA-IR values were categorized as without (<3.0), moderate (3.0-5.0), or severe (>5.0). Lung function included FEV
and FVC measured before and after treatment with inhaled albuterol and intramuscular triamcinolone acetonide and yearly for 5 years.
Among 307 participants in SARP-3, 170 (55%) were obese and 140 (46%) had IR. Compared with patients without IR, those with IR had significantly lower values for FEV
and FVC, and these lower values were not attributable to obesity effects. Compared with patients without IR, those with IR had lower FEV
responses to β-adrenergic agonists and systemic corticosteroids. The annualized decline in FEV
was significantly greater in patients with moderate IR (-41 ml/year) and severe IR (-32 ml/year,) than in patients without IR (-13 ml/year,
< 0.001 for both comparisons).
IR is common in asthma and is associated with lower lung function, accelerated loss of lung function, and suboptimal lung function responses to bronchodilator and corticosteroid treatments. Clinical trials in patients with asthma and IR are needed to determine if improving IR might also improve lung function.
Accurate information is needed to direct healthcare systems' efforts to control methicillin-resistant Staphylococcus aureus (MRSA). Assembling complete and correct microbiology data is vital to ...understanding and addressing the multiple drug-resistant organisms in our hospitals.
Herein, we describe a system that securely gathers microbiology data from the Department of Veterans Affairs (VA) network of databases. Using natural language processing methods, we applied an information extraction process to extract organisms and susceptibilities from the free-text data. We then validated the extraction against independently derived electronic data and expert annotation.
We estimate that the collected microbiology data are 98.5% complete and that methicillin-resistant Staphylococcus aureus was extracted accurately 99.7% of the time.
Applying natural language processing methods to microbiology records appears to be a promising way to extract accurate and useful nosocomial pathogen surveillance data. Both scientific inquiry and the data's reliability will be dependent on the surveillance system's capability to compare from multiple sources and circumvent systematic error. The dataset constructed and methods used for this investigation could contribute to a comprehensive infectious disease surveillance system or other pressing needs.
The US government considers veterans to have been exposed to Agent Orange if they served in Vietnam while the carcinogen was in use, and these veterans are often deemed at high risk of prostate ...cancer (PCa). Here, we assess whether presumed Agent Orange exposure is independently associated with increased risk of any metastatic or fatal PCa in a diverse Veteran cohort still alive in the modern era (at least 2011), when accounting for race/ethnicity, family history, and genetic risk.
Participants in the Million Veteran Program (MVP; enrollment began in 2011) who were on active duty during the Vietnam War era (August 1964-April 1975) were included (n = 301,470). Agent Orange exposure was determined using the US government definition. Genetic risk was assessed via a validated polygenic hazard score. Associations with age at diagnosis of any PCa, metastatic PCa, and death from PCa were assessed via Cox proportional hazards models.
On univariable analysis, exposure to Agent Orange was not associated with increased PCa (hazard ratio HR: 1.02, 95% confidence interval CI: 1.00-1.04, p = 0.06), metastatic PCa (HR: 0.98, 95% CI: 0.91-1.05, p = 0.55), or fatal PCa (HR: 0.94, 95% CI: 0.79-1.09, p = 0.41). When accounting for race/ethnicity and family history, Agent Orange exposure was independently associated with slightly increased risk of PCa (HR: 1.06, 95% CI: 1.04-1.09, <10-6) but not with metastatic PCa (HR: 1.07, 95% CI: 0.98-1.15, p = 0.10) or PCa death (HR: 1.02, 95% CI: 0.83-1.23, p = 0.09). Similar results were found when accounting for genetic risk. Agent Orange exposure history may not improve modern PCa risk stratification.
In this study we sought to explore the possibility of using patient centered care (PCC) documentation as a measure of the delivery of PCC in a health system.
We first selected 6 VA medical centers ...based on their scores for a measure of support for self-management subscale from a national patient satisfaction survey (the Survey for Healthcare Experience-Patients). We accessed clinical notes related to either smoking cessation or weight management consults. We then annotated this dataset of notes for documentation of PCC concepts including: patient goals, provider support for goal progress, social context, shared decision making, mention of caregivers, and use of the patient's voice. We examined the association of documentation of PCC with patients' perception of support for self-management with regression analyses.
Two health centers had < 50 notes related to either tobacco cessation or weight management consults and were removed from further analysis. The resulting dataset includes 477 notes related to 311 patients total from 4 medical centers. For a majority of patients (201 out of 311; 64.8%) at least one PCC concept was present in their clinical notes. The most common PCC concepts documented were patient goals (patients n = 126; 63% clinical notes n = 302; 63%), patient voice (patients n = 165, 82%; clinical notes n = 323, 68%), social context (patients n = 105, 52%; clinical notes n = 181, 38%), and provider support for goal progress (patients n = 124, 62%; clinical notes n = 191, 40%). Documentation of goals for weight loss notes was greater at health centers with higher satisfaction scores compared to low. No such relationship was found for notes related to tobacco cessation.
Providers document PCC concepts in their clinical notes. In this pilot study we explored the feasibility of using this data as a means to measure the degree to which care in a health center is patient centered.
clinical EHR notes are a rich source of information about PCC that could potentially be used to assess PCC over time and across systems with scalable technologies such as natural language processing.
The Cleveland airshed comprises a complex mixture of industrial source emissions that contribute to periods of non-attainment for fine particulate matter (PM2.5) and are associated with increased ...adverse health outcomes in the exposed population. Specific PM sources responsible for health effects however are not fully understood. Size-fractionated PM (coarse, fine, and ultrafine) samples were collected using a ChemVol sampler at an urban site (G.T. Craig (GTC)) and rural site (Chippewa Lake (CLM)) from July 2009 to June 2010, and then chemically analyzed. The resulting speciated PM data were apportioned by EPA positive matrix factorization to identify emission sources for each size fraction and location. For comparisons with the ChemVol results, PM samples were also collected with sequential dichotomous and passive samplers, and evaluated for source contributions to each sampling site. The ChemVol results showed that annual average concentrations of PM, elemental carbon, and inorganic elements in the coarse fraction at GTC were ∼2, ∼7, and ∼3 times higher than those at CLM, respectively, while the smaller size fractions at both sites showed similar annual average concentrations. Seasonal variations of secondary aerosols (e.g., high NO3− level in winter and high SO42− level in summer) were observed at both sites. Source apportionment results demonstrated that the PM samples at GTC and CLM were enriched with local industrial sources (e.g., steel plant and coal-fired power plant) but their contributions were influenced by meteorological conditions and the emission source's operation conditions. Taken together the year-long PM collection and data analysis provides valuable insights into the characteristics and sources of PM impacting the Cleveland airshed in both the urban center and the rural upwind background locations. These data will be used to classify the PM samples for toxicology studies to determine which PM sources, species, and size fractions are of greatest health concern.
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•PM sources in the Cleveland airshed varied across regions and with seasons.•Local industrial source impacts in the urban site were higher than the rural site.•Local industrial sources were mostly emitted from steel and coal-fired power plants.•Local industrial source impacts were associated with meteorological conditions.
The Cleveland airshed was enriched with local industrial sources but their contributions were influenced by meteorological conditions and emission source operation conditions.
Many patients with bipolar disorder (BD) are initially misdiagnosed with major depressive disorder (MDD) and are treated with antidepressants, whose potential iatrogenic effects are widely discussed. ...It is unknown whether MDD is a comorbidity of BD or its earlier stage, and no consensus exists on individual conversion predictors, delaying BD's timely recognition and treatment. We aimed to build a predictive model of MDD to BD conversion and to validate it across a multi-national network of patient databases using the standardization afforded by the Observational Medical Outcomes Partnership (OMOP) common data model. Five "training" US databases were retrospectively analyzed: IBM MarketScan CCAE, MDCR, MDCD, Optum EHR, and Optum Claims. Cyclops regularized logistic regression models were developed on one-year MDD-BD conversion with all standard covariates from the HADES PatientLevelPrediction package. Time-to-conversion Kaplan-Meier analysis was performed up to a decade after MDD, stratified by model-estimated risk. External validation of the final prediction model was performed across 9 patient record databases within the Observational Health Data Sciences and Informatics (OHDSI) network internationally. The model's area under the curve (AUC) varied 0.633-0.745 (µ = 0.689) across the five US training databases. Nine variables predicted one-year MDD-BD transition. Factors that increased risk were: younger age, severe depression, psychosis, anxiety, substance misuse, self-harm thoughts/actions, and prior mental disorder. AUCs of the validation datasets ranged 0.570-0.785 (µ = 0.664). An assessment algorithm was built for MDD to BD conversion that allows distinguishing as much as 100-fold risk differences among patients and validates well across multiple international data sources.
Abstract
Objective
Patients with autoimmune diseases were advised to shield to avoid coronavirus disease 2019 (COVID-19), but information on their prognosis is lacking. We characterized 30-day ...outcomes and mortality after hospitalization with COVID-19 among patients with prevalent autoimmune diseases, and compared outcomes after hospital admissions among similar patients with seasonal influenza.
Methods
A multinational network cohort study was conducted using electronic health records data from Columbia University Irving Medical Center USA, Optum (USA), Department of Veterans Affairs (USA), Information System for Research in Primary Care-Hospitalization Linked Data (Spain) and claims data from IQVIA Open Claims (USA) and Health Insurance and Review Assessment (South Korea). All patients with prevalent autoimmune diseases, diagnosed and/or hospitalized between January and June 2020 with COVID-19, and similar patients hospitalized with influenza in 2017–18 were included. Outcomes were death and complications within 30 days of hospitalization.
Results
We studied 133 589 patients diagnosed and 48 418 hospitalized with COVID-19 with prevalent autoimmune diseases. Most patients were female, aged ≥50 years with previous comorbidities. The prevalence of hypertension (45.5–93.2%), chronic kidney disease (14.0–52.7%) and heart disease (29.0–83.8%) was higher in hospitalized vs diagnosed patients with COVID-19. Compared with 70 660 hospitalized with influenza, those admitted with COVID-19 had more respiratory complications including pneumonia and acute respiratory distress syndrome, and higher 30-day mortality (2.2–4.3% vs 6.32–24.6%).
Conclusion
Compared with influenza, COVID-19 is a more severe disease, leading to more complications and higher mortality.
This work establishes that Kupffer cell release of platelet activating factor (PAF), a lipidic molecule with pro-inflammatory and vasoactive signaling properties, dictates dose-limiting siRNA ...nanocarrier-associated toxicities. High-dose intravenous injection of siRNA-polymer nano-polyplexes (si-NPs) elicited acute, shock-like symptoms in mice, associated with increased plasma PAF and consequently reduced PAF acetylhydrolase (PAF-AH) activity. These symptoms were completely prevented by prophylactic PAF receptor inhibition or Kupffer cell depletion. Assessment of varied si-NP chemistries confirmed that toxicity level correlated to relative uptake of the carrier by liver Kupffer cells and that this toxicity mechanism is dependent on carrier endosome disruptive function. 4T1 tumor-bearing mice, which exhibit increased circulating leukocytes, displayed greater sensitivity to these toxicities. PAF-mediated toxicities were generalizable to commercial delivery reagent in vivo-jetPEI® and an MC3 lipid formulation matched to an FDA-approved nanomedicine. These collective results establish Kupffer cell release of PAF as a key mediator of siRNA nanocarrier toxicity and identify PAFR inhibition as an effective strategy to increase siRNA nanocarrier tolerated dose.
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