Follow the Arrows: Using a Co-Created Causal Loop Diagram to Explore Leverage Points to Strengthen Population Physical Activity Promotion in British Columbia, Canada.

BACKGROUND: Population physical activity promotion (PPAP) is one of the most effective noncommunicable disease prevention strategies, yet coordination is lacking around the world. Whole-of-system approaches and complex systems methods are called for to advance PPAP. This paper reports on a project which (1) used an Attributes Framework with system mapping (group model building and causal loop diagramming of feedback loops) and (2) identified potential leverage points to address the challenge of effective coordination of multisectoral PPAP in British Columbia. METHODS: Key findings from stakeholder interviews and workshops described the current system for PPAP in terms of attributes and dimensions in the framework. These were translated into variables and used in group model building. Participants prioritized the importance of variables to address the coordination challenge and then created causal loop diagrams in 3 small groups. One collective causal loop diagram was created, and top priority variables and associated feedback loops were highlighted to explore potential leverage points. RESULTS: Leverage points included the relationships and feedback loops among priority variables: political leadership, visible policy support and governance, connectivity for knowledge translation, collaborative multisector grants, multisector collaboration, and integrating co-benefits. Leveraging and altering "vicious" cyclical patterns to increase coordinated multisector PPAP are key. CONCLUSIONS: The Attributes Framework, group model building and causal loop diagrams, and emergent feedback loops were useful to explore potential leverage points to address the challenge of multisectoral coordination of PPAP. Future research could apply the same methods in other jurisdictions and compare and contrast resultant frameworks, variables, feedback loops, and leverage points.

Elusive boundaries: using an attribute framework to describe systems for population physical activity promotion.

The cost of physical inactivity is alarming, and calls for whole-of-system approaches to population physical activity promotion (PPAP) are increasing. One innovative approach to PPAP is to use a framework of interdependent attributes and associated dimensions of effective systems for chronic disease prevention. Describing system boundaries can be an elusive task, and this article reports on using an attribute framework as a first step in describing and then assessing and strengthening a provincial system for PPAP in British Columbia, Canada. Interviews were conducted with provincial stakeholders to gather perspectives regarding attributes of the system. Following this, two workshops were facilitated to document important stories about the current system for PPAP and link story themes with attributes. Results from interviews and workshops were summarized into key findings and a set of descriptive statements. One hundred and twenty-one statements provide depth, breadth and scope to descriptions of the system through the lens of an adapted framework including four attributes: (i) implementation of desired actions, (ii) resources, (iii) leadership and (iv) collaborative capacity. The attribute framework was a useful tool to guide a whole-of-system approach and turn elusive boundaries into rich descriptors of a provincial system for PPAP. Immediate implications for our research are to translate descriptive statements into variables, then assess the system through group model building and identify leverage points from a causal loop diagram to strengthen the system. Future application of this approach in other contexts, settings and health promotion and disease prevention topics is recommended.

CellCover Defines Conserved Cell Types and Temporal Progression in scRNA-seq Data across Mammalian Neocortical Development.

Accurate identification of cell classes across the tissues of living organisms is central in the analysis of growing atlases of single-cell RNA sequencing (scRNA-seq) data across biomedicine. Such analyses are often based on the existence of highly discriminating "marker genes" for specific cell classes which enables a deeper functional understanding of these classes as well as their identification in new, related datasets. Currently, marker genes are defined by methods that serially assess the level of differential expression (DE) of individual genes across landscapes of diverse cells. This serial approach has been extremely useful, but is limited because it ignores possible redundancy or complementarity across genes, that can only be captured by analyzing several genes at the same time. We wish to identify discriminating panels of genes. To efficiently explore the vast space of possible marker panels, leverage the large number of cells often sequenced, and overcome zero-inflation in scRNA-seq data, we propose viewing panel selection as a variation of the "minimal set-covering problem" in combinatorial optimization which can be solved with integer programming. In this formulation, the covering elements are genes, and the objects to be covered are cells of a particular class, where a cell is covered by a gene if that gene is expressed in that cell. Our method, CellCover, identifies a panel of marker genes in scRNA-seq data that covers one class of cells within a population. We apply this method to generate covering marker gene panels which characterize cells of the developing mouse neocortex as postmitotic neurons are generated from neural progenitor cells (NPCs). We show that CellCover captures cell class-specific signals distinct from those defined by DE methods and that CellCover's compact gene panels can be expanded to explore cell type specific function.Transfer learning experiments exploring these covering panels across in vivo mouse, primate, and human scRNA-seq datasets demonstrate that CellCover identifies markers of conserved cell classes in neurogenesis, as well as markers of temporal progression in the molecular identity of these cell types across development of the mammalian neocortex. The gene covering panels we identify across cell types and developmental time can be freely explored in visualizations across all the public data we use in this report at with NeMo Analytics [1] through https://nemoanalytics.org/p?l=CellCover . The code for CellCover is written in R and the Gurobi R interface and is available at [2].

A scoping review of complex systems methods used in population physical activity research: do they align with attributes of a whole system approach?

BACKGROUND: Complex systems approaches are increasingly used in health promotion and noncommunicable disease prevention research, policy and practice. Questions emerge as to the best ways to take a complex systems approach, specifically with respect to population physical activity (PA). Using an Attributes Model is one way to understand complex systems. We aimed to examine the types of complex systems methods used in current PA research and identify what methods align with a whole system approach as reflected by an Attributes Model. METHODS: A scoping review was conducted and two databases were searched. Twenty-five articles were selected and data analysis was based upon the following: the complex systems research methods used, research aims, if participatory methods were used and evidence of discussion regarding attributes of systems. RESULTS: There were three groups of methods used: system mapping, simulation modelling and network analysis. System mapping methods appeared to align best with a whole system approach to PA promotion because they largely aimed to understand complex systems, examined interactions and feedback among variables, and used participatory methods. Most of these articles focused on PA (as opposed to integrated studies). Simulation modelling methods were largely focused on examining complex problems and identifying interventions. These methods did not generally focus on PA or use participatory methods. While network analysis articles focused on examining complex systems and identifying interventions, they did not focus on PA nor use participatory methods. All attributes were discussed in some way in the articles. Attributes were explicitly reported on in terms of findings or were part of discussion and conclusion sections. System mapping methods appear to be well aligned with a whole system approach because these methods addressed all attributes in some way. We did not find this pattern with other methods. CONCLUSIONS: Future research using complex systems methods may benefit from applying the Attributes Model in conjunction with system mapping methods. Simulation modelling and network analysis methods are seen as complementary and could be used when system mapping methods identify priorities for further investigation (e.g. what interventions to implement or how densely connected relationships are in systems).

Current Breast Milk PFAS Levels in the United States and Canada: After All This Time, Why Don't We Know More?

BACKGROUND: Despite 20 y of biomonitoring studies of per- and polyfluoroalkyl substances (PFAS) in both serum and urine, we have an extremely limited understanding of PFAS concentrations in breast milk of women from the United States and Canada. The lack of robust information on PFAS concentrations in breast milk and implications for breastfed infants and their families were brought to the forefront by communities impacted by PFAS contamination. OBJECTIVES: The objectives of this work are to: a) document published PFAS breast milk concentrations in the United States and Canada; b) estimate breast milk PFAS levels from maternal serum concentrations in national surveys and communities impacted by PFAS; and c) compare measured/estimated milk PFAS concentrations to screening values. METHODS: We used three studies reporting breast milk concentrations in the United States and Canada We also estimated breast milk PFAS concentrations by multiplying publicly available serum concentrations by milk:serum partitioning ratios for perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), perfluorohexane sulfonate (PFHxS), and perfluorononanoic acid (PFNA). Measured and estimated breast milk concentrations were compared to children's drinking water screening values. DISCUSSION: Geometric means of estimated breast milk concentrations ranged over approximately two orders of magnitude for the different surveys/communities. All geometric mean and mean estimated and measured breast milk PFOA and PFOS concentrations exceeded drinking water screening values for children, sometimes by more than two orders of magnitude. For PFHxS and PFNA, all measured breast milk levels were below the drinking water screening values for children; the geometric mean estimated breast milk concentrations were close to-or exceeded-the children's drinking water screening values for certain communities. Exceeding a children's drinking water screening value does not indicate that adverse health effects will occur and should not be interpreted as a reason to not breastfeed; it indicates that the situation should be further evaluated. It is past time to have a better understanding of environmental chemical transfer to-and concentrations in-an exceptional source of infant nutrition. https://doi.org/10.1289/EHP10359.

Sex Differences in Health Status and Clinical Outcomes After Nonprimary Percutaneous Coronary Intervention.

BACKGROUND: Greater insight into sex-based differences in health status can lay the foundation for more equitable health care. This study compares differences in health status of women and men in the CPORT-E trial (Cardiovascular Patient Outcomes Research Team Non-Primary Percutaneous Coronary Intervention) undergoing nonprimary percutaneous coronary intervention. METHODS: We compared Seattle Angina Questionnaire scores at baseline, 6 weeks, and 9 months for 6851 women and 12 016 men undergoing nonprimary percutaneous coronary intervention. RESULTS: Proportions of angina-free patients increased from 26.2% and 29.8% at baseline to 71.6% and 78.7% at 6 weeks to 78.1% and 83.0% at 9 months in women and men, respectively (P<0.001 for all). After adjusting for clinical and procedural characteristics as well as baseline angina, freedom from angina in women was 34% less likely at 6 weeks (odds ratio, 0.66 [95% CI, 0.61-0.71]; P<0.001) and 32% less likely at 9 months (odds ratio, 0.68 [95% CI, 0.62-0.74]; P<0.001) compared with men. CONCLUSIONS: Although health status increased significantly after percutaneous coronary intervention in both women and men, women had poorer health status outcomes than men before and after percutaneous coronary intervention. Additional investigation into therapies that address the causes of poorer health status in women with coronary artery disease is needed. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT00549796.

Randomized trial of two artificial intelligence coaching interventions to increase physical activity in cancer survivors.

Physical activity (PA) has numerous health benefits. Personalized coaching may increase adherence to PA recommendations, but it is challenging to deliver personalized coaching in a scalable manner. The objective of our study was to determine whether novel artificially intelligent (AI) coaching interventions increase PA among overweight or obese, physically inactive cancer survivors compared to a control arm that receives health information. We conducted a single-center, three-arm randomized trial with equal allocation to (1) voice-assisted AI coaching delivered by smart speaker (MyCoach), (2) autonomous AI coaching delivered by text message (SmartText), and (3) control. Data collection was automated via sensors and voice technology, effectively masking outcome ascertainment. The primary outcome was change in mean steps per day from baseline to the end of follow-up at 4 weeks. Of the 42 randomized participants, 91% were female, and 36% were Black; mean age was 62.1 years, and mean BMI was 32.9 kg/m2. The majority were breast cancer survivors (85.7%). At the end of 4 weeks follow-up, steps increased in the MyCoach arm by an average of 3618.2 steps/day; the net gain in this arm was significantly greater [net difference = 3568.9 steps/day (95% CI: 1483-5655), P value <0.001] compared to control arm, and [net difference = 2160.6 steps/day (95% CI: 11-4310), P value 0.049] compared to SmartText. In conclusion, AI-based voice-assisted coaching shows promise as a practical method of delivering scalable, individualized coaching to increase physical activity in sedentary cancer survivors. Additional research is needed to replicate these findings in a broader population of cancer survivors and to investigate the effects of these interventions in the general population.ClinicalTrials.gov Identifier: NCT03212079, July 11, 2017, https://clinicaltrials.gov/ct2/show/NCT03212079 .

Does ozone inhalation cause adverse metabolic effects in humans? A systematic review.

We utilized a practical, transparent approach for systematically reviewing a chemical-specific evidence base. This approach was used for a case study of ozone inhalation exposure and adverse metabolic effects (overweight/obesity, Type 1 diabetes [T1D], Type 2 diabetes [T2D], and metabolic syndrome). We followed the basic principles of systematic review. Studies were defined as "Suitable" or "Supplemental." The evidence for Suitable studies was characterized as strong or weak. An overall causality judgment for each outcome was then determined as either causal, suggestive, insufficient, or not likely. Fifteen epidemiologic and 33 toxicologic studies were Suitable for evidence synthesis. The strength of the human evidence was weak for all outcomes. The toxicologic evidence was weak for all outcomes except two: body weight, and impaired glucose tolerance/homeostasis and fasting/baseline hyperglycemia. The combined epidemiologic and toxicologic evidence was categorized as weak for overweight/obesity, T1D, and metabolic syndrome,. The association between ozone exposure and T2D was determined to be insufficient or suggestive. The streamlined approach described in this paper is transparent and focuses on key elements. As systematic review guidelines are becoming increasingly complex, it is worth exploring the extent to which related health outcomes should be combined or kept distinct, and the merits of focusing on critical elements to select studies suitable for causal inference. We recommend that systematic review results be used to target discussions around specific research needs for advancing causal determinations.

Bias and noise in proportion estimation: A mixture psychophysical model.

The importance of proportional reasoning has long been recognized by psychologists and educators, yet we still do not have a good understanding of how humans mentally represent proportions. In this paper we present a psychophysical model of proportion estimation, extending previous approaches. We assumed that proportion representations are formed by representing each magnitude of a proportion stimuli (the part and its complement) as Gaussian activations in the mind, which are then mentally combined in the form of a proportion. We next derived the internal representation of proportions, including bias and internal noise parameters -capturing respectively how our estimations depart from true values and how variable estimations are. Methodologically, we introduced a mixture of components to account for contaminating behaviors (guessing and reversal of responses) and framed the model in a hierarchical way. We found empirical support for the model by testing a group of 4th grade children in a spatial proportion estimation task. In particular, the internal density reproduced the asymmetries (skewedness) seen in this and in previous reports of estimation tasks, and the model accurately described wide variations between subjects in behavior. Bias estimates were in general smaller than by using previous approaches, due to the model's capacity to absorb contaminating behaviors. This property of the model can be of especial relevance for studies aimed at linking psychophysical measures with broader cognitive abilities. We also recovered higher levels of noise than those reported in discrimination of spatial magnitudes and discuss possible explanations for it. We conclude by illustrating a concrete application of our model to study the effects of scaling in proportional reasoning, highlighting the value of quantitative models in this field of research.

How Many Urine Samples Are Needed to Accurately Assess Exposure to Non-Persistent Chemicals? The Biomarker Reliability Assessment Tool (BRAT) for Scientists, Research Sponsors, and Risk Managers.

In epidemiologic and exposure research, biomonitoring is often used as the basis for assessing human exposure to environmental chemicals. Studies frequently rely on a single urinary measurement per participant to assess exposure to non-persistent chemicals. However, there is a growing consensus that single urine samples may be insufficient for adequately estimating exposure. The question then arises: how many samples would be needed for optimal characterization of exposure? To help researchers answer this question, we developed a tool called the Biomarker Reliability Assessment Tool (BRAT). The BRAT is based on pharmacokinetic modeling simulations, is freely available, and is designed to help researchers determine the approximate number of urine samples needed to optimize exposure assessment. The BRAT performs Monte Carlo simulations of exposure to estimate internal levels and resulting urinary concentrations in individuals from a population based on user-specified inputs (e.g., biological half-life, within- and between-person variability in exposure). The BRAT evaluates-through linear regression and quantile classification-the precision/accuracy of the estimation of internal levels depending on the number of urine samples. This tool should guide researchers towards more robust biomonitoring and improved exposure classification in epidemiologic and exposure research, which should in turn improve the translation of that research into decision-making.

Factors affecting interpretation of national biomonitoring data from multiple countries: BPA as a case study.

INTRODUCTION: The use of biomonitoring data as an indicator of national levels of human exposure to environmental chemicals has grown in importance and prevalence. Nationally representative urinary bisphenol A (BPA) data are now available for Canada, the United States and Korea. Here we address the following questions: Are urinary BPA data from these countries comparable? What can be discerned regarding geographic and/or temporal similarities or differences? Are there generalizable lessons to be learned regarding comparison of biomonitoring results from different countries? METHODS: We examined underlying methods and resultant urinary BPA data from national surveys of three countries: Canada (Canadian Health Measures Survey, CHMS, 2009-2015); United States (National Health and Nutrition Examination Survey, NHANES, 2009-2014); and Korea (Korean National Environmental Health Survey, KoNEHS, 2009-2014). We estimated BPA daily intakes on both a volume- and creatinine-adjusted basis. RESULTS: The three countries use similar methods for analyzing urine samples for BPA and participate in external proficiency testing with acceptable results. Field blanks are only used in the CHMS program. There were program-specific differences in fasting times of participants. Median urinary BPA levels in Canada remained relatively constant over the three cycles (1.1-1.2 ng/ml), while US levels decreased (from 1.9 to 1.3 ng/ml) and Korean levels increased (from 0.7 to 1.1 ng/ml) over similar time periods. The most recent survey year data indicate that levels do not differ substantially across countries. Canadian urinary BPA levels have been stable; the subtle, non-significant decrease in intakes may be due to higher body weight in the more recent Canadian surveys. In contrast, the decrease in intakes in the US appears to be due to decreases in urinary BPA as body weights in the US have been stable. Estimated 95th percentile intakes are over an order of magnitude below current health-based guidance values. DISCUSSION: Our assessment of urinary BPA data from Canada, the US and Korea indicates that methodological differences, methods for dilution adjustment, and population characteristics should be carefully considered when interpreting biomonitoring data. Despite the plethora of publications describing issues with use of creatinine levels for urinary dilution adjustment, there have been no major methodological advances that would assist in interpreting urinary chemical data. A combination of biomonitoring and traditional exposure assessment approaches may be needed to fully assess human exposures to BPA and other chemicals. CONCLUSIONS: National biomonitoring surveys provide important information on population levels of chemicals such as BPA and can assist in understanding temporal and geographic similarities, differences, and trends. However, caution must be exercised when using these data to draw anything but broad conclusions, due to both intercountry methodological differences and factors affecting urinary chemical levels that are still poorly understood. While the issues raised in this paper do not appear to be a major concern specifically for the national-scale monitoring of BPA described here, they must be considered when comparing data for other chemicals measured as part of both national and smaller-scale biomonitoring-based research as well as for BPA data from other studies.

Biomonitoring and Nonpersistent Chemicals-Understanding and Addressing Variability and Exposure Misclassification.

PURPOSE OF REVIEW: We offer here a review of intraindividual variability in urinary biomarkers for assessing exposure to nonpersistent chemicals. We provide thoughts on how to better evaluate exposure to nonpersistent chemicals. RECENT FINDINGS: We summarized reported values of intraclass correlation coefficients and found that most values fall into categories that indicate only poor to good reproducibility. Even within the "good" classification, a large percentage of study participants is likely to be misclassified as to their exposure. There is sufficient information to support the statement that studies using only one spot measurement of a nonpersistent chemical will be unreliable. It is unequivocal that multiple samples have to be collected over a period of toxicological relevance and with consideration of exposure patterns. Sponsors of research and researchers themselves should be vocal about ensuring that sufficient resources are made available to properly characterize exposures when studying nonpersistent chemicals. Otherwise, we will continue to see an ever-growing body of literature yielding inconsistent and/or uninterpretable results.

ExpoQual: Evaluating measured and modeled human exposure data.

Recent rapid technological advances are producing exposure data sets for which there are no available data quality assessment tools. At the same time, regulatory agencies are moving in the direction of data quality assessment for environmental risk assessment and decision-making. A transparent and systematic approach to evaluating exposure data will aid in those efforts. Any approach to assessing data quality must consider the level of quality needed for the ultimate use of the data. While various fields have developed approaches to assess data quality, there is as yet no general, user-friendly approach to assess both measured and modeled data in the context of a fit-for-purpose risk assessment. Here we describe ExpoQual, an instrument developed for this purpose which applies recognized parameters and exposure data quality elements from existing approaches for assessing exposure data quality. Broad data streams such as quantitative measured and modeled human exposure data as well as newer and developing approaches can be evaluated. The key strength of ExpoQual is that it facilitates a structured, reproducible and transparent approach to exposure data quality evaluation and provides for an explicit fit-for-purpose determination. ExpoQual was designed to minimize subjectivity and to include transparency in aspects based on professional judgment. ExpoQual is freely available on-line for testing and user feedback (exposurequality.com).

Effectiveness of viable cryopreserved placental membranes for management of diabetic foot ulcers in a real world setting.

In a multicenter randomized controlled trial (RCT), the use of viable cryopreserved placental membrane (vCPM) for chronic diabetic foot ulcers (DFUs) resulted in a higher proportion of wound closure in comparison to good wound care: 62% versus 21% (p < 0.01). However, patients in RCTs are not representative of daily physician practice. Healthcare databases serve as a valuable tool to evaluate therapy effectiveness and to supplement evidence from RCTs. The objective of this study was to evaluate the effectiveness of vCPM for DFU management using Net Health's WoundExpert® electronic health records (EHR). The primary endpoint was the proportion of DFUs that achieved complete closure. Other endpoints included time and number of grafts to closure, probability of wound closure by week 12, and the number of wound-related infections and amputations. De-identified EHR data for 360 patients with 441 wounds treated with vCPM were extracted from the database. Average patient age was 63.7 years with a mean wound size of 5.1 cm2 and an average wound duration of 102 days prior to vCPM treatment. For evaluation of clinical outcomes, 350 DFUs larger than 0.25 cm2 at baseline were analyzed. Closure at the end of treatment was achieved in 59.4% of wounds with a median treatment duration of 42.0 days and 4 applications of vCPM. The probability of wound closure at week 12 was 71%, and the number of amputations and wound-related infections was 13 (3.0%) and 9 (2.0%), respectively. Data also demonstrated a correlation between wound size and closure rate as well as a correlation between > 50% wound area reduction by week 4 and wound closure by week 12. The results of this study mirror previous RCT efficacy data, supporting the benefits of vCPM for DFU management. These results can also influence policy and treatment decisions regarding advanced vCPM technology.

Increasing Physical Activity Amongst Overweight and Obese Cancer Survivors Using an Alexa-Based Intelligent Agent for Patient Coaching: Protocol for the Physical Activity by Technology Help (PATH) Trial.

BACKGROUND: Physical activity has established health benefits, but motivation and adherence remain challenging. OBJECTIVE: We designed and launched a three-arm randomized trial to test artificial intelligence technology solutions to increase daily physical activity in cancer survivors. METHODS: A single-center, three-arm randomized clinical trial with an allocation ration of 1:1:1: (A) control, in which participants are provided written materials about the benefits of physical activity; (B) text intervention, where participants receive daily motivation from a fully automated, data-driven algorithmic text message via mobile phone (Coachtext); and (C) Voice Assist intervention, where participants are provided with an in-home on demand autonomous Intelligent Agent using data driven Interactive Digital Voice Assist on the Amazon Alexa/Echo (MyCoach). RESULTS: The study runs for 5 weeks: a one-week run-in to establish baseline, followed by 4 weeks of intervention. Data for study outcomes is collected automatically through a wearable sensor, and data are transferred in real-time to the study server. The recruitment goal is 42 participants, 14 in each arm. Electronic health records are used to prescreen candidates, with 39 participants recruited to date. DISCUSSION: This study aims to investigate the effects of different types of intelligent technology solutions on promoting physical activity in cancer survivors. This innovative approach can easily be expanded and customized to other interventions. Early lessons from our initial participants are helping us develop additional advanced solutions to improve health outcomes. TRIAL REGISTRATION: Retrospectively registered on July 10, 2017 at ClinicalTrials.gov: NCT03212079; https://clinicaltrials.gov/ct2/show/NCT03212079 (Archived by WebCite at http://www.webcitation.org/6wgvqjTji).

Nonprimary PCI at hospitals without cardiac surgery on-site: Consistent outcomes for all?

BACKGROUND: The CPORT-E trial showed the noninferiority of nonprimary percutaneous coronary intervention (PCI) at hospitals without cardiac surgery on-site (SoS) compared with hospitals with SoS for 6-week mortality and 9-month major adverse cardiac events (MACE). However, target vessel revascularization (TVR) was increased at non-SoS hospitals. Therefore, we aimed to determine the consistency of the CPORT-E trial findings across the spectrum of enrolled patients. METHODS: Post hoc subgroup analyses of 6-week mortality and 9-month MACE, defined as the composite of death, Q-wave myocardial infarction, or TVR, were performed. Patients with and without 9-month TVR and rates of related outcomes were compared. RESULTS: There was no interaction between SoS status and clinically relevant subgroups for 6-week mortality or 9-month MACE (P for any interaction=.421 and .062, respectively). In addition to increased 9-month rates of TVR and diagnostic catheterization at hospitals without SoS, non-TVR was also increased (2.7% vs 1.9%, P=.002); there was no difference in myocardial infarction-driven TVR, non-TVR, or diagnostic catheterization. Predictors of 9-month TVR included intra-aortic balloon pump use, any index PCI complication, and 3-vessel PCI, whereas predictors of freedom from TVR included SoS, discharge on a P2Y12 inhibitor, and stent implantation. CONCLUSIONS: The noninferiority of nonprimary PCI at non-SoS hospitals was consistent across clinically relevant subgroups. Elective PCI at an SoS hospital conferred a TVR benefit which may be related to a lower rate of referral for diagnostic catheterization for reasons other than myocardial infarction.

Systematic review of the literature on triclosan and health outcomes in humans.

The ability of epidemiologic evidence to inform regulatory decisions is largely dependent on the coherence and quality of the published literature. This systematic review examines the quality and consistency of studies assessing health outcomes associated with exposure to triclosan (TCS), an antimicrobial chemical with a short physiologic half-life. We used elements of the Biomonitoring, Environmental Epidemiology, and Short-Lived Chemicals instrument to evaluate aspects of study quality. Each methodological domain - overall design, exposure assessment, and data analysis - was categorized according to three tiers where Tier 1 indicated the highest quality. We also examined consistency of methods, results and reporting as considerations for weight of evidence (WOE) assessment. Studies were considered sufficiently comparable if they addressed the same or similar research questions. Forty-two studies met the criteria for inclusion. Only one randomized cross-over clinical trial of TCS was assigned to Tier 1 for all three domains. Most other studies were assigned to Tier 3 for at least one domain. Although the available literature examined more than 100 different health endpoints and reported hundreds of different measures of association, few studies were considered comparable. For reported measures of association, most were not significantly different from the null; the few statistically significant results represented isolated findings without a discernable across- or within-study pattern. We conclude that the current body of epidemiologic literature does not allow a meaningful WOE assessment due to methodological limitations of individual studies and lack of inter-study consistency. On the other hand, methodologically stronger studies may be used to inform future research.

Critical and systematic evaluation of data for estimating human exposures to 2,4-dichlorophenoxyacetic acid (2,4-D) - quality and generalizability.

The herbicide 2,4-dichlorophenoxyacetic acid (2,4-D) has been commercially available since the 1940's. Despite decades of data on 2,4-D in food, air, soil, and water, as well as in humans, the quality the quality of these data has not been comprehensively evaluated. Using selected elements of the Biomonitoring, Environmental Epidemiology, and Short-lived Chemicals (BEES-C) instrument (temporal variability, avoidance of sample contamination, analyte stability, and urinary methods of matrix adjustment), the quality of 156 publications of environmental- and biomonitoring-based 2,4-D data was examined. Few publications documented steps were taken to avoid sample contamination. Similarly, most studies did not demonstrate the stability of the analyte from sample collection to analysis. Less than half of the biomonitoring publications reported both creatinine-adjusted and unadjusted urine concentrations. The scope and detail of data needed to assess temporal variability and sources of 2,4-D varied widely across the reviewed studies. Exposures to short-lived chemicals such as 2,4-D are impacted by numerous and changing external factors including application practices and formulations. At a minimum, greater transparency in reporting of quality control measures is needed. Perhaps the greatest challenge for the exposure community is the ability to reach consensus on how to address problems specific to short-lived chemical exposures in observational epidemiology investigations. More extensive conversations are needed to advance our understanding of human exposures and enable interpretation of these data to catch up to analytical capabilities. The problems defined in this review remain exquisitely difficult to address for chemicals like 2,4-D, with short and variable environmental and physiological half-lives and with exposures impacted by numerous and changing external factors.

Heparin versus bivalirudin for non-primary percutaneous coronary intervention: A post-Hoc analysis of the CPORT-E trial.

OBJECTIVES: To compare bivalirudin to heparin during non-primary percutaneous coronary intervention (PCI). BACKGROUND: The optimal anticoagulant to support PCI remains uncertain. METHODS: We performed a propensity score-based analysis comparing clinical outcomes of patients receiving heparin to those receiving bivalirudin during non-primary PCI. RESULTS: Of 18,867 patients in the Cardiovascular Patient Outcomes Research Team Non-Primary PCI (CPORT-E) trial, we selected 7,913 patients undergoing non-staged PCI of whom 57.3% received heparin and 42.7% received bivalirudin. In-hospital myocardial infarction occurred in 4.4% of patients receiving bivalirudin and 3.0% of patients receiving heparin (relative risk [RR] 1.5, 95% confidence interval [CI] 1.1-2.1, P = 0.022); this difference persisted at 6 weeks (5.0% vs. 3.6%, RR 1.4, 95% CI 1.0-1.8, P = 0.041). There was no difference in all-cause mortality either in-hospital (0.2% vs. 0.1% for heparin vs. bivalirudin, P = 0.887) or at 6 weeks (0.5% vs. 0.7%, P = 0.567). In-hospital bleeding requiring transfusion occurred in 0.9% of patients receiving bivalirudin and 1.9% of patients receiving heparin (RR 0.4, 95% CI 0.3-0.7, P <0.001), but there was no difference at 6 weeks (2.7% for heparin vs. 1.9% for bivalirudin, RR 0.7, 95% CI 0.5-1.0, P = 0.062). CONCLUSIONS: In patients undergoing non-primary PCI at hospitals without on-site cardiac surgery, bivalirudin was associated with a decreased risk of in-hospital bleeding requiring transfusion and an increased risk of in-hospital MI compared to heparin. © 2017 Wiley Periodicals, Inc.