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Assessing the ecological risk of contaminants in the field typically involves consideration of a complex mixture of compounds which may or may not be detected via instrumental analyses. Further, there are insufficient data to predict the potential biological effects of many detected compounds, leading to their being characterized as contaminants of emerging concern (CECs). Over the past several years, advances in chemistry, toxicology, and bioinformatics have resulted in a variety of concepts and tools that can enhance the pragmatic assessment of the ecological risk of CECs. The present Focus article describes a 10+- year multiagency effort supported through the U.S. Great Lakes Restoration Initiative to assess the occurrence and implications of CECs in the North American Great Lakes. State-of-the-science methods and models were used to evaluate more than 700 sites in about approximately 200 tributaries across lakes Ontario, Erie, Huron, Michigan, and Superior, sometimes on multiple occasions. Studies featured measurement of up to 500 different target analytes in different environmental matrices, coupled with evaluation of biological effects in resident species, animals from in situ and laboratory exposures, and in vitro systems. Experimental taxa included birds, fish, and a variety of invertebrates, and measured endpoints ranged from molecular to apical responses. Data were integrated and evaluated using a diversity of curated knowledgebases and models with the goal of producing actionable insights for risk assessors and managers charged with evaluating and mitigating the effects of CECs in the Great Lakes. This overview is based on research and data captured in approximately about 90 peer-reviewed journal articles and reports, including approximately about 30 appearing in a virtual issue comprised of highlighted papers published in Environmental Toxicology and Chemistry or Integrated Environmental Assessment and Management. Environ Toxicol Chem 2023;42:2506-2518. © 2023 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA., (© 2023 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

Objective: To identify factors influencing cardiologists' and hospitalists' decisions regarding palliative care referral among hospitalised patients with advanced heart failure., Design: An exploratory, randomised vignette-based survey., Setting: Cardiology and hospitalist divisions at three Michigan State institutions and the Society of Hospital Medicine's Michigan Chapter., Participants: 145 hospitalists and 64 cardiologists., Outcome Measures: Primary outcomes included participants' reports of their likelihood of referring a standardised patient with an acute heart failure exacerbation with multiple prior hospital admissions and acute renal failure to palliative care (scale of 0%-100%) after the initial stem and after being cued with three randomised vignette modifiers, including the presence versus the absence of continuity with an outpatient cardiologist; the presence versus the absence of documented advance care planning; and the patient voicing that he is accepting of his severe illness versus wanting everything done. Adjusted generalised linear models and predictive margins were used to evaluate the impact of each randomised modifier on referral decisions. An interaction term evaluated the effect of provider specialty on outcomes. Secondary outcomes included participants' reports of their general practices around palliative care delivery to hospitalised patients with heart failure., Results: Response rate was 31.3%. Predictive margins from generalised linear models demonstrated a statistically significantly higher likelihood of referral to inpatient palliative care if the patient lacked an outpatient cardiologist (mean difference: 6.3% (95% CI 1.8% to 10.8%)); had prior advance care planning documentation (mean difference: 9.7% (95% CI 4.4% to 15.0%)); and was accepting of illness severity (mean difference: 29.6% (95% CI 24.8% to 34.4%)). No interaction effect was noted based on provider specialty. Most hospitalists and cardiologists were unaware of palliative care guidelines for patients with heart failure (74.3% vs 70.3%, p=0.71)., Conclusions: A number of patient and provider factors influence palliative care referral decisions in hospitalised patients with advanced heart failure., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background In patients with heart failure (HF), malnutrition and dietary sodium excess are common and may worsen outcomes. No prior studies have provided low-sodium, nutritionally complete meals following HF hospitalization. Methods and Results The GOURMET-HF study (Geriatric Out-of-Hospital Randomized Meal Trial in Heart Failure) randomized patients discharged from HF hospitalization to 4 weeks of home-delivered sodium-restricted Dietary Approaches to Stop Hypertension meals (DASH/SRD; 1500 mg sodium/d) versus usual care. The primary outcome was the between-group change in the Kansas City Cardiomyopathy Questionnaire summary score from discharge to 4 weeks postdischarge. Additional outcomes included changes in the Kansas City Cardiomyopathy Questionnaire clinical summary score and cardiac biomarkers. All patients were followed 12 weeks for death/all-cause readmission and potential diet-related adverse events (symptomatic hypotension, hyperkalemia, acute kidney injury). Sixty-six patients were randomized 1:1 at discharge to DASH/SRD versus usual care (age, 71±8 years; 30% female; ejection fraction, 39±18%). The Kansas City Cardiomyopathy Questionnaire summary score increased similarly between groups (DASH/SRD 46±23-59±20 versus usual care 43±19-53±24; P=0.38), but the Kansas City Cardiomyopathy Questionnaire clinical summary score increase tended to be greater in DASH/SRD participants (47±22-65±19 versus 45±20-55±26; P=0.053). Potentially diet-related adverse events were uncommon; 30-day HF readmissions (11% versus 27%; P=0.06) and days rehospitalized within that timeframe (17 versus 55; P=0.055) trended lower in DASH/SRD participants. Conclusions Home-delivered DASH/SRD after HF hospitalization appeared safe in selected patients and had directionally favorable effects on HF clinical status and 30-day readmissions. Larger studies are warranted to clarify the effects of postdischarge nutritional support in patients with HF. Clinical Trial Registration URL: https://www.clinicaltrials.gov . Unique identifier: NCT02148679.

Objective: To determine how all-cause hospitalizations within 12 months preceding an index heart failure (HF) hospitalization affect risk stratification for 30-day all-cause readmission., Patients and Methods: Early readmission of inpatients with HF is challenging to predict, yet this outcome is used to compare hospital performance and guide reimbursement. Most risk models do not consider the potentially important variable of prior admissions. We analyzed Medicare inpatients with HF aged 66 years or older admitted to 14 Michigan community hospitals from October 1, 2002, to March 31, 2003, and from January 1 to June 30, 2004. Clinical data were obtained from admission charts, hospitalization dates from Centers for Medicare & Medicaid Services (CMS) claims, and mortality dates from the Social Security Death Index. We used mixed-effects logistic regression and reclassification indices to evaluate the ability of a CMS chart-based readmission risk model, prior admissions, and their combination to predict 30-day readmission in survivors of the index HF hospitalization., Results: Of 1807 patients, 43 (2.4%) died during the index admission; 476 of 1764 survivors (27%) were readmitted 30 or fewer days after discharge. Adjusted for the CMS readmission model, prior admissions significantly increased the odds of 30-day readmission (1 vs 0: odds ratio, 4.67; 95% CI, 3.37-6.46; ≥2 vs 0: odds ratio, 6.49; 95% CI, 4.93-8.55; both P<.001), improved model discrimination (c statistic, 0.61-0.74, P<.001), and reclassified many patients (net reclassification index, 0.40; integrated discrimination index, 0.12)., Conclusion: In Medicare inpatients with HF, prior all-cause admissions strongly increase all-cause readmission risk and markedly improve risk stratification for 30-day readmission., (Copyright © 2014 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.)

Background: Hospitalizations for decompensated heart failure (HF) are thought to increase long-term mortality. However, previous reports focus on newly hospitalized HF patients or clinical trial populations and do not always adjust for baseline mortality risk. We hypothesized that the number of HF hospitalizations within the prior 12 months would improve overall mortality risk stratification, particularly in otherwise "low-risk" HF inpatients., Methods: We studied 2221 HF patients admitted to 14 Michigan community hospitals during 2002-2004. We estimated 1-year mortality using the multivariable (Enhanced Feedback For Effective Cardiac Treatment [EFFECT]) model and classified patients as low (EFFECT <90), moderate (90-120), and high risk (>120). We used logistic regression and stratified Cox proportional hazard modeling to explore the overall EFFECT model performance and the influence of HF hospitalizations within the prior 12 months on mortality risk., Results: The EFFECT model adequately predicted and stratified for 1-year mortality (odds ratio 1.35 [95% confidence interval (CI), 1.30-1.40] per 10 points, P <.001, C-statistic 0.698), with low-, moderate-, and high-risk group mortality 18%, 35%, and 58%, respectively. The number of prior HF hospitalizations only modestly improved overall discrimination (C-statistic 0.704, P=.04). However, in low-risk patients the number of prior HF hospitalizations progressively increased the hazard for 1-year mortality (none: mortality 13%; 1: mortality 20%, hazard ratio [HR] 1.50 (95% CI, 0.86-2.60), P=.15; 2 or 3: mortality 27%, HR 2.24 (95% CI, 1.39-3.60); P=.001; 4 or more: mortality 31%, HR 2.80 (95% CI, 1.70-4.63); P <.001; P <.001 for trend). There was no consistent relationship between prior HF hospitalizations and 1-year mortality in moderate- or high-risk HF patients., Conclusion: In otherwise "low-risk" HF inpatients, a history of 2 or more HF hospitalizations within the prior 12 months markedly increases 1-year mortality risk. This easily obtained information could help allocate specialized HF resources to the subset of "low-risk" patients most likely to benefit., (Published by Elsevier Inc.)