Publications

BACKGROUND

Hazard identification, risk assessment, regulatory, and policy activity are usually conducted on a chemical-by-chemical basis. Grouping chemicals into categories or classes is an underutilized approach that could make risk assessment and management of chemicals more efficient for regulators.

OBJECTIVE AND METHODS

While there are some available methods and regulatory frameworks that include the grouping of chemicals (e.g.,same molecular mechanism or similar chemical structure) there has not been a comprehensive evaluation of these different approaches nor a recommended course of action to better consider chemical classes in decision-making. This manuscript: 1) reviews current national and international approaches to grouping; 2) describes how groups could be defined based on the decision context (e.g., hazard/risk assessment, restrictions, prioritization, product development) and scientific considerations (e.g., intrinsic physical-chemical properties); 3) discusses advantages of developing a decision tree approach for grouping; 4) uses ortho-phthalates as a case study to identify and organize frameworks that could be used across agencies; and 5) discusses opportunities to advance the class concept within various regulatory decision-making scenarios.

RESULTS

Structural similarity was the most common grouping approach for risk assessment among regulatory agencies (national and state level) and non-regulatory organizations, albeit with some variations in its definition. Toxicity to the same target organ or to the same biological function was also used in a few cases. The phthalates case study showed that a decision tree approach for grouping should include questions about uses regulated by other agencies to encourage more efficient, coherent, and protective chemical risk management.

DISCUSSION AND CONCLUSION

Our evaluation of how classes of chemicals are defined and used identified commonalities and differences based on regulatory frameworks, risk assessments, and business strategies. We also identified that using a class-based approach could result in a more efficient process to reduce exposures to multiple hazardous chemicals and, ultimately, reduce health risks. We concluded that, in the absence of a prescribed method, a decision tree approach could facilitate the selection of chemicals belonging to a pre-defined class (e.g., chemicals with endocrine-disrupting activity; organohalogen flame retardants [OFR]) based on the decision-making context (e.g., regulatory risk management).

The manufacture and production of industrial chemicals continues to increase, with hundreds of thousands of chemicals and chemical mixtures used worldwide, leading to widespread population exposures and resultant health impacts. Low-wealth communities and communities of color often bear disproportionate burdens of exposure and impact; all compounded by regulatory delays to the detriment of public health. Multiple authoritative bodies and scientific consensus groups have called for actions to prevent harmful exposures via improved policy approaches. We worked across multiple disciplines to develop consensus recommendations for health-protective, scientific approaches to reduce harmful chemical exposures, which can be applied to current US policies governing industrial chemicals and environmental pollutants. This consensus identifies five principles and scientific recommendations for improving how agencies like the US Environmental Protection Agency (EPA) approach and conduct hazard and risk assessment and risk management analyses: (1) the financial burden of data generation for any given chemical on (or to be introduced to) the market should be on the chemical producers that benefit from their production and use; (2) lack of data does not equate to lack of hazard, exposure, or risk; (3) populations at greater risk, including those that are more susceptible or more highly exposed, must be better identified and protected to account for their real-world risks; (4) hazard and risk assessments should not assume existence of a "safe" or "no-risk" level of chemical exposure in the diverse general population; and (5) hazard and risk assessments must evaluate and account for financial conflicts of interest in the body of evidence. While many of these recommendations focus specifically on the EPA, they are general principles for environmental health that could be adopted by any agency or entity engaged in exposure, hazard, and risk assessment. We also detail recommendations for four priority areas in companion papers (exposure assessment methods, human variability assessment, methods for quantifying non-cancer health outcomes, and a framework for defining chemical classes). These recommendations constitute key steps for improved evidence-based environmental health decision-making and public health protection.

BACKGROUND

Myocardial injury in patients with COVID-19 and suspected cardiac involvement is not well understood.

OBJECTIVES

The purpose of this study was to characterize myocardial injury in a multicenter cohort of patients with COVID-19 and suspected cardiac involvement referred for cardiac magnetic resonance (CMR).

METHODS

This retrospective study consisted of 1,047 patients from 18 international sites with polymerase chain reaction-confirmed COVID-19 infection who underwent CMR. Myocardial injury was characterized as acute myocarditis, nonacute/nonischemic, acute ischemic, and nonacute/ischemic patterns on CMR.

RESULTS

In this cohort, 20.9% of patients had nonischemic injury patterns (acute myocarditis: 7.9%; nonacute/nonischemic: 13.0%), and 6.7% of patients had ischemic injury patterns (acute ischemic: 1.9%; nonacute/ischemic: 4.8%). In a univariate analysis, variables associated with acute myocarditis patterns included chest discomfort (OR: 2.00; 95% CI: 1.17-3.40, P = 0.01), abnormal electrocardiogram (ECG) (OR: 1.90; 95% CI: 1.12-3.23; P = 0.02), natriuretic peptide elevation (OR: 2.99; 95% CI: 1.60-5.58; P = 0.0006), and troponin elevation (OR: 4.21; 95% CI: 2.41-7.36; P < 0.0001). Variables associated with acute ischemic patterns included chest discomfort (OR: 3.14; 95% CI: 1.04-9.49; P = 0.04), abnormal ECG (OR: 4.06; 95% CI: 1.10-14.92; P = 0.04), known coronary disease (OR: 33.30; 95% CI: 4.04-274.53; P = 0.001), hospitalization (OR: 4.98; 95% CI: 1.55-16.05; P = 0.007), natriuretic peptide elevation (OR: 4.19; 95% CI: 1.30-13.51; P = 0.02), and troponin elevation (OR: 25.27; 95% CI: 5.55-115.03; P < 0.0001). In a multivariate analysis, troponin elevation was strongly associated with acute myocarditis patterns (OR: 4.98; 95% CI: 1.76-14.05; P = 0.003).

CONCLUSIONS

In this multicenter study of patients with COVID-19 with clinical suspicion for cardiac involvement referred for CMR, nonischemic and ischemic patterns were frequent when cardiac symptoms, ECG abnormalities, and cardiac biomarker elevations were present.