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Background Although there has been a decrease in the incidence of ST-segment-elevation myocardial infarction (STEMI) in the United States, this trend might be stagnant or increasing in young women. We assessed the trends, characteristics, and outcomes of STEMI in women aged 18 to 55 years. Methods and Results We identified 177 602 women aged 18 to 55 with the primary diagnosis of STEMI from the National Inpatient Sample during years 2008 to 2019. We performed trend analyses to assess hospitalization rates, cardiovascular disease (CVD) risk factor profile, and in-hospital outcomes stratified by three age subgroups (18-34, 35-44, and 45-55 years). We found STEMI hospitalization rates were decreased in the overall study cohort from 52 per 100 000 hospitalizations in 2008 to 36 per 100 000 in 2019. This was driven by decreased proportion of hospitalizations in women aged 45 to 55 years (74.2% to-71.7%; P <0.001). Proportion of STEMI hospitalizationincreased in women aged 18-34 (4.7%-5.5%; P <0.001) and 35-44 years (21.2%-22.7%; P <0.001). The prevalence of traditional and non-traditional female-specific or female-predominant CVD risk factors increased in all age subgroups. The adjusted odds of in-hospital mortality in the overall study cohort and age subgroups were unchanged throughout the study period. Additionally, we observed an increase in the adjusted odds of cardiogenic shock, acute stroke, and acute kidney injury in the overall cohort over the study period. Conclusions STEMI hospitalizations are increasing among women aged <45 years, and in-hospital mortality has not changed over the past 12 years in women aged <55 years. Future studies on the optimization of risk assessment and management of STEMI in young women are urgently needed.

The COVID-19 pandemic is presenting a disproportionate impact on minorities in terms of infection rate, hospitalizations, and mortality. Many believe artificial intelligence (AI) is a solution to guide clinical decision-making for this novel disease, resulting in the rapid dissemination of underdeveloped and potentially biased models, which may exacerbate the disparities gap. We believe there is an urgent need to enforce the systematic use of reporting standards and develop regulatory frameworks for a shared COVID-19 data source to address the challenges of bias in AI during this pandemic. There is hope that AI can help guide treatment decisions within this crisis; yet given the pervasiveness of biases, a failure to proactively develop comprehensive mitigation strategies during the COVID-19 pandemic risks exacerbating existing health disparities., (© The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Current affiliation strategies tend to focus on joint ventures and employment. Careful planning and organizing of a joint venture can mitigate their associated legal, tax, regulatory, and cultural risks. The success of an employment model depends upon a compensation structure that aligns the incentives of physicians and the hospital. Fora successful affiliation program, hospitals should determine needs and trends, implement strategic planning, and conduct due diligence.

In an earlier issue, a doctor told you about a friend accused of stealing supplies. Here's what you told us you'd do in his place.