Purpose of review Preeclampsia complicates 3–5% of first and 15% of subsequent pregnancies. This study reviews the evidence of increase cardiovascular risk in these women. Recent findings Women with preeclampsia are at two-fold higher risk for development of coronary artery disease, stroke and death, and four-fold increased risk of heart failure. Preeclampsia developed in early part of pregnancy confers greater risk than later in pregnancy. Common factors that predispose women to preeclampsia also confer high risk for developing cardiovascular disease include obesity, metabolic abnormalities, dyslipidaemia, insulin resistance, heightened inflammatory responses, hypercoagulable states and endothelia dysfunction. Summary Patients with preeclampsia should be screened at regular intervals by a preventive cardiologist and treated accordingly.

Objective: To evaluate clinical characteristics of patients admitted to the hospital with coronavirus disease 2019 in Southern United States and development as well as validation of a mortality risk prediction model. Patients and Methods: Southern Louisiana was an early hotspot during the pandemic, which provided a large collection of clinical data on inpatients with COVID-19. We designed a risk stratification model to assess the mortality risk for patients admitted to the hospital with COVID-19. Data from 1673 consecutive patients diagnosed with COVID-19 infection and hospitalized between March 1, 2020, and April 30, 2020, was used to create an 11-factor mortality risk model based on baseline comorbidity, organ injury, and laboratory results. The risk model was validated using a subsequent cohort of 2067 consecutive hospitalized patients admitted between June 1, 2020, and December 31, 2020.Results: The resultant model has an area under the curve of 0.783 (95% CI, 0.76 to 0.81), with an optimal sensitivity of 0.74 and specificity of 0.69 for predicting mortality. Validation of this model in a subsequent cohort of 2067 consecutively hospitalized patients yielded comparable prognostic performance. Conclusion:We have developed an easy-to-use, robust model for systematically evaluating patients presenting to acute care settings with COVID-19 infection.

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