BackgroundThere are few data characterizing temporal changes in hospitalization for recurrent acute myocardial infarction (AMI) after AMI.Methods and ResultsUsing a national sample of 2 305 441 Medicare beneficiaries hospitalized for AMI from 1999 to 2010, we evaluated changes in the incidence of 1‐year recurrent AMI hospitalization and mortality using Cox proportional hazards models. The observed recurrent AMI hospitalization rate declined from 12.1% (95% CI 11.9 to 12.2) in 1999 to 8.9% (95% CI 8.8 to 9.1) in 2010, a relative decline of 26.4%. The observed recurrent AMI hospitalization rate declined by a relative 27.7% in whites, from 11.9% (95% CI 11.8 to 12.1) to 8.6% (95% CI 8.5 to 8.8) versus a relative decline in blacks of 13.6% from 13.2% (95% CI 12.6 to 13.8) to 11.4% (95% CI 10.9 to 12.0). The risk‐adjusted rate of annual decline in recurrent AMI hospitalizations was 4.1% (HR 0.959; 95% CI 0.958 to 0.961), and whites experienced a higher rate of decline (HR 0.957, 95% CI 0.956 to 0.959) than blacks (HR 0.974, 95% CI 0.970 to 0.979).The overall, observed 1‐year mortality rate after hospitalization for recurrent AMI declined from 32.4% in 1999 to 29.7% in 2010, a relative decline of 8.3% (P<0.05). In adjusted analyses, 1‐year mortality after recurrent AMI hospitalization declined 1.8% per year (HR, 0.982; 95% CI 0.980 to 0.985).ConclusionsIn a national sample of Medicare beneficiaries hospitalized for AMI from 1999 to 2010, hospitalization for recurrent AMI decreased, as did subsequent mortality, albeit to a lesser extent. The risk of recurrent AMI hospitalization declined less in black patients than in whites, increasing observed racial disparities by the end of the study period.

Occupational and non-occupational risk factors for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have been reported in healthcare workers (HCWs), but studies evaluating risk factors for infection among physician trainees are lacking. We aimed to identify sociodemographic, occupational, and community risk factors among physician trainees during the first wave of coronavirus disease 2019 (COVID-19) in New York City. In this retrospective study of 328 trainees at the Mount Sinai Health System in New York City, we administered a survey to assess risk factors for SARS-CoV-2 infection between 1 February and 30 June 2020. SARS-CoV-2 infection was determined by self-reported and laboratory-confirmed IgG antibody and reverse transcriptase-polymerase chain reaction test results. We used Bayesian generalized linear mixed effect regression to examine associations between hypothesized risk factors and infection odds. The cumulative incidence of infection was 20.1%. Assignment to medical-surgical units (OR, 2.51; 95% CI, 1.18–5.34), and training in emergency medicine, critical care, and anesthesiology (OR, 2.93; 95% CI, 1.24–6.92) were independently associated with infection. Caring for unfamiliar patient populations was protective (OR, 0.16; 95% CI, 0.03–0.73). Community factors were not statistically significantly associated with infection after adjustment for occupational factors. Our findings may inform tailored infection prevention strategies for physician trainees responding to the COVID-19 pandemic.

Background: Occupational and non-occupational risk factors for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have been reported in healthcare workers (HCWs), but studies evaluating risk factors for infection among physician trainees are lacking. We aimed to identify sociodemographic, occupational, and community risk factors among physician trainees during the first wave of coronavirus disease 2019 in New York City. Methods:In this retrospective study of 328 trainees at the Mount Sinai Health System (MSHS) in New York City, we administered a survey to assess risk factors for SARS-CoV-2 infection between February 1 and June 30, 2020. SARS-CoV-2 infection was determined by self-reported and laboratory-confirmed IgG antibody and reverse transcriptase-polymerase chain reaction test results. We used Bayesian generalized linear mixed effect regression to examine associations between hypothesized risk factors and infection odds.

guidelines for the diagnosis and treatment of asymptomatic bacteriuria in adults.

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