Das prozessierte EEG zur personalisierten Dosierung von Anästhetika während Allgemeinanästhesie

Die Anaesthesiologie - Die Elektroenzephalogramm(EEG)-gesteuerte Anästhesie ist aus modernen Operationssälen nicht mehr wegzudenken und hat sich als Standard-Monitoring etabliert. Viele...     

The impact of neighborhoods and friendships on interracial anxiety among medical students and residents: A report from the medical student CHANGES study

Objective

To examine the experience of interracial anxiety among health professionals and how it may affect the quality of their interactions with patients from racially marginalized populations. We explored the influence of prior interracial exposure—specifically through childhood neighborhoods, college student bodies, and friend groups—on interracial anxiety among medical students and residents. We also examined whether levels of interracial anxiety change from medical school through residency.

Data Source

Web-based longitudinal survey data from the Medical Student Cognitive Habits and Growth Evaluation Study.

Study Design

We used a retrospective longitudinal design with four observations for each trainee. The study population consisted of non-Black US medical trainees surveyed in their 1st and 4th years of medical school and 2nd and 3rd years of residency. Mixed effects longitudinal models were used to assess predictors of interracial anxiety and assess changes in interracial anxiety scores over time.

Principal Findings

In total, 3155 non-Black medical trainees were followed for 7 years. Seventy-eight percent grew up in predominantly White neighborhoods. Living in predominantly White neighborhoods and having less racially diverse friends were associated with higher levels of interracial anxiety among medical trainees. Trainees' interracial anxiety scores did not substantially change over time; interracial anxiety was highest in the 1st year of medical school, lowest in the 4th year, and increased slightly during residency.

Conclusions

Neighborhood and friend group composition had independent effects on interracial anxiety, indicating that premedical racial socialization may affect medical trainees' preparedness to interact effectively with diverse patient populations. Additionally, the lack of substantial change in interracial anxiety throughout medical training suggests the importance of providing curricular tools and structure (e.g., instituting interracial cooperative learning activities) to foster the development of healthy interracial relationships.     

Machine learning to predict myocardial injury and death after non-cardiac surgery

Myocardial injury due to ischaemia within 30 days of non-cardiac surgery is prognostically relevant. We aimed to determine the discrimination, calibration, accuracy, sensitivity and specificity of single-layer and multiple-layer neural networks for myocardial injury and death within 30 postoperative days. We analysed data from 24,589 participants in the Vascular Events in Non-cardiac Surgery Patients Cohort Evaluation study. Validation was performed on a randomly selected subset of the study population. Discrimination for myocardial injury by single-layer vs. multiple-layer models generated areas (95%CI) under the receiver operating characteristic curve of: 0.70 (0.69–0.72) vs. 0.71 (0.70–0.73) with variables available before surgical referral, p < 0.001; 0.73 (0.72–0.75) vs. 0.75 (0.74–0.76) with additional variables available on admission, but before surgery, p < 0.001; and 0.76 (0.75–0.77) vs. 0.77 (0.76–0.78) with the addition of subsequent variables, p < 0.001. Discrimination for death by single-layer vs. multiple-layer models generated areas (95%CI) under the receiver operating characteristic curve of: 0.71 (0.66–0.76) vs. 0.74 (0.71–0.77) with variables available before surgical referral, p = 0.04; 0.78 (0.73–0.82) vs. 0.83 (0.79–0.86) with additional variables available on admission but before surgery, p = 0.01; and 0.87 (0.83–0.89) vs. 0.87 (0.85–0.90) with the addition of subsequent variables, p = 0.52. The accuracy of the multiple-layer model for myocardial injury and death with all variables was 70% and 89%, respectively.     

Examining the Influence of Racial Discrimination on Adverse Birth Outcomes: An Analysis of the Virginia Pregnancy Risk Assessment Monitoring System (PRAMS), 2016–2018

Maternal and Child Health Journal - In Virginia, Black women experience higher rates of adverse birth and labor outcomes that may not be explained solely by risky behaviors or social standing....