Racialized Risk in Clinical Care: Clinician Vigilance and Patient Responsibility

Racial/ethnic identity is contingent and arbitrary, yet it is commonly used to evaluate disease risk and treatment response. Drawing on open-ended interviews with patients and clinicians in two US clinics, we explore how racialized risk is conceptualized and how it impacts patient care and experience. We found that racial/ethnic risk was a common but poorly defined construct for both patients and clinicians, who intermingled concepts of genetics, biology, behavior, and culture, while disregarding historical or structural context. We argue that racializing risk embodies social power in marked and unmarked bodies, reinforcing inequality along racial lines and undermining equitable health care.     

Human epididymis protein 4 (HE4) levels inversely correlate with lung function improvement (delta FEV1) in cystic fibrosis patients receiving ivacaftor treatment

Background

We have recently shown that human epididymis protein 4 (HE4) levels correlate with the severity of cystic fibrosis (CF) lung disease. However, there are no data on how HE4 levels alter in patients receiving CFTR modulating therapy.

A case of autonomic failure in post-craniectomy syndrome of the trephined

Clinical Autonomic Research -     

Validation of a fast method for quantification of intra‐abdominal and subcutaneous adipose tissue for large‐scale human studies

Central obesity is the hallmark of a number of non‐inheritable disorders. The advent of imaging techniques such as MRI has allowed for a fast and accurate assessment of body fat content and distribution. However, image analysis continues to be one of the major obstacles to the use of MRI in large‐scale studies. In this study we assess the validity of the recently proposed fat–muscle quantitation system (AMRA^TM Profiler) for the quantification of intra‐abdominal adipose tissue (IAAT) and abdominal subcutaneous adipose tissue (ASAT) from abdominal MR images. Abdominal MR images were acquired from 23 volunteers with a broad range of BMIs and analysed using sliceOmatic, the current gold‐standard, and the AMRA^TM Profiler based on a non‐rigid image registration of a library of segmented atlases. The results show that there was a highly significant correlation between the fat volumes generated by the two analysis methods, (Pearson correlation r = 0.97, p < 0.001), with the AMRA^TM Profiler analysis being significantly faster (~3 min) than the conventional sliceOmatic approach (~40 min). There was also excellent agreement between the methods for the quantification of IAAT (AMRA 4.73 ± 1.99 versus sliceOmatic 4.73 ± 1.75 l, p = 0.97). For the AMRA^TM Profiler analysis, the intra‐observer coefficient of variation was 1.6% for IAAT and 1.1% for ASAT, the inter‐observer coefficient of variation was 1.4% for IAAT and 1.2% for ASAT, the intra‐observer correlation was 0.998 for IAAT and 0.999 for ASAT, and the inter‐observer correlation was 0.999 for both IAAT and ASAT. These results indicate that precise and accurate measures of body fat content and distribution can be obtained in a fast and reliable form by the AMRA^TM Profiler, opening up the possibility of large‐scale human phenotypic studies. Copyright © 2015 John Wiley & Sons, Ltd.