An examination of the unique contributions of body image and internalized weight bias to psychological well-being outcomes.

High correlations between measures of internalized weight bias (IWB) and body image (BI) have resulted in concerns that IWB is conceptually redundant with BI. This investigation examined the contribution of the unique variance of BI and IWB on three important, weight-related factors: self-esteem, depressive symptoms, and body shame. The study included 403 participants recruited through a Qualtrics research panel. Participants were required to be aged 18 + and have a BMI > 25. The sample contained three equally represented, self-identified racial/ethnic groups: Black non-Hispanic (N = 140), Hispanic (N = 133), and White non-Hispanic (N = 130). When BI was entered in the first step of the regression model, it accounted for 14-40% of the variance in various models; the addition of IWB in step two contributed 11-18% of unique variance. By contrast, when IWB was entered in the first step, it accounted for 25-56% of the variance in various models, with the addition of BI contributing between 0% and 2% unique variance. Therefore, even with a high correlation among the constructs of IWB and BI, IWB was able to contribute unique variance in predicting depressive symptoms, self-esteem, and body shame, and is not redundant with the construct of BI.

Adipose Tissue Insulin Resistance Predicts the Severity of Liver Fibrosis in Patients With Type 2 Diabetes and NAFLD.

CONTEXT: Although type 2 diabetes (T2D) is a risk factor for liver fibrosis in nonalcoholic fatty liver disease (NAFLD), the specific contribution of insulin resistance (IR) relative to other factors is unknown. OBJECTIVE: Assess the impact on liver fibrosis in NAFLD of adipose tissue (adipose tissue insulin resistance index [adipo-IR]) and liver (Homeostatic Model Assessment of Insulin Resistance [HOMA-IR]) IR in people with T2D and NAFLD. DESIGN: Participants were screened by elastography in the outpatient clinics for hepatic steatosis and fibrosis, including routine metabolites, cytokeratin-18 (a marker of hepatocyte apoptosis/steatohepatitis), and HOMA-IR/adipo-IR. SETTING: University ambulatory care practice. PARTICIPANTS: A total of 483 participants with T2D. INTERVENTION: Screening for steatosis and fibrosis with elastography. MAIN OUTCOME MEASURES: Liver steatosis (controlled attenuation parameter), fibrosis (liver stiffness measurement), and measurements of IR (adipo-IR, HOMA-IR) and fibrosis (cytokeratin-18). RESULTS: Clinically significant liver fibrosis (stage F ≥ 2 = liver stiffness measurement ≥8.0 kPa) was found in 11%, having more features of the metabolic syndrome, lower adiponectin, and higher aspartate aminotransferase (AST), alanine aminotransferase, liver fat, and cytokeratin-18 (P < 0.05-0.01). In multivariable analysis including just clinical variables (model 1), obesity (body mass index [BMI]) had the strongest association with fibrosis (odds ratio, 2.56; CI, 1.87-3.50; P < 0.01). When metabolic measurements and cytokeratin-18 were included (model 2), only BMI, AST, and liver fat remained significant. When fibrosis stage was adjusted for BMI, AST, and steatosis (model 3), only Adipo-IR remained strongly associated with fibrosis (OR, 1.51; CI, 1.05-2.16; P = 0.03), but not BMI, hepatic IR, or steatosis. CONCLUSIONS: These findings pinpoint to the central role of dysfunctional, insulin-resistant adipose tissue to advanced fibrosis in T2D, beyond simply BMI or steatosis. The clinical implication is that targeting adipose tissue should be the priority of treatment in NAFLD.

Advanced Liver Fibrosis Is Common in Patients With Type 2 Diabetes Followed in the Outpatient Setting: The Need for Systematic Screening.

OBJECTIVE: Assess the prevalence of nonalcoholic fatty liver disease (NAFLD) and of liver fibrosis associated with nonalcoholic steatohepatitis in unselected patients with type 2 diabetes mellitus (T2DM). RESEARCH DESIGN AND METHODS: A total of 561 patients with T2DM (age: 60 ± 11 years; BMI: 33.4 ± 6.2 kg/m2; and HbA1c: 7.5 ± 1.8%) attending primary care or endocrinology outpatient clinics and unaware of having NAFLD were recruited. At the visit, volunteers were invited to be screened by elastography for steatosis and fibrosis by controlled attenuation parameter (≥274 dB/m) and liver stiffness measurement (LSM; ≥7.0 kPa), respectively. Secondary causes of liver disease were ruled out. Diagnostic panels for prediction of advanced fibrosis, such as AST-to-platelet ratio index (APRI) and Fibrosis-4 (FIB-4) index, were also measured. A liver biopsy was performed if results were suggestive of fibrosis. RESULTS: The prevalence of steatosis was 70% and of fibrosis 21% (LSM ≥7.0 kPa). Moderate fibrosis (F2: LSM ≥8.2 kPa) was present in 6% and severe fibrosis or cirrhosis (F3-4: LSM ≥9.7 kPa) in 9%, similar to that estimated by FIB-4 and APRI panels. Noninvasive testing was consistent with liver biopsy results. Elevated AST or ALT ≥40 units/L was present in a minority of patients with steatosis (8% and 13%, respectively) or with liver fibrosis (18% and 28%, respectively). This suggests that AST/ALT alone are insufficient as initial screening. However, performance may be enhanced by imaging (e.g., transient elastography) and plasma diagnostic panels (e.g., FIB-4 and APRI). CONCLUSIONS: Moderate-to-advanced fibrosis (F2 or higher), an established risk factor for cirrhosis and overall mortality, affects at least one out of six (15%) patients with T2DM. These results support the American Diabetes Association guidelines to screen for clinically significant fibrosis in patients with T2DM with steatosis or elevated ALT.

Impact of Electronic Medical Record Alerts on Emergency Physician Workflow and Medical Management.

BACKGROUND: Electronic medical record (EMR) alerts are automated messages that notify the physician of important information. However, little is known about how EMR alerts affect the workflow and decision-making of emergency physicians (EPs). STUDY OBJECTIVES: This study aimed to quantify the number of EMR alerts EPs receive, the time required to resolve alerts, the types of alerts EPs receive, and the impact of alerts on patient management. METHODS: We performed a prospective observational study at a tertiary care ED with 130,000 visits annually. Research assistants observed EPs on shift from May to December 2018. They recorded the number of EMR alerts received, time spent addressing the alerts, the types of alerts received, and queried the EP to determine if the alert impacted patient management. RESULTS: Seven residents and six attending physicians were observed on a total of 17 shifts and 153 patient encounters; 78% (119) of patient encounters involved alerts. These 119 patients triggered 530 EMR alerts. EPs spent a mean of 7.06 s addressing each alert and addressed 3.46 alerts per total patient seen. In total, EPs spent approximately 24 s per patient resolving alerts. Only 12 alerts (2.26%) changed clinical management. CONCLUSION: EPs frequently receive EMR alerts, however, most alerts were not perceived to impact patient care. These alerts contribute to the high volume of interruptions EPs must contend with in the clinical environment of the ED.