Background HIV-infected persons have an increased risk of atherosclerosis relative to uninfected individuals. Inflammatory processes may contribute to this risk. We evaluated the associations of 10 biomarkers of systemic inflammation (CRP, IL-6, sTNF-αR1 and 2), monocyte activation (CCL2, sCD163, sCD14), coagulation (fibrinogen, D-dimer), and endothelial dysfunction (ICAM-1) with subclinical carotid atherosclerosis among participants in the Multicenter AIDS Cohort Study (MACS). Methods Carotid plaque and intima media thickness (IMT) in the common carotid (CCA-IMT) and bifurcation region were assessed by B mode ultrasound among 452 HIV-infected and 276 HIV-uninfected men from 2010–2013. Associations between levels of each biomarker and presence of focal plaque and IMT were assessed by logistic and linear regression models, adjusting for demographics, risk behaviors, traditional cardiovascular disease (CVD) risk factors, and HIV disease characteristics. Results Compared to HIV-uninfected men, HIV-infected men had significantly higher levels of 8 of the 10 biomarkers. Overall, men with sCD163, CCL2, IL-6, and CRP levels in the highest quintile had approximately 2 times the odds of carotid plaque relative to those with levels in the lowest quintile, independent of demographic and CVD risk factors. Fibrinogen levels were positively associated with CCA-IMT while ICAM-1, CCL2, and sTNF-αR1 levels were positively associated with bifurcation-IMT. Among HIV-uninfected men, higher levels of sTNF-αR2 were positively associated with CCA-IMT, fibrinogen with bifurcation-IMT and carotid plaque, and ICAM-1 with carotid plaque. Conclusion In addition to greater levels of systemic inflammation, heightened monocyte activation (sCD163, CCL2) may contribute to the burden of atherosclerosis among HIV-infected persons.

Objectives Elite controllers (ECs), viraemic controllers (VCs), and long‐term nonprogressors (LTNPs) control HIV viral replication or maintain CD4 T‐cell counts without antiretroviral therapy, but may have increased cardiovascular disease (CVD) risk compared to HIV‐uninfected persons. We evaluated subclinical carotid and coronary atherosclerosis and inflammatory biomarker levels among HIV controllers, LTNPs and noncontrollers and HIV‐uninfected individuals in the Multicenter AIDS Cohort Study (MACS) and the Women’s Interagency HIV Study (WIHS). Methods We measured carotid plaque presence and common carotid artery intima‐media thickness (IMT) in 1729 women and 1308 men, and the presence of coronary artery calcium and plaque in a subgroup of men. Associations between HIV control category and carotid and coronary plaque prevalences were assessed by multivariable regression analyses adjusting for demographics and CVD risk factors. Serum inflammatory biomarker concentrations [soluble CD163 (sCD163), soluble CD14 (sCD14), galectin‐3 (Gal‐3), galectin‐3 binding protein (Gal‐3BP) and interleukin (IL)‐6] were measured and associations with HIV control category assessed. Results We included 135 HIV controllers (30 ECs) and 135 LTNPs in the study. Carotid plaque prevalence and carotid IMT were similar in HIV controllers, LTNPs and HIV‐uninfected individuals. HIV controllers and LTNPs had lower prevalences of carotid plaque compared to viraemic HIV‐infected individuals. The prevalence of coronary atherosclerosis was similar in HIV controllers/LTNPs compared to HIV‐uninfected and viraemic HIV‐infected men. Controllers and LTNPs had higher concentrations of sCD163 and sCD14 compared to HIV‐uninfected persons. Conclusions Subclinical CVD was similar in HIV controllers, LTNPs and HIV‐uninfected individuals despite elevated levels of some inflammatory biomarkers. Future studies of HIV controllers and LTNPs are needed to characterize the risk of CVD among HIV‐infected persons.

Myositis-associated interstitial lung disease (MA-ILD) is associated with increased mortality, but no prognostic model exists in this population. The ILD-GAP index was developed to predict mortality risk across all subtypes of chronic ILD. The purpose of this study was to validate the ILD-GAP risk prediction model in patients with MA-ILD. Procedures: We completed a retrospective cross-sectional study of patients enrolled in the Johns Hopkins Myositis Center database between 2006 and 2017. Cumulative mortality rates were estimated using the Kaplan-Meier test. Model calibration was determined by using standardized mortality ratios of observed versus expected deaths. Main findings: 179 participants with MA-ILD were included. The mean baseline percent predicted forced vital capacity was 65.2 ± 20.6%, forced expiratory volume in the first second 65.4 ± 20.4%, and carbon monoxide diffusing capacity 61.6 ± 20.0%. Thirty-two participants died (17.9%). The ILD-GAP model had poor discriminative performance and calibration. Conclusions: The ILD-GAP risk prediction model is a poor predictor of mortality among individuals with MA-ILD. The identification of a better predictive model for MA-ILD is needed to help guide care in this patient population.

Background: Intermediate care units (IMCUs) are heterogeneous in design and operation, which makes comparative effectiveness studies challenging. A generalizable outcome prediction model could improve such comparisons. However, little is known about the performance of critical care outcome prediction models in the intermediate care setting. The purpose of this study is to evaluate the performance of the Acute Physiology and Chronic Health Evaluation version II (APACHE II), Simplified Acute Physiology Score version II (SAPS II) and version 3 (SAPS 3), and Mortality Probability Model version III (MPM0III) in patients admitted to a well-characterized IMCU. Materials and Methods: In the IMCU of an academic medical center (July to December 2012), the discrimination and calibration of each outcome prediction model were evaluated using the area under the receiver–operating characteristic and Hosmer-Lemeshow goodness-of-fit test, respectively. Standardized mortality ratios (SMRs) were also calculated. Results: The cohort included data from 628 unique IMCU admissions with an inpatient mortality rate of 8.3%. All models exhibited good discrimination, but only the SAPS II and MPM0III were well calibrated. While the APACHE II and SAPS 3 both markedly overestimated mortality, the SMR for the SAPS II and MPM0III were 0.91 and 0.91, respectively. Conclusions: The SAPS II and MPM0III exhibited good discrimination and calibration, with slight overestimation of mortality. Each model should be further evaluated in multicenter studies of patients in the intermediate care setting.