Gastro-esophageal reflux disease symptoms and demographic factors as a pre-screening tool for Barrett's esophagus.

BACKGROUND: Barrett's esophagus (BE) occurs as consequence of reflux and is a risk factor for esophageal adenocarcinoma. The current "gold-standard" for diagnosing BE is endoscopy which remains prohibitively expensive and impractical as a population screening tool. We aimed to develop a pre-screening tool to aid decision making for diagnostic referrals. METHODOLOGY/PRINCIPAL FINDINGS: A prospective (training) cohort of 1603 patients attending for endoscopy was used for identification of risk factors to develop a risk prediction model. Factors associated with BE in the univariate analysis were selected to develop prediction models that were validated in an independent, external cohort of 477 non-BE patients referred for endoscopy with symptoms of reflux or dyspepsia. Two prediction models were developed separately for columnar lined epithelium (CLE) of any length and using a stricter definition of intestinal metaplasia (IM) with segments ≥ 2 cm with areas under the ROC curves (AUC) of 0.72 (95%CI: 0.67-0.77) and 0.81 (95%CI: 0.76-0.86), respectively. The two prediction models included demographics (age, sex), symptoms (heartburn, acid reflux, chest pain, abdominal pain) and medication for "stomach" symptoms. These two models were validated in the independent cohort with AUCs of 0.61 (95%CI: 0.54-0.68) and 0.64 (95%CI: 0.52-0.77) for CLE and IM ≥ 2 cm, respectively. CONCLUSIONS: We have identified and validated two prediction models for CLE and IM ≥ 2 cm. Both models have fair prediction accuracies and can select out around 20% of individuals unlikely to benefit from investigation for Barrett's esophagus. Such prediction models have the potential to generate useful cost-savings for BE screening among the symptomatic population

Integrated cardiovascular assessment of atherosclerosis using PET/MRI.

Atherosclerosis is a systemic inflammatory disease typified by the development of lipid-rich atheroma (plaques), the rupture of which are a major cause of myocardial infarction and stroke. Anatomical evaluation of the plaque considering only the degree of luminal stenosis overlooks features associated with vulnerable plaques, such as high-risk morphological features or pathophysiology, and hence risks missing vulnerable or ruptured non-stenotic plaques. Consequently, there has been interest in identifying these markers of vulnerability using either MRI for morphology, or positron emission tomography (PET) for physiological processes involved in atherogenesis. The advent of hybrid PET/MRI scanners offers the potential to combine the strengths of PET and MRI to allow comprehensive assessment of the atherosclerotic plaque. This review will discuss the principles and technical aspects of hybrid PET/MRI assessment of atherosclerosis, and consider how combining the complementary modalities of PET and MRI has already furthered our understanding of atherogenesis, advanced drug development, and how it may hold potential for clinical application.National Institute of Health Research Wellcome Trust EPSR

CT pericoronary adipose tissue density predicts coronary allograft vasculopathy and adverse clinical outcomes after cardiac transplantation.

AIMS: To assess pericoronary adipose tissue (PCAT) density on Coronary Computed Tomography Angiography (CCTA) as a marker of inflammatory disease activity in coronary allograft vasculopathy (CAV). METHODS AND RESULTS: PCAT density, lesion volumes, and total vessel volume-to-myocardial mass ratio (V/M) were retrospectively measured in 126 CCTAs from 94 heart transplant patients (mean age 49 [SD 14.5] years, 40% female) who underwent imaging between 2010 to 2021; age and sex-matched controls; and patients with atherosclerosis. PCAT density was higher in transplant patients with CAV (n = 40; -73.0 HU [SD 9.3]) than without CAV (n = 86; -77.9 HU [SD 8.2]), and controls (n = 12; -86.2 HU [SD 5.4]), p < 0.01 for both. Unlike patients with atherosclerotic coronary artery disease (n = 32), CAV lesions were predominantly non-calcified, comprised of mostly fibrous or fibrofatty tissue. V/M was lower in patients with CAV than without (32.4 mm3/g [SD 9.7] vs. 41.4 mm3/g [SD 12.3], p < 0.0001). PCAT density and V/M improved the ability to predict CAV from AUC 0.75 to 0.85 when added to donor age and donor hypertension status (p < 0.0001). PCAT density above -66 HU was associated with a greater incidence of all-cause mortality (OR 18.0 [95%CI 3.25-99.6], p < 0.01) and the composite endpoint of death, CAV progression, acute rejection, and coronary revascularization (OR 7.47 [95%CI 1.8-31.6], p = 0.01) over 5.3 (SD 2.1) years. CONCLUSIONS: Heart transplant patients with CAV have higher PCAT density and lower V/M than those without. Increased PCAT density is associated with adverse clinical outcomes. These CCTA metrics could be useful for diagnosis and monitoring of CAV severity

The coefficients, weights and odds ratios of selected predictors for BE.

<p>^*n/a: not applicable.</p

Summary of the predictors for BE in the external validation cohort^*.

<p>^*Data shown are mean (SD) for continuous variables and number (percentage) for categorical variables.</p

Demographic characteristics according to endoscopic BE and pathological BE in the training cohort^*.

<p>^*Data shown are mean (SD) for continuous variables and number (percentage) for categorical variables</p>†<p>P for trend test.</p

ROC curve for a) endoscopically visible CLE of any length independent of histology (AUC: 0.61), b) segment containing IM≥2 cm (AUC: 0.64) in the external validation cohort (N = 477).

<p>ROCs curve were developed using the risk scores which are calculated by the weights of different predictors. The weights were developed based on the coefficients of predictors in the backward logistic regression model in the training cohort.</p

ROC curve for a) endoscopically visible CLE of any length independent of histology (AUC: 0.72), b) segment containing IM≥2 cm (AUC: 0.81) in the training cohort (N = 1603).

<p>ROCs curve were developed using the risk scores which are calculated using the weights of different predictors. The weights were developed based on the coefficients of predictors in the backward logistic regression model in the training cohort.</p

Pattern of arterial inflammation and inflammatory markers in people living with HIV compared with uninfected people.

Funder: Alma Mater Studiorum - Università di BolognaSTUDY DESIGN: To compare arterial inflammation (AI) between people living with HIV (PLWH) and uninfected people as assessed by 18F-Fluorodeoxyglucose (18F-FDG)-positron emission tomography (PET). METHODS: We prospectively enrolled 20 PLWH and 20 uninfected people with no known cardiovascular disease and at least 3 traditional cardiovascular risk factors. All patients underwent 18F-FDG-PET/computed tomography (CT) of the thorax and neck. Biomarkers linked to inflammation and atherosclerosis were also determined. The primary outcome was AI in ascending aorta (AA) measured as mean maximum target-to-background ratio (TBRmax). The independent relationships between HIV status and both TBRmax and biomarkers were evaluated by multivariable linear regression adjusted for body mass index, creatinine, statin therapy, and atherosclerotic cardiovascular 10-year estimated risk (ASCVD). RESULTS: Unadjusted mean TBRmax in AA was slightly higher but not statistically different (P = .18) in PLWH (2.07; IQR 1.97, 2.32]) than uninfected people (2.01; IQR 1.85, 2.16]). On multivariable analysis, PLWH had an independent risk of increased mean log-TBRmax in AA (coef = 0.12; 95%CI 0.01,0.22; P = .032). HIV infection was independently associated with higher values of interleukin-10 (coef = 0.83; 95%CI 0.34, 1.32; P = .001), interferon-γ (coef. = 0.90; 95%CI 0.32, 1.47; P = .003), and vascular cell adhesion molecule-1 (VCAM-1) (coef. = 0.75; 95%CI: 0.42, 1.08, P < .001). CONCLUSIONS: In patients with high cardiovascular risk, HIV status was an independent predictor of increased TBRmax in AA. PLWH also had an increased independent risk of IFN-γ, IL-10, and VCAM-1 levels