Background Cerebral amyloid angiopathy associated with inflammation is an increasingly recognized condition, characterized by an inflammatory response to the vascular deposits of β-amyloid within the brain that are the hallmark of cerebral amyloid angiopathy. Two main patterns of this inflammatory response have been identified to date: one involving a perivascular inflammatory cell infiltrate (cerebral amyloid angiopathy-related inflammation); the other a transmural vasculitic process (A-beta related angiitis). Unlike cerebral amyloid angiopathy itself, which predisposes to intracerebral hemorrhage and has no known treatment, cerebral amyloid angiopathy associated with inflammation typically presents in diverse ways and diagnosis may be challenging and delayed. Aims We sought to summarize the clinical features, imaging appearances and available data on outcome and treatment responses, using information derived from a systematic review of pathologically proven cases of cerebral amyloid angiopathy associated with inflammation. Summary of review We identified 213 distinct pathologically proven cases of cerebral amyloid angiopathy-related inflammation/A-beta related angiitis, from 104 publications. The clinical presentation, imaging features, pathology, treatment, and outcomes of cerebral amyloid angiopathy associated with inflammation are described. Conclusions Cerebral amyloid angiopathy associated with inflammation is an important and increasingly recognized clinical condition, which affects the older patient population and presents most commonly with cognitive decline, seizures, and headaches. Future research is required to develop and validate diagnostic criteria and determine optimum treatment strategies.

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BackgroundBarrett’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 FindingsA 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.ConclusionsWe 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.

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