Caustic Ingestion in the Elderly: Influence of Age on Clinical Outcome

Caustic poisonings are still associated with many fatalities. Studies focusing on the elderly are rare. The purpose of the present study was to compare the clinical outcomes of caustic ingestion injury in elderly and non-elderly adults with regard to gender, intent of exposure, substance ingested, severity of mucosal injury, complications, and mortality. Caustic substance exposures reported to the National Toxicological Information Centre in Slovakia during 1998–2015 were reviewed retrospectively. The patients were divided into two groups: the non-elderly (<60 years) and elderly adults (≥60 years). The mortality rate in the elderly was significantly higher (elderly 23.0% vs. non-elderly 11.3%; p = 0.041). The risk of fatal outcome in the elderly was increased by acid ingestion (OR = 7.822; p = 0.002), particularly hydrochloric acid (OR = 5.714, p = 0.006). The incidence of respiratory complications was almost two times higher in the elderly was 31.1% vs. 17.4% for the non-elderly (p = 0.037). Respiratory complications significantly correlated with an increased mortality rate (p = 0.001) in the elderly whereas there was no association between GI complications and mortality in the elderly (p = 0.480). Elderly patients with respiratory complications had the poorest clinical outcomes. The highest risk of complications and fatalities was observed in patients after hydrochloric acid ingestion

Rotation-invariant multi-contrast non-local means for MS lesion segmentation

Multiple sclerosis (MS) lesion segmentation is crucial for evaluating disease burden, determining disease progression and measuring the impact of new clinical treatments. MS lesions can vary in size, location and intensity, making automatic segmentation challenging. In this paper, we propose a new supervised method to segment MS lesions from 3D magnetic resonance (MR) images using non-local means (NLM). The method uses a multi-channel and rotation-invariant distance measure to account for the diversity of MS lesions. The proposed segmentation method, rotation-invariant multi-contrast non-local means segmentation (RMNMS), captures the MS lesion spatial distribution and can accurately and robustly identify lesions regardless of their orientation, shape or size. An internal validation on a large clinical magnetic resonance imaging (MRI) dataset of MS patients demonstrated a good similarity measure result (Dice similarity = 60.1% and sensitivity = 75.4%), a strong correlation between expert and automatic lesion load volumes (R2 = 0.91), and a strong ability to detect lesions of different sizes and in varying spatial locations (lesion detection rate = 79.8%). On the independent MS Grand Challenge (MSGC) dataset validation, our method provided competitive results with state-of-the-art supervised and unsupervised methods. Qualitative visual and quantitative voxel- and lesion-wise evaluations demonstrated the accuracy of RMNMS method

ECTRIMS/EAN Guideline on the pharmacological treatment of people with multiple sclerosis

Background: Multiple sclerosis (MS) is a complex disease with new drugs becoming available in the past years. There is a need for a reference tool compiling current data to aid professionals in treatment decisions