Clinical characteristics and serological profiles of Lyme disease in children: a 15-year retrospective cohort study in Switzerland.

Background: Lyme disease (LD) is caused by and is the most common tickborne disease in the northern hemisphere. Although classical characteristics of LD are well-known, the diagnosis and treatment are often delayed. Laboratory diagnosis by serological testing is recommended for most LD manifestations.

Impact of Metastatic Pattern on Survival Following Pancreatectomy for Cancer.

Background And Methods: The incidence of pancreatic cancer is increasing, and up to 55% of patients present with metastatic disease at the time of diagnosis. Many patients also develop metastatic disease following surgical resection. The impact of metastatic patterns on outcomes has not been described.

Unique infrared thermographic profiles and altered hypothalamic neurochemistry associated with mortality in endotoxic shock.

Neonatal sepsis results in significant morbidity and mortality, but early detection is clinically challenging. In a neonatal rat model of endotoxic shock, we identified unique infrared thermographic (IRT) profiles in skin temperature that could identify risk of later mortality. Ten-day old rats were placed in a thermally stable isolette and IRT images of cranial (T), scapula (T) and rump (T) skin temperature were obtained continuously for 8 h following an intraperitoneal injection of LPS (or saline).

Intensity of Intrathecal Total IgG Synthesis in Multiple Sclerosis Correlates with the Degree of Pleocytosis, Diversity of Intrathecal Antiviral Antibody Specificities, and Female Sex.

Background: The presence of intrathecal total IgG production is a hallmark of cerebrospinal fluid (CSF) characteristics in multiple sclerosis (MS). Herein, we systematically analyze how the intensity (instead of mere presence) of intrathecal total IgG production relates to basic CSF parameters in MS.

Methods: We retrospectively assessed clinical routine CSF findings from 390 therapy-naïve relapsing-remitting MS patients diagnosed according to 2017 revised McDonald criteria.

Artificial intelligence virtual assistants in primary eye care practice.

Purpose: To propose a novel artificial intelligence (AI)-based virtual assistant trained on tabular clinical data that can provide decision-making support in primary eye care practice and optometry education programmes.

Method: Anonymised clinical data from 1125 complete optometric examinations (2250 eyes; 63% women, 37% men) were used to train different machine learning algorithm models to predict eye examination classification (refractive, binocular vision dysfunction, ocular disorder or any combination of these three options). After modelling, adjustment, mining and preprocessing (one-hot encoding and SMOTE techniques), 75 input (preliminary data, history, oculomotor test and ocular examinations) and three output (refractive, binocular vision status and eye disease) features were defined.