Lipoprotein(a) as a Risk Factor for Recurrent Acute Myocardial Infarction and Mortality: Insights from Routine Clinical Practice.

Background: Lipoprotein(a) [Lp(a)] is a well-established risk factor for incident atherosclerotic cardiovascular (CV) disease. However, evidence regarding its association with recurrent events is limited. To address this gap, we conducted a retrospective analysis of routine clinical data, focusing on patients hospitalized for acute myocardial infarction (AMI) between 2000 and 2022 with available admission Lp(a) results.

Trusting AI made decisions in healthcare by making them explainable.

Objectives: In solving the trust issues surrounding machine learning algorithms whose reasoning cannot be understood, advancements can be made toward the integration of machine learning algorithms into mHealth applications. The aim of this paper is to provide a transparency layer to black-box machine learning algorithms and empower mHealth applications to maximize their efficiency.

Methods: Using a machine learning testing framework, we present the process of knowledge transfer between a white-box model and a black-box model and the evaluation process to validate the success of the knowledge transfer.

Trends in Physiotherapy of Chronic Low Back Pain Research: Knowledge Synthesis Based on Bibliometric Analysis.

Background: Physiotherapy and chronic low back pain (CLBP) form a broad and quickly developing research area. The aim of this article was to holistically, thematically and chronologically analyze and synthesize the literature production in this research area and identify the most prolific research entities and research themes.

Methods: This article quantitatively and qualitatively analyzed research literature production harvested from the Scopus bibliometric database, using a triangulation of bibliometric and thematic analysis.

The role of correspondence analysis in medical research.

Correspondence analysis (CA) is a multivariate statistical and visualization technique. CA is extremely useful in analyzing either two- or multi-way contingency tables, representing some degree of correspondence between columns and rows. The CA results are visualized in easy-to-interpret "bi-plots," where the proximity of items (values of categorical variables) represents the degree of association between presented items.

The Effects of Diabetes and Being Overweight on Patients with Post-COVID-19 Syndrome.

In the aftermath of the COVID-19 pandemic, post-COVID-19 syndrome (PCS) remains a challenge and may continue to pose a major health problem in the future. Moreover, the influences of type 2 diabetes and being overweight on PCS remain unclear. This study aimed to assess these influences.