Primary Extradural Meningioma: A Systematic Review of Diagnostic Features, Clinical Management, and Surgical Outcomes.

This systematic review consolidates the literature on primary extradural meningiomas (PEMs), a rare subset of meningiomas. We describe the clinical features, management strategies used, and treatment outcomes for published cases. A systematic review was conducted using PRISMA guidelines across multiple databases to 29 July 2024.

The risk of death according to left ventricular ejection fraction and right ventricular dilatation in 17 321 adults with heart failure from 40 high-, middle- and low-income countries - A Global Congestive Heart Failure (G-CHF) study.

Aims: The aim of this study was to describe the prognostic importance of left ventricular ejection fraction (LVEF) versus right ventricular (RV) dilatation and dysfunction in patients with heart failure (HF) from countries of different income levels.

Methods And Results: We enrolled 17 321 participants with HF from 40 countries. Participants were followed for a median (25th-75th percentile) of 2.

Guanidinium and hydrogen carbonate rosette layers: Distance and degree topological indices, Szeged-type indices, entropies, and NMR spectral patterns.

Supramolecular chemistry explores non-covalent interactions between molecules, and it has facilitated the design of functional materials and understanding of molecular self-assembly processes. We investigate a captivating class of supramolecular structures, the guanidinium and hydrogen carbonate rosette layers. These rosette layers are composed of guanidinium cations and carbonate anions, exhibiting intricate hydrogen-bonding networks that lead to their unique structural properties.

Detecting irregularities in randomized controlled trials using machine learning.

Background: Over the course of a clinical trial, irregularities may arise in the data. Trialists implement human-intensive, expensive central statistical monitoring procedures to identify and correct these irregularities before the results of the trial are analyzed and disseminated. Machine learning algorithms have shown promise for identifying center-level irregularities in multi-center clinical trials with minimal human intervention.