Efficacy and safety of trifluridine/tipiracil plus bevacizumab across different subgroups of patients with refractory colorectal cancer: a meta-analysis.

Introduction: Metastatic colorectal cancer (mCRC) patients who are refractory to initial treatment lines exhibit a challenging clinical scenario characterised by a poor prognosis and constrained therapeutic options. This systematic review and meta-analysis assess the integration of bevacizumab into trifluridine-tipiracil (TFD/TPI) therapy for mCRC, examining its benefits across patient subgroups and evaluating safety relative to TFD/TPI monotherapy.

Materials And Methods: Following preferred reporting items for systematic reviews and meta-analysis statements, we conducted a thorough literature search from 15 October to 11 November 2023, covering MEDLINE, Embase and the Cochrane database.

An online platform for COVID-19 diagnostic screening using a machine learning algorithm.

Objective: COVID-19 has brought emerging public health emergency and new challenges. It configures a complex panorama that has been requiring a set of coordinated actions and has innovation as one of its pillars. In particular, the use of digital tools plays an important role.

Machine Learning Algorithms to Distinguish Myocardial Perfusion SPECT Polar Maps.

Myocardial perfusion imaging (MPI) plays an important role in patients with suspected and documented coronary artery disease (CAD). Machine Learning (ML) algorithms have been developed for many medical applications with excellent performance. This study used ML algorithms to discern normal and abnormal gated Single Photon Emission Computed Tomography (SPECT) images.

Machine Learning Algorithms to Detect Sex in Myocardial Perfusion Imaging.

Myocardial perfusion imaging (MPI) is an essential tool used to diagnose and manage patients with suspected or known coronary artery disease. Additionally, the General Data Protection Regulation (GDPR) represents a milestone about individuals' data security concerns. On the other hand, Machine Learning (ML) has had several applications in the most diverse knowledge areas.

Recent Trends in Cardiovascular Mortality in Rio de Janeiro State Health Regions and Capital.

Background: Cardiovascular disease (CVD) mortality, after several decades of decrease, has shown a tendency towards the stabilization in some countries, including Brazil and Rio de Janeiro state. This new tendency was not further analyzed by gender, age group and region of the Rio de Janeiro state.

Objective: To analyze the trends of premature and late mortality from CVD, ischemic heart disease (IHD) and cerebrovascular disease (CBVD) by gender in the city of Rio de Janeiro (capital) and the health regions of Rio de Janeiro state (from 1996 to 2016.

Artificial Intelligence in Cardiology: Concepts, Tools and Challenges - "The Horse is the One Who Runs, You Must Be the Jockey".

The recent advances at hardware level and the increasing requirement of personalization of care associated with the urgent needs of value creation for the patients has helped Artificial Intelligence (AI) to promote a significant paradigm shift in the most diverse areas of medical knowledge, particularly in Cardiology, for its ability to support decision-making and improve diagnostic and prognostic performance. In this context, the present work does a non-systematic review of the main papers published on AI in Cardiology, focusing on its main applications, potential impacts and challenges.

Trends in Mortality Rates from Cardiovascular Disease and Cancer between 2000 and 2015 in the Most Populous Capital Cities of the Five Regions of Brazil.

Background: In many cities around the world, the mortality rate from cancer (CA) has exceeded that from disease of the circulatory system (DCS).

Objectives: To compare the mortality curves from DCS and CA in the most populous capital cities of the five regions of Brazil.

Methods: Data of mortality rates from DCS and CA between 2000 and 2015 were collected from the Mortality Information System of Manaus, Salvador, Goiania, Sao Paulo and Curitiba, and categorized by age range into early (30-69 years) and late (≥ 70 years), and by gender of the individuals.

Are there normal values of phase analysis parameters for left ventricular dyssynchrony in patients with no structural cardiomyopathy?: a systematic review.

Background: ECG-gated single photon emission computed tomography (SPECT) myocardial perfusion scintigraphy combined with phase analysis allows for the assessment of left ventricular dyssynchrony. However, there are several software programs available thereby introducing variability in outcome and normal values. The aim of this systematic review was to evaluate the variability between different programs as currently available in literature with a focus on normal values.