Human immunodeficiency virus infection is associated with greater risk of pneumonia and readmission after cardiac surgery.

Objective: Human immunodeficiency virus infection (HIV+) is associated with a 2-fold increased risk of cardiovascular disease. Increasingly, patients who are HIV + are being evaluated to undergo cardiac surgery. Current risk-adjusted scoring systems, including the Society of Thoracic Surgeons Predicted Risk of Mortality score, fail to stratify HIV + risk.

Risk of 30-Day All-Cause Readmission in Interstitial Lung Disease Patients after COVID-19: National-Level Data.

Hospital readmission within 30 days poses challenges for healthcare providers, policymakers, and patients because of its impact on care quality, costs, and outcomes. Patients with interstitial lung disease (ILD) are particularly affected by readmission, which is associated with increased morbidity and mortality and reduced quality of life. Because small sample sizes have hindered previous studies, this study seeks to address this gap in knowledge by examining a large-scale dataset.

Guideline-based and restricted fluid resuscitation strategy in sepsis patients with heart failure: A systematic review and meta-analysis.

Objectives: To examine whether a fluid resuscitation strategy based on guidelines (at least 30 mL/kg IV crystalloids) vs. a restrictive approach with <30 mL/kg within three hours affects in-hospital mortality in patients with sepsis and a history of heart failure (HF).

Data Sources: On 03/07/2023, we searched Embase, PubMed, and Scopus for peer-reviewed papers and abstracts using the PRISMA guidelines.

Decrease in Exacerbations During the Coronavirus Disease 2019 Pandemic in a Cohort of Veterans with COPD.

Background: Studies have shown a decline in hospitalizations due to acute exacerbations of COPD (AECOPD) during the coronavirus disease 2019 (COVID-19) pandemic. However, the impact of the pandemic in AECOPD of all severities in longitudinal cohorts of patients is lacking.

Methods: We conducted analysis of 123 individuals with COPD who have been followed since 2017.

Machine-learning-based COVID-19 mortality prediction model and identification of patients at low and high risk of dying.

Background: The coronavirus disease 2019 (COVID-19) pandemic caused by the SARS-Cov2 virus has become the greatest health and controversial issue for worldwide nations. It is associated with different clinical manifestations and a high mortality rate. Predicting mortality and identifying outcome predictors are crucial for COVID patients who are critically ill.