Search

This prospective observational study compared the 1H NMR blood lipidomes and metabolomes of 71 patients with community-acquired pneumonia (CAP), 75 patients with COVID-19 pneumonia, and 75 healthy controls (matched by age and sex) to identify potential biomarkers and pathways associated with respiratory infections. Both pneumonia groups had comparable severity indices, including mortality, invasive mechanical ventilation, and intensive care unit admission rates. Patients with COVID-19 pneumonia exhibited more pronounced hypolipidemia, with significantly lower levels of total cholesterol and LDL-c compared to patients with CAP. Atherogenic lipoprotein subclasses (VLDL-cholesterol, IDL-cholesterol, IDL-triglyceride, and LDL-triglyceride/LDL-cholesterol) were significantly increased in severe cases of both pneumonia types, while lower HDL-c and small, dense HDL particles were associated with more severe illness. Both infected groups showed decreased esterified cholesterol and increased triglycerides, along with reduced phosphatidylcholine, lysophosphatidylcholine, PUFA, omega-3 fatty acids, and DHA. Additionally, infected patients had elevated levels of glucose, lactate, 3-hydroxybutyrate, and acetone, which are linked to inflammation, hypoxemia, and sepsis. Increased levels of branched-chain amino acids, alanine, glycine, and creatine, which are involved in energy metabolism and protein catabolism, were also observed. Neurotransmitter synthesis metabolites like histidine and glutamate were higher in infected patients, especially those with COVID-19. Notably, severe infections showed a significant decrease in glutamine, essential for lymphocyte and macrophage energy. The severity of COVID-19 pneumonia was also associated with elevated glycoprotein levels (glycoprotein A, glycoprotein B, and glycoprotein F), indicating an inflammatory state. These findings suggest that metabolomic and lipidomic changes in pneumonia are connected to bioenergetic pathways regulating the immune response., Competing Interests: Conflicts of interest The authors declare that they have no conflicts of interest with the contents of this article., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Aims: The prognosis of chronic heart failure (CHF) is extremely variable, although generally poor. The purpose of this study was to develop prognostic models for CHF patients., Methods and Results: A cohort of 992 consecutive ambulatory CHF patients was prospectively followed for a median of 44 months. Multivariable Cox models were developed to predict all-cause mortality (n = 267), cardiac mortality (primary end-point, n = 213), pump-failure death (n = 123), and sudden death (n = 90). The four final models included several combinations of the same 10 independent predictors: prior atherosclerotic vascular event, left atrial size >26 mm/m(2), ejection fraction < or =35%, atrial fibrillation, left bundle-branch block or intraventricular conduction delay, non-sustained ventricular tachycardia and frequent ventricular premature beats, estimated glomerular filtration rate <60 mL/min/1.73 m(2), hyponatremia < or =138 mEq/L, NT-proBNP >1.000 ng/L, and troponin-positive. On the basis of Cox models, the MUSIC Risk scores were calculated. A cardiac mortality score >20 points identified a high-risk subgroup with a four-fold cardiac mortality risk., Conclusion: A simple score with a limited number of non-invasive variables successfully predicted cardiac mortality in a real-life cohort of CHF patients. The use of this model in clinical practice identifies a subgroup of high-risk patients that should be closely managed.

Aims: The identification of valuable markers of sudden cardiac death (SCD) in patients with established HF remains a challenge. We sought to assess the value of clinical, echocardiographic and biochemical variables to predict SCD in a consecutive cohort of patients with heart failure (HF) due to systolic dysfunction., Methods: A cohort of 494 patients with established HF had baseline echocardiographic and NT-proBNP measurements and were followed for 942+/-323 days., Results: Fifty patients suffered SCD. Independent predictors of SCD were indexed LA size>26 mm/m2 (HR 2.8; 95% CI 1.5-5.0; p=0.0007), NT-proBNP>908 ng/L (HR 3.1; 95% CI 1.5-6.7; p=0.003), history of myocardial infarction (HR 2.3; 95% CI 1.3-4.1; p=0.007), peripheral oedema (HR 2.1; 95% CI 1.1-3.9; p=0.02), and diabetes mellitus (HR 1.9; 95% CI 1.1-3.3; p=0.03). NYHA functional class, left ventricular ejection fraction and glomerular filtration rate were not independent predictors of SCD in this cohort. Notably, the combination of both LA size>26 mm/m2 and NT-proBNP>908 ng/L increased the risk of SCD (HR 4.3; 95% CI 2.5-7.6; p<0.0001). At 36 months, risk of SCD in patients with indexed LA size26 mm/m2 and NT-proBNP>908 ng/L reached 25% (p<0.0001)., Conclusions: Among HF patients, indexed LA size and NT-proBNP levels are more useful to stratify risk of SCD than other clinical, echocardiographic or biochemical variables. The combination of these two parameters should be considered for predicting SCD in patients with HF.