Objective: Risk factors for major adverse coronary events (MACE) in renal transplant recipients are often different from those of non-transplanted populations. We compared the predictive power of lipoprotein components (LC) to that of more traditional risk factors such as serum creatinine, diabetes and inflammation measured by C-reactive protein (CRP) in the assessment of lescol in renal transplantation (ALERT) trial population.
Methods: From the 2102 randomized patients in ALERT we selected 1734 patients with a complete set of risk and adjustment factors used in the study. Cox regression analysis was used to estimate relationships between baseline values of risk factors and first occurrence of MACE. Chi square statistics, receiver operating characteristics (ROC) and net reclassification improvement (NRI) were used to compare the information value of different risk factors.
Results: Atherogenic LC and especially non-high density cholesterol (nHDL-C) were as predictive as creatinine and nHDL-C was about as predictive as diabetes. CRP, body mass index, hypertension and glucose had less prediction ability than nHDL-C. The rank order of prediction was the same in the two treatment groups. By regression modelling the actual MACE risk reduction from 6 weeks onwards was well predicted from the difference in LC at 6 week.
Conclusion: LC and especially nHDL-C predicted MACE at least as good as creatinine. Diabetes was about equally good as nHDL-C to predict MACE occurrence. Inflammation had less prediction ability than the other factors. Treated levels of atherogenic LC predicted MACE risk reduction well.
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http://dx.doi.org/10.1016/j.atherosclerosis.2009.06.020 | DOI Listing |
Front Biosci (Landmark Ed)
January 2025
School of Cardiovascular and Metabolic Medicine & Sciences, British Heart Foundation Centre of Research Excellence, King's College London, SE5 9NU London, UK.
Cardiovascular disease (CVD) is the most prevalent cause of mortality and morbidity in the Western world. A common underlying hallmark of CVD is the plaque-associated arterial thickening, termed atherosclerosis. Although the molecular mechanisms underlying the aetiology of atherosclerosis remain unknown, it is clear that both its development and progression are associated with significant changes in the pattern of DNA methylation within the vascular cell wall.
View Article and Find Full Text PDFEur Stroke J
January 2025
Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Background: We aimed to assess impairments on health-related quality of life, and mental health resulting from Retinal artery occlusion (RAO) with monocular visual field loss and posterior circulation ischemic stroke (PCIS) with full or partial hemianopia using patient-reported outcome measures (PROMs).
Methods: In a prospective study, consecutive patients with acute RAO on fundoscopy and PCIS on imaging were recruited during their surveillance on a stroke unit over a period of 15 months. Baseline characteristics were determined from medical records and interviews.
Br J Hosp Med (Lond)
January 2025
Department of Nephrology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
The Geriatric Nutritional Risk Index (GNRI) is an effective tool for identifying malnutrition, and helps monitor the prognosis of patients undergoing maintenance hemodialysis. However, the association between the GNRI and cardiovascular or all-cause mortality in hemodialysis patients remains unclear. Therefore, this study investigated the correlation of the GNRI with all-cause and cardiovascular mortality in patients undergoing maintenance hemodialysis.
View Article and Find Full Text PDFBr J Hosp Med (Lond)
January 2025
Department of Surgery & Cancer, Imperial College London, London, UK.
Predictive algorithms have myriad potential clinical decision-making implications from prognostic counselling to improving clinical trial efficiency. Large observational (or "real world") cohorts are a common data source for the development and evaluation of such tools. There is significant optimism regarding the benefits and use cases for risk-based care, but there is a notable disparity between the volume of clinical prediction models published and implementation into healthcare systems that drive and realise patient benefit.
View Article and Find Full Text PDFBr J Hosp Med (Lond)
January 2025
Speech and Language Rehabilitation Department, Beijing Rehabilitation Hospital Affiliated with Capital Medical University, Beijing, China.
The background for establishing and verifying a dehydration prediction model for elderly patients with post-stroke dysphagia (PSD) based on General Utility for Latent Process (GULP) is as follows: For elderly patients with PSD, GULP technology is utilized to build a dehydration prediction model. This aims to improve the accuracy of dehydration risk assessment and provide clinical intervention, thereby offering a scientific basis and enhancing patient prognosis. This research highlights the innovative application of GULP technology in constructing complex medical prediction models and addresses the special health needs of elderly stroke patients.
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