Objectives: The susceptibility to infection increases in systemic lupus erythematosus (SLE) patients with neutropenia, but the link between infection risk and the cutoff neutrophil count still remains controversial. In this study, we investigated a valuable parameter associated with early serious infection in SLE patients during the first follow-up year.
Methods: We reviewed the medical records of 160 patients with SLE. The initial levels were defined as the mean of the results of the first two consecutive tests. The adjusted levels were defined as the results of the accumulated area under the curve divided by interval follow-up days. Patients were divided into two groups according to early serious infection and initial and adjusted neutropenia and were then compared.
Results: Immunosuppressive-naïve SLE patients with early serious infection more frequently had initial, latest, and adjusted leukopenia and neutropenia (<2,500/mm(3)) and hypocomplementemia than those without. Adjusted neutropenia was the only independent predictive value for early serious infection [odds ratio (OR 11.366)]. Initial neutropenia was the independent predictive value for adjusted neutropenia (OR 6.504).
Conclusions: We suggest that adjusted neutropenia is useful for predicting early serious infection in SLE patients during the first follow-up year.
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http://dx.doi.org/10.1007/s10165-012-0666-1 | DOI Listing |
Sci Rep
January 2025
D. Y. Patil Agriculture and Technical University, Talsande, Maharashtra, India.
Indian agriculture is vital sector in the country's economy, providing employment and sustenance to millions of farmers. However, Plant diseases are a serious risk to crop yields and farmers' livelihoods. Traditional plant disease diagnosis methods rely heavily on human expertise, which can lead to inaccuracies due to the invisible nature of early disease symptoms and the labor-intensive process, making them inefficient for large-scale agricultural management.
View Article and Find Full Text PDFArq Bras Cir Dig
January 2025
Universidade de São Paulo, Faculty of Medicine, Department of Gastroenterology - São Paulo (SP), Brazil.
Background: Obesity is a predisposing factor for serious comorbidities, particularly those related to elevated cardiovascular mortality. The atherogenic index of plasma (AIP) has been shown to be a useful indicator of patients with insulin resistance.
Aims: The aim of this study was to assess cardiovascular risk before and after surgical treatment of obesity.
Naunyn Schmiedebergs Arch Pharmacol
January 2025
Pharmacology Department, Medical and Clinical Research Institute, National Research Centre, Dokki, Cairo, 12622, Egypt.
Rheumatoid arthritis (RA) is one of the most common systemic autoimmune inflammatory diseases, with a progressive etiology that results in serious complications and a higher chance of early death. Visfatin, an adipokine, is correlated with disease pathologic features and becomes a key biomarker and therapeutic target for RA. This study aimed to evaluate the anti-arthritic activity of metformin (an antidiabetic drug with anti-inflammatory activities) and methotrexate (the first choice for disease-modifying antirheumatic drugs in RA, with diverse adverse effects) in complete Freund's adjuvant (CFA)-induced arthritis in female rats.
View Article and Find Full Text PDFFront Clin Diabetes Healthc
January 2025
Department of Clinical Pharmacy, School of Pharmacy, Institute of Health Sciences, Wallaga University, Nekemte, Ethiopia.
Background: Diabetic ketoacidosis (DKA) is a serious and acute complication of diabetes mellitus. In Ethiopia, the mortality associated with acute diabetes complications ranges from 9.8% to 12%.
View Article and Find Full Text PDFJ Cheminform
January 2025
Department of Intelligent Electronics and Computer Engineering, Chonnam National University, Gwangju, Republic of Korea.
The human ether-a-go-go-related gene (hERG) channel plays a critical role in the electrical activity of the heart, and its blockers can cause serious cardiotoxic effects. Thus, screening for hERG channel blockers is a crucial step in the drug development process. Many in silico models have been developed to predict hERG blockers, which can efficiently save time and resources.
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