Early recognition of vulnerable patients is an important issue for stroke prevention. In our study, a multiscore analysis of various biomarkers was performed to evaluate its superiority over the analysis of single factors. Study subjects (n = 110) were divided into four groups: asymptomatic patients with stable (n = 25) and unstable (n = 36) plaques and symptomatic patients with stable (n = 13) and unstable (n = 36) plaques. Serum levels of MMP-1, -2, -3, -7, -8, -9, TIMP-1, -2, TNF-α, IL-1b, and IL-6, -8, -10, -12 were measured. Multi-score analysis was performed using multiple receiver operating characteristics (ROC) and determination of appropriate cutoff values. Significant differences between the groups were observed for MMP-1, -7, -9 and TIMP-1 in serum of the study subjects (P < 0.05). Multiple biomarker analysis led to a significant increase in the AUC (area under curve). In case of plaque instability, positive predictive value (PPV) for up to 86.4% could be correctly associated with vulnerable plaques. Thus, multiscore analysis might be preferable than the use of single biomarkers.
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http://dx.doi.org/10.1155/2012/906954 | DOI Listing |
J Med Internet Res
November 2024
Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea.
Background: Assessing the complex and multifaceted symptoms of patients with acute psychiatric disorders proves to be significantly challenging for clinicians. Moreover, the staff in acute psychiatric wards face high work intensity and risk of burnout, yet research on the introduction of digital technologies in this field remains limited. The combination of continuous and objective wearable sensor data acquired from patients with deep learning techniques holds the potential to overcome the limitations of traditional psychiatric assessments and support clinical decision-making.
View Article and Find Full Text PDFEncephale
August 2024
Faculté des lettres et des sciences humaines, laboratoire de psychologie Clinique et Cognitive (LPCC), université-saint Joseph, Beyrouth, Liban.
Objectives: Evaluate the prevalence of depression in a population of children aged 8 to 10 years with learning disabilities treated in a Special Education and Home Care Service (SESSAD) and identify the protective factors that might preserve these children from depressive and affective problems.
Methods: Twenty children, aged 8 to 10, with learning disabilities were evaluated prior to their admission in SESSAD. Depression had been assessed through the Multiscore Depression Inventory for Children (MDIC), adapted to the French population as well as their developmental position in relation with their perceptual maturity of their body schema, through the Draw your family drawing.
BMC Med Res Methodol
December 2017
Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.
Background: Prediction models and prognostic scores have been increasingly popular in both clinical practice and clinical research settings, for example to aid in risk-based decision making or control for confounding. In many medical fields, a large number of prognostic scores are available, but practitioners may find it difficult to choose between them due to lack of external validation as well as lack of comparisons between them.
Methods: Borrowing methodology from network meta-analysis, we describe an approach to Multiple Score Comparison meta-analysis (MSC) which permits concurrent external validation and comparisons of prognostic scores using individual patient data (IPD) arising from a large-scale international collaboration.
Int J Vasc Med
August 2012
Clinic of Vascular Surgery, Klinikum Rechts der Isar der Technischen Universitaet Muenchen, Ismaninger Straße 22, 81675 Munich, Germany.
Early recognition of vulnerable patients is an important issue for stroke prevention. In our study, a multiscore analysis of various biomarkers was performed to evaluate its superiority over the analysis of single factors. Study subjects (n = 110) were divided into four groups: asymptomatic patients with stable (n = 25) and unstable (n = 36) plaques and symptomatic patients with stable (n = 13) and unstable (n = 36) plaques.
View Article and Find Full Text PDFPLoS One
March 2012
Informatics and Systems Department and Biomedical Informatics and Chemoinformatics Group, Division of Engineering Research and Centre of Excellence for Advanced Sciences, National Research Centre, Cairo, Egypt.
The design of small interfering RNA (siRNA) is a multi factorial problem that has gained the attention of many researchers in the area of therapeutic and functional genomics. MysiRNA score was previously introduced that improves the correlation of siRNA activity prediction considering state of the art algorithms. In this paper, a new program, MysiRNA-Designer, is described which integrates several factors in an automated work-flow considering mRNA transcripts variations, siRNA and mRNA target accessibility, and both near-perfect and partial off-target matches.
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