Amongst 556 CXCR Antagonist site neurosurgical sufferers, 73 underwent postsurgery venous US for improved D-dimer levels and 35 had a DVT; F. Boscaro1; A. Rizzoli3; G. Avruscio2; F. FabrisClinical Medicine 1, Department of Medicine, University Hospitalof Padova, Padova, Italy; 2Unit of Angiology, Department of Cardiac, Thoracic and Vascular Sciences, University Hospital of Padova, Padova, Italy; 3Neurosurgery, Department of Neuroscience, University Hospital of Padova, Padova, ItalyABSTRACT869 of|between the 3rd -15th post-operative day, DVT occurred in 20/43 (46.5 ) sufferers. We identified no association involving DVT and all variables deemed, except D-dimer levels, which have been greater in sufferers who developed DVT. Logistic regression analysis revealed OR 1.98 (CI 1.04.78, p 0.03) for every single 1000 g/L D-dimer improve. The ROC curve identified an optimal D-dimer cutoff 1334 g/L (SEN 0.90, SPE 0.52, LR- 0.two) (OR 9.eight, CI 1.8.7, p 0.007); 2200 g/L Ddimer levels were linked using the best constructive predictive value (SPE 0.87, PPV 77 , LR+ 3.8). Conclusions: Elevated D-dimer levels were linked with improved risk of building DVT immediately after neurosurgery.Table 1 Clinical summary of the sufferers.Thrombosis Number of Sufferers Age (years) Male ( ) Typical Body Mass Index (kg/m Family History of VTE Obesity Surgery Gestacional/postpartum Hormonal contraceptive 40 37.5 (188) 20 25 (190) 23 9 two 3 19 Control 50 40 (236) 26 24 (186) 0 eight 0 0PB1188|Diagnosing Deep Venous Thrombosis using Artificial Neural Networks and Metabolomics by 1H-NMR Information T.D. Martins1; M. Quintero2,three; L. Tasic3; T.B.B.C. Costa3; D. Stanisic ; S.A.L. Montalv two; S.C. Huber2; E.V. de Paula2; R.M. Filho four; J.M. Annichino-Bizzacchi1Results: The most beneficial result was obtained having a two hidden layer ANN, containing 20 and five neurons inside the initially and second hidden layers, respectively. Each of the statistical parameters discovered for the ideal model are shown in Table 2. The model presented high ACC, AUC, TPR, and TNR. Also, it presented a low probability to indicate false benefits, which was confirmed by the LR+ and LR- values. Table two Summary final results obtained for the validation datasetPerformance Metric Accuracy (ACC) AUC Positive Predicted Value (PPV) Unfavorable Predicted Value (NPV) Accurate Positive Price (TPR) False Positive Price (FPR) Correct Adverse Rate (TNR) Good Likelihood Ratio (LR+) Unfavorable Likelihood Ratio (LR-) Value 93.three 0.982 0.860 1.000 1.000 0.110 0.890 9.000 0.Universidade Federal de S Paulo, Diadema, Brazil; 2Hemostasisand Thrombosis Laboratory, Hematology and Hemotherapy Center, University of Campinas, Campinas, Brazil; 3Chemical Biology Laboratory, Division of Organic Chemistry, Institute of Chemistry, University of Campinas, Campinas, Brazil; 4School of Chemical Engineering, University of Campinas, Campinas, Brazil Background: The metabolic profile of a BRPF2 Inhibitor drug patient can alterations when Deep Venous Thrombosis (DVT) requires place. It can be utilised on the disease’s diagnosis and to develop of an artificial intelligence predictive model. Aims: To get a neural network (ANN) to classify sufferers who have DVT (or not) according to their metabolic profile, obtained by Magnetic Resonance spectroscopy (NMR), and clinical data. Solutions: Table 1 summarizes the clinical patient traits. These sufferers presented a exceptional confirmed prior DVT of lower limbs or cerebral region and up to three years soon after the acute episode. Data had been collected in between 2015 and 2018. The inputs had been: sex, age, physique mass index, initially and second