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Introduction Brain dysfunction is a frequent complication of sepsis even in cases of extra-cranial origin and is related to several underlying mechanisms. Encephalography (EEG) seems to be a useful tool in detecting the presence of encephalopathy in patients with sepsis. Although EEG is not a specific test, it is sensitive and can detect abnormalities even when clinical neurologic examination is normal. The aim of this study was to document the EEG abnormalities and search for correlations between EEG findings and commonly used severity and prognostic scores

patient visits, and is therefore not easily applicable to large patient populations. In recent years, a number of serum-based fibrosis tests have been developed and validated. Many studies have reported reasonable performance characteristics and good agreement with biopsy or elastography data.[ 4 , 5 ] With the advent of electronic medical record systems, fibrosis scores can be easily calculated after extracting the pertinent test results for each patient. This process does not require additional patient visits, and can be applied to large patient cohorts. As such, EMR


Introduction: Depression and cognitive impairment are the most frequent mental disorders in multiple sclerosis (MS) and represent an important cause of morbidity and mortality. The aim of the study was to analyse the main determinants of depression in multiple sclerosis.

Materials and methods: Thirty-two patients with relapsing remitting multiple sclerosis (RRMS), treated with Interferon Beta 1a, without relapses and corticosteroid treatment in the last 30 days, were included in the study. The mean age of the patients was 35.4±9.2 years, M/F ratio 0.33. Depression level was evaluated by the Romanian version of Beck Depression Inventory (BDI) and the cognitive function with Paced Auditory Serial Addition Test 3 (PASAT 3), Symbol Digit Modalities Test (SDMT). The functional status and disability level of the patients were evaluated with Multiple Sclerosis Functional Composite and Expanded Disability Status Scale. In all patients a cerebral MRI with intravenous contrast administration was performed using a 1.5T MRI device.

Results: Twenty-three patients were free of depression (score 1-10), 4 patients presented mild mood disturbance (score 11-16), 3 borderline clinical depression (score 17-20) and 2 moderate depression (score 21-30). The mean BDI score was 8.71±7.16. BDI score correlated significantly with EDSS (R=0.38, p=0.03), PASAT 3 (R=-0.42, p=0.01), SDMT (R=-0.58, p=0.0007), Timed 25-Foot Walk (R=0.43, p=0.01) and 9-Hole Peg Test (R=0.45, p=0.008). From the EDSS functional scores, significant correlations were found with the urinary score (R=0.4, p=0.01) and sensitive score (R=0.49, p=0.004). BDI score correlated significantly with the total number of T2 lesions (R=0.31, p=0.05) while there was no correlation with the number of active lesions.

Conclusions: The main determinants of depression in RRMS patients are the cognitive impairment, the affection of fine hand movements (9-HP), gait impairment (T25FT) and bladder and sensitive dysfunction.

. Clinical Antecedents to In-Hospital Cardiopulmonary Arrest. Chest. 1990;98(6):1388-1392. doi: 8. Simpson SQ. SIRS in the Time of Sepsis-3. Chest. 2018;153(1):34-38. doi: 9. Churpek, Matthew & Snyder, Ashley & Han, Xuan & Sokol, Sarah & Pettit, Natasha & Howell, Michael & Edelson, Dana. (2016). qSOFA, SIRS, and Early Warning Scores for Detecting Clinical Deterioration in Infected Patients Outside the ICU. American Journal of Respiratory and Critical Care Medicine. 195. 10.1164/rccm.201604

complications has been observed.[ 7 - 8 ] In the past few years, several biochemical indices have been proposed for the noninvasive evaluation of liver fibrosis in patients with chronic viral hepatitis and normal renal function. However, little data is available regarding this issue among the ESRD population.[ 9 , 10 , 11 ] To minimize the need of liver biopsy and overcome its aforementioned limitations, there is a need to use tests that are less invasive and relatively easier to perform. We studied the diagnostic accuracy of two scoring systems, aspartate aminotransferase

References [1] P. Avery, Score sequences of oriented graphs, J. Graph Theory , 15, 3 (1991) 251–257. ⇒257 [2] R. A. Brualdi and J. Shen, Landau’s inequalities for tournament scores and a short proof of a Theorem on transitive sub-tournaments, J. Graph Theory , 38 (2001) 244–254. ⇒258 [3] R. A. Brualdi and J. Shen, Landau’s inequalities for tournament scores and a short proof of a Theorem on transitive sub-tournaments, J. Graph Theory , 38 (2001) 244–254. ⇒258 [4] J. R. Griggs and K. B. Reid, Landau’s theorem revisited, Australasian J. Combinatorics


This study presents the evaluation of chosen anthropometric and motor parameters in group of female junior competitors throughout the course of 2-year preparation of aerobic gymnastics by means of Z-scores. The observed group consisted of 12 girls (average age at the beginning of observance 14.08 ± 1.19 years). Evaluation of anthropometric (body height, body weight, body mass index, percentage of body fat, acting body weight) and motor parameters (sit-ups in 30 seconds and 60 seconds, pull-ups to bar, modified push-ups, standing long jump, backwards tandem walking, shuttle run 4×10 m, Jacík’s test) was carried out in standard conditions in nine girls at 3-month intervals. It has been confirmed that female probands with higher Z-score of motor parameters together with lower Z-score of anthropometric parameters achieved higher sport performance during the 2-year observance at competitions, with an exception of one such proband.

2014). Rosenbaum, P. and D. Rubin. 1983. “The Central Role of the Propensity Score in Observational Studies for Causal Effects.” Biometrika 70: 41-55. DOI: Särndal, C.-E. 2011. “The 2010 Morris Hansen Lecture Dealing with Survey Nonresponse in Data Collection, in Estimation.” Journal of Official Statistics 27: 1-21. SAS Institute Inc. Enterprise Miner 6.2 Help and Documentation. Cary, NC: SAS Institute Inc., 2009. Schouten, B. 2007. “A Selection Strategy for Weighting Variables Under a Not-Missingat- Random Assumption

References [1] G. G. Alway, Matrices and sequences, Math. Gazette 46 (1962) 208-213. ⇒21 [2] C. M. Bang, H. Sharp, An elementary proof of Moon’s theorem on generalized tournaments, J. Comb. Theory, Ser. B 22, 3 (1977) 299-301. ⇒21 [3] C. M. Bang, H. Sharp, Score vectors of tournaments, J. Comb. Theory, Ser. B 26, 1, (1979) 81-84. ⇒31 [4] A. Brauer, I. C. Gentry, K. Shaw, A new proof of a theorem by H. G. Landau on tournament matrices, J. Comb. Theory 5, 3 (1968) 289-292. ⇒21 [5] R. A. Brualdi, E. Fritscher, Tournaments associated with multigraphs, Discrete Math

References [1] G. Chartrand, L. Lesniak, J. Roberts, Degree sets for digraphs, Periodica Math. Hung., 7 (1976) 77-85. ⇒212 [2] T. H. Cormen, Ch. E. Leiserson, R. L. Rivest, C. Stein, Introduction to Algorithms (third edition), The MIT Press/McGraw Hill, Cambridge/New York, 2009. ⇒216 [3] J. L. Gross, J. Yellen, P. Zhang, Handbook of Graph Theory, CRC Press, Boca Raton, FL, 2013. ⇒210 [4] M. Hager. On score sets for tournaments, Discrete Math., 58 (1986) 25-34. ⇒ 210, 212 [5] A. Iványi, J. Elek, Degree sets of tournaments, Studia Univ. Babe,s-Bolyai, Informatica