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Use of aVR and Jastrzębski algorithms in the classification of wide complex tachycardia in dogs – a preliminary study

algorithms as well as the VT score developed by Jastrzębski et al . ( 1 , 6 , 7 , 12 ). In veterinary medicine, no such algorithms are available, and the only parameter used for VT description is the duration of the QRS complexes. It is widely accepted that a duration of the QRS complex above 50 ms or 60 ms in large animals indicates a ventricular origin of the tachycardia ( 3 , 11 ). As previously mentioned, such an assumption may be erroneous due to preexisting or temporary interventricular conduction abnormalities, which could present with a similar ventricular

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Correlations Between Severity of Coronary Calcification and Impairment of Left Ventricular Ejection Fraction

Radiology and Intervention, and the Councils on Clinical Cardiology and Cardiovascular Disease in the Young. Circulation. 2008;118:586-606. 3. Greenland P, Bonow RO, Brundage BH, et al. ACCF/AHA 2007 Clinical Expert Consensus Document on Coronary Artery Calcium Scoring By Computed Tomography in Global Cardiovascular Risk Assessment and in Evaluation of Patients With Chest Pain. Journal of the American College of Cardiology. 2007;49(3):378-402. 4. Benedek T, Gyongyosi M, Benedek I. Multislice Computed Tomographic Coronary Angiography for

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Characteristics of Coronary Lesions in Small Vessel Disease Treated with Elective Stenting in Patients with Type 2 Diabetes Mellitus

C, Callister TQ, Browner WS. What does my patient's coronary artery calcium score mean? Combining information from the coronary artery calcium score with information from conventional risk factors to estimate coronary heart disease risk. BMC Med . 2004;2:31. 11. Moses JW1, Leon MB, Popma JJ et al. Sirolimus-Eluting Stents versus Standard Stents in Patients with Stenosis in a Native Coronary Artery. N Engl J Med . 2003;349(14):1315-23. 12. Wiebe J, Nef HM, Hamm CW. Current status of bioresorbable scaffolds in the treatment of coronary artery disease

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Measuring Fielding Performance in Cricket


Introduction. In cricket, the evaluation of individual player performance has been based on measures such as batting and bowling averages. These statistics are used to quantify the batting and bowling performance of cricketers, but there are no statistics for measuring the performance of fielders. This paper introduces a measure that can be used to assess the fielding performance of cricketers. Method. Various factors that are considered important in fielding are quantified to scores based on the ball-by-ball information of a match for each cricketer. The fielding points of each ball are then combined to calculate the total fielding points of a cricketer in a given match. All the fielding points are then added in order to obtain total fielding points of a cricketer up to a given match. Average fielding points are obtained by dividing the total fielding score by the number of matches played. Data. To demonstrate these measures, the first ODI match of India against Zimbabwe played on 11th June, 2016, is examined. Conclusion. The recommended measures can be used to quantify the fielding performances of cricketers for a series of matches, whether it is ODI or Twenty20 cricket. They make it possible to assess the average fielding performance of each player. Individual fielding performance scores can then be aggregated to measure the overall fielding performance of a team.

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Inter-relation between Altered Nutritional Status and Clinical Outcomes in Patients with Acute Myocardial Infarction Admitted in a Tertiary Intensive Cardiac Care Unit

-0959.2004.17603.x. 15. Ignacio de Ulibarri J, Gonzalez-Madrono A, de Villar NG, et al. CONUT: a tool for controlling nutritional status. First validation in a hospital population. Nutr Hosp. 2005;20:38-45. 16. Iwakami N, Nagai T, Furukawa TA, et al. Prognostic value of malnutrition assessed by Controlling Nutritional Status score for long-term mortality in patients with acute heart failure. Int J Cardiol. 2017;230:529-536. doi: 10.1016/j.ijcard.2016.12.064. 17. Toyokawa T, Kubo N, Tamura T, et al. The pretreatment Controlling Nutritional Status (CONUT) score is

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Relations Between Diabetes, Kidney Disease and Metabolic Syndrome: Dangerous Liaisons

, Fitzgerald AP et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J 24: 987-1003, 2003. 6. D’Agostino RB Sr, Vasan RS, Pencina MJ et al. General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation 117: 743-753, 2008. 7. Centers for Disease Control and Prevention . National diabetes fact sheet: National estimates and general information on diabetes and prediabetes in the United States, 2011. Atlanta, GA: U.S. Department of Health and Human Services, Centers for

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Outcomes in Anterior Cruciate Ligament Reconstruction Surgery

ligament injuries. Clin Orthop Relat Res. 1985;(198):43-49. 4. Mitsou A, Vallianatos P, Piskopakis N, et al. Anterior cruciate ligament reconstruction by over-the-top repair combined with popliteus tendon plasty. J Bone Joint Surg Br. 1990;72:398-404. 5. Roos EM, Roos HP, Lohmander LS, Ekdahl C, Beynnon BD. Knee Injury and Osteoarthritis Outcome Score (KOOS) - development of a selfadministered outcome measure. J Orthop Sports Phys Ther. 1998;28:88-96. 6. Irrgang JJ, Anderson AF, Boland AL, et al. Development and validation

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Evidence Based Practice in Using Antibiotics for Acute Tonsillitis in Primary Care Practice

;1(3):239–246. 7. McIsaac WJ, Goel V, To T. Low DE. The validity of a sore throat score in family practice. CMAJ 2000;163:811–815. 8. Marjukka Makela Article ID: ebm00007 (038.020) EBM Guidelines, 27.04.2011, available at 9. Teng CL, Tong SF, Khoo EM, Lee V, Zailinawati AH, Mimi O, et al. Antibiotics for URTI and UTI—prescribing in Malaysian primary care settings. Aust Fam Physician 2011;40:325–9. 10. Teixeira Rodrigues A, Roque F, Falcão A, Figueiras A

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Prevalence of Claw Diseases in Dairy Cows with Different Body Condition

, H., 1989: Associations between types of lameness and fertility. Vet. Rec. , 125, 103—106. 4. Danscher, A. M., Toelboell, T. H., Wattle, O., 2010: B iomechanics and histology of bovine claw suspensory tissue in early acute laminitis. J. Dairy Sci. , 93, 53—62. 5. Edmonson, A. J., Lean, I. J., Weaver, L. D., Farver, T., Webster, G., 1989: A body condition scoring chart for Holstein cows. J. Dairy Sci. , 72, 68—78. 6. Egger-Danner, C., Nielsen, P., Fiedler, A., Müller, K., Fjeldaas, T., Döpfer, D., et al., 2015: ICAR Claw Health Atlas. Rome

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An Integrated Database to Measure Living Standards

Survey Non-response.” International Statistical Review 78(1): 40–64. Doi: . Attanasio, O., E. Hurst, and L. Pistaferri. 2015. “The Evolution of Income, Consumption, and Leisure Inequality in the US, 1980–2010.” In Improving the Measurement of Consumer Expenditures , edited by C.D. Carroll, T.F. Crossley, and J. Sabelhaus, 100–140. University of Chicago Press. Augurzy, B. and C.M. Schmidt. 2001. The Propensity Score: A Means to an End , IZA Discussion Paper No. 271. Available at: https

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