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The hematocrit known as erythrocyte volume fraction (EVF) or packed cell volume (PCV), is the volume percentage of red blood cells in blood. The present report examines the association between hematocrit (HCT) and anyone of seven cardiac parameters such as shock type (SHOCKT), heart rate (HR), mean arterial pressure (MAP), cardiac index (CI), systolic blood pressure (SBP), mean central venous pressure (MCVP), diastolic blood pressure (DBP) for shock patients. It is reported herein that that mean HR is partially positively associated with HCT (P = 0.1002), while mean MAP is partially negatively associated with HCT (P = 0.0988). Variance of MAP is partially positively associated with HCT (P = 0.0703), while variance of CI is negatively associated with HCT (P = 0.0039). On the other hand, mean HCT is negatively associated with shock type (SHOCKT) at level 2 (P = 0.0014) & at level 3 (P = 0.0281). Variance of HCT is partially negatively associated with SBP (P = 0.0947) and HR (P = 0.0718), while it is partially positively associated with CI (P = 0.1049). Note that in epidemiology, partially significant (herein considered around 10% level of significance) effects are known as confounders. It is observed herein that HCT has some effects on HR, MAP, shock type, SBP & CI, but it has no effect on DBP & MCVP for the considered data set. and stickiness of blood, which is a direct measure of the ability of blood to flow through the vessels. It may have inverse relationship with blood flow. It was reported that in the range of 60.16% and 25.32%, a 10.99% increase of hematocrit produced an increase of 1 unit relative viscosity, which means approximately a 20% increase in blood viscosity for a healthy individual [7]. Due to HCT increased, increasing viscosity is a possible cause of changes in blood flow rate, blood pressure, and the equivalent physiologic compensation ratios [6-8]. Most of the earlier conclusions regarding the association between HCT and the incidence of CVD have been drawn based on inappropriate statistical methods such as genderpooled multivariable Cox proportional hazards models, generalized additive models, nonparametric regression smoothing [1,7,8]. Best of our knowledge, there is a little study regarding the association between HCT and any cardiac parameter based on probabilistic model along with model justification. The report focuses the effects of HCT on every one of seven cardiac parameters such as shock type, HR, SBP, MAP, DBP, CI and MCVP with the help of a real data set of 113 study units containing 20 study characters [9]. The given data set is a multivariate data, which has been recorded twice (measurements upon admission and just before death or discharge). The association of HCT with any cardiac parameter can be observed in two ways. One way is with the help of probabilistic modeling of HCT on cardiac parameters, and along with other independent variables. Another way is with the help of probabilistic modeling of any cardiac parameter on HCT, and along with other independent variables. Note *Corresponding author: Rabindra Nath Das, Professor, Department of Statistics, College of Natural Science, Seoul National University, Seoul, 151-747, Korea ShoRt ReSeaRch aRticLe

Effects of Hematocrit on Cardiac Parameters for Shock Patients