Short-term effectiveness of different volume replacement therapies in postoperative hypovolaemic patients
ABSTRACT To examine the kinetics of volume loading with crystalloid and colloid infusions in critically ill patients after major surgery, using the pulse contour cardiac output (PiCCO) monitoring technique.
This prospective, randomized, multicentre study of 11 ICUs involved 200 mixed postoperative hypovolaemic patients (50 patients per group) in Hungary. Patients received 10 ml kg of lactated Ringer's solution, succinylated gelatin 4% w/v, 130/0.4 hydroxyethyl starch 6% w/v (HES) or human albumin 5% w/v over 30 min. A complete haemodynamic profile was obtained at 30, 45, 60, 90 and 120 min after baseline. The peak haemodynamic effects, the 120 min changes compared with baseline, the area under the curve (AUC) for the haemodynamic parameters over 120 min and the haemodilution effect of the solutions were analysed. The primary outcome was to compare the AUCs and the secondary outcome was to evaluate the haemodynamic changes at 120 min.
There were significant differences in the AUCs of the haemodynamic parameters between colloids and lactated Ringer's solution in the cardiac index and global end-diastolic volume index (GEDVI); human albumin vs. lactated Ringer's solution in stroke volume variation (SVV); and succinylated gelatin, HES vs. lactated Ringer's solution in the oxygen delivery index (DO2I). Colloid infusions (mainly HES and human albumin) at 120 min caused significant changes in central venous pressure, cardiac index, GEDVI, SVV, DO2I and central venous oxygen saturation compared with baseline. The haemodilution effect was significantly greater in colloids vs. lactated Ringer's solution.
In postoperative hypovolaemic patients, lactated Ringer's solution can significantly improve haemodynamics at the end of volume loading, but this effect completely disappears at 120 min. Ten millilitres per kilogram of colloid bolus (especially HES) improved the haemodynamics at 120 min; however, this was by only 5-25% compared with baseline. The colloids caused significantly larger AUCs than lactated Ringer's solution, but only in the cardiac index, GEDVI and DO2I, plus human albumin in the SVV.
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ABSTRACT: PURPOSE: To determine whether fluid resuscitation of acutely ill adults with 6 % hydroxyethyl starch (6 % HES 130) with a molecular weight of 130 kD and a molar substitution ratio of approximately 0.4 (6 % HES 130) compared with other resuscitation fluids results in a difference in the relative risk of death or treatment with renal replacement therapy (RRT). METHODS: Systematic review and meta-analysis of randomized controlled trials comparing intravascular fluids for resuscitation of hospitalised adults that reported mortality or treatment with RRT. The risk of bias was assessed independently by two reviewers and meta-analysis was performed using random effects. RESULTS: Thirty-five trials enrolling 10,391 participants were included. The three largest trials had the lowest risk of bias, were published (or completed) in 2012, and together enrolled 77 % of all participants. Death occurred in 928 of 4,691 patients (19.8 %) in the 6 % HES 130 group versus 871 of 4,720 (18.5 %) in the control fluid groups relative risk (RR) in the 6 % HES 130 group 1.08, 95 % confidence interval (CI) 1.00 to 1.17, I (2) = 0 %). Treatment with RRT occurred in 378 of 4,236 patients (8.9 %) in the 6 % HES 130 group versus 306 of 4,260 (7.2 %) in the control fluid group (RR in the 6 % HES 130 group 1.25, 95 % CI 1.08 to 1.44, I (2) = 0 %). CONCLUSIONS: The quality and quantity of data evaluating 6 % hydroxyethyl starch (130/0.4 and 130/0.42) as a resuscitation fluid has increased in the last 12 months. Patients randomly assigned to resuscitation with 6 %HES 130 are at significantly increased risk of being treated with RRT.European Journal of Intensive Care Medicine 02/2013; 39(4). DOI:10.1007/s00134-013-2840-0 · 5.54 Impact Factor
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ABSTRACT: SubPcBCl is synthesized from 1,4-benzene diboronic acid with a yield of 45%. The infrared, electronic and proton NMR spectra are in accordance with the results of literature.Comptes Rendus Chimie 06/2011; 14(6):530-533. DOI:10.1016/j.crci.2010.09.008 · 1.48 Impact Factor
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ABSTRACT: Diagnosing hypovolemia is not a trivial task. Hypovolemia itself has several physical signs, but their specificity and sensitivity is limited, even using sophisticated monitoring techniques. However, diagnosing hypovolemia is crucial in critically ill patients to avoid worse outcomes. The aim of this paper is to provide methods for better estimation of the degree of hypovolemia in ill patients. The so-called hypovolemic index (HVI) is introduced which classifies the degree of hypovolemia with a number in the interval [0, 1]. Four new methods are presented for the more precise diagnosis of hypovolemia. All methods rely on fuzzy logic. In the first method, clinical thresholds are used in the fuzzy rule system. The second method uses an iterative ROC analysis to determine the thresholds. The third one determines the thresholds using one single ROC analysis ("One step" method). The fourth method uses a genetic algorithm (GA) for the determination of the thresholds. The HVI is calculated using the data of patients from a previous investigation. Each method (except the first one) is tuned on a so called training database. Afterwards, they are carried out on a test database in order to determine the potential of the method. All four methods are capable of differentiating between hypovolemic and normovolemic patients. However, using the first and the second methods, several patients get a HVI of around 0.5, therefore, their degree of hypovolemia is ambiguous. The third and fourth methods deliver a better classification, hypovolemic and normovolemic patients are clearly separated from each other. All four novel methods deliver powerful tools for the diagnosis of hypovolemic patients. The degree of the hypovolemic state of each patient can be estimated with a hitherto unattained degree of reliability. Using ROC analysis and GA the estimation can be improved further.Computers in Biology and Medicine 09/2011; 41(11):1022-32. DOI:10.1016/j.compbiomed.2011.09.002 · 1.90 Impact Factor