Therefore, the aim of this study was to measure HMGB1 levels in circulating next monocytes as well as in the serum of patients undergoing elective surgical trauma. In addition, we evaluated a possible relationship between HMGB1 and Interleukin-6 (IL-6) production, since IL-6 is a key cytokine involved in surgical stress response.Materials and methodsPatientsFollowing approval by the Human Subjects Review Committee and the Research Ethics Board, 47 adult subjects, American Society of Anesthesiologists (ASA) physical status I and II, scheduled for major abdominal procedures, were included in a prospective study. Patients with diabetes, cardiac, pulmonary, renal, vascular, immunologic, neurodegenerative, infectious or hepatic diseases were excluded from the study.

Subjects who were taking medication known to interfere with hormonal, metabolic or immunological function as well as pregnant or breast feeding women were also excluded.Written informed consent was obtained from eligible patients during the screening period, at which time physical examination and medical history were evaluated. Postoperative complications were recorded throughout seven post-surgery days. Fifteen control subjects matched for sex, age and weight were also enrolled. Informed consent was obtained from the control subjects as well as the patients.Anesthesia techniqueAfter intravenous medication with midazolam (0.025 mg/Kg), all patients received a standard general anesthesia protocol. Anesthesia induction was performed by thiopentone sodium (5 mg/Kg) and fentanyl (1.4 ��g/Kg). Vecuronium (0.

08 mg/Kg) was injected to facilitate orotracheal intubation during direct laryngoscopy.Anesthesia was maintained with 60% air in oxygen supplemented with 1 to 2.5% inspired concentration of sevoflurane, fentanyl and vecuronium administered according to clinical need. In all patients a radial artery catheter was inserted for continuous monitoring of arterial blood pressure.In addition, standard parameters such as electrocardiogram (ECG), oxygen saturation (SaO2), End-Tidal carbon dioxide (ETCO2) and hemoglobin (HB) were measured during surgery. All patients’ lungs were mechanically ventilated by means of S/5 AVANCE device (Datex-Ohmeda, Helsinki, Finland) with the goal of achieving an ETCO2 level of 38 to 40 mmHg. Normal saline and Ringer Lactate solutions were administered with the infusion rate being adjusted from 6 to 10 ml/Kg/h according to blood loss.

Rectal temperature was maintained at 37��C by warming fluids before administration and using an upper body Bair Hugger (Arizant Brefeldin_A Healthcare Inc., Eden Prairie, MN, USA). Duration of both surgery and anesthesia was recorded. The same surgical team performed all operative procedures.After surgery neuromuscular blockade was antagonized with 0.5 to 1.5 mg atropine and 1 to 2.5 mg intrastigmine. Post-operative pain relief was provided by intravenous morphine bolus administered (0.

03 ��g/kg/minute). selleck Vandetanib Overall the Wilcoxon test showed a significant reduction in the noradrenaline dose (median from 0.06 to 0.035 ��g/kg/minute; P = 0.016; Table Table2)2) while the mean arterial pressure was stable during the bioreactor-treatment (median before 74, after 80 mmHg; not significant). Systemic vascular resistance index (SVRI) was not monitored in this study.Table 2Main laboratory parameters before and after the extracorporeal treatments.Coagulation disordersThere was no significant change in mean platelet counts during the extracorporeal treatment (Table (Table2).2). D-dimers did increase significantly during the extracorporeal treatment from 752 �� 505 ��g/l to 853 �� 450 ��g/l but returned to 609 �� 381 ��/l within 12 hours.

Antithrombin III concentration also changed significantly from 66 �� 17% at the beginning to 58 �� 15% at the end of the treatments, and improved slightly over the following 12 h to 61 �� 15%. Both activated partial thromboplastin time (aPTT) and prothrombin time (as International Normalized Ratio, INR) increased during the treatments due to heparin use but returned to pre-treatment values within 12 h after the extracorporeal circulation. No hemorrhages were observed.HemolysisNo signs of hemolysis were observed. Haptoglobin remained within the normal range and no significant change in lactate dehydrogenase was seen during the treatments.Moreover, no allergic reactions were recognized.Secondary endpoints (safety and efficacy): comparison of projected and observed mortalityExpected in-hospital mortality based on the ICU entrance APACHE II (29.

9 �� 7.2) and SAPS II (66.2 �� 19.5) scores were 69.1% and 71.5%, respectively [18-20]. The observed mortality rate was 3 out of 10 within 28 days (on days 6, 9, and 18), and four during hospital stay (Patient 7 died on Day 40). Six patients could be discharged from the hospital in stable condition. No significant differences were seen between the survivors and non-survivors in the time at ICU before inclusion or the time between inclusion and first treatment.Organ functions, vital signs and laboratory parametersThe body temperature of the patients was stable during the treatments (Table (Table2).2). While creatinine did not show a significant change during the six-hour treatments there were small but significant increases in urea (Table (Table2),2), most probably due to interruption of dialysis in patients with renal failure. However, urea decreased again slightly within 12 h post treatment to 14.7 �� 8.4 mmol/l. No difference in PaO2 and FiO2 has been observed between start and end of the extracorporeal treatment (Table (Table2).2). Furthermore, no significant changes have Drug_discovery been seen in PaO2 or FiO2 between the treatment day and the day after the treatment.

By d12 = 4 + = 64/21, the distance needed is obtained.The pseudo codes of GSOS as shown in Pseudocode 1.4. Simulations and ResultsTo verify the feasibility of GSOS, we have tested Tipifarnib price two simulations of different scales.Case 1 ��According to [9], there are 41 workpieces of 10 orders, detailed information are shown in Tables Tables33 and and4;4; target of optimization is maximizing the number of weighted whole-set orders.Table 3Orders and weights.Table 4Information of orders.In Table 4, numbers in row-1 account for deadlines, in line-1 account for orders and in brackets for processing time. According to the above information, we contrast the results between GSOS and GA.

Simulation environment: Microsoft Windows-XP system, AMD-A6-3400M CPU, 2G-RAM, and the codes are programmed by MATLAB2012a, the population size is fixed n = 400, maximum iteration Tmax = 80, and the program run 10 times independently.The efficiency of results is shown in Table 5. From Table 5, we can find that average solving time of GSOS is shortened by about 34.74 seconds compared with GA, which increases by about 29.3%.Table 5Comparison of time consumption.The results of optimization numbers are shown in Table 6. Form Table 6, we realize that GSOS performs better than GA in terms of average value, minimum value, and variance.Table 6Results of numbers.Case 2 ��To insure the performance of GSOS, Example 2 is generated randomly, information is in detail in Tables Tables77 and and88.Table 7Orders and weights.Table 8(a) Information of orders for Job 1�C10.

(b) Information of orders for Job 11�C21.The results of optimization numbers are shown in Table 9, and the efficiency of results are shown in Table 10. Table 9Results of numbers.Table 10Comparison of time consumption.From Tables Tables99 and and10,10, we can find that the proposed algorithm is better than GA.The searching curves of GSOS and GA are shown in Figures Figures22 and and3,3, there solid lines account for GSOS while dotted lines for GA. Figure 2Curves in case 1.Figure 3 Curves in case 2.According to the Figures Figures22 and and3,3, GSOS and GA both have a high rate of convergence, but GSOS performs better than GA in terms of average value, minimum value, and variance, which proved its high-accuracy of solutions, the solving time of GSOS decreases by about 29% compared with GA which reflects its efficiency.

In conclusion, GSOS is more suitable for solving whole-set orders problem.5. ConclusionsAn improved glowworm swarm optimization for scheduling (GSOS) is proposed in this paper; we have verified its high rate of convergence, efficiency, accuracy, and easy operation through simulations on different scales of whole-set orders problem. To test its performance on parallel machines and Anacetrapib bigger scales that will be our research direction later on.

, Edison, NJ). Different capillaries having internal diameters of 0.9, 1.8, 3.0, and 4.0mm were used to determine viscosity of chitosan solutions. The measurements were performed selleck chemicals Ganetespib at inclination angle of 15�� at 25��C. For solution viscosities higher than 800cP, measurements were made with a rheometer using parallel plate geometry (RHOIS 902-30004, Rheometric Scientific Inc., Piscataway, NY, USA). The viscosities data was used to study kinetics of chitosan fragmentation.2.3.2. Intrinsic Viscosity Measurement The intrinsic viscosities of the original chitosan and its fragments were measured in two solvents: (1) 0.1M HAc/0.02M NaCl (solvent A) and (2) 0.25M HAc/0.25M NaAc (solvent B) at 25��C using a capillary viscometer with an internal capillary diameter of 0.9mm at inclination angle of 15��.

These conditions along with the use of solution concentration lower than 1.0% (w/v) were selected, so corrections for kinetic energy and shear rate were negligible. Efflux times were measured for chitosan solutions (ts) and the solvent (t0). Measurement of efflux times was repeated four times and average efflux time was then converted to the ratio of ts/t0, which is proportional to relative viscosity of chitosan solution. The intrinsic viscosity was determined by both Huggins and Kraemer plots [29, 30]. The average value of two intercepts obtained from the two linear plots was considered as intrinsic viscosity of the polymer sample, [��]. The intrinsic viscosity data was used to calculate viscosity-average molecular weight of the polymer samples, Mv. 2.3.3.

Calculation of Viscosity-Average Molecular Weight and Number of Chain Scissions The value of Mv was calculated in solvent A according to [31][��]=3.04��10?5Mv1.26(1)and in solvent B was calculated using [32][��]=1.49��10?4Mv0.79.(2)The average number of chain scissions, ��, was calculated using the following equation [33]:��=(Mv,oMv,f)?1,(3)where Mv,o and Mv,f are viscosity-average molecular weights of the original and the fragments, respectively.2.3.4. Size Exclusion Chromatography Size exclusion chromatography (SEC) was used to compare molecular weight and molecular weight distribution of the original chitosan and its fragments. A HPLC/SEC instrument (Hewlett-Packard, Series 1050) was used with a refractive index detector, whose response is directly proportional to the polymer concentration in the eluting solution.

Separation Drug_discovery was achieved at 35��C using a TosoHaas-TSK gel column (GMPWXL, 30cm �� 7.8mm) with 0.25M HAc/0.25M NaAc (solvent B for intrinsic viscosity measurement) as an eluent at a flow rate of 0.4mL?min?1. 2.3.5. Structural Analysis The chemical structure and the DA of the purified original chitosan and two fragments were determined by 1H NMR spectroscopy and elemental analysis. The procedures for structural analysis by the two techniques were the same as the procedures described by Hirai et al. [34] and Kasaai et al. [35].3. Results and Discussion3.1.

Thus, the average number of transmissions per active www.selleckchem.com/products/Gefitinib.html session is expressed asNT��=1ns��j=1nsNT(Tj).(4)Since more transmissions take longer time on scheduling frame, minimizing the number of transmissions helps to improve the network’s throughput. In a typical multicast/broadcast tree Tj, there are three kinds of nodes: source node sj, forwarding nodes set (FWDj), and leaf nodes set (LFj). For example, consider the multicast tree shown in Figure 1. Here, the number associated with each link represents the channel assigned to that link. All nodes of tree, except the source node, have one parent. The source node (e.g., node A), as the root of the tree, sends data toward its children. A forwarding node (e.g.

, nodes B, C, E, F, and I) acts as both parent and child node; as a child node, it receives data from its parent, while in the role of a parent node, it sends the traffic toward its children. A leaf node (e.g., nodes D, K, L, M, N, and P) only plays the role of a child and receives data from its parent. It is clear from Figure 1 that NTAj = NTBj = NTCj = NTEj = 1, while NTIj = NTFj = 2 (i.e., NT(Tj) = 8).Figure 1 A typical multicast routing tree.Since we assume the bandwidth-guaranteed trees with bandwidth requirement trsj, the created load by the jth session on the ith node can be generally formulated by the role of node and the number of its transmissions aslij={trsj(1+NTij)if??i��FWDj,trsj��NTijif??i=sj,trsjif??i��LFj,0if??i?Tj.(5)Here, we define the utilization of the ith mesh router, denoted by U(i), as follows:U(i)=l(i)C(i)=1C(i)��j=1nslij,(6)where U(i) indicates the percentage of the ith node’s capacity used for routing of ns multicast/broadcast sessions.

For this case, the average utilization of the nodes is defined asU��=1n��i=1nU(i),(7)where n is the total number of nodes in the network.On the other hand, due to the shared nature of the wireless medium, adjacent transmissions cannot occur simultaneously on the same channel. To formulate this issue, we use the channel utilization concept defined in [17] with minor modifications. For the described MCMR-WMN model, consider a fixed transmission rate of c0. Each MAC multicast transmission in the jth routing tree uses a time fraction of the scheduling frame that is equal to trsj/c0. By definition, the utilization of channel k observed by node y (Xyk) is the sum of the time fractions assigned to all nodes within the interference range of node y that are intended to transmit on channel k.

Thus, considering ns admitted multicast/broadcast sessions, the utilization of channel k observed by node y is formulated asXyk=��j=1ns??��i��intf(y)trsjc0qi,kj,(8)where intf(y) denotes the set of interfering nodes located within the interference range of node y. For this case, the channel capacity constraint is given ?y��V,???k��ch_list(y),(9)where ch_list(y) indicates the set of?byXyk��1, assigned channels Entinostat to the radios of node y.

Categorical variables are expressed as proportions and compared Crizotinib with the Mantel-Haenszel chi-squares test or Fisher’s exact test.For the analysis of RRT dose versus outcome, CRRT and IRRT patients were analysed separately because of well-recognised differences between these populations in observational studies [21,22]. Exploratory univariate analysis for several variables was performed to identify possible risk (or protective) factors associated with ICU mortality. Multivariable logistic regression analysis was then conducted to test the relationship between RRT dose and ICU mortality, adjusted for confounding factors.Based on the results of the univariate analysis, the covariates included in the CRRT model were sex, age (10-year increments), sequential organ failure assessment (SOFA) and serum creatinine at CRRT initiation and CRRT downtime (hours); for IRRT the covariates included were age (10-years increments), sex and RIFLE class at IRRT initiation.

In addition to adjusting for significant covariates, residual confounding and selection effects were addressed using propensity scores. We generated a propensity score using multivariable logistic regression with more-intensive RRT dose as the dependent variable, as previously described [22,23]. Variables included in the propensity score were gender, weight, SOFA score and serum creatinine at RRT initiation. We fitted models for ICU mortality only adjusted for covariates and a combination of covariates plus the propensity score. We assessed for collinearity between variables using tolerance and variance inflation factors; there was no significant collinearity detected.

The model’s goodness of fit was tested with the Hosmer-Lemeshow statistic.As sensitivity analyses, RRT dose was evaluated as both continuous variables and categorical variables. As continuous variable for CRRT, we used the actual value or as increments of 10 ml/kg/hour; for IRRT, we used number of IRRT sessions per week (possible range: 1 to 7). As categorical variables, we created RRT dose categories based on the literature, as well as standard statistical groupings (median, tertiles). Posthoc multivariate analyses were also performed limiting the analysis to specific subgroups of CRRT patients (septic patients, by simplified acute physiology score (SAPS) scores, �� 25 hours of CRRT).

Because of the relatively small sample size of the IRRT, subgroup analysis was not performed.Finally, ICU survival by RRT dose categories was presented graphically using Kaplan-Meier product limit survival plot. Two-tailed p values less than 0.05 were considered significant. Statistical analyses were conducted using STATA 10 (StataCorp LP, College Station, TX, USA).ResultsEnrollment and baseline characteristicsCharacteristics Cilengitide of the participating centres are shown in Table 1 in Additional data file 2.

Three out of the 4 rejected kidneys on account of poor macroscopic appearance had their ‘twin’ kidney transplanted with good results. In addition, eight kidneys were discarded because intra-renal vascular resistance was abnormally elevated during pulsatile perfusion.Among the EPZ-5676 mll 31 kidney grafts, 24 were transplanted in our institution and could enter our follow up. There was a rate of delayed graft function of 92%. The mean duration was 22 �� 9 days. Among these transplantations, three major complications led to graft loss: one untimely cessation of immunosuppressive therapy by the patient leading to acute rejection, one renal venous thrombosis with early graft removal, and one primary non function which may be related to longer warm ischaemia duration (185 minutes).

The serum creatinine evolution is shown in Figure Figure33 for the remaining 21 patients. At three months, creatinine level was 162 �� 69 ��mol/l and 152 �� 65 ��mol/l at six months. Creatinine clearance at one month was 28 �� 14 ml/min, and 58 �� 21 and 66 �� 24 ml/min at three and six months after transplantation, respectively (n = 22). Graft survival rate was 89% at three and six months.Figure 3Serum creatinine individual evolution in the NHBD kidney recipients transplanted in the authors’ institution (n = 21). Steady state creatinine level was obtained on average three months after transplantation. NHBD = non heart beating donor.Limited information was available through the Agence de la biom��decine for six out of the seven recipients transplanted elsewhere.

For a follow-up period ranging from 6 to 12 months, graft survival rate was 100% and mean serum creatinine level was 135 �� 53 ��mol/l.DiscussionThese data from uncontrolled NHBD showed that such a program was feasible in France and profitable in terms of successful organ transplantation. Indeed, even though only half of the out-of-hospital cardiac arrests that were proposed could enter this program and only one-quarter had their kidneys actually retrieved, this program provided at least 27 successful renal transplants, including 21 carried out at our institution, within 17 months.Renal transplantation remains the treatment of choice for patients with end-stage renal failure [16]. In 2007 in France, 2911 kidney grafts were provided by BDD for 90.6%, by living donors for 8% and from NHBD for 1.4%.

In 2007, 128 patients died on the waiting list for kidney transplantation. To counter the shortage of grafts, an alternative source was organ harvesting from NHBD. This procedure, previously described in Europe, Japan and the USA [2,3,5,17], concerned mainly Maastricht 3 category NHBD. If harvesting controlled donors (withdrawal of care) provokes ethical controversies [18-20], ‘uncontrolled donors’ triggers many organisational problems.In our institution, the initiation GSK-3 of this program proved satisfactory in many ways.

A recent in vitro study [13] reported meropenem and vancomycin recovery of 89% and 67% at 180 minutes in neonatal circuits that used a centrifugal pump and polypropylene hollow-fiber membrane oxygenators. Whereas the meropenem recovery at 180 minutes is comparable to our results, vancomycin recovery was much lower in the neonatal circuits. In contrast, the fentanyl and midazolam circuit losses seen moreover in this study are consistent with the results of the neonatal circuit studies [13,26-28]. Morphine appears to be relatively stable in both neonatal and adult ECMO circuits and may be the preferred analgesic during ECMO. Future clinical studies should compare the efficacy of different classes of drugs to rationalize sedation and analgesia during ECMO.

Studies that compare drug losses in clinically used versus new neonatal circuits have demonstrated significant variability in drug sequestration between the used and new circuits [10,13,28]. Consequently, it is still unclear whether there is saturation of the drug-binding sites in the ECMO circuit over time. Similarly, the effect of priming with various solutions on drug sequestration is not well characterized in the available literature. Drug sequestration in blood-primed circuits has been shown to be much lower than that in crystalloid-primed circuits [27]. It is possible that some of the blood components may compete with drugs for circuit-binding sites. Even though ECMO circuits are not routinely primed with blood prior to their use in adult patients, the circuits get primed with the patient’s own blood once ECMO is commenced.

In our study, we tried to replicate the clinical situation ex vivo which allowed us to study the interactions between the drug and the device in the absence of disease-related factors which independently can significantly alter PK [29,30]. Repeat dose experiments are required in long-term model systems to estimate the degree of circuit saturation with time. The concurrent presence of several other physically compatible study drugs in the circuit and control jars mimicked the clinical scenario in which patients receive these drugs concurrently, but the drugs may have had an impact on competitive binding to blood proteins or the circuit components. The presence of a reservoir bladder may have influenced the circuit drug losses.

Similarly, quantification of drug lost in control jars because of binding of drugs to the polypropylene container was not feasible. However, the results confirm the findings of neonatal ECMO circuit studies.ConclusionsThis ex vivo study highlights the role of the ECMO circuit in altering PK during Anacetrapib ECMO. These alterations are more pronounced for lipophilic drugs and may result in therapeutic failure. Morphine may be a useful alternative to fentanyl in a patient with escalating sedative and analgesic drug requirements.

Extracellular TRX has been reported to reduce interleukin 1-beta expression by monocyte-macrophages in inflammatory conditions [7]. In addition, circulating TRX suppresses neutrophil chemotaxis http://www.selleckchem.com/products/azd9291.html [44]. More recently, it has been suggested that the anti-inflammatory mechanisms of TRX could be mediated, at least in part, by migration inhibitory factor (MIF) downregulation [45]. However, in septic conditions, TRX and MIF plasma levels showed a strong correlation, suggesting that pro- and anti-inflammatory agents are balanced to maintain homeostasis [46].In the present study, we confirm the limited interest of AOPP measurement and thiol content determination in acute setting, at least after CA, despite their place in experimental conditions [5,6].

On the contrary, high CRP and PCT levels are consistent with previous findings suggesting the overwhelming impact of systemic inflammation [4]. Overall, these results enhance the value of TRX after CA.Despite the large number of post-CA patients enrolled, some limitations of this study need consideration. First, we considered a retrospective single-institution cohort. However, all analyzed data were prospectively collected, and medical management was homogeneous. Second, this is a merely observational study, allowing only association rather than causation conclusions. Third, the utility of TRX to predict death was evaluated as a single parameter, without combination of TRX level to clinical or biological data that may have improved the overall prognosis value.

Fourth, measurement of other oxidative stress parameters, like MIF or manganese superoxide dismutase (MnSOD), or main inflammatory cytokines would have provided further mechanistic tracks. Similarly, determination of the TRX interacting protein (TXNIP) could give valuable data to help explain the TRX kinetics after CA. However, TXNIP is an intracellular protein that cannot be routinely measured in serum samples. Fifth, CA has the particularity of exhibiting two main causes of ICU death, that is, shock and neurological damage with subsequent care withdrawal. As inflammation and oxidative stress are expected to be greater in case of shock, subanalysis focused on this last group. Finally, the vast majority of patients underwent therapeutic hypothermia. If the relationship between inflammatory cytokines or biomarkers and effect of therapeutic hypothermia is controversial [4,25], the influence of hypothermia on TRX is as yet, unknown.

As the vast majority of our patients were treated by hypothermia, we could not perform a meaningful analysis of the impact of temperature on TRX levels. Similarly, there is no data about clearance of TRX during renal replacement therapy, which is widely applied in post-cardiac arrest survivors. To note, we report a high proportion of patients experiencing post-resuscitation shock. This is related to the study design, including Batimastat all consecutive patients and in particular those dying within 24 hours.

24 (95% CI = 0.10 to 0.59; P = 0.003) (Figure (Figure2A2A).Figure license with Pfizer 2Kaplan-Meier curves for hyperchloraemic acidosis. Hyperchloraemic acidosis was defined as the association of hyperchloraemia (>108 mmol/L) with strong ion difference (SID) (<40 mmol/L). SID = (Na + K + Ca + Mg) - (Cl + lactate). Na; sodium, ...In the FAS analysis, 18 patients (90%) in the saline group and 10 patients (50%) in the balanced group had hyperchloraemic acidosis within the first 48 hours (P = 0.01). The Kaplan-Meier estimators at hour 48 were 90% (range = 73% to 98%) in the saline group and 50% (range = 31% to 72%) in the balanced group, with a HR for hyperchloraemic acidosis in the balanced group of 0.28 (95% CI = 0.11 to 0.70; P = 0.006) (Figure (Figure2B).2B). Two sensitivity analyses did not change the results.

The HR for hyperchloraemic acidosis in the balanced group was 0.18 (95% CI = 0.06 to 0.55; P = 0.002) when the patients with acidosis prior to inclusion were excluded, and it was 0.25 (95% CI = 0.09 to 0.69; P = 0.008) with a censorship of the biological values (SID, chloraemia) prior to inclusion. In the subgroup of TBI patients, the HR for hyperchloraemic acidosis in the balanced group was 0.30 (95% CI = 0.12 to 0.80; P = 0.015) (Figure (Figure2C2C).Secondary efficacy outcomesThe pH was lower in the saline group than in the balanced group (mean difference = -0.03 (-0.05 to -0.01); P = 0.004) (Figure (Figure3A).3A). Patients in the saline group had a lower SID than the balanced group (mean difference = -1.55 mEq/L (-3.09 to -0.02); P = 0.047) (Figure (Figure3B).3B).

Chloraemia was higher in the saline group than in the balanced group (mean difference = 4.8 mmol/L (1.9 to 7.6); P = 0.002) (Figure (Figure3C).3C). Compared with the balanced group, patients in the saline group had lower phosphataemia (mean difference = -0.12 mmol/L [-0.21 to -0.04); P = 0.008) (Figure (Figure3D).3D). From hour 0 to hour 48, albuminaemia and partial pressure of carbon dioxide in arterial blood (PaCO2) were not altered in the saline group compared with the balanced group (Figures (Figures3E3E and and3F).3F). The reported differences in the acid-base status between groups were not significantly modified in the subgroup of TBI patients (Additional file, Figure S1). The results for base excess, effective SID, simplified anion gap and corrected anion gap are provided in the Additional file, Table S2.

The blood osmolarity was higher in the saline group than in the balanced group (mean difference Anacetrapib = 7 mOsmol/L (1 to 14); P = 0.024) (Figure (Figure4A).4A). The natraemia levels were higher in the saline group than in the balanced group (mean difference = 2 mmol/L (0 to 4); P = 0.036) (Figure (Figure4B).4B). ICP was not altered in the study group (mean difference = 4 mmHg (-1 to 8); P = 0.088) (Figure (Figure4C).4C).