Asthma represents a significant clinical and economic burden to the US healthcare system. Along with other clinical manifestations of the disease, elevated sputum and blood eosinophil levels are observed in patients experiencing asthma exacerbations. The aim of this study was to evaluate the association between blood eosinophil levels and asthma severity defined using Expert Panel Report 3 guidelines.Patients with asthma diagnosis between 2004 and 2011 were extracted from the EMRClaims+ database  containing electronic medical records linked to insurance claims for over 675,000 patients. The date of first asthma diagnosis was defined as the ‘index date’. Patients were required to have at least 1 peripheral eosinophil test (elevated defined as ≥ 400 cells/μL) in the 12 month ‘assessment’ period following the index date. We classified patients as those with mild asthma and moderate-to-severe asthma based on the pattern of medication use, as recommended by the 2007 National Institutes of Health Expert Panel Report. Logistic regression models were used to determine if patients with moderate-to-severe asthma had increased likelihood of an elevated peripheral eosinophil count, after accounting for demographics and comorbidities.p = 0.053). Logistic regression showed that moderate-to-severe asthma was associated with 38 % increased odds of elevated eosinophil level .Among 1,144 patients with an asthma diagnosis, 60 % were classified as having moderate-to-severe asthma. Twenty four percent of patients with moderate-to-severe asthma and 19 % of patients with mild asthma had an elevated peripheral eosinophil count (Patients with moderate-severe asthma are significantly more likely to have an elevated peripheral eosinophil count than patients with mild asthma. The American Lung Association has reported that nearly 26 million people (84.8 per 1000 people) in the US suffered from asthma in 2011, with children representing 27 % of them [The first Expert Panel Report (EPR) Guidelines  for asthMuch progress has been made over the years in identifying external or environmental risk factors/triggers of asthma attacks such as allergens, pollutants, irritants, etc. , 5, 6. RThis study aimed to correlate asthma severity (based on EPR guideline step-therapy recommendations) and eosinophil elevation. In the absence of patient reported symptom classification, we explore the use of eosinophil biomarkers to identify patients who remain at risk for chronic exacerbation despite treatment.We conducted a retrospective data analysis of patients with asthma diagnosis, extracted from the EMRClaims+ integrated health services database  of patients located in the Midwest region of the United States. The database includes administrative insurance claims from approximately 675,000 lives linked to an overlapping healthcare provider database of over 20 million electronic medical records data (EMR), including laboratory values, and provider billing files.The population was comprised of patients 12 years or older, who had at least two encounters (separated by at least 1 day) in the emergency room, outpatient or inpatient setting with a primary or secondary diagnosis of asthma  between January 2004 and July 2011 (“study period”). The date of the first asthma diagnosis in the study period was recorded as the index diagnosis date. The 12-month period following the index diagnosis was considered the ‘assessment period’. Patients were also required to have at least 1 eosinophil test conducted during the assessment period. To account for the masking effect of systemic steroid use on eosinophil levels, patients only having eosinophil results under 400 cells/μL and all those eosinophil tests conducted while on systemic steroids (based on days of supply plus 14 days) were excluded. This approach minimizes misclassification of patients with lower eosinophil levels due to systemic steroid use. Patients with confounding diseases states of COPD, emphysema , Churg Strauss syndrome/Wegener’s granulomatosis (ICD-9-CM code: 446.4), eosinophilia (ICD-9-CM code: 288.3), pulmonary fibrosis (ICD-9-CM code: 516.3), allergic bronchopulmonary aspergillosis (ICD-9-CM code: 518.6), cystic and pulmonary fibrosis , and lung cancer (ICD-9-CM code: 162.x) in the assessment period, were excluded.Asthma severity was estimated using the medication use information reported in outpatient and/or inpatient pharmacy records during the assessment period using step-treatment recommendations for mild, moderate or severe disease by the EPR-3 criteria and adapted for use with retrospective data based on clinical guidance from asthma specialists Table . PreviouDescriptive statistics were used to compare baseline characteristics between the different severity groups. Frequency distribution of patients with elevated eosinophils versus normal eosinophils were reported and cross tabulated with asthma severity level. Chi-square tests were used to compare the proportion of patients with elevated eosinophil between those that had mild and moderate-to-severe asthma. Logistic regression was used to determine the association between asthma severity (key factor) and eosinophil elevation, adjusting for patient demographics , and comorbidity burden . To further assess the appropriate cut-off level for elevated eosinophils, we utilized cut-off levels adopted in other studies and conducted sensitivity analyses by defining elevated eosinophils as the cut off at ≥ 300 cells/μL and ≥ 140 cells/μL. All data management and analyses were conducted using SAS Enterprise Guide version 4.3 .The study identified 2,164 patients with at least one eosinophil test during the assessment period, of which 1,144 met our criteria for severity classification. Figure p = 0.116). Mean age of the overall sample was 47 years. Age distribution was significantly different between the two severity groups (P < 0.0001). Fifty-five percent of all asthmatics were in the 36–64 year age group; however, almost 17.5 % of patients with mild asthma were children between the ages of 12–17 years compared to 5 % in patients with moderate-to-severe asthma. Diabetes was a prominent comorbidity recorded in 14 % of asthmatic patients but the proportions of patients with diabetes were not significantly different among between the two severity groups (p = 0.057).There was a greater proportion of women compared to men Table , but thep = 0.053). However, logistic regression showed a 38 % increase in the odds  of elevated eosinophils for moderate-to-severe asthma compared to mild asthma after adjusting for differences in demographic characteristics and comorbidities .Results of sensitivity analyses conducted for elevated eosinophil level defined as ≥ 300 cells/μL showed that elevated blood eosinophils was not associated with moderate-to-severe asthma  asthma, a common approach when using retrospective claims data . Asthma This study highlights the association between asthma severity, defined by using EPR guidelines, and eosinophil elevation. The probability of eosinophil elevation is increased for patients with greater asthma severity. Blood eosinophil level may represent an important characteristic of disease severity as new therapeutic alternatives emerge for this patient phenotype after exhausting less aggressive medication regimes. Further research correlating blood eosinophil level with risk-based severity and control measures  is warranted to externally validate the presence of our observed association. Evidence of the association between blood eosinophil levels and asthma severity underscores the need for treatment options designed for asthma patients with elevated eosinophil.CCI, Charlson Comorbidity Index; CI, Confidence Interval; EMR, Electronic Medical Record; EOS, Eosinophil; EPR, Expert Panel Report; FEV, Forced Expiratory Volume; ICD-9-CM, International Classification of Diseases-9- Clinical Modification; ICS, Inhaled Corticosteroid; LABA, Long acting Beta agonist; NIH, National Institute of Health; OR, Odds Ratio; SAS, Statistical Analysis Software.


We therefore undertook a first-in-human HF proof of concept/safety study, evaluating the hemodynamic effects of short-term NaNO2 infusion.Nitrite exhibits hypoxia-dependent vasodilator properties, selectively dilating capacitance vessels in healthy subjects. Unlike organic nitrates, it seems not to be subject to the development of tolerance. Currently, therapeutic options for decompensated heart failure (HF) are limited. We hypothesized that by preferentially dilating systemic capacitance and pulmonary resistance vessels although only marginally dilating resistance vessels, sodium nitrite , with marked falls in pulmonary vascular resistance  and right atrial pressure , but with only modest falls in mean arterial blood pressure . The increase in stroke volume correlated with the increase in estimated trans-septal gradient , suggesting relief of diastolic ventricular interaction as a contributory mechanism. Directionally similar effects were observed for the above hemodynamic parameters with 10 μg/kg/min; this was significant only for stroke volume, not for other parameters.Twenty-five patients with severe chronic HF were recruited. Eight received short-term (5 minutes) intravenous NaNO2 infusion that may be beneficial in decompensated HF and warrants further evaluation with longer infusion regimens.This first-in-human HF efficacy/safety study demonstrates an attractive profile during short-term systemic NaNO Some patients with HF are relatively resistant to organic nitrates, and almost all patients rapidly develop tolerance during sustained infusion.3 An effective agent devoid of tolerance would therefore be attractive. Unfortunately, several novel pharmacological agents that have shown promise in early phase trials have not been successful in larger hard end point–driven trials.5In some patients with decompensated HF, intravenous diuretics are safe and well tolerated, but in others may be associated with a marked worsening of renal function. In these circumstances, intravenous organic nitrates are commonly used. At low doses, these agents preferentially dilate capacitance vessels but, although of lesser magnitude, also dilate resistance vessels at higher doses and reduce arterial wave reflection.2) has a vasodilator profile that is potentially attractive for the treatment of decompensated HF. In healthy subjects, NaNO2 exhibits hypoxic augmentation of its vasodilator properties when administered intravenously or intra-arterially, presumably because it is reduced under hypoxic conditions to nitric oxide (NO).8 We previously demonstrated that in healthy subjects breathing room air, intra-arterial NaNO2 only modestly dilated forearm resistance vessels, whereas markedly dilating forearm capacitance vessels.6 When these subjects breathed a hypoxic gas mixture, the forearm resistance vessel dilation was augmented.6 Furthermore, NaNO2 reduced pulmonary vascular resistance (PVR) in experimental models of pulmonary hypertension9 and systemic nitrite infusion substantially ameliorated the pulmonary vasoconstriction associated with systemic hypoxemia in healthy volunteers.10 Previous studies have suggested that nitrite therapy may not be subject to the development of tolerance.11Sodium nitrite  and right ventricle (diastolic ventricular interaction [DVI]), whereas only modestly reducing systemic vascular resistance and therefore resulting in only a minor fall in blood pressure. We therefore undertook a proof-of-concept study to evaluate the hemodynamic effects of systemic short-term NaNO2 infusion in patients with severe chronic HF. We chose a brief (5 minute) infusion for safety reasons because this was a first-in-man use of intravenous nitrite in HF.Based on these observations, we hypothesized that intravenous NaNOTwenty-five patients with severe chronic HF who were undergoing right heart catheterization as part of their heart transplant assessment protocol were recruited to the study. The study conformed to the Declaration of Helsinki and was approved by the University of Birmingham ERN10-0247) and Local Research Ethics Committee (08/H1207/67). Each patient gave written informed consent after satisfying the inclusion criteria  and exclusion criteria  myocardial infarction, G6PD deficiency, and women of child-bearing potential or nursing mothers). The patients had a diagnosis of HF with reduced left ventricular (LV) ejection fraction (<40%) of various etiologies, and all patients were on optimal tolerated standard HF therapy . The patients were then placed in a supine position to allow the insertion of a Swanz–Ganz catheter via a sheath into the right internal jugular vein under local anesthesia with positioning confirmed by fluoroscopy and pressure waveform. After 15 minutes of stabilization at baseline, the following pressures were measured at end-expiration: pulmonary arterial pressure, pulmonary capillary wedge pressure (PCWP), and right atrial pressure (RAP). The trans-septal pressure gradient (TSG) was estimated as PCWP-RAP. CO was measured using the Fick technique from the mixed venous and arterial oxygen saturations and from predicted oxygen consumption. Systemic vascular resistance (Wood units) was calculated as . Arterial elastance (a lumped measure of pulsatile and static LV afterload) was calculated as .12 Left ventricular stroke work was calculated as SV×mean arterial blood pressure (MABP). Arterial oxygen saturation was measured by pulse oximetry. The measurements were repeated 5 minutes later to ensure stability. NaNO2 was then infused intravenously over 5 minutes, and the above hemodynamic measurements were repeated at the end of the infusion. Blood pressure, ECG, and oxygen saturation were monitored continuously.Patients were randomized  measurements. Blood for determination of venous plasma nitrite, nitrate, and RXNO concentrations were collected into EDTA tubes and immediately centrifuged (800g for 10 minutes at 4°C). Samples were stored at −80°C before assay. Plasma nitrite, nitrate, and RXNO concentrations were determined, after addition of N-ethylmaleimide  during the thawing process, via high-performance liquid chromatography and chemiluminescence as previously described.13Venous blood samples were taken at baseline and after infusion of NaNOt test. Changes from baseline between treatment groups were performed by unpaired 1-tailed Student t test; a P value of <0.05 was taken to indicate statistical significance. Changes in TSG  during NaNO2 infusion were estimated as change in PCWP–RAP.14 Statistical analysis was undertaken using Prism software .Data are presented as mean±SD. Hemodynamic comparisons were performed by paired 1-tailed Student P=0.046) and systemic vascular resistance (SVR) was significantly higher in group 2 (P=0.03).The demographics for the entire cohort and the groups receiving 10 μg/kg/min (group 1) and 50 μg/kg/min group 2) are shown in Table  are show2 infusion did not significantly affect MABP, whereas in contrast 50 μg/kg/min of NaNO2 infusion modestly but significantly decreased MABP by a mean of 4 mm Hg (P<0.004).As shown in Table 2 infusion significantly decreased PVR by 29% (P=0.03), and systemic vascular resistance fell by 12% . Mean arterial oxygen saturation remained unchanged at either infusion rate.As shown in Table P=0.3).Patients receiving the higher dose infusion regime were divided into those with SVR above versus below the mean for the group at baseline (33.17 wood units). There was no significant difference in the change in LV SV between these 2 groups , whereas in those with PCWP <15 mm Hg (n=6), there was no significant change in SV . Estimated TSG increased by 3.6 mm Hg in the high PCWP subgroup  and by 2 mm Hg in the lower PCWP subgroup .In 11 patients with PCWP >15 mm Hg (mean 22.4±8.0 mm Hg), infusion of sodium nitrite at the higher concentration increased SV by 20% from 43.22±21.5 to 51.84±23.6 mL  infusion regime as a proof of concept for safety reasons because this was a first-in-man study of systemic nitrite infusion in chronic HF. The effects were observed at the 50 μg/kg/min infusion rate and, although directionally similar, were not significant at the 10 μg/kg/min infusion rate, although the latter may partly be because of a smaller sample size in the lower dose group. Although only modest increases in methemoglobin levels were observed with either dose, based on studies in healthy volunteers, sustained infusion of 50 μg/kg/min would be expected to cause marked  methemoglobinemia. However, we have subsequently undertaken pilot studies (data not shown) in patients with chronic HF (without hemodynamic assessment) and have demonstrated that sustained infusion of 10 μg/kg/min caused a progressive increase in plasma nitrite and RXNO, such that by 3 hours these levels were almost as high as we observed in the present study with 50 μg/kg/min infused over 5 minutes, without inducing dangerous methemoglobinemia and without inducing significant hypotension. In a study in healthy volunteers, Pluta and colleagues reported that sustained infusion  of doses of ≈5 μg/kg/min sodium nitrite resulted in significant hypotension and methemoglobin >5%.16 usually in the context of pulmonary hypertension. By preferentially dilating the systemic capacitance and pulmonary resistance vessels,10 nitrite may be expected to reduce RV volume and hence pericardial stretch, thereby augmenting LV filling and SV. Consistent with relief of DVI as an important mechanism, the increase in SV was only observed in the group of patients with PCWP >15 mm Hg—a cutoff that we have previously shown to identify HF patients with significant DVI.16 In this subgroup, the SV increased by 20%.16 In accordance with this concept, the reduction in RA pressure 17 was greater than the reduction in PCWP; hence, the estimated TSG —a measure of the true filling pressure of the LV at end diastole18—was increased by sodium nitrite. Furthermore, the increase in SV was significantly correlated with the change in estimated TSG. We cannot exclude a significant direct myocardial effect of nitrite as a contributory mechanism. In the vertebrate, heart nitrite positively modulated the Frank–Starling response via a NO-dependent mechanism.19 In contrast, another study reported negative inotropic effects via a NO/cGMP-dependent mechanism in the Langendorff rat heart.20 In a recent study, chronic oral inorganic nitrite supplementation ameliorated the development of HF in a murine thoracic aortic constriction model in association with an upregulation of cytoprotective pathways.21The increase in SV in the face of a reduced PCWP represents an apparent descending limb of the Starling curve. This is because in severe chronic HF, despite high left ventricular end diastolic pressures, LV filling is impeded by external constraint from the stretched pericardium  and via the interventricular septum from the right ventricle (DVI),22 Cardiac index increased substantially (by 25%), but systemic vascular resistance also fell substantially (by 25%) and MABP fell by 13 mm Hg. The reduction in mean PCWP (by 14 mm Hg) was substantially greater than that of RA pressure (by 4 mm Hg), that is, mean TSG fell substantially, which suggests that relief of DVI was not an important mechanism of the increase in CO.22Intravenous sodium nitroprusside is sometimes used in the treatment of acute decompensated HF. Fifer et al reported the effects of intravenous sodium nitroprusside in patients with severe CHF.23 or positive airways pressure24 in the management of patients with acute pulmonary edema. These agents dilate capacitance and resistance vessels.25 At lower doses, the vasodilator effects of glyceryl trinitrate (GTN) are predominantly on capacitance vessels, but at higher doses, effects on vascular resistance are increasingly observed.26 Rabinowitz et al reported the hemodynamic effects of intravenous isosorbide dinitrate in patients with decompensated HF. CO increased similarly to our study (by 17%), but the reduction in systemic vascular resistance (35%) and the fall in mean arterial pressure (10 mm Hg) were substantially more than we observed with sodium nitrite. The increase in CO was substantially greater in those patients with high resting SVR, suggesting that afterload reduction may have been an important contributor to the increase in CO.27 Armstrong et al reported the effects of GTN infusion in patients with severe CHF. CO increased by ≈20%. Systemic vascular resistance fell by ≈21% and MABP by 7 mm Hg. In contrast to our findings with nitrite, the fall in PCWP (by 8 mm Hg) was greater than that of RAP (by 5 mm Hg), indicating that overall the estimated TSG fell with this therapy rather than the increase we observed with sodium nitrite infusion.28 However, Dupuis and colleagues showed that during sustained (72 hour) infusion of GTN, SV increased in a subgroup of patients in whom LV end diastolic volume increased and fell in those in whom LV end diastolic volume fell during GTN infusion.29 These data suggest that GTN may relieve DVI in some patients with decompensated HF, but this effect seems less marked than we have observed in this study with intravenous sodium nitrite.Organic nitrates are more commonly used in the treatment of decompensated HF. Indeed intravenous isosorbide dinitrate has been shown to be superior to either intravenous furosemide22 or isosorbide dinitrate (35%),27 suggesting that this may play a less important role in the increase in CO with sodium nitroprusside. Furthermore, in our study, there was no significant difference in the change in SV induced by sodium nitrite between those with higher versus lower systemic vascular resistance before infusion. However, left ventricular afterload has a pulsatile component, as well as a static component, and changes in SVR do not therefore completely describe effects on LV afterload. GTN has previously been shown to reduce wave reflection.2 In the present study, the reduction in arterial elastance (a measure of LV afterload encompassing both static and pulsatile components) was 18%.The reduction in SVR (by 12%) observed in the present study was substantially less than that observed in the above studies with either sodium nitroprusside (25%)10 Based on changes in estimated TSG, this mechanism may be less marked with organic nitrates and sodium nitroprusside, and changes in LV afterload may be relatively more important for these drugs than with sodium nitrite.In summary, our data are consistent with an effect of sodium nitrite on SV largely mediated via relief of DVI because of relatively selective and potent dilation of capacitance vessels and pulmonary vasculature.32 In contrast, during intra-arterial infusion of NaNO2, we observed an enhanced response in patients with HF versus controls.11 Furthermore, organic nitrate therapy is subject to the rapid development of tolerance. In primates, tolerance was not observed with sodium nitrite.7Nitrite has further characteristics that may make it a potentially attractive agent for the treatment of decompensated HF and therefore worthy of further investigation based on the findings of this short-term proof of concept/safety study. Some patients with HF exhibit nitrate (and NO) resistance, potentially because of increased oxidative stress.33 or some form of NO delivery from a circulating plasma storage form of NO 13 to heart and vasculature. Although intriguing, establishing the mechanistic basis for this observation was well beyond the scope of the present study.Although nitrite infusion resulted in clear increases in plasma nitrite concentrations at both infusion rates, only the one associated with a concomitant elevation in circulating RXNO levels increased CO. This suggests that, in this setting, the beneficial hemodynamic effects of nitrite are associated either with the involvement of a post-translational modification of cardiac tissue proteins2 infusion in patients with severe chronic HF. Further studies are warranted to assess longer term safety and hemodynamic efficacy, and if these are confirmed, this may warrant a randomized controlled trial of sodium nitrite versus current therapy in decompensated HF focussing on hard end points. Sodium nitrite could be administered either intravenously in such studies or perhaps in nebulized form,34 the latter may be particularly attractive in decompensated HF. Unfortunately, several therapies shown to have attractive acute hemodynamic profiles have failed in phase 3 trials in decompensated HF.35 However, a notable exception was a recent study of Serelaxin in patients with acute HF with dyspnea, in which a significant reduction in dyspnea score and 6 month mortality was reported.36This is the first-in-man proof of concept/safety study demonstrating a potentially favorable hemodynamic response to short-term NaNOWe thank Dr Peter Nightingale for his statistical guidance.This work was supported by the UK Medical Research Council [grant number G1001536].None.


To examine a potential association between intraocular pressure (IOP) and cerebrospinal fluid pressure (CSFP) in a population-based setting.2]+0.16×Diastolic Blood Pressure [mm Hg]–0.18×Age [Years].The population-based Beijing Eye Study 2011 included 3468 individuals with a mean age of 64.6±9.8 years (range: 50–93 years). A detailed ophthalmic examination was performed. Based on a previous study with lumbar cerebrospinal fluid pressure (CSFP) measurements, CSFP was calculated as CSFP [mm Hg] = 0.44×Body Mass Index [kg/mIn multivariate analysis, IOP was associated with higher estimated CSFP : 0.16, 0.24), after adjusting for thinner central corneal thickness , smaller corneal curvature radius , shallower anterior chamber depth  and longer axial length ), and after adjusting for the systemic parameters of higher pulse rate , higher prevalence of arterial hypertension ), frequency of drinking alcohol , higher blood concentration of triglycerides  and cholesterol , and body mass index . In a parallel manner, estimated CSFP (mean: 10.8±3.7 mm Hg) was significantly associated with higher IOP  after adjusting for rural region of habitation , higher systolic blood pressure , higher pulse rate , taller body height , higher blood concentration of cholesterol  and higher level of education .IOP was positively associated with estimated CSFP after adjusting for other ocular and systemic parameters. As a corollary, higher estimated CSFP was significantly associated with higher IOP in multivariate analysis. It fits with the notion that the arterial blood pressure, estimated CSFP and IOP are physiologically correlated with each other. Previous studies have suggested a physiologic correlation between cerebrospinal fluid pressure (CSFP), blood pressure and intraocular pressure (IOP) The Beijing Eye Study 2011 is a population-based cross-sectional study in Northern China 2]+0.16×Diastolic Blood Pressure [mm Hg]–0.18×Age [Years]−1.91. We then tested the formula in the test group. In this test group which was independent of the training group, the measured lumbar CSFP (12.6±4.8 mm Hg) did not differ significantly (P = 0.29) from the calculated CSFP (13.3±3.2 mm Hg). The Durbin-Watson value was 2.08. Values falling into the acceptable range of 1.5 to 2.5 indicate a non-significant autocorrelation for the residuals in the multiple regression models. The intra-class correlation coefficient was 0.71. The Bland-Altman analysis revealed that 40 out of 42 measurements were within the 95% limits of agreement. If the test group was taken as training group, the algorithm to calculate the CSFP was CSFP [mm Hg] = 0.85×Body Mass Index [kg/m2]+0.27×Diastolic Blood Pressure [mm Hg]–0.08×Age [Years]−24.8.Using the lumbar CSF-P measurements obtained in a previous pilot study on neurological patients, we assessed the associations between lumbar CSFP measurements, diastolic blood pressure, body mass index and age P-values. Fourth, in a reverse manner, we checked for associations between CSFP and other systemic and ocular parameters including IOP. All P-values were 2-sided and were considered statistically significant when the values were less than 0.05; 95% confidence intervals (CI) were presented.Inclusion criterion for the present study was the availability of IOP measurements, body mass index values and diastolic blood pressure measurements. Statistical analysis was performed using a commercially available statistical software package . First, we examined the mean values (presented as mean ± standard deviation). Second, we searched for associations between IOP, estimated CSFP and other systemic and ocular parameters in univariate analysis. Third, we performed a multivariate analysis, with IOP as dependent variable and all those parameters as independent variables, which had a significant association with IOP in the univariate analysis. We then dropped step-by-step those parameters which were no longer significantly associated with IOP, starting with the parameters with the highest P<0.001) older (69.8±11.4 years versus 64.4±9.7 years), while both groups did not differ significantly in refractive error , axial length  nor gender (P = 0.06). Glaucomatous optic neuropathy was detected in 385 (5.4%) eyes, with 256 (3.8%) eyes with open-angle glaucoma, 125 (1.9%) eyes with primary angle-closure glaucoma, and 4 (0.1%) eyes with secondary angle-closure glaucoma.Measurements of IOP, blood pressure and body mass index were available for 6684 eyes of 3353 (96.7%) subjects with a mean age of 64.4±9.7 years , a mean refractive error of −0.22±2.10 diopters , and a mean axial length of 22.3±1.1 mm . The group of subjects not participating in the study as compared with the group of subjects included into the study was significantly (P<0.05) associated with the numerous ocular parameters and systemic parameters including higher estimated CSFP ), after adjusting for the ocular parameters of thinner central corneal thickness ), shorter corneal curvature radius ), shallower anterior chamber depth ) and longer axial length ), and after adjusting for the systemic parameters of younger age ), higher pulse rate ), higher prevalence of arterial hypertension ), higher blood concentration of triglycerides ) and cholesterol ), and higher frequency of drinking alcohol ). In this model of multivariate analysis, the highest overall correlation coefficient of r = 0.53 was achieved.In the multivariate analysis, we included as independent variables all parameters, which were significantly associated with IOP in the univariate analysis. We first dropped parameters with a high collinearity . We then dropped step by step parameters which were no longer significantly associated with IOP. IOP was eventually associated with higher estimated CSFP ).If age was dropped and body mass index was added to the list of independent variables, the weight of estimated CSFP in the model increased , while the overall correlation coefficient remained unchanged (r = 0.53). If additionally body mass index and arterial hypertension were dropped (since they were included in the CSFP formula), higher IOP remained to be significantly correlated with higher estimated CSFP  than in the group of subjects without arterial hypertension . The association between IOP and estimated CSFP was mostly unchanged  versus . In the whole study group, pulse rate itself was weakly associated with diastolic blood pressure , but not with systolic blood pressure (P = 0.10) or with arterial hypertension (P = 0.09).Interestingly, the association between IOP and pulse rate in the multivariate analysis was considerably stronger in the group of subjects with arterial hypertension (P = 0.74). As also shown in a previous investigation (own data), estimated CSFP was significantly associated  with younger age (P<0.001), rural region (P<0.001), taller body height (P<0.001), higher body weight (P<0.001), higher body mass index (P<0.001), longer waist circumference (P<0.001), higher diastolic blood pressure (P<0.001) and systolic blood pressure (P<0.001), higher pulse (P<0.001), lower level of education (P<0.001), and higher prevalence of arterial hypertension (P<0.001), and higher blood concentration of glucose (P = 0.002), glycosylated hemoglobin (P = 0.002), trigylcerides (P<0.001), low-density lipoproteins (P<0.001) and cholesterol (P<0.001), and with the ocular parameters of shorter axial length (P<0.001), thinner central cornea (P = 0.02), refractive error (P = 0.02), higher IOP (P<0.001) and thicker lens (P<0.001).In the non-glaucomatous study population, mean estimated CSFP was 10.8±3.7 mm Hg and showed a Gaussian distribution curve , higher systolic blood pressure , higher pulse rate , taller body height , higher blood concentration of cholesterol , and higher level of education , and with the ocular parameter of higher IOP .The multivariate analysis included estimated CSFP as dependent variable and all those parameters which were significantly associated with estimated CSFP in the univariate analysis, except of age, blood pressure and body mass index. The three latter parameters had been used to calculate the CSFP. We then dropped out of the list of independent parameters those variables, which were no longer significantly associated with estimated CSFP, starting with the parameters with the highest P<0.001) associated with higher estimated CSFP after adjusting for the ocular parameters of thinner central corneal thickness, shorter corneal curvature radius, shallower anterior chamber depth and longer axial length, and after adjusting for the systemic parameters of higher pulse rate, higher prevalence of arterial hypertension, higher blood concentration of triglycerides and cholesterol, higher frequency of drinking alcohol and body mass index. As a corollary, higher estimated CSFP was significantly associated with higher IOP after adjusting for the systemic parameters of rural region of habitation, higher systolic blood pressure, higher pulse rate, taller body height, higher blood concentration of cholesterol, and higher level of education.In our population-based study, IOP was significantly -A receptor antagonist into the dorsomedial and perifornical hypothalamus in rats Care must be taken not to transfer the result of our study performed on neurologically normal individuals onto neurologically abnormal patients, in whom a neurophysiologic reason is the likely cause of abnormal CSFP. In that case, the physiological relationships between CSFP, IOP and blood pressure may potentially no longer prevail. In a previous study by Saijadi and colleagues on 50 patients , CSFP as measured by direct lumbar puncture was strongly correlated with IOP P-value of <0.05, the low coefficients showed that only a fraction of the variability of intraocular pressure could be explained by that relationship. Future studies may address dynamic aspects of the association between IOP and CSFP based on the previous study by Morgan and coworkers Potential limitations of our study should be mentioned. First, the whole statistical analysis depended on the formula to calculate the CSFP. The pilot study, in which the basis parameter for that formula were assessed included a relatively small number of subjects, and these subjects had a clinical reason to undergo lumbar puncture In conclusion, IOP is positively associated with estimated CSFP after adjusting for other systemic and ocular parameters. As a corollary, higher estimated CSFP is significantly associated with higher IOP in multivariate analysis. It agrees with previous studies with direct lumbar CSFP measurements. It fits with the hypothesis that the pressures in all three fluid body compartments  are physiologically correlated with each other.


Hypertension is the most prevalent cardiovascular long-term condition in the UK and is associated with a high rate of multimorbidity (MM). Multimorbidity increases with age, ethnicity and social deprivation. Previous studies have yielded conflicting findings about the relationship between MM and blood pressure (BP) control. Our aim was to investigate the relationship between multimorbidity and systolic blood pressure (SBP) in patients with hypertension.A cross-sectional analysis of anonymised primary care data was performed for a total of 299,180 adult patients of whom 31,676 (10.6 %) had a diagnosis of hypertension. We compared mean SBP in patients with hypertension alone and those with one or more co-morbidities and analysed the effect of type of comorbidity on SBP. We constructed a regression model to identify the determinants of SBP control.p < 0.05). Other predictors included Afro-Caribbean ethnicity, β 0.05 (p < 0.05), South Asian ethnicity, β −0.03 (p < 0.05), age, β 0.05 (p < 0.05), male gender, β 0.05 (p < 0.05) and number of hypotensive drugs β 0.06 (p < 0.05). SBP was lower by a mean of 2.03 mmHg  for each additional comorbidity and was lower in MM regardless of the type of morbidity.The strongest predictor of mean SBP was the number of comorbidities, β −0.13 (Hypertensive patients with MM had lower SBP than those with hypertension alone; the greater the number of MM, the lower the SBP. We found no evidence that BP control was related to BP targets, medication category or specific co-morbidity. Further research is needed to determine whether consultation rate, “white-coat hypertension” or medication adherence influence BP control in MM. Multimorbidity (MM), the presence of more than one long-term condition (LTC), is common, increases with age, occurs 10–15 years earlier in deprived populations and is twice as prevalent in the non-white population . The preHypertension is the most common long-term condition in the UK, with 13.7 % of the population on the QOF hypertension register . The truUncertainty exists about the relationship between blood pressure control and MM. Paulsen et al.  comparedStudies looking at health outcomes in other long-term conditions suggest worse outcomes compared to those with no LTCs. MM was shown to be a poor prognostic factor with regards to mortality and treatment complications in patients with cancer , 13, carTherefore, we aimed to determine the relationship between systolic blood pressure (SBP) which is associated with greater CVD risk compared to diastolic BP  in patieData for this study were collected from Lambeth DataNet, a patient level primary care database containing information on patient demographics, QOF conditions, clinical measurements and medication. We used data from the year 2011/12 covering 299,180 patients over 18 years old registered at 51 of the 52 general practices in Lambeth (the remaining practice had an incompatible computer system). Lambeth is the ninth most deprived borough in London . The patn = 117). Inclusion of BP values was not influenced by the process of exception reporting, whereby GPs exclude some patients from QOF targets; our study included all BP data, regardless of whether the GP had exception reported the patient. Our final analysis was conducted on the remaining 31,676 cases with a recorded diagnosis of hypertension.There were 31,793 persons on the QOF hypertension register, giving a recorded prevalence of 10.6 % in the adult population. This value is lower than estimates of national prevalence and reflects the relatively young population in Lambeth . Data thWe selected twelve QOF conditions commonly included in studies of multimorbidity . These ip < 0.1. Because of multiple testing, we only considered predictor variables in the regression model as significant if p <0.01. We conducted tests of colinearity and for the normality of residuals in order to ensure robustness of the model. Our analysis was conducted using SPSS version 20 [We calculated mean SBP for all patients with hypertension, using the last recorded SBP for each patient, and stratified the sample according to the presence of comorbidity, the number of comorbidities and their type. We used the analysis of covariance (ANCOVA) method to adjust the mean SBP values for age, ethnicity and gender. We also constructed linear regression models in order to identify the most important determinants of SBP in patients with hypertension using the ‘enter’ regression method. The following potential predictor variables were considered: age, gender, deprivation, ethnicity , medication  and number of comorbidities. Variables were only included in the model if they were found to be significant on univariate analysis, rsion 20 .In our sample of patients with hypertension, 16,140 (51 %) had one or more of the QOF co-morbidities. Patients with hypertension alone had a mean SBP of 139.4 mmHg  whereas those with any multimorbidity had a mean SBP of 136.3 mmHg .n = 9626) was 137.1 mmHg , for those with two comorbidities (n = 4028) was 136.0 mmHg  and for those with three comorbidities was 134.3 mmHg . Full results for patients with up to 5 or more comorbidities are displayed in Fig. Patients with MM were further categorised by the number of comorbidities in addition to hypertension. The mean SBP of those with one comorbidity (n = 4028) of cardiovascular, mental health and respiratory diseases , beta =−0.13 (p < 0.05). Other significant predictors included the number of different hypotensive drug classes prescribed, ethnicity, gender and age (Table In our regression model, the strongest predictor of mean systolic BP was the number of comorbidities, B value =−2.03 (Patients with hypertension with one or more comorbidities had a lower mean SBP than those with hypertension alone. The mean SBP was lower in patients with a greater number of comorbidities. Following adjustment for age, gender and ethnicity, the mean SBP was 2.03 mmHg lower for each additional morbidity. The improvement in BP control was independent of the type of comorbidity or comorbidity combination.Our data provided further information on the factors with the potential to influence BP control. Firstly, we considered the effect of different QOF targets for SBP. We found no difference in mean SBP in patients with CKD or DM, both conditions for which the SBP QOF target is lower than for hypertension alone. Secondly, we found no evidence that the relationship between MM and SBP was mediated through the use of additional classes of hypotensive medication. Patients prescribed more classes of hypotensive agents had higher mean SBP. This is likely to be the result of reverse causality: that higher SBP resulted in more intensive hypotensive prescribing. Thirdly, we explored whether the overall relationship between MM and SBP might differ according to specific multimorbidity combinations. Morbidities which show a common pathophysiology, risk factor profile or management plan have been termed ‘concordant’; those that do not have been termed ‘discordant’ and in some studies these have been associated with poorer health outcomes . There hOur results differed from the Danish study  in that Other studies produced findings consistent with ours , 11, 26 Our study minimised selection bias though a large sample size covering 96 % of patients registered to practices in one inner London borough. This sample included a wide diversity in deprivation and ethnicity. We confined our analysis to QOF conditions which standardised the GP coding of these conditions. There are limitations in the interpretation of QOF data as it was not designed as a research tool and therefore the data are not externally validated  and inacWe considered other factors which we were unable to study because of the limitations of our dataset and which may have influenced the relationship between MM and SBP control. We were only able to use the last recorded SBP and not calculate an average over a period of time which may have given a better indication of overall SBP control. Patients with a greater number of comorbidities are likely to have higher consultation rates with health care professionals, be exposed to more opportunities for adjusting medication and discussing lifestyle measures, and more frequent BP recordings which in turn might reduce the ‘white coat’ effect on blood pressure readings and result in lower recorded SBP. Burstyn et al. suggested that patients who have their BP taken regularly are ‘trained’ and have a lower BP reading compared to those who are ‘untrained’ or not used to having their BP taken . HoweverOur findings demonstrate that overall BP control is improved in multimorbidity patients seen in primary care. The findings are reassuring given the growing number of people with MM, but whether improved intermediate outcome measures in patients with MM translate into improved cardiovascular health outcomes needs to be explored. Following these findings which in some ways were counter-intuitive, we plan to extend out work to look at other intermediate outcomes such as HbA1c and cholesterol levels. National data on consultation rates have not been produced since 2008  and in fEthical approval was given by the South East ResearchEthics Committee-07MRE01/26.


Objectives. The accumulation of lipids stored as excess triglycerides in the liver (steatosis) is highly prevalent in obesity and has been associated with several clinical characteristics, but most studies have been based on relatively small sample sizes using a limited set of variables. We sought to identify clinical factors associated with liver fat accumulation in a large cohort of patients with extreme obesity. Methods. We analyzed 2929 patients undergoing intraoperative liver biopsy during a primary bariatric surgery. Univariate and multivariate regression modeling was used to identify associations with over 200 clinical variables with the presence of any fat in the liver and with moderate to severe versus mild fat accumulation. Results. A total of 19 data elements were associated with the presence of liver fat and 11 with severity of liver fat including ALT and AST, plasma lipid, glucose, and iron metabolism variables, several medications and laboratory measures, and sleep apnea. The accuracy of a multiple logistic regression model for presence of liver fat was 81% and for severity of liver fat accumulation was 77%. Conclusions. A limited set of clinical factors can be used to model hepatic fat accumulation with moderate accuracy and may provide potential mechanistic insights in the setting of extreme obesity. Obesity is associated with fat accumulation in the liver, diagnosed as nonalcoholic fatty liver disease, and considered a manifestation of the metabolic syndrome , 2. AlthBoth environmental and genetic factors play a significant role in mediating risk for development of increased fat in the liver . A majorThe clinical standard for diagnosis and staging of hepatic fat is liver biopsy . Such da2, no evidence of hepatitis B virus (HBV), hepatitis C virus (HCV), or human immunodeficiency virus (HIV), evaluable liver biopsy results, and no diagnosis of alcohol abuse were included in this study. Alcohol abuse was evaluated during a required comprehensive behavioral evaluation with a clinical psychologist prior to surgery, where patients were asked about current and past substance and alcohol use. If a patient endorsed using alcohol, they were further queried based on the clinical criteria for alcohol use disorders [Patients enrolled in the Bariatric Surgery Program at the Geisinger Clinic Center for Nutrition and Weight Management were offered participation in an IRB approved research program on obesity. Clinical data were obtained during a standardized in-depth preoperative preparation program as described . Particiisorders . PatientWedge biopsies of the liver, obtained intraoperatively during the bariatric surgery from a similar anatomic location as part of clinical standard of care , were fihttp://dx.doi.org/10.1155/2014/368210). The research was approved by the Geisinger Clinic Institutional Review Board and all participants provided written informed consent.Clinical variables were obtained from an electronic database as described previously . BrieflyP values <0.10 were considered for subsequent inclusion in the model.Mean with interquartile range and overall range was used to describe the distribution of quantitative variables. Logistic regression was used to determine which of the more than 200 preoperative clinical variables were independently associated with the presence of any degree of hepatic lipid versus normal histology. In separate analyses, logistic regression was used to determine which preoperative clinical variables were independently associated with grade 1 steatosis versus grade 0 steatosis, that is, mild versus normal, and which variables were associated with grade 2 and grade 3 steatosis versus grade 1 steatosis, that is, severe versus mild. For all analyses, univariate analysis was conducted first to identify a subset of variables for consideration in model building; that is, those variables with univariate Regression modeling was conducted in two phases. First, variables were selected based on (1) whether statistical significance was achieved in univariate analysis and (2) whether published information was available implicating them in NAFLD/NASH. For the second phase, the variables significant in univariate analysis but not included in the first phase were each added individually to determine their effect on the association strength. Potential nonlinearity of continuous variables, for example, lab results, was evaluated through various transformations including the use of quartiles and categorization based on clinically relevant thresholds, for example, classifying glucose values by potentially diagnostic groups, <100 mg/dL, 100–124 mg/dL, and ≥125 mg/dL. The homeostasis model assessment of insulin resistance (HOMA-IR) was calculated using the equation :(1)HOMA-P values < 0.05 were considered significant.Effect modification was determined with interaction terms between variables within the final multiple regression models. c-statistics (area under the curve) and receiver operator characteristics (ROC) curves were used to evaluate discrimination of the final multiple regression models. SAS version 9.3 was used for statistical analysis and 2 who had no evidence of HBV, HCV, or HIV and no diagnosis of alcohol abuse and who had undergone primary bariatric surgery [P = 0.035) and slightly younger  but with similar levels of body mass index (BMI) of 49.5 kg/m2 versus 49.6 kg/m2 (P = 0.897) and liver function test (LFT) results .We analyzed clinical and pathology data on 3209 patients with BMI >35 kg/m surgery . PatholoOf the 2970 patients with available liver pathology results, 41 (1%) were excluded from analysis due to adverse histological findings, that is, 7 with inflammation, 33 with fibrosis, and 1 with cirrhosis, in the setting of grade 0 hepatic fat. In the remaining 2929 patients , the disμU/mL, triglycerides ≥ 125 mg/dL, HDL < 50 mg/dL, and an increasing odds ratio for increasing ALT levels. In addition, ferritin levels of more than 400 ng/mL for males or more than 100 ng/mL for females as well as red blood cell count of more than 4.38 M/uL, chloride of more than 103 mmol/L, iron binding capacity of at least 320 mcg/dL, and a serum zinc level of more than 70 mcg/dL were associated with a greater risk for hepatic fat. Use of the medications metformin, benzodiazepine anticonvulsants, and topical corticosteroids was also associated with an increased risk. Clinical variables including a waist-height ratio of more than 0.9, a clinical diagnosis of sleep apnea, and failing to lose at least 10% of excess body weight in the preoperative period also placed patients at increased risk. Only two variables, the use of estrogen and/or progestin or serum creatinine level of >1.2 mg/dL, were associated with a decreased risk for hepatic fat. Interaction terms between these measures were not significant, suggesting that the effects are consistent within selected subsets of the population.In a univariate analysis comparing the 702 patients with grade 0 hepatic fat to the 2227 patients with mild, moderate, and severe hepatic fat accumulation, 87 of the 204 clinical variables were selected for the initial multiple regression model. These 87 variables were included in stepwise model building, resulting in 19 variables that demonstrated independent association  and resuThe above analysis was repeated comparing grade 1 (mild) to grade 0, which produced essentially identical results (data not shown). A reanalysis was also conducted for the patients who were documented to have no use of alcohol. In this subgroup, the overall area under the curve (c-statistic) increased slightly to 0.826, although the no alcohol group had a higher percentage of T2D that may have also influenced hepatic fat content. Similarly, the HOMA-IR was used instead of glucose and insulin, which slightly increased the area under the curve (c-statistic) to 0.817.μU/mL), triglycerides (≥125 mg/dL), and use of metformin. Lower preoperative weight loss was again associated with increased risk. A graded increased risk was associated with ALT levels to more than 5-fold at ALT >37 U/L, while AST levels >31 U/L showed an almost 1.7-fold increased risk. Independent factors increasing the odds of moderate to severe hepatic fat included female gender (30% increase), patients with a BUN level <13 mg/dL (>50% increase), and use of tricyclic or modified cyclic antidepressants (50% increase) or fibric acid derivatives (>75% increase). Interaction terms between these measures were not significant (data not shown). We also evaluated the association in patients who were documented to have no use of alcohol. In this subgroup, the overall area under the curve (c-statistic) increased slightly to 0.785. Reanalysis using HOMA-IR increased the area under the curve (c-statistic) to 0.777.We then sought to determine what clinical factors were associated with higher levels of hepatic fat versus low levels by comparing moderate (grade 2) and severe (grade 3) to mild (grade 1). For this analysis, the 702 patients with grade 0 hepatic fat levels were excluded from the analysis, leaving 2227. In univariate analysis, the 1248 patients with grade 1 were compared to the 979 patients with grades 2 and 3. A total of 56 of the 204 clinical variables were brought forward for multiple regression analysis. These 56 variables were included in stepwise model building, resulting in 11 variables that were independently associated with the higher level (grades 2 and 3) of hepatic fat , includi2, and 75% steatosis prevalence reported in these studies (Supplementary Table S2). The overall prevalence of hepatic fat in these studies is slightly lower than previously reported [Fatty liver is a highly prevalent finding in extreme obesity that has several potentially significant clinical sequelae. The characterization of associated clinical characteristics in populations with high prevalence, such as those with extreme obesity, is thus important for identifying potentially modifiable risk factors and putative pathophysiological mechanisms. To date, most studies have been limited by small sample sizes, use of noninvasive methods to assess hepatic fat, and a focus on a relatively small number of clinical variables. We surveyed 22 published reports (Supplementary References) on hepatic fat accumulation representing 4274 patients with extreme obesity undergoing bariatric surgery and liver biopsy (Supplementary Table S2), a prime opportunity in which to assess population-based aspects since such patients generally are not documented to have, nor are suspected of having, liver disease, which is a bias for studies based on percutaneous liver biopsies. Our single center study thus represents a sample size of nearly 75% of that of the combined reports we were able to identify. Our basic cohort characteristics were similar to the 78% female, average age of 41.5 years, average BMI of 47.6 kg/mreported  in the mThe accuracy of our final multiple logistic regression model for presence of hepatic fat was over 80%. The variables contributing to this moderate level of accuracy included elevated AST and/or ALT, where risk progressively increased over a relatively restricted range (by quartile) considered “normal,” from <20 U/L to greater than 37 U/L. These data are consistent with that reported in other studies  and a prFatty liver has been independently associated with a lower level of HDL cholesterol and a higher serum triglyceride level, similar to our findings, although large studies have used imaging as a surrogate for classifying hepatic fat , 24. IntWe found that patients with a diagnosis of obstructive sleep apnea had more severe levels of hepatic fat accumulation, replicating findings from recent meta-analyses . This inHigher ferritin, iron binding capacity, red blood cell count, and serum zinc levels were also found to be associated with hepatic fat accumulation. The ferritin, iron binding capacity, and red cell count are consistent with a dysregulation of iron metabolism that has previously been described , given tFemale sex and the use of estrogens and progestins  were associated with slightly increased odds for hepatic fat, consistent with previous human and animal studies . SeveralDespite the large sample size, our data were limited to a single center with patients who were primarily of Caucasian European ancestry and were predominantly middle-aged women, limiting generalizability of the data, though allowing for comparison to other bariatric surgery studies. The extreme level of obesity limits extension of the findings to lower BMI levels. A cohort of bariatric surgery patients may also be a biased population relative to the vast majority of individuals with extreme obesity who do not undergo the procedure.We characterized histologically defined fatty liver in the context of the largest prospectively enrolled single center cohort of extremely obese adults coupled to a comprehensive and well-curated entry database of clinical data . RegressThe Supplemental materials contain Table S1 that contains the clinical variables used in regression analysis (n=204 variables) and Table S2 that contains a summary of 22 available published reports on 4274 patients with extreme obesity undergoing bariatric surgery and liver biopsy.


Airway management in critically ill patients involves the identification and management of the potentially difficult airway in order to avoid untoward complications. This focus on difficult airway management has traditionally referred to identifying anatomic characteristics of the patient that make either visualizing the glottic opening or placement of the tracheal tube through the vocal cords difficult. This paper will describe the physiologically difficult airway, in which physiologic derangements of the patient increase the risk of cardiovascular collapse from airway management. The four physiologically difficult airways described include hypoxemia, hypotension, severe metabolic acidosis, and right ventricular failure. The emergency physician should account for these physiologic derangements with airway management in critically ill patients regardless of the predicted anatomic difficulty of the intubation. The “difficult airway” has traditionally been used to describe intubations that have anatomic characteristics that make visualization of the vocal cords and placement of the tracheal tube challenging. Although scoring systems and prediction rules to identify the potentially difficult airway may be helpful, the performance of these prediction methods is only moderately successful. Additionally, the last decade has seen an incredible expansion of devices available to successfully ventilate, visualize the vocal cords, and place a tracheal tube leaving these prediction methods less useful.2Critically ill patients represent the highest risk patients to intubate because of these contextual factors that increase the incidence of adverse events leading to dangerous hypoxemia, hemodynamic collapse and cardiac arrest.Hypoxemic respiratory failure (Type I) in which there is failure to maintain adequate arterial oxygenation is a relatively common indication for intubation and invasive mechanical ventilation in the emergency department (ED). The mechanism of acute hypoxemic respiratory failure is most commonly due to any etiology that disrupts optimal alveolar-capillary gas exchange, such as pneumonia, acute respiratory distress syndrome (ARDS), and cardiogenic or non-cardiogenic pulmonary edema. In each of these instances a portion of the blood passing through the pulmonary circulation shunts past the remaining functional alveoli without the opportunity to participate in gas exchange. This hypoxemia is different than that which occurs with hypercapneic respiratory failure (Type II), which is due to decreased alveolar ventilation or an increase in dead space. Hypoxemia from Type II respiratory failure is relatively easily corrected with supplemental oxygen or an increase in minute ventilation. Hypoxemic respiratory failure patients are at high risk for rapid desaturation during intubation, which may result in hemodynamic instability, hypoxic brain injury, and potentially cardiopulmonary arrest.2), the rigid mask does not create an adequate seal and thus ambient air is entrained around the mask and decreases the effective FiO2 to much less than 100%. The higher the minute ventilation, the more this ambient air dilutes the FiO2 by admixing with the oxygen reservoir from the NRB. This relationship of FiO2 with underlying minute ventilation makes preoxygenation with a NRB less effective in critically ill patients. Noninvasive positive pressure ventilation (NIPPV) has been shown to improve oxygenation beyond usual preoxygenation methods, particularly in patients with obesity and shunt physiology.34Preoxygenation is an important step in every intubation with the goals of achieving the following: 1) maximal hemoglobin saturation and, 2) maximal partial pressure of arterial oxygen.Occasionally NIPPV is inadequate due to anatomic characteristics that make obtaining or maintaining an adequate mask seal difficult. In these patients that have significant mask leaks, or when higher pressures are required for preoxygenation, such as in patients with pulmonary edema or morbid obesity, supraglottic airways may be an option for preoxygenation. Current data for the use of supraglottic airways for preoxygenation in the ED are limited to a case report; however, there are some limited data showing success with prolonging safe apnea time in morbidly obese patients in the operating room.38Pharmacologic assistance to decrease anxiety or even induce sedation may be useful if chosen carefully to improve patient tolerance of either the NIPPV mask or supraglottic airway. A recent observational study formalized a protocol, termed delayed sequence intubation (DSI), in which ketamine was administered to induce a dissociated state to allow preoxygenation with a NRB mask or NIPPV prior to the administration of a neuromuscular blocking agent, and showed most patients had improved preoxygenation.39Apneic oxygenation, also known as “diffusion respiration” or “aventilatory mass flow,” occurs because oxygen removal from the aveoli by circulating blood brings alveolar pressure to slightly subatmospheric levels, generating a negative pressure gradient, drawing oxygen from the upper airway into the lungs.492 up to 60Lpm for preoxygenation and apneic oxygenation is mixed. Vourc’h and colleagues found no difference in desaturation rates when HFNC for preoxygenation and apneic oxygenation was compared to high-flow facemask in hypoxemic patients.2 saturation after preoxygenation, during intubation, and at 5- and 30-minutes post-intubation.2 to the nasopharynx during the apneic period and may prevent desaturation in some patients. For a more detailed description of preoxygenation and apneic oxygenation, see Weingart and Levitan’s comprehensive review.54Recent evidence with the use of a high-flow nasal cannula (HFNC) capable of delivering a humidified, adjustable FiOPreoxygenation and apneic oxygenation should be performed in all critically ill patients. Despite mixed data, apneic oxygenation is a low-risk intervention that may provide significant benefit in prolonging the safe apneic period. If a HFNC system is not available, a wide-bore nasal cannula or standard nasal prongs should be used to augment preoxygenation and provide apneic oxygenation.In patients with shunt physiology due to atelectasis or alveolar filling from pneumonia, ARDS or pulmonary edema, NIPPV can improve alveolar recruitment and oxygenation. In select patients, supraglottic airways may be considered when higher pressures are needed or a mask seal with NIPPV cannot be achieved. One must balance this potential benefit of a supraglottic airway with the risk of aspiration or upper airway injury. Nasal continuous positive airway pressure with a nasal mask may be useful to maintain alveolar recruitment during intubation in patients at high risk.For patients who cannot tolerate the NIPPV mask (e.g. delirium), analgesia, anxiolysis, or DSI may be considered to optimize preoxygenation. If procedural sedation for preoxygenation is performed, one must be prepared to intubate at the onset of DSI, even with ketamine, due risk of cardiac arrest, laryngospasm and apnea, which have all been reported with ketamine.56Peri-intubation hypotension is common and roughly one-quarter of patients develop transient hypotension after emergent intubation and transition to positive pressure ventilation.62Venous return to the heart is driven by the difference between venous pressure (i.e. mean systemic pressure) and right atrial pressure. During spontaneous respiration, the negative intrathoracic pressure augments this pressure gradient, which in essence “pulls” blood back to the right heart. Any physiologic disturbance that disrupts this driving pressure gradient will decrease venous return. Transition to positive pressure ventilation increases intrathoracic pressure and thus right atrial pressure, decreasing the pressure differential driving venous return.Fluid resuscitation is important in critically ill patients, as an increase in circulating volume will increase mean systemic pressure and venous return.71The choice of induction agents can contribute to peri-intubation hypotension as many have adverse hemodynamic effects. Benzodiazepines and propofol have a sympatholytic effect, leading to myocardial depression and a decrease in vascular tone.Patients with conditions that reduce venous return are particularly susceptible to hypotension and patients at risk are suggested by pre-intubation hypotension or an elevated shock index >0.8. These patients should be hemodynamically optimized prior to intubation. This includes aggressive volume resuscitation if the patient is likely to be a volume responder. Hemodynamically stable induction agents should be used when possible.For patients unresponsive to volume resuscitation, a norepinephrine infusion should be initiated.If pre-intubation resuscitation is not feasible due to impending cardiopulmonary arrest in patients with shock, peripherally administered vasopressor boluses can be prepared quickly at the bedside and may maintain blood pressure during intubation and resuscitation. This intervention has not been studied in critically ill adults; however, diluted epinephrine (given as 10–50mcg boluses with a concentration of 1–10mcg/mL) may be preferred due to its inotropic effect.For patients without shock who have a transient drop in blood pressure after intubation due to the vasodilatory effects of induction agents or transition to positive pressure ventilation, diluted phenylephrine (given as 50–200mcg boluses with a concentration of 100mcg/mL) may be useful.2, roughly by half. Respiratory acidosis is then usually corrected easily by interventions that increase the alveolar ventilation such as bag-valve mask ventilation, NIPPV, or mechanical ventilation. When acidemia develops from a metabolic acidosis, maintenance of acid-base homeostasis depends on a compensatory respiratory alkalosis from alveolar hyperventilation.2 possible during hypoventilatory states, when hypocapnia is already present due to a compensatory respiratory alkalsosis, further hyperventilation results in incrementally smaller decreases in PaCO2 and eventually reaches a plateau at which point there is no effect of further increasing alveolar ventilation.When acidemia develops from a respiratory acidosis, rapid correction of that acidemia can occur by increasing the alveolar ventilation. Doubling the alveolar ventilation will reduce the PaCOIntubation should be avoided, if possible, in patients with severe metabolic acidosis who have a minute ventilation requirement not likely to be met by the mechanical ventilator, despite a low pH. A short trial of NIPPV may adequately support the respiratory work of breathing until correction of the underlying metabolic acidosis can occur and will provide an estimate of the patient’s intrinsic minute ventilation by measuring the patient’s respiratory rate and tidal volume delivered with each breath.If intubation is necessary, maintaining spontaneous respiration becomes the critical action both during intubation and with mechanical ventilation. This will allow the patient to maintain their own high minute ventilation and includes using sedative agents that are less likely to reduce the patient’s respiratory drive. Rapid sequence intubation should be avoided if possible, and if one is deemed necessary, a short-acting neuromuscular blocker such as succinylcholine should be used.After intubation, we recommend choosing a ventilator mode that allows the patient to set and maintain their own minute ventilation in order to best maintain their respiratory compensation. A pressure-targeted ventilator mode such as pressure support ventilation or pressure control mode will allow the patient to set the rate and tidal volume received. Special care should be taken to monitor for air trapping given the high rates and tidal volumes reached as well as monitor for respiratory muscle fatigue, which will result in a loss of compensation.Under normal circumstances, the right ventricle is a low-pressure, high-compliance, flow-based chamber geared to propel venous blood returning to the heart into the pulmonary circulation.85Intrathoracic pressure changes with respiration have an exaggerated effect on hemodynamics in the patient with RV failure, worsening cardiopulmonary interactions and making intubation extremely risky. Unlike left ventricular function, which improves with positive pressure ventilation, RV function worsens with the increase in intrathoracic pressure induced by positive pressure ventilation. This occurs because the intrathoracic pressure is transmitted to the alveolar capillary bed, leading to collapse of these small vessels and increases the pulmonary vascular resistance against which the RV must pump.Patients with increased RV afterload often present with varying degrees of RV strain on bedside echocardiography, including a dilated RV and inferior vena cava, septal flattening during systole in pressure overloaded states, and septal flattening during diastole in volume overloaded states. While patients with RV dysfunction may respond to small fluid challenges or an inotropic agent, further increasing preload with a fluid challenge in patients with RV failure is unlikely to be fruitful, and may be deleterious as volume overloading a pressure overloaded RV increases diastolic wall tension and left ventricular diastolic dysfunction, directly worsening left ventricular filling and stroke volume.91Bedside echocardiographic assessment of RV function should be performed to assess RV dysfunction versus RV failure. If the patient has some contractile reserve (RV dysfunction), cautious fluid resuscitation should be performed.Preoxygenation is essential despite the difficulties resulting from intracardiac shunt and ventilation-perfusion (V/Q) mismatch, which commonly occur in right heart failure.28Apneic oxygenation should be performed given the potential for benefit.90Induction agents should be considered carefully. Hemodynamically neutral sedatives such as etomidate should be used for induction. Intravenous fentanyl premedication may be useful to blunt the hypertensive response to laryngoscopy.Continuous norepinephrine infusion should be started prior to induction in hypotensive patients with the goal of increasing mean arterial pressure higher than pulmonary artery pressure, which can be determined by bedside echocardiography. For patients without hypotension, norepinephrine should be primed and “in-line” in the event of post intubation or sedative induced hypotension.95The goals of mechanical ventilation include maintenance of a low mean airway pressure and avoidance of hypoxemia, atelectasis, and hypercapnea, which increase RV afterload.The difficult airway is well recognized as a clinical entity and is classically based on anatomic considerations. In this paper we describe another aspect of the difficult airway that involves physiologic abnormalities that must be considered in developing an intubation plan. These physiologic abnormalities must be considered and addressed prior to intubation. If they are not, significant untoward outcomes can result. We present four physiologic disturbances that must be considered carefully when planning for and performing tracheal intubation in the ED to avoid complications from the very procedure intended to be life saving. Many of the recommendations presented are based on clinical experience and physiologic principles and thus represent opportunities for formal investigation.


Whether the incidence of coronary heart disease (CHD) is related to a decrease in total antioxidant capacity (TAC) has not yet been completely clarified. We assessed TAC of blood serum in a group of 163 men with CHD aged 34.8–77.0 years and in 163 age-matched peers without CHD. Two spectrophotometric methods were applied to assess TAC: ferric reducing ability of serum (TAC-FRAS) and 2.2-diphenyl-1-picryl-hydrazyl (TAC-DPPH) tests. In the CHD group, multivariate analysis revealed that uric acid (UA), triglycerides, and systolic blood pressure contributed independently to the TAC-FRAS variance. TAC-DPPH was favorably predicted by UA concentration, but negatively so by current smoking and glucose levels. In men without CHD, UA was the only independent determinant of both TAC-FRAS and TAC-DPPH. Presence of CHD was not an independent predictor of TAC—observed between-group differences (higher TAC in CHD patients) disappeared after adjustment for other confounders. We conclude that UA is the main determinant of TAC of blood serum in men. TAC is not directly influenced by age or CHD but is related to several indices of overweight/obesity and laboratory measures of metabolic syndrome, especially in patients with CHD. An increasing number of studies focus on the role of reactive oxygen species (ROS) in the pathogenesis of premature ageing as well as of numerous civilization diseases, such as cardiovascular diseases –3. It haCoronary heart disease (CHD) is the most important cause of mortality in developed countries. Numerous discrepancies have been observed in the study results and no unequivocal answer has been reached whether the incidence of CHD is related to a decrease in antioxidant potential. Relationship of CHD to antioxidant defenses may be modified not only by many demographic, anthropometric, physiological, and biochemical confounders but also by different exogenic substances such as applied medications or cigarette smoking , 6.Total antioxidant capacity (TAC) assessment is an established methodology to measure different elements of antioxidant defense system together . In ordeTherefore, the aim of the present study was to compare TAC in CHD patients and in healthy age-matched subjects, taking into account anthropometric and biochemical correlates.n = 147), statins (n = 142), fibrates (n = 4), beta-blockers (n = 134), angiotensin-converting enzyme (ACE) inhibitors (n = 87), ticlopidine (n = 51), long-acting nitrates (n = 48), clopidogrel (n = 25), diuretics (n = 25), calcium channel blockers (n = 16), oral antidiabetic drugs , and insulin (n = 4).The study was carried out in the two age-matched groups of men. Group I consisted of 163 CHD patients aged 34.8–77.0 (56.59 ± 8.04) years. In the course of myocardial ischemia and reperfusion the increased concentration of free radicals may also cause an increase in antioxidant enzymes activities. In order to exclude the possibility of acute ischemia-reperfusion reactions we qualified the patients in whom the most recent acute coronary event, cardiac or cardio-surgery intervention had occurred at least a minimum of one month earlier. Among the males with CHD 130 had a history of myocardial infarction (MI) (13 patients-twice), 137 underwent coronary catheterization, 107 underwent percutaneous transluminal coronary angioplasty (PTCA), 23 underwent coronary artery bypass surgery (CABG), 107 men demonstrated arterial hypertension (HA), and 25 displayed diabetes mellitus (DM). An applied pharmacotherapy regimen usually involved aspirin (n = 13) and ACE inhibitors (n = 24). Fourteen men were treated for hypercholesterolemia with statins and 16 used preventive treatment with low-dose aspirin. All the subjects in the study were free from known malignant diseases, important chronic inflammatory diseases, renal disorders, disability, or dementia. Apart from salt, glucose, and cholesterol limitations, none of the subjects was following a special diet. The presence of CHD was excluded in the control group based on clinical examination and exercise testing. The graded submaximal exercise test was carried out on a Monark type 818E  bicycle ergometer with 30 watt increments every 3 min to achieve at least 85% of maximal age-predicted heart rate (220-age) with a continuous ECG tracing. All the subjects were informed of the purpose of the study. The study had been approved by the Ethics Committee and written informed consent was obtained from all the subjects.To every patient, an age-matched peer without CHD was assigned. Control group consisted of men who attended the Healthy Men Centre of the Medical University of Lodz and were regularly monitored at least once a year. All the participants were relatively healthy community-dwelling men able and willing to visit the outpatient clinic as well as to take part in the multiple examinations. Group II comprised 163 males aged 34.3–76.1 (56.66 ± 7.99) years. Thirty-five of these men had HA and were treated with beta-blockers  and after overnight rest, restraining from physical exercises, smoking, and alcohol for at least 12 h before laboratory measurements. After fasting blood drawing all the participants were given a light breakfast and a multidimensional assessment was performed with each subject. During the standard medical interview the applied pharmacotherapy regimen was assessed. The smoking and usual dietary habits were evaluated using the World Health Organization Countrywide Integrated Noncommunicable Diseases Intervention (WHO CINDI) questionnaire .·m−2) was calculated. Skinfold measurements were taken at four sites: triceps, biceps, subscapula, and supraileum. The percentage of body fat was estimated from skinfold measurements according to Durnin and Womersley [Anthropometric data was collected by standard methods. Height and weight were measured and the body mass index-BMI (kgomersley . Measure·L−1) or into siliconized tubes (for other tests). Enzymatic methods were used to determine serum total cholesterol , triglycerides , glucose (CORMAY LiquickCor-GLUCOSE), and uric acid concentrations . High density lipoprotein cholesterol (HDL-C) was measured by the precipitation method (CORMAY-HDL). Low density lipoprotein cholesterol (LDL-C) was estimated using the Friedewald formula.Fasting blood samples were drawn from the antecubital vein: for measurements of TAC into Vacuette tubes  with sodium heparin (200 mgn = 30) calculated for TAC-DPPH and TAC-FRAS were 0.049 and 0.018, respectively. In addition, both TAC assessments were performed in parallel using the same laboratory equipment (spectrophotometer) and within the same time frame. TAC-FRAS values are expressed in mmol·L−1 of formed FeCl2 (mmol FeCl2·L−1). DPPH test consists of the scavenging of free radical DPPH  by a complex of antioxidants in the assayed sample of deproteinized serum. A decline of absorbance values equivalent to % of DPPH reduction expresses the level of the TAC-DPPH. The precise methodology of both tests has been described elsewhere [Blood samples were incubated for 30 minutes at 37°C and then centrifuged for 10 minutes  for further TAC measurements. Subsequently the samples were stored at −80°C for no longer than 30 days prior to the assays of antioxidant activity . The mea post hoc testing, the Kruskal-Wallis test, and chi-square test (with Yates' correction for 2 × 2 tables) were used for comparison between the two groups of men. Pearson product moment or Spearman correlations were used to determine the relationships between variables. Multiple linear regression (with forward stepwise technique) was used with all the independent variables to select variables that independently predict TAC levels. Comorbidities, drugs, and current smoking were entered as dummy variables . TAC-FRAS values were normalized using a log transformation and TAC-DPPH values were normalized using a square root transformation for the purpose of statistical analyses. The results are presented as the mean ± standard deviation. The level of significance was set at P ≤ 0.05 for all the analyses.Data were verified for normality of distribution and equality of variances. Variables that did not meet the assumption of normality were analyzed with nonparametric statistics. A one-way analysis of variance (ANOVA) with Bonferronir = 0.38; P < 0.001) and in CHD group .Correlations between TAC, UA, and selected anthropometric, biochemical, and blood pressure characteristics for both groups are shown in n = 140) were characterized with significantly higher (P < 0.01) values of TAC-FRAS (1.33 ± 0.27 mmol FeCl2·L−1) and TAC-DPPH (13.0 ± 4.93% reduction) than ones who were currently smoking .Currently nonsmoking cardiac patients .In group I (CHD patients), TAC-FRAS was favorably predicted by UA, TG, and SBP:TAC-DPPH was favorably predicted by UA while negatively so by glucose and current smoking. ConsiderWhen current pharmacotherapy was taken into account, ticlopidine and clopidogrel contributed also to the TAC-DPPH variance .In group II (men without CHD), both TAC values were predicted only by UA. ConsiderPresence of CHD was not an independent predictor of TAC—observed between-group differences for TAC disappeared after adjustment for other confounders. In the combined population of all 326 studied men, TAC—FRAS was favorably predicted by UA, TG, and DBP. ConsiderTAC-DPPH was favorably predicted by UA while negatively so by glucose and current smoking. ConsiderPrevious studies provided confusing results on the relationship of the presence of cardiovascular diseases to TAC. Several studies found significantly lower blood antioxidants and TAC in patients with CHD , 14. SimIn our study, several direct correlations for obesity measures and TAC were observed both in healthy men and in men with CHD. These associations were more visible for TAC-FRAS and in CHD patients. In CHD patients several significant positive correlations were also observed between TAC-FRAS and other cardiovascular risk factors as elevated TC, TG, and blood pressure. The explanation of these associations may be based on the classical physiological concept of hormesis. This Greek word means a state in which a sublethal dose of toxin can increase the tolerance of organism to stand up to higher doses of toxin . In obesThe next discrepancy appears in correlation with TAC and age. Our findings are contrary to several other studies which report that antioxidant capacities of human blood serum decrease along with age , 35 and Depletion of the antioxidant barrier may occur during prolonged exposure to sustained oxidative stress, with this being the case with current smoking and probably also elevated glucose levels in our CHD patients. It has been well documented that cigarette smoke increases the level of oxidative stress, decreases antioxidant capacities, and induces several chronic diseases  . It has UA, which also serves as a water-soluble antioxidant and a free radical scavenger in humans, is an end-product of purine metabolism and is present in high concentrations in plasma , 42. SysSeveral shortcomings of the present study should be acknowledged. This is a cross-sectional study performed in volunteers: CHD patients and their age-matched peers. Active well-educated subjects in relatively good health are more prone to participate in such studies. Antioxidants status is the result of the interaction of many different compounds and systemic metabolic connections and the TAC is modulated either by ROS overload (not measured in the present study) or by antioxidants concentration. Correlations between TAC and selected patients characteristics were relatively modest. Although both DPPH and FRAS tests measure the TAC of blood serum, they reflect somewhat different physiological properties . Future We conclude that TAC, assayed with either the FRAS or the DPPH methods, does not differ between men with and without CHD when additional confounders are taken into consideration. Age was not a determinant affecting the antioxidative barrier, regardless of the presence of CHD. In both groups, UA was the strongest determinant of TAC-FRAS and TAC-DPPH. TAC is directly related to several indices of overweight/obesity and laboratory measures of metabolic syndrome, especially in patients with CHD.


However, because both SVV and PPV were obtained from pulse pressure analysis, a mathematical coupling factor could not be excluded. We therefore designed this study to confirm whether Eadyn, obtained from two independent signals, allows the prediction of arterial pressure response to VE in fluid-responsive patients.Functional assessment of arterial load by dynamic arterial elastance  and SVV . A total of 80 fluid challenges were performed . Patients were classified according to the increase in mean arterial pressure (MAP) after fluid administration in pressure responders (≥10%) and non-responders.We analyzed the response of arterial pressure to an intravenous infusion of 500 ml of normal saline in 53 mechanically ventilated patients with acute circulatory failure and preserved preload dependence. Eadyn was higher in pressure responders . Preinfusion Eadyn was related to changes in MAP after fluid administration . At baseline, Eadyn predicted the arterial pressure increase to volume expansion : 0.86 to 0.98; P <0.0001). A preinfusion Eadyn value ≥0.73 (gray zone: 0.72 to 0.88) discriminated pressure responder patients with a sensitivity of 90.9% (95% CI: 75.6 to 98.1%) and a specificity of 91.5% (95% CI: 79.6 to 97.6%).Thirty-three fluid challenges (41.2%) significantly increased MAP. At baseline, Eadyn, obtained from two independent signals, enabled the prediction of arterial pressure response to fluid administration in mechanically ventilated, preload-dependent patients with acute circulatory failure.Functional assessment of arterial load by EaThe online version of this article (doi:10.1186/s13054-014-0626-6) contains supplementary material, which is available to authorized users. Correction of arterial hypotension is essential for adequate cellular metabolism ,2. Althodyn), defined as the pulse pressure variation (PPV) to stroke volume variation (SVV) ratio, could predict the arterial pressure increase after volume expansion (VE) in hypotensive, preload-dependent patients [dyn could be recommended for clinical decision-making [In a previous study, we found that dynamic arterial elastance . Approval from our Institutional Research Ethics Committee  was obtained. Informed consent was deemed unnecessary because the study protocol and the monitoring procedures were considered to be part of routine clinical care.−1∙hr−1 during at least 2 hours, heart rate >100 beats/min and/or the presence of skin mottling. Preload dependency was assessed according to our institutional protocol for hemodynamic resuscitation and defined as a CO increase ≥10% after a 2-minute leg-raising maneuver [We prospectively included all patients equipped with an indwelling arterial catheter and evaluated by esophageal Doppler monitoring who were receiving a fluid challenge for the presence of clinical signs of acute circulatory failure, including hypotension  ≤90 mmHg); requirement for vasopressor drugs, presence of lactic acidosis, urine output ≤0.5 ml∙kgmaneuver . In all Patients were under controlled mechanical ventilation with no spontaneous respiratory efforts, as assessed by visual inspection of the airway pressure curve. Patients with unstable cardiac rhythm were excluded, although this condition did not affect the decision to administer fluids.Patients were monitored with an esophageal Doppler monitoring system . This system combines a standard Doppler monitor with arterial pressure analysis capability. The probe was inserted into the esophagus, preferably using the nasal route, and advanced until the maximal peak velocity of the aortic blood flow was reached. The gain setting was adjusted to obtain the optimum outline of the Doppler waveform. In order to reduce signal noise from heart valves and wall thump artifact, a built-in filter function was activated in some patients and kept unchanged throughout the study.An arterial pressure transducer  was zeroed to atmospheric pressure, and optimal damping of the arterial waveform was carefully checked by fast-flushing the line. The arterial pressure signal was transferred from the patient’s bedside monitor to the Doppler system using a serial cable and automatically synchronized with the aortic blood flow waveform for analysis  relationship and can be described by a resistive element or the systemic vascular resistance (SVR = MAP/CO*80) and a pulsatile element or the net arterial compliance  . This diial load . PPV obtial load  and averAll hemodynamic variables were measured prior to and just after VE, consisting of 500 ml of normal saline given within 30 minutes. No changes in ventilatory settings or vasoactive drugs were made during volume administration. No paralyzing agents were used for the study. All hemodynamic variables were automatically recorded every 10 seconds and averaged over 1 minute for statistical purposes.dyn but also on the magnitude of CO changes, we also calculated the weighted least-squares regression, taking into consideration the contribution of CO changes in the relationship between arterial pressure increase and preinfusion Eadyn. Differences at baseline between pressure responders and non-responders were compared by means of an independent sample t-test, and their evolution over time was assessed by one-way analysis of variance with repeated measurements, using group (pressure responders vs. non-responders) as the between-subjects factor and time (preinfusion vs. postinfusion) as the within-subjects factor. Differences between groups were compared using an independent samples t-test. Comparison between preinfusion and postinfusion periods was tested using a t-test for repeated measurements. Categorical variables were compared using the χ2 test. For each arterial load variable, a receiver operating characteristic (ROC) curve was created to test the ability of predicting a positive MAP response after VE. Areas under the ROC curve (AUC) with 95% confidence intervals (95% CIs) were compared by using the method described by DeLong et al. [dyn was also assessed on the basis of its positive and negative likelihood ratios (LHRs). A diagnostic variable with potential to influence clinical decisions is usually considered when its positive LHR is >10, its negative LHR is <0.1 and the AUC is >0.9 [dyn cutoff was created using a resampling method [The normality of the data distribution was tested using the Kolmogorov-Smirnov test. The results are expressed as mean ± standard deviation or as median (25th to 75th interquartile range), as appropriate. Patients were classified as hypotensive if they had a MAP ≤65 mmHg and/or SAP <90 mmHg. Sepsis was defined according to standard criteria . The relg et al. . Optimalg method . In summg method .A preliminary power analysis determined that a sample size of 48 patients was required for detecting an AUC difference of 0.1 .P-value <0.05 was considered significant. All statistical analyses were two-tailed and performed using MedCalc statistical software version 14.8.0 [A n 14.8.0 .The patients’ characteristics are summarized in Table P = 0.18), or between hypotensive and non-hypotensive patients . There was a weak relationship between VE-induced changes in MAP and CO  .Hemodynamic changes after VE are shown in Table P <0.0001) and SVR from 1,229 ± 554 dyn∙s∙cm−5 to 1,150 ± 514 dyn∙s∙cm−5 (P <0.0001). Net arterial compliance did not change. In non-responder patients, VE reduced the static component of arterial load but did not affect Eadyn (Table Fluid administration decreased Ea from 1.75 (1.54 to 1.91) mmHg/ml to 1.59 (1.45 to 1.81) mmHg/ml    Figure . Pressurdyn was correlated with VE-induced changes in SAP , diastolic arterial pressure , MAP  and arterial pulse pressure   was higher than for any other variable of arterial load: Ea , C ; SVR  and preinfusion MAP   and a specificity of 91.5% (95% CI: 79.6% to 97.6%), with a positive predictive value of 88.2 (95% CI: 72.5% to 96.7%) and a negative predictive value of 93.5 (95% CI: 82.1% to 98.6%). The positive and negative LHRs for Eadyn were 10.68 (95% CI: 4.2 to 27.4) and 0.1 (95% CI: 0.03 to 0.3), respectively. The bootstrapped 95% CI defined a gray zone for Eadyn ranging between 0.72 and 0.88. Only ten fluid challenges (12.5%) were situated in the inconclusive zone.At baseline, an Eadyn was similar    , defined as the ratio between pulse pressure variation (PPV) and stroke volume variation (SVV), measured from two independent signals, predicted the arterial pressure response to fluid administration in mechanically ventilated, preload-dependent patients.Dynamic arterial elastance (Eadyn value ≥0.73 predicted a mean arterial pressure increase ≥10% after volume expansion with 90.9% sensitivity and 91.5% specificity, as well as a narrow gray zone ranging between 0.72 and 0.88. The predictive performance of Eadyn was similar in septic and non-septic patients and regardless of the presence of systemic hypotension.An EaThe arterial pressure response to volume administration was not related to static arterial load variables.Preload-dependent patients in whom arterial pressure did not increase after volume expansion showed a decrease in the static component of arterial load.