999 resultados para Trough Levels


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Upon agonist stimulation, endothelial cells trigger smooth muscle relaxation through the release of relaxing factors such as nitric oxide (NO). Endothelial cells of mouse aorta are interconnected by gap junctions made of connexin40 (Cx40) and connexin37 (Cx37), allowing the exchange of signaling molecules to coordinate their activity. Wild-type (Cx40(+/+)) and hypertensive Cx40-deficient mice (Cx40(-/-)), which also exhibit a marked decrease of Cx37 in the endothelium, were used to investigate the link between the expression of endothelial connexins (Cx40 and Cx37) and endothelial nitric oxide synthase (eNOS) expression and function in the mouse aorta. With the use of isometric tension measurements in aortic rings precontracted with U-46619, a stable thromboxane A(2) mimetic, we first demonstrate that ACh- and ATP-induced endothelium-dependent relaxations solely depend on NO release in both Cx40(+/+) and Cx40(-/-) mice, but are markedly weaker in Cx40(-/-) mice. Consistently, both basal and ACh- or ATP-induced NO production were decreased in the aorta of Cx40(-/-) mice. Altered relaxations and NO release from aorta of Cx40(-/-) mice were associated with lower expression levels of eNOS in the aortic endothelium of Cx40(-/-) mice. Using immunoprecipitation and in situ ligation assay, we further demonstrate that eNOS, Cx40, and Cx37 tightly interact with each other at intercellular junctions in the aortic endothelium of Cx40(+/+) mice, suggesting that the absence of Cx40 in association with altered Cx37 levels in endothelial cells from Cx40(-/-) mice participate to the decreased levels of eNOS. Altogether, our data suggest that the endothelial connexins may participate in the control of eNOS expression levels and function.

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Background: It is suggested that a low dose of valganciclovir can be equally effective than a standard dose for cytomegalovirus (CMV) prophylaxis after kidney transplantation. The aim of our study was to determine the ganciclovir exposure observed under a routine daily dosage of 450 mg valganciclovir in kidney transplant recipients with a wide range of renal function. Methods: In this prospective study, kidney transplant recipients with a GFR MDRD above 25 mL/min at risk for CMV (donor or recipient seropositive for CMV) received a dose of valganciclovir (450 mg daily) prophylaxis for 3 months. Ganciclovir levels at trough (Ctrough) and at peak (C3h) were measured monthly. Ganciclovir exposure (AUC0-24) was estimated using Bayesian non-linear mixed-effect modelling (NONMEM) and compared between 3 groups of patients according to their kidney function: GFRMDRD 26-39 mL/min (Group 1), GFRMDRD 40-59 mL/min (Group 2) and GFRMDRD 60-90 mL/min (Group 3). CMV DNAemia was assessed during and after prophylaxis using PCR. Results: Thirty-six patients received 450 mg daily of valganciclovir for 3 months. Median ganciclovir C3h was 3.9 mg/L (range: 1.3-7.1) and Ctrough was 0.4 mg/L (range 0.1-2.7). Median (range) AUC0-24 of ganciclovir was 59.3 mg.h/L (39.0-85.3) in Group 1 patients, 35.8 mg.h/L (24.9-55.8) in Group 2 patients and 29.6 mg.h/L (22.0- 43.2) in Group 3 patients (p<0.001). Anemia was more common in Group 1 patients compared to patients on the other groups (p=0.01). No differences in other adverse events according to ganciclovir exposure were observed. CMV DNAemia was not detected during prophylaxis. After discontinuing prophylaxis, CMV DNAemia was seen in 8/34 patients (23.5%) and 4/36 patients (11%) developed CMV disease. Conclusion: A routine dosage of valganciclovir achieved plasma levels of ganciclovir in patients with GFR>60 mL/min similar to those previously reported using oral ganciclovir. A daily dose of 450 mg valganciclovir appears to be acceptable for CMV prophylaxis in most kidney transplant recipients.

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C receptor type 1 (CR1, CD35) is present in a soluble form in plasma (sCR1). Soluble CR1 was measured with a specific ELISA assay in normal individuals and in patients with different diseases. The mean serum concentration of sCR1 in 31 normal donors was 31.4 +/- 7.8 ng/ml, and was identical in plasma. An increase in sCR1 was observed in 36 patients with end-stage renal failure on dialysis (54.8 +/- 11.7 ng/ml, p &lt; 0.0001), and in 22 patients with liver cirrhosis (158.3 +/- 49.9 ng/ml, p &lt; 0.0001). The mean sCR1 levels dropped from 181 +/- 62.7 to 52.1 +/- 24.0 ng/ml (p &lt; 0.001) in nine patients who underwent liver transplantation, and was 33.5 +/- 7.3 in 10 patients with functioning renal grafts, indicating that the increase in sCR1 was reversible. Soluble CR1 was elevated in some hematologic malignancies (&gt; 47 ng/ml), which included B cell lymphoma (12/19 patients), Hodgkin's lymphoma (4/4), and chronic myeloproliferative syndromes (4/5). By contrast, no increase was observed in acute myeloid or lymphoblastic leukemia (10) or myeloma (5). In two patients with chronic myeloproliferative syndromes, sCR1 decreased rapidly after chemotherapy. The mean concentration of sCR1 was not significantly modified in 181 HIV-infected patients at various stages of the disease (34.8 +/- 14.4 ng/ml), and in 13 patients with active SLE (38.3 +/- 19.6 ng/ml), although in both groups the number of CR1 was diminished on E. There was a weak but significant correlation between sCR1 and CR1 per E in HIV infection and SLE (r = 0.39, p &lt; 0.0001, and r = 0.60, p &lt; 0.03 respectively). In vitro, monocytes, lymphocytes, and neutrophils were found to release sCR1 into culture supernatants. In vivo, sCR1 was detected in the serum of SCID mice populated with human peripheral blood leukocytes. The sCR1 levels correlated with those of human IgG (r = 0.97, p &lt; 0.0001), suggesting synthesis of sCR1 by the transferred lymphocytes. The mechanisms underlining the increased levels of sCR1 and its biologic consequences remain to be defined.

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OBJECTIVE: This study examines the physiological impact of a glucose load on serum testosterone (T) levels in men with varying glucose tolerance (GT). DESIGN: Cross-sectional study. PATIENTS AND METHODS: 74 men (19-74 years, mean 51·4 ± 1·4 years) underwent a standard 75-g oral glucose tolerance test with blood sampling at 0, 30, 60, 90 and 120 min. Fasting serum glucose, insulin, total T (and calculated free T), LH, SHBG, leptin and cortisol were measured. RESULTS: 57% of the men had normal GT, 30% had impaired GT and 13% had newly diagnosed type 2 diabetes. Glucose ingestion was associated with a 25% decrease in mean T levels (delta = -4·2 ± 0·3 nm, P < 0·0001). T levels remained suppressed at 120 min compared with baseline (13·7 ± 0·6 vs 16·5 ± 0·7 nm, P < 0·0001) and did not differ across GT or BMI. Of the 66 men with normal T levels at baseline, 10 (15%) had levels that decreased to the hypogonadal range (<9·7 nm) at one or more time points. SHBG, LH and cortisol levels were unchanged. Leptin levels decreased from baseline at all time points (P < 0·0001). CONCLUSIONS: Glucose ingestion induces a significant reduction in total and free T levels in men, which is similar across the spectrum of glucose tolerance. This decrease in T appears to be because of a direct testicular defect, but the absence of compensatory changes in LH suggests an additional central component. Men found to have low nonfasting T levels should be re-evaluated in the fasting state.

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Empirical modeling of exposure levels has been popular for identifying exposure determinants in occupational hygiene. Traditional data-driven methods used to choose a model on which to base inferences have typically not accounted for the uncertainty linked to the process of selecting the final model. Several new approaches propose making statistical inferences from a set of plausible models rather than from a single model regarded as 'best'. This paper introduces the multimodel averaging approach described in the monograph by Burnham and Anderson. In their approach, a set of plausible models are defined a priori by taking into account the sample size and previous knowledge of variables influent on exposure levels. The Akaike information criterion is then calculated to evaluate the relative support of the data for each model, expressed as Akaike weight, to be interpreted as the probability of the model being the best approximating model given the model set. The model weights can then be used to rank models, quantify the evidence favoring one over another, perform multimodel prediction, estimate the relative influence of the potential predictors and estimate multimodel-averaged effects of determinants. The whole approach is illustrated with the analysis of a data set of 1500 volatile organic compound exposure levels collected by the Institute for work and health (Lausanne, Switzerland) over 20 years, each concentration having been divided by the relevant Swiss occupational exposure limit and log-transformed before analysis. Multimodel inference represents a promising procedure for modeling exposure levels that incorporates the notion that several models can be supported by the data and permits to evaluate to a certain extent model selection uncertainty, which is seldom mentioned in current practice.

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Objective: To produce age-related normograms for serum antimullerian hormone (AMH) level in infertile women without polycystic ovaries (non-PCO).Design: Retrospective cohort analysis.Setting: Fifteen academic reproductive centers.Patient(s): A total of 3,871 infertile women.Intervention(s): Blood sampling for AMH level.Main Outcome Measure(s): Serum AMH levels and correlation between age and different percentiles of AMH.Result(s): Age-related normograms for the 3rd, 10th, 25th, 50th, 75th, 90th, and 97th percentiles of AMH were produced. We found that the curves of AMH by age for the 3rd to 50th percentiles fit the model and appearance of linear relation, whereas the curves of >75th percentiles fit cubic relation. There were significant differences in AMH and FSH levels and in antral follicle count (AFC) among women aged 24-33 years, 34-38 years, and >= 39 years. Multivariate stepwise linear regression analysis of FSH, age, AFC, and the type of AMH kit as predictors of AMH level shows that all variables are independently associated with AMH level, in the following order: AFC, FSH, type of AMH kit, and age.Conclusion(s): Age-related normograms in non-PCO infertile women for the 3rd to 97th percentiles were produced. These normograms could provide a reference guide for the clinician to consult women with infertility. However, future validation with longitudinal data is still needed. (Fertil Steril (R) 2011; 95: 2359-63. (C) 2011 by American Society for Reproductive Medicine.)

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BACKGROUND: Hepatitis C virus (HCV) infection is a major cause of morbidity in HIV infected individuals. Coinfection with HIV is associated with diminished HCV-specific immune responses and higher HCV RNA levels. AIMS: To investigate whether long-term combination antiretroviral therapy (cART) restores HCV-specific T cell responses and improves the control of HCV replication. METHODS: T cell responses were evaluated longitudinally in 80 HIV/HCV coinfected individuals by ex vivo interferon-gamma-ELISpot responses to HCV core peptides, that predominantly stimulate CD4(+) T cells. HCV RNA levels were assessed by real-time PCR in 114 individuals. RESULTS: The proportion of individuals with detectable T cell responses to HCV core peptides was 19% before starting cART, 24% in the first year on cART and increased significantly to 45% and 49% after 33 and 70 months on cART (p=0.001). HCV-specific immune responses increased in individuals with chronic (+31%) and spontaneously cleared HCV infection (+30%). Median HCV RNA levels before starting cART were 6.5 log(10) IU/ml. During long-term cART, median HCV-RNA levels slightly decreased compared to pre-cART levels (-0.3 log10 IU/ml, p=0.02). CONCLUSIONS: Successful cART is associated with increasing cellular immune responses to HCV core peptides and with a slight long-term decrease in HCV RNA levels. These findings are in line with the favourable clinical effects of cART on the natural history of hepatitis C and with the current recommendation to start cART earlier in HCV/HIV coinfected individuals.

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In order to evaluate the effect of head injury in severely traumatized patients on the response of ACTH, GH, PRL, and TSH plasma levels, 36 patients were prospectively studied over 5 consecutive days following injury. They were divided into three groups: Group I, severe isolated head injury (n = 14); Group II, multiple injury combined with severe head injury (n = 12); Group III, multiple injury without head injury (n = 10). No significant trend was observed during the 5 consecutive days. The following changes in plasma levels were observed, compared to normal reference value (median values): ACTH was normal in the three groups; PRL was elevated in Group II and normal in the other groups; GH was elevated in all groups; TSH was elevated in Group III and reduced in Groups I and II. Intergroup comparisons showed significantly lower plasma levels for PRL (p less than 0.05) and TSH (p less than 0.01) in Groups I and II, i.e., head-injured patients, compared to Group III, i.e., traumatized patients without head injury. A relationship was observed between the severity of head injury, as expressed by Glasgow Coma Score, intracranial pressure levels, outcome, and TSH and PRL levels.

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BACKGROUND: Prediction of clinical course and outcome after severe traumatic brain injury (TBI) is important. OBJECTIVE: To examine whether clinical scales (Glasgow Coma Scale [GCS], Injury Severity Score [ISS], and Acute Physiology and Chronic Health Evaluation II [APACHE II]) or radiographic scales based on admission computed tomography (Marshall and Rotterdam) were associated with intensive care unit (ICU) physiology (intracranial pressure [ICP], brain tissue oxygen tension [PbtO2]), and clinical outcome after severe TBI. METHODS: One hundred one patients (median age, 41.0 years; interquartile range [26-55]) with severe TBI who had ICP and PbtO2 monitoring were identified. The relationship between admission GCS, ISS, APACHE II, Marshall and Rotterdam scores and ICP, PbtO2, and outcome was examined by using mixed-effects models and logistic regression. RESULTS: Median (25%-75% interquartile range) admission GCS and APACHE II without GCS scores were 3.0 (3-7) and 11.0 (8-13), respectively. Marshall and Rotterdam scores were 3.0 (3-5) and 4.0 (4-5). Mean ICP and PbtO2 during the patients' ICU course were 15.5 ± 10.7 mm Hg and 29.9 ± 10.8 mm Hg, respectively. Three-month mortality was 37.6%. Admission GCS was not associated with mortality. APACHE II (P = .003), APACHE-non-GCS (P = .004), Marshall (P < .001), and Rotterdam scores (P < .001) were associated with mortality. No relationship between GCS, ISS, Marshall, or Rotterdam scores and subsequent ICP or PbtO2 was observed. The APACHE II score was inversely associated with median PbtO2 (P = .03) and minimum PbtO2 (P = .008) and had a stronger correlation with amount of time of reduced PbtO2. CONCLUSION: Following severe TBI, factors associated with outcome may not always predict a patient's ICU course and, in particular, intracranial physiology.

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BACKGROUND: Copeptin, a surrogate marker for arginin vasopressin production, is evaluated as an osmo-dependent stress and inflammatory biomarker in different diseases. We investigated copeptin during the menstrual cycle and its relationship to sex hormones, markers of subclinical inflammation and estimates of body fluid. METHODS: In 15 healthy women with regular menstrual cycles, blood was drawn on fifteen defined days of their menstrual cycle and was assayed for copeptin, progesterone, estradiol, luteinizing hormone, high-sensitive C-reactive protein, tumor necrosis factor-alpha and procalcitonin. Symptoms of fluid retention were assessed on each visit, and bio impedance analysis was measured thrice to estimate body fluid changes. Mixed linear model analysis was performed to assess the changes of copeptin across the menstrual cycle and the relationship of sex hormones, markers of subclinical inflammation and estimates of body fluid with copeptin. RESULTS: Copeptin levels did not significantly change during the menstrual cycle (p = 0.16). Throughout the menstrual cycle, changes in estradiol (p = 0.002) and in the physical premenstrual symptom score (p = 0.01) were positively related to copeptin, but changes in other sex hormones, in markers of subclinical inflammation or in bio impedance analysis-estimated body fluid were not (all p = ns). CONCLUSION: Although changes in estradiol and the physical premenstrual symptom score appear to be related to copeptin changes, copeptin does not significantly change during the menstrual cycle.

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A wide variation in patient exposure has been observed in interventional radiology and cardiology. The purpose of this study was to investigate the patient dose from fluoroscopy-guided procedures performed in non-academic centres when compared with academic centres. Four procedures (coronary angiography, percutaneous coronary intervention, angiography of the lower limbs and percutaneous transluminal angioplasty of the lower limbs) were evaluated. Data on the dose-area product, fluoroscopy time and number of images for 1000 procedures were obtained from 23 non-academic centres and compared with data from 5 academic centres. No differences were found for cardiology procedures performed in non-academic centres versus academic ones. However, significantly lower doses were delivered to patients for procedures of the lower limbs when they were performed in non-academic centres. This may be due to more complex procedures performed in the academic centres. Comparison between the centres showed a great variation in the patient dose for these lower limb procedures.

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OBJECTIVE: The associations between inflammation, diabetes and insulin resistance remain controversial. Hence, we assessed the associations between diabetes, insulin resistance (using HOMA-IR) and metabolic syndrome with the inflammatory markers high-sensitive C-reactive protein (hs-CRP), interleukin-1 beta (IL-1β), interleukin-6 (IL-6) and tumour necrosis factor-α (TNF-α). DESIGN: Cross-sectional study. PARTICIPANTS: Two thousand eight hundred and eighty-four men and 3201 women, aged 35-75, participated in this study. METHODS: C-reactive protein was assessed by immunoassay and cytokines by multiplexed flow cytometric assay. In a subgroup of 532 participants, an oral glucose tolerance test (OGTT) was performed to screen for impaired glucose tolerance (IGT). RESULTS: IL-6, TNF-α and hs-CRP were significantly and positively correlated with fasting plasma glucose (FPG), insulin and HOMA-IR. Participants with diabetes had higher IL-6, TNF-α and hs-CRP levels than participants without diabetes; this difference persisted for hs-CRP after multivariate adjustment. Participants with metabolic syndrome had increased IL-6, TNF-α and hs-CRP levels; these differences persisted after multivariate adjustment. Participants in the highest quartile of HOMA-IR had increased IL-6, TNF-α and hs-CRP levels; these differences persisted for TNF-α and hs-CRP after multivariate adjustment. No association was found between IL-1β levels and all diabetes and insulin resistance markers studied. Finally, participants with IGT had higher hs-CRP levels than participants with a normal OGTT, but this difference disappeared after controlling for body mass index (BMI). CONCLUSION: We found that subjects with diabetes, metabolic syndrome and increased insulin resistance had increased levels of IL6, TNF-α and hs-CRP, while no association was found with IL-1β. The increased inflammatory state of subjects with IGT is partially explained by increased BMI.

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OBJECTIVES: Darunavir is a protease inhibitor that is administered with low-dose ritonavir to enhance its bioavailability. It is prescribed at standard dosage regimens of 600/100 mg twice daily in treatment-experienced patients and 800/100 mg once daily in naive patients. A population pharmacokinetic approach was used to characterize the pharmacokinetics of both drugs and their interaction in a cohort of unselected patients and to compare darunavir exposure expected under alternative dosage regimens. METHODS: The study population included 105 HIV-infected individuals who provided darunavir and ritonavir plasma concentrations. Firstly, a population pharmacokinetic analysis for darunavir and ritonavir was conducted, with inclusion of patients' demographic, clinical and genetic characteristics as potential covariates (NONMEM(®)). Then, the interaction between darunavir and ritonavir was studied while incorporating levels of both drugs into different inhibitory models. Finally, model-based simulations were performed to compare trough concentrations (Cmin) between the recommended dosage regimen and alternative combinations of darunavir and ritonavir. RESULTS: A one-compartment model with first-order absorption adequately characterized darunavir and ritonavir pharmacokinetics. The between-subject variability in both compounds was important [coefficient of variation (CV%) 34% and 47% for darunavir and ritonavir clearance, respectively]. Lopinavir and ritonavir exposure (AUC) affected darunavir clearance, while body weight and darunavir AUC influenced ritonavir elimination. None of the tested genetic variants showed any influence on darunavir or ritonavir pharmacokinetics. The simulations predicted darunavir Cmin much higher than the IC50 thresholds for wild-type and protease inhibitor-resistant HIV-1 strains (55 and 550 ng/mL, respectively) under standard dosing in >98% of experienced and naive patients. Alternative regimens of darunavir/ritonavir 1200/100 or 1200/200 mg once daily also had predicted adequate Cmin (>550 ng/mL) in 84% and 93% of patients, respectively. Reduction of darunavir/ritonavir dosage to 600/50 mg twice daily led to a 23% reduction in average Cmin, still with only 3.8% of patients having concentrations below the IC50 for resistant strains. CONCLUSIONS: The important variability in darunavir and ritonavir pharmacokinetics is poorly explained by clinical covariates and genetic influences. In experienced patients, treatment simplification strategies guided by drug level measurements and adherence monitoring could be proposed.

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Objectives: Gentamicin is among the most commonly prescribed antibiotics in newborns, but large interindividual variability in exposure levels exists. Based on a population pharmacokinetic analysis of a cohort of unselected neonates, we aimed to validate current dosing recommendations from a recent reference guideline (Neofax®). Methods: From 3039 concentrations collected in 994 preterm (median gestational age 32.3 weeks, range 24.2-36.5) and 455 term newborns, treated at the University Hospital of Lausanne between 2006 and 2011, a population pharmacokinetic analysis was performed with NONMEM®. Model-based simulations were used to assess the ability of dosing regimens to bring concentrations into targets: trough ≤ 1mg/L and peak ~ 8mg/L. Results: A two-compartment model best characterized gentamicin pharmacokinetics. Model parameters are presented in the table. Body weight, gestational age and postnatal age positively influence clearance, which decreases under dopamine administration. Body weight and gestational age influence the distribution volume. Model based simulations confirm that preterm infants need doses superior to 4 mg/kg, and extended dosage intervals, up to 48 hours for very preterm newborns, whereas most term newborns would achieve adequate exposure under 4 mg/kg q. 24 h. More than 90% of neonates would achieve trough concentrations below 2 mg/L and peaks above 6 mg/L following most recent guidelines. Conclusions: Simulated gentamicin exposure demonstrates good accordance with recent dosing recommendations for target concentration achievement.