ORCID Profile
0000-0002-0703-9114
Current Organisations
University of Oxford
,
Oxford University Hospitals NHS Foundation Trust
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Publisher: American Society for Microbiology
Date: 10-2017
DOI: 10.1128/AAC.00707-17
Abstract: The aim of this study was to develop a population pharmacokinetic (PK) model for teicoplanin across childhood age ranges to be used as Bayesian prior information in the software constructed for in idualized therapy. We developed a nonparametric population model fitted to PK data from neonates, infants, and older children. We then implemented this model in the BestDose multiple-model Bayesian adaptive control algorithm to show its clinical utility. It was used to predict the dosages required to achieve optimal teicoplanin predose targets (15 mg/liter) from day 3 of therapy. We performed in idual simulations for an infant and a child from the original population, who provided early first dosing interval concentration-time data. An allometric model that used weight as a measure of size and that also incorporated renal function using the estimated glomerular filtration rate (eGFR), or the ratio of postnatal age (PNA) to serum creatinine concentration (SCr) for infants months old, best described the data. The median population PK parameters were as follows: elimination rate constant (Ke) = 0.03 · (wt/70) −0.25 · Renal (h −1 ) V = 19.5 · (wt/70) (liters) Renal = eGFR 0.07 (ml/min/1.73 m 2 ), or Renal = PNA/SCr (μmol/liter). Increased teicoplanin dosages and alternative administration techniques (extended infusions and fractionated multiple dosing) were required in order to achieve the targets safely by day 3 in simulated cases. The software was able to predict in idual measured concentrations and the dosages and administration techniques required to achieve the desired target concentrations early in therapy. Prospective evaluation is now needed in order to ensure that this in idualized teicoplanin therapy approach is applicable in the clinical setting. (This study has been registered in the European Union Clinical Trials Register under EudraCT no. 2012-005738-12.)
Publisher: Oxford University Press (OUP)
Date: 19-08-2016
DOI: 10.1093/JAC/DKW295
Publisher: Elsevier BV
Date: 06-2007
DOI: 10.1016/J.CLIM.2007.03.003
Abstract: Evidence suggests that Toll-like receptor 4 (TLR4) contributes to immune recognition of respiratory syncytial virus (RSV). The TLR4 gene harbours a polymorphism-Asp299Gly-previously associated with reduced TLR4 signalling. To understand of how host genetic variation influences the outcome of RSV infection in children, we examined the association between the TLR4 299Gly allele and severe RSV disease. By genotyping 236 children with RSV infection and 219 healthy controls we found no association between the risk of severe RSV infection and Asp299Gly polymorphisms (P>0.05), and we demonstrate that the TLR4 Asp299Gly genotype does not influence susceptibility to either RSV serotype A or B (P>0.05). Finally, examining the functional impact of the TLR4 Asp299Gly polymorphism (n=58), we demonstrate that proinflammatory cytokine production following TLR4 activation was indistinguishable between homozygous (Asp/Asp) and heterozygous (Asp/Gly) subjects. We conclude that the Asp299Gly TLR4 polymorphism does not alter receptor function and does not influence the risk of severe RSV infection.
Publisher: Cold Spring Harbor Laboratory
Date: 31-07-2023
DOI: 10.1101/2023.07.28.23293197
Abstract: Multisystem inflammatory syndrome in children (MIS-C) is a rare but serious hyperinflammatory complication following infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The mechanisms underpinning the pathophysiology of MIS-C are poorly understood. Moreover, clinically distinguishing MIS-C from other childhood infectious and inflammatory conditions, such as Kawasaki Disease (KD) or severe bacterial and viral infections is challenging due to overlapping clinical and laboratory features. We aimed to determine a set of plasma protein biomarkers that could discriminate MIS-C from those other diseases. Seven candidate protein biomarkers for MIS-C were selected based on literature and from whole blood RNA-Sequencing data from patients with MIS-C and other diseases. Plasma concentrations of ARG1, CCL20, CD163, CORIN, CXCL9, PCSK9 and ADAMTS2 were quantified in MIS-C (n=22), KD (n=23), definite bacterial (DB n=28) and viral (DV, n=27) disease, and healthy controls (n=8). Logistic regression models were used to determine the discriminatory ability of in idual proteins and protein combinations to identify MIS-C, and association with severity of illness. Plasma levels of CD163, CXCL9, and PCSK9 were significantly elevated in MIS-C with a combined AUC of 86% (95% CI: 76.8%-95.1%) for discriminating MIS-C from other childhood diseases. Lower ARG1 and CORIN plasma levels were significantly associated with severe MIS-C cases requiring oxygen, inotropes or with shock. Our findings demonstrate the feasibility of a host protein biomarker signature for MIS-C and may provide new insight into its pathophysiology.
Publisher: American Academy of Pediatrics (AAP)
Date: 08-2017
Abstract: Improving the diagnosis of serious bacterial infections (SBIs) in the children’s emergency department is a clinical priority. Early recognition reduces morbidity and mortality, and supporting clinicians in ruling out SBIs may limit unnecessary admissions and antibiotic use. A prospective, diagnostic accuracy study of clinical and biomarker variables in the diagnosis of SBIs (pneumonia or other SBI) in febrile children & years old. A diagnostic model was derived by using multinomial logistic regression and internally validated. External validation of a published model was undertaken, followed by model updating and extension by the inclusion of procalcitonin and resistin. There were 1101 children studied, of whom 264 had an SBI. A diagnostic model discriminated well between pneumonia and no SBI (concordance statistic 0.84, 95% confidence interval 0.78–0.90) and between other SBIs and no SBI (0.77, 95% confidence interval 0.71–0.83) on internal validation. A published model discriminated well on external validation. Model updating yielded good calibration with good performance at both high-risk (positive likelihood ratios: 6.46 and 5.13 for pneumonia and other SBI, respectively) and low-risk (negative likelihood ratios: 0.16 and 0.13, respectively) thresholds. Extending the model with procalcitonin and resistin yielded improvements in discrimination. Diagnostic models discriminated well between pneumonia, other SBIs, and no SBI in febrile children in the emergency department. Improvements in the classification of nonevents have the potential to reduce unnecessary hospital admissions and improve antibiotic prescribing. The benefits of this improved risk prediction should be further evaluated in robust impact studies.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 11-11-2021
Publisher: American Society for Microbiology
Date: 11-2014
DOI: 10.1128/AAC.03685-14
Abstract: Teicoplanin is frequently administered to treat Gram-positive infections in pediatric patients. However, not enough is known about the pharmacokinetics (PK) of teicoplanin in children to justify the optimal dosing regimen. The aim of this study was to determine the population PK of teicoplanin in children and evaluate the current dosage regimens. A PK hospital-based study was conducted. Current dosage recommendations were used for children up to 16 years of age. Thirty-nine children were recruited. Serum s les were collected at the first dose interval (1, 3, 6, and 24 h) and at steady state. A standard 2-compartment PK model was developed, followed by structural models that incorporated weight. Weight was allowed to affect clearance (CL) using linear and allometric scaling terms. The linear model best accounted for the observed data and was subsequently chosen for Monte Carlo simulations. The PK parameter medians/means (standard deviation [SD]) were as follows: CL, [0.019/0.023 (0.01)] × weight liters/h/kg of body weight volume, 2.282/4.138 liters (4.14 liters) first-order rate constant from the central to peripheral compartment ( K cp ), 0.474/3.876 h −1 (8.16 h −1 ) and first-order rate constant from peripheral to central compartment ( K pc ), 0.292/3.994 h −1 (8.93 h −1 ). The percentage of patients with a minimum concentration of drug in serum ( C min ) of mg/liter was 53.85%. The median/mean (SD) total population area under the concentration-time curve (AUC) was 619/527.05 mg · h/liter (166.03 mg · h/liter). Based on Monte Carlo simulations, only 30.04% (median AUC, 507.04 mg · h/liter), 44.88% (494.1 mg · h/liter), and 60.54% (452.03 mg · h/liter) of patients weighing 50, 25, and 10 kg, respectively, attained trough concentrations of mg/liter by day 4 of treatment. The teicoplanin population PK is highly variable in children, with a wider AUC distribution spread than for adults. Therapeutic drug monitoring should be a routine requirement to minimize suboptimal concentrations. IMPORTANCE (This trial has been registered in the European Clinical Trials Database Registry [EudraCT] under registration number 2012-005738-12.)
Publisher: Springer Science and Business Media LLC
Date: 27-11-2019
DOI: 10.1038/S41598-019-53721-1
Abstract: Fever is the most common reason that children present to Emergency Departments. Clinical signs and symptoms suggestive of bacterial infection are often non-specific, and there is no definitive test for the accurate diagnosis of infection. The ‘omics’ approaches to identifying biomarkers from the host-response to bacterial infection are promising. In this study, lipidomic analysis was carried out with plasma s les obtained from febrile children with confirmed bacterial infection (n = 20) and confirmed viral infection (n = 20). We show for the first time that bacterial and viral infection produces distinct profile in the host lipidome. Some species of glycerophosphoinositol, sphingomyelin, lysophosphatidylcholine and cholesterol sulfate were higher in the confirmed virus infected group, while some species of fatty acids, glycerophosphocholine, glycerophosphoserine, lactosylceramide and bilirubin were lower in the confirmed virus infected group when compared with confirmed bacterial infected group. A combination of three lipids achieved an area under the receiver operating characteristic (ROC) curve of 0.911 (95% CI 0.81 to 0.98). This pilot study demonstrates the potential of metabolic biomarkers to assist clinicians in distinguishing bacterial from viral infection in febrile children, to facilitate effective clinical management and to the limit inappropriate use of antibiotics.
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: Belgium
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Stéphane Paulus.