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2.
J Clin Pharmacol ; 64(7): 860-865, 2024 Jul.
Article in English | MEDLINE | ID: mdl-38497326

ABSTRACT

Daptomycin is an antibiotic with Gram-positive activity, including methicillin-resistant Staphylococcus aureus, for which optimal pediatric dosing is unknown. This study aimed to evaluate daptomycin exposures achieved with package label dosing and to identify dosing regimens necessary to enhance efficacy and minimize toxicity in children with S. aureus bacteremia. Monte Carlo simulations were performed to determine probability of target attainment (PTA) for six pediatric age cohorts. Area under the curve to minimum inhibitory concentration ratio (AUC0-24:MIC) ≥666 was used to determine the PTA for efficacy (PTAE). Minimum concentration (Cmin) ≥24.3 mg/L determined the PTA for toxicity (PTAT). Acceptable dosing regimens were those which achieved the combined target of ≥90% PTAE and ≤5% PTAT. Package label dosing of daptomycin yielded insufficient efficacy with only 26.3% PTAE in children 13-24 months, 39.5% PTAE in children 2-6 years, 30.1% PTAE in children 7-11 years, and 50.1% PTAE in adolescents ≥12 years. To achieve the combined efficacy and safety target, doses of 18-24 mg/kg in children 3-12 months, 20-24 mg/kg in children 13-24 months, 19-24 mg/kg in children 2-6 years, 17-19 mg/kg in children 7-11 years, and 10-14 mg/kg in adolescents ≥12 years are necessary. Package label dosing resulted in suboptimal exposure for the majority of pediatric patients in all age groups evaluated. If targeting validated efficacy and safety endpoints, daily daptomycin doses of at least 20 mg/kg in children ≤6 years, 17 mg/kg in children 7-11 years, and 10 mg/kg in adolescents ≥12 years are necessary. Clinical studies evaluating these higher doses are needed.


Subject(s)
Anti-Bacterial Agents , Bacteremia , Daptomycin , Microbial Sensitivity Tests , Monte Carlo Method , Staphylococcal Infections , Humans , Daptomycin/pharmacokinetics , Daptomycin/administration & dosage , Daptomycin/pharmacology , Child , Anti-Bacterial Agents/pharmacokinetics , Anti-Bacterial Agents/administration & dosage , Anti-Bacterial Agents/adverse effects , Anti-Bacterial Agents/pharmacology , Child, Preschool , Adolescent , Infant , Bacteremia/drug therapy , Bacteremia/microbiology , Staphylococcal Infections/drug therapy , Male , Female , Dose-Response Relationship, Drug , Staphylococcus aureus/drug effects , Area Under Curve , Methicillin-Resistant Staphylococcus aureus/drug effects
3.
PLoS Negl Trop Dis ; 14(10): e0008677, 2020 10.
Article in English | MEDLINE | ID: mdl-33035209

ABSTRACT

BACKGROUND: Diarrhea is one of the leading causes of childhood morbidity and mortality in lower- and middle-income countries. In such settings, access to laboratory diagnostics are often limited, and decisions for use of antimicrobials often empiric. Clinical predictors are a potential non-laboratory method to more accurately assess diarrheal etiology, the knowledge of which could improve management of pediatric diarrhea. METHODS: We used clinical and quantitative molecular etiologic data from the Global Enteric Multicenter Study (GEMS), a prospective, case-control study, to develop predictive models for the etiology of diarrhea. Using random forests, we screened the available variables and then assessed the performance of predictions from random forest regression models and logistic regression models using 5-fold cross-validation. RESULTS: We identified 1049 cases where a virus was the only etiology, and developed predictive models against 2317 cases where the etiology was known but non-viral (bacterial, protozoal, or mixed). Variables predictive of a viral etiology included lower age, a dry and cold season, increased height-for-age z-score (HAZ), lack of bloody diarrhea, and presence of vomiting. Cross-validation suggests an AUC of 0.825 can be achieved with a parsimonious model of 5 variables, achieving a specificity of 0.85, a sensitivity of 0.59, a NPV of 0.82 and a PPV of 0.64. CONCLUSION: Predictors of the etiology of pediatric diarrhea can be used by providers in low-resource settings to inform clinical decision-making. The use of non-laboratory methods to diagnose viral causes of diarrhea could be a step towards reducing inappropriate antibiotic prescription worldwide.


Subject(s)
Bacterial Infections/complications , Diarrhea/etiology , Virus Diseases/complications , Bacterial Infections/microbiology , Case-Control Studies , Data Interpretation, Statistical , Humans , Infant , Models, Biological , Prospective Studies , Virus Diseases/virology
4.
Biomech Model Mechanobiol ; 11(3-4): 355-61, 2012 Mar.
Article in English | MEDLINE | ID: mdl-21604147

ABSTRACT

Soft tissues, such as tendons, skin, arteries, or lung, are constantly subject to mechanical stresses in vivo. None more so than the aortic heart valve that experiences an array of forces including shear stress, cyclic pressure, strain, and flexion. Anisotropic biaxial cyclic stretch maintains valve homeostasis; however, abnormal forces are implicated in disease progression. The response of the valve endothelium to deviations from physiological levels has not been fully characterized. Here, we show the design and validation of a novel stretch apparatus capable of applying biaxial stretch to viable heart valve tissue, while simultaneously allowing for live en face endothelial cell imaging via confocal laser scanning microscopy (CLSM). Real-time imaging of tissue is possible while undergoing highly characterized mechanical conditions and maintaining the native extracellular matrix. Thus, it provides significant advantages over traditional cell culture or in vivo animal models. Planar biaxial tissue stretching with simultaneous live cell imaging could prove useful in studying the mechanobiology of any soft tissue.


Subject(s)
Aortic Valve/pathology , Heart Valve Prosthesis , Microscopy, Confocal/methods , Tissue Engineering/methods , Anisotropy , Biomechanical Phenomena , Bioreactors , Chemistry, Physical/methods , Endothelium/pathology , Equipment Design , Glucose/chemistry , Humans , Hydrogen-Ion Concentration , Imaging, Three-Dimensional/methods , Prosthesis Design , Stress, Mechanical , Time Factors
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