Pharmacokinetic-Pharmacodynamic Modeling in Pediatric Drug Development, and the Importance of Standardized Scaling of Clearance.

Pharmacokinetic/pharmacodynamic (PKPD) modeling is important in the design and conduct of clinical pharmacology research in children. During drug development, PKPD modeling and simulation should underpin rational trial design and facilitate extrapolation to investigate efficacy and safety. The application of PKPD modeling to optimize dosing recommendations and therapeutic drug monitoring is also increasing, and PKPD model-based dose individualization will become a core feature of personalized medicine. Following extensive progress on pediatric PK modeling, a greater emphasis now needs to be placed on PD modeling to understand age-related changes in drug effects. This paper discusses the principles of PKPD modeling in the context of pediatric drug development, summarizing how important PK parameters, such as clearance (CL), are scaled with size and age, and highlights a standardized method for CL scaling in children. One standard scaling method would facilitate comparison of PK parameters across multiple studies, thus increasing the utility of existing PK models and facilitating optimal design of new studies

Extended-spectrum β-lactamase producing E. coli in urinary tract infections: A two-center, cross-sectional study of prevalence, genotypes and risk factors in Amman, Jordan

Background: To determine the prevalence, phenotypes, and genotypes of extended spectrum β-lactamase (ESBL)-producing Escherichia coli (E. coli) among patients with urinary tract infection along with identifying the associated risk factors. Methods: A cross-sectional study was conducted at two tertiary hospitals in Amman, Jordan between June and October, 2016. One hundred twenty one E. coli isolates from hospitalized patients with urinary tract infection were phenotypically assessed for ESBL production using the double disc diffusion test. Positive isolates to ESBL production were further genotyped using multiplex PCR. A nested case-control study was used to determine the independent risk factors. Results: ESBL-producing E. coli were found in 75/121 (62%) isolates. Molecular genotyping demonstrated that CTX-M group1 (42.7%) predominated followed by combination of SHV and CTX-M group1 (20%). In the regression model, previous hospitalization and use of urinary catheter were identified as independent risk factors for ESBL-producing E. coli infections. Conclusion: We report a high prevalence of ESBL-producing E. coli which is in concordance with other studies from developing countries. Additionally, CTX-M group1 has emerged as the predominant ESBL produced by E. coli, which is consistent with reported results throughout the world. Independent risk factors to UTI infections due to ESBL-producing E. coli include previous hospitalization and use of urinary catheter. Keywords: E. coli, ESBL, CTX-M group 1, Urinary tract infection, Risk factor

Attitudes, motivators, and barriers toward influenza vaccination for children: a study from a conflict-ridden country

Abstract Background Despite the increased recommendations for influenza vaccination, particularly among high-risk groups such as young children, Yemen lacks an influenza vaccination program, and the influenza vaccine is not included in the national immunization regime. This is exacerbated by the country’s fragile infrastructure, as well as the devastating consequences of the ongoing conflict, which include child undernutrition and strained healthcare resources. Thus, the objective of the current study is to assess the public attitudes and perceptions toward vaccinating children against influenza in Yemen. Methods A cross-sectional study was conducted by distributing a validated survey questionnaire to potential participants using convenience sampling. Descriptive statistics were used to summarize sociodemographic data, knowledge of influenza vaccines, and attitudes and perceptions regarding vaccinating children against influenza. Logistic regression analysis was employed to identify associations between independent variables and the acceptance of vaccines for children. Results A total of 853 eligible individuals, parents and non-parents, successfully completed the survey. The uptake of the influenza vaccine among the participants was notably low as the majority (69.2%) had not previously received the vaccine, although the majority expressed a willingness to get vaccinated in the future (59.4%). The majority (68.5%) were willing to vaccinate children. The largest percentage of the participants who expressed hesitancy toward children’s vaccination cited multiple reasons to reject the vaccine (39.7%), with concerns regarding the safety of the vaccine being the predominant barrier to its acceptance for children (29.6%). On the other hand, motivating factors for vaccinating children included the validation of the vaccine’s safety and efficacy, endorsement of the vaccine by the government and physicians, integration of the vaccine into the national immunization program, and the provision of the vaccine free of charge and through schools. Significant predictors for vaccine acceptance in children included male gender, knowledge of the protective effect of the influenza vaccine, previous receipt of the vaccine, and a willingness to receive the vaccine in the future. Conclusions The study highlights the need for educational health campaigns to raise awareness and remove misconceptions regarding influenza and the role, benefits, and availability of its vaccine. These findings can serve as a robust foundation for the future design and implementation of an influenza vaccination program for children in Yemen

The prevalence and clinical seriousness of medication discrepancies identified upon hospital admission of pediatric patients

Abstract Background Medication discrepancies are seen frequently in hospital setting upon admission or discharge. Medication Reconciliation service is a practice designed to ensure that patients’ medications are ordered in a correct manner upon hospital admission, thus reducing the risk of having medication discrepancies. This study aimed to determine the prevalence of medication discrepancies and their clinical seriousness in pediatric patients at the time of hospital admission. Methods A prevalence cross-sectional study was conducted at the pediatric departement at the Jordan University hospital between March–May 2018. During the study period, 100 pediatric patients were enrolled using a convenience sampling method. Patients’ medical records were reviewed by two clinical pharmacist-reserachers to obtain patients' demographic, medical, and admission medication information. All parents were interviewed to obtain information regarding their children’s Best Possible Medication History (BPMH). Following data collection, differences between patient’s current admission medications and the BPMH were identified as medication discrepancies, and then they were classified into either undocumented intentional or unintentional discrepancies. Results Among the 100 medication records reviewed, 13.0% (13 out of 100) contained at least one unintentional discrepancy, with the majority (n = 11, 84.6%) being classified to be associated with mild potential harm to patients. Of those discrepancies, 8 were omission of medications (61.5%) and 5 were addition of unnecessary medication (38.5%). On the other hand, 35.0% (35 out of 100) of medication records contained at least one intentional undocumented discrepancy. Conclusions This study revealed that unintentional medication discrepancies exist at the time of hospital admission for pediatric patients but with low proportion. The low proportion of medication discrepancies might be explained by the recent implementation of medication reconciliation service at the studied hospital. Also, intentional undocumented discrepancies were common, which may carry a potential harm to such vulnerable population at discharge. These data may inform the need for a strict policies to regulate medication documentation, thus decreasing the possibilities of medication errors

Total Dissolved Salt Prediction Using Neurocomputing Models: Case Study of Gypsum Soil Within Iraq Region

Quantification of the soil physicochemical properties is one of the essential process in the field of soil geo-science. In the current research, three types of machine learning (ML) models including support vector machine (SVM), random forest (RF), and gradient boosted decision tree (GBDT) were developed for Total Dissolved Salt (TDS) prediction over several locations in Iraq region. Various physicochemical soil properties were used as predictors for the TDS prediction. Four modeling scenarios are constructed based on the types of the associated soil input variables properties. The applied ML models were analyzed and discussed based on several statistical measures and graphical presentations. Based on the correlation analysis; Gypsum concentration, Sulfur trioxide (SO3), Chloride (Cl), and organic matter (OR) were the essential soil properties for the TDS concentration influence. The prediction results indicated that incorporating all the types of input variables including chemical, soil consistency limits, and soil sieve analysis attained the best prediction process. In quantitative terms, the SVM model attained the maximum coefficient of determination (R-2 = 0.849) and minimum root mean square error (RMSE = 3.882). Overall, the development of the ML models for the TDS of soil prediction provided a robust and reliable methodology that contributes to the soil geoscience field