Creation of a Multicenter Pediatric Inpatient Data Repository Derived from Electronic Health Records

Characterizing Enoxaparin's Population Pharmacokinetics to Guide Dose Individualization in the Pediatric Population

BACKGROUND AND OBJECTIVE

Pediatric dosing of enoxaparin was derived based on extrapolation of the adult therapeutic range to children. However, a large fraction of children do not achieve therapeutic anticoagulation with initial dosing. We aim to use real-world anti-Xa data obtained from children receiving enoxaparin per standard of care to characterize the population pharmacokinetics (PopPK).Author names: Please confirm if the author names are presented accurately and in the correct sequence (given name, middle name/initial, family name). Also, kindly confirm the details in the metadata are correct.The author names are accurately presented and the metadata are correct.  METHODS: A PopPK analysis was performed using NONMEM, and a stepwise covariate modeling approach was applied for the covariate selection. The final PopPK model, developed with data from 1293 patients ranging in age from 1 day to 18 years, was used to simulate enoxaparin subcutaneous dosing for prophylaxis and treatment based on total body weight (0-18 years, TBW) or fat-free mass (2-18 years, FFM). Simulated exposures in children with obesity (body mass index percentile ≥95th percentile) were compared with those without obesity.

RESULTS

A linear, one-compartment PopPK model that included allometric scaling using TBW (<2 years) or FFM (≥2 years) characterized the enoxaparin pharmacokinetic data. In addition, serum creatinine was identified as a significant covariate influencing clearance. Simulations indicated that in patients aged <2 years, the recommended 1.5 mg/kg TBW-based dosing achieves therapeutic simulated concentrations. In pediatric patients aged ≥2 years, the recommended 1.0 mg/kg dose resulted in exposures more comparable in children with and without obesity when FFM weight-based dosing was applied.

CONCLUSION

Using real-world data and PopPK modeling, enoxaparin's pharmacokinetics were characterized in pediatric patients. Using FFM and twice-daily dosing might reduce the risk of overdosing, especially in children with obesity.

A point-of-care pharmacokinetic/pharmacodynamic trial in critically ill children: Study design and feasibility

Background

High-quality, efficient, pharmacokinetic (PK), pharmacodynamic (PD), and safety studies in children are needed. Point-of-care trials in adults have facilitated clinical trial participation for patients and providers, minimized the disruption of clinical workflow, and capitalized on routine data collection. The feasibility and value of point-of-care trials to study PK/PD in children are unknown, but appear promising. The Opportunistic PK/PD Trial in Critically Ill Children with Heart Disease (OPTIC) is a programmatic point-of-care approach to PK/PD trials in critically ill children that seeks to overcome barriers of traditional pediatric PK/PD studies to generate safety, efficacy, PK, and PD data across multiple medications, ages, and disease processes.

Methods

This prospective, open-label, non-randomized point-of-care trial will characterize the PK/PD and safety of multiple drugs given per routine care to critically ill children with heart disease using opportunistic and scavenged biospecimen samples and data collected from the electronic health record. OPTIC has one informed consent form with drug-specific appendices, streamlining study structure and institutional review board approval. OPTIC capitalizes on routine data collection through multiple data sources that automatically capture demographics, medications, laboratory values, vital signs, flowsheets, and other clinical data. This innovative automatic data collection minimizes the burden of data collection and facilitates trial conduct. Data will be validated across sources to ensure accuracy of dataset variables.

Discussion

OPTIC's point-of-care trial design and automated data acquisition via the electronic health record may provide a mechanism for conducting minimal risk, minimal burden, high efficiency trials and support drug development in historically understudied patient populations.

Trial registration

clinicaltrials.gov number: NCT05055830. Registered on September 24, 2021.

Association between simulated ketamine exposures and oxygen saturations in children

Aim

We performed a real-world data analysis to evaluate the relationship between simulated ketamine exposures and oxygen desaturation in children.

Materials & methods

A previously developed population pharmacokinetic model was used to simulate exposures and evaluate target attainment, as well as the association with oxygen desaturation in children ≤17 years treated with intravenous ketamine.

Results

In 2022 children, there was no significant association between simulated plasma ketamine concentrations and oxygen saturation; however, a higher cumulative area under the curve was associated with increased odds of progression to significant desaturation (<85%), though magnitude of effect was small.

Conclusion

By leveraging a population pharmacokinetic model and real-world data, we confirmed there is no relationship between simulated ketamine plasma concentration and oxygen desaturation.

Implementation of a Regional Standardised Model for Perinatal Electronic Medical Records

Electronic recording of newborn health information contributes to improving the quality of care. Nonetheless, there is limited evidence on the implementation of perinatal electronic medical records models. We describe the development and implementation of an electronic recording model that includes data on the health care provided to both the mother and the newborn, standardised for six hospitals of a regional health care system. The implementation process was developed in 2 stages. During stage 1, the tool was introduced in hospitals to stablish first contact with the healthcare staff. The second stage consisted in designing a new strategy to stabilise the model. Technical issues were fixed, and a new version was drawn up based on multidisciplinary agreement. Indicators to monitor implementation were measured in both stages and compared using the chi-squared test. During stage 1, nearly every newborn got its electronic medical record with an appropriate connection to the mother's data. However, certain forms that were meant to be filled in by staff were frequently neglected (completion rates: 36.7%-55.3%). In stage 2, there was a statistically significant increase in the completion rates of all these forms. As a result, a standardised discharge report was provided to every newborn at the end of stage 2. The PCR model implemented in the Region of Murcia is an innovative example of how the digitalisation and standardisation of data related to the care of healthy newborns at maternity wards is feasible across an entire network of hospitals.

A scoping review of semantic integration of health data and information

OBJECTIVE

We summarized a decade of new research focusing on semantic data integration (SDI) since 2009, and we aim to: (1) summarize the state-of-art approaches on integrating health data and information; and (2) identify the main gaps and challenges of integrating health data and information from multiple levels and domains.

MATERIALS AND METHODS

We used PubMed as our focus is applications of SDI in biomedical domains and followed the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) to search and report for relevant studies published between January 1, 2009 and December 31, 2021. We used Covidence-a systematic review management system-to carry out this scoping review.

RESULTS

The initial search from PubMed resulted in 5,326 articles using the two sets of keywords. We then removed 44 duplicates and 5,282 articles were retained for abstract screening. After abstract screening, we included 246 articles for full-text screening, among which 87 articles were deemed eligible for full-text extraction. We summarized the 87 articles from four aspects: (1) methods for the global schema; (2) data integration strategies (i.e., federated system vs. data warehousing); (3) the sources of the data; and (4) downstream applications.

CONCLUSION

SDI approach can effectively resolve the semantic heterogeneities across different data sources. We identified two key gaps and challenges in existing SDI studies that (1) many of the existing SDI studies used data from only single-level data sources (e.g., integrating individual-level patient records from different hospital systems), and (2) documentation of the data integration processes is sparse, threatening the reproducibility of SDI studies.

Use of Real-World Data and Physiologically-Based Pharmacokinetic Modeling to Characterize Enoxaparin Disposition in Children With Obesity

Dosing guidance for children with obesity is often unknown despite the fact that nearly 20% of US children are classified as obese. Enoxaparin, a commonly prescribed low-molecular-weight heparin, is dosed based on body weight irrespective of obesity status to achieve maximum concentration within a narrow therapeutic or prophylactic target range. However, whether children with and without obesity experience equivalent enoxaparin exposure remains unclear. To address this clinical question, 2,825 anti-activated factor X (anti-Xa) surrogate concentrations were collected from the electronic health records of 596 children, including those with obesity. Using linear mixed-effects regression models, we observed that 4-hour anti-Xa concentrations were statistically significantly different in children with and without obesity, even for children with the same absolute dose (P = 0.004). To further mechanistically explore obesity-associated differences in anti-Xa concentration, a pediatric physiologically-based pharmacokinetic (PBPK) model was developed in adults, and then scaled to children with and without obesity. This PBPK model incorporated binding of enoxaparin to antithrombin to form anti-Xa and elimination via heparinase-mediated metabolism and glomerular filtration. Following scaling, the PBPK model predicted real-world pediatric concentrations well, with an average fold error (standard deviation of the fold error) of 0.82 (0.23) and 0.87 (0.26) in children with and without obesity, respectively. PBPK model simulations revealed that children with obesity have at most 20% higher 4-hour anti-Xa concentrations under recommended, total body weight-based dosing compared to children without obesity owing to reduced weight-normalized clearance. Enoxaparin exposure was better matched across age groups and obesity status using fat-free mass weight-based dosing.

The relationship between simulated milrinone exposure and hypotension in children

INTRODUCTION

Hypotension is an adverse event that may be related to systemic exposure of milrinone; however, the true exposure-safety relationship is unknown.

METHODS

Using the Pediatric Trials Network multicentre repository, we identified children ≤17 years treated with milrinone. Hypotension was defined according to age, using the Pediatric Advanced Life Support guidelines. Clinically significant hypotension was defined as hypotension with concomitant lactate >3 mg/dl. A prior population pharmacokinetic model was used to simulate milrinone exposures to evaluate exposure-safety relationships.

RESULTS

We included 399 children with a median (quarter 1, quarter 3) age of 1 year (0,5) who received 428 intravenous doses of milrinone (median infusion rate 0.31 mcg/kg/min [0.29,0.5]). Median maximum plasma milrinone concentration was 110.7 ng/ml (48.4,206.2). Median lowest systolic and diastolic blood pressures were 74 mmHg (60,85) and 35 mmHg (25,42), respectively. At least 1 episode of hypotension occurred in 178 (45%) subjects; clinically significant hypotension occurred in 10 (2%). The maximum simulated milrinone plasma concentrations were higher in subjects with clinically significant hypotension (251 ng/ml [129,329]) versus with hypotension alone (86 ng/ml [44, 173]) versus without hypotension (122 ng/ml [57, 208], p = 0.002); however, this relationship was not retained on multivariable analysis (odds ratio 1.01; 95% confidence interval 0.998, 1.01).

CONCLUSIONS

We successfully leveraged a population pharmacokinetic model and electronic health record data to evaluate the relationship between simulated plasma concentration of milrinone and systemic hypotension occurrence, respectively, supporting the broader applicability of our novel, efficient, and cost-effective study design for examining drug exposure-response and -safety relationships.

Preventing pediatric chronic postsurgical pain: Time for increased rigor

Chronic postsurgical pain (CPSP) results from a cascade of events in the peripheral and central nervous systems following surgery. Several clinical predictors, including the prior pain state, premorbid psychological state (e.g., anxiety, catastrophizing), intraoperative surgical load (establishment of peripheral and central sensitization), and acute postoperative pain management, may contribute to the patient's risk of developing CPSP. However, research on the neurobiological and biobehavioral mechanisms contributing to pediatric CPSP and effective preemptive/treatment strategies are still lacking. Here we evaluate the perisurgical process by identifying key problems and propose potential solutions for the pre-, intra-, and postoperative pain states to both prevent and manage the transition of acute to chronic pain. We propose an eight-step process involving preemptive and preventative analgesia, behavioral interventions, and the use of biomarkers (brain-based, inflammatory, or genetic) to facilitate timely evaluation and treatment of premorbid psychological factors, ongoing surgical pain, and postoperative pain to provide an overall improved outcome. By achieving this, we can begin to establish personalized precision medicine for children and adolescents presenting to surgery and subsequent treatment selection.

Development and Evaluation of a Virtual Population of Children with Obesity for Physiologically Based Pharmacokinetic Modeling

BACKGROUND AND OBJECTIVE

While one in five children in the USA are now obese, and more than three-quarters receive at least one drug during childhood, there is limited dosing guidance for this vulnerable patient population. Physiologically based pharmacokinetic modeling can bridge the gap in the understanding of how pharmacokinetics, including drug distribution and clearance, changes with obesity by incorporating known obesity-related physiological changes in children. The objective of this study was to develop a virtual population of children with obesity to enable physiologically based pharmacokinetic modeling, then use the novel virtual population in conjunction with previously developed models of clindamycin and trimethoprim/sulfamethoxazole to better understand dosing of these drugs in children with obesity.

METHODS

To enable physiologically based pharmacokinetic modeling, a virtual population of children with obesity was developed using national survey, electronic health record, and clinical trial data, as well as data extracted from the literature. The virtual population accounts for key obesity-related changes in physiology relevant to pharmacokinetics, including increased body size, body composition, organ size and blood flow, plasma protein concentrations, and glomerular filtration rate. The virtual population was then used to predict the pharmacokinetics of clindamycin and trimethoprim/sulfamethoxazole in children with obesity using previously developed physiologically based pharmacokinetic models.

RESULTS

Model simulations predicted observed concentrations well, with an overall average fold error of 1.09, 1.24, and 1.53 for clindamycin, trimethoprim, and sulfamethoxazole, respectively. Relative to children without obesity, children with obesity experienced decreased clindamycin and trimethoprim/sulfamethoxazole weight-normalized clearance and volume of distribution, and higher absolute doses under recommended pediatric weight-based dosing regimens.

CONCLUSIONS

Model simulations support current recommended weight-based dosing in children with obesity for clindamycin and trimethoprim/sulfamethoxazole, as they met target exposure despite these changes in clearance and volume of distribution.

Supporting research, protecting data: one institution's approach to clinical data warehouse governance

Institutions must decide how to manage the use of clinical data to support research while ensuring appropriate protections are in place. Questions about data use and sharing often go beyond what the Health Insurance Portability and Accountability Act of 1996 (HIPAA) considers. In this article, we describe our institution’s governance model and approach. Common questions we consider include (1) Is a request limited to the minimum data necessary to carry the research forward? (2) What plans are there for sharing data externally?, and (3) What impact will the proposed use of data have on patients and the institution? In 2020, 302 of the 319 requests reviewed were approved. The majority of requests were approved in less than 2 weeks, with few or no stipulations. For the remaining requests, the governance committee works with researchers to find solutions to meet their needs while also addressing our collective goal of protecting patients.

Electronic Health Record Network Research in Infectious Diseases

With the marked increases in electronic health record (EHR) use for providing clinical care, there have been parallel efforts to leverage EHR data for research. EHR repositories offer the promise of vast amounts of clinical data not easily captured with traditional research methods and facilitate clinical epidemiology and comparative effectiveness research, including analyses to identify patients at higher risk for complications or who are better candidates for treatment. These types of studies have been relatively slow to penetrate the field of infectious diseases, but the need for rapid turnaround during the COVID-19 global pandemic has accelerated the uptake. This review discusses the rationale for her network projects, opportunities and challenges that such networks present, and some prior studies within the field of infectious diseases.

Neonatal sepsis registry: Time to antibiotic dataset

This article describes the process of extracting electronic health record (EHR) data into a format that supports analyses related to the timeliness of antibiotic administration. The de-identified data that accompanies this article were collected from a cohort of infants who were evaluated for possible sepsis in the Neonatal Intensive Care Unit (NICU) at the Children's Hospital of Philadelphia (CHOP). The interpretation of findings from these data are reported in a separate manuscript [1]. For purposes of illustration for interested readers, scripts written in the R programming language related to the creation and use of the dataset have also been provided. Interested researchers are encouraged to contact the research team to discuss opportunities for collaboration.