Download PDF
J Pediatr Intensive Care 2022; 11(04): 300-307
DOI: 10.1055/s-0041-1725148
Original Article

Use of Electronic Health Records to Identify Exposure-Response Relationships in Critically Ill Children: An Example of Midazolam and Delirium

Kanecia O. Zimmerman
1   Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States
2   Department of Pediatrics, Duke University Medical Center, Durham, North Carolina, United States
,
Tracy G. Spears
1   Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States
,
Marjan Cobbaert 
1   Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States
,
Felix Boakye-Agyeman 
1   Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States
,
Huali Wu
1   Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States
,
Michael Cohen-Wolkowiez 
1   Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States
2   Department of Pediatrics, Duke University Medical Center, Durham, North Carolina, United States
,
Kevin M. Watt
1   Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States
2   Department of Pediatrics, Duke University Medical Center, Durham, North Carolina, United States
,
Daniel K. Benjamin Jr.
1   Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States
2   Department of Pediatrics, Duke University Medical Center, Durham, North Carolina, United States
,
Mara L. Becker
1   Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States
,
Chani Traube 
3   Division of Critical Care Medicine, Weill Cornell Medical College, New York City, New York, United States
,
P. Brian Smith
1   Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States
2   Department of Pediatrics, Duke University Medical Center, Durham, North Carolina, United States
› Author Affiliations Funding The work for this project was supported by KL2TR001115–03.
M.C.W. receives support for research from the National Institutes of Health (1R01-HD076676–01A1), National Institute of Allergy and Infectious Diseases (HHSN272201500006I and HHSN272201300017I), NICHD (HHSN275201000003I), the Biomedical Advanced Research and Development Authority (HHSO100201300009C), and industry for drug development in adults and children (https://scholars.duke.edu/person/michael.cohenwolkowiez).
K.M.W. receives support from the National Institute of Child Health and Human Development (1R01HD097775, 1K23HD075891) and the U.S. government for his work in pediatric and neonatal clinical pharmacology (Government Contract HHSN267200700051C, PI: Benjamin, under the Best Pharmaceuticals for Children Act).
D.K.B. receives support from the National Institutes of Health (award 2K24HD058735–10, National Institute of Child Health and Human Development (HHSN275201000003I), National Institute of Allergy and Infectious Diseases (HHSN272201500006I), ECHO Program (1U2COD023375–02), and the National Center for Advancing Translational Sciences (1U24TR001608–03); he also receives research support from Cempra Pharmaceuticals (subaward to HHSO100201300009C) and industry for neonatal and pediatric drug development, https://scholars.duke.edu/person/danny.benjamin.
M.L.B. receives support from the National Institutes of Health (National Institute of Child Health and Human Development (R01HD089928) and the National Center for Advancing Translational Sciences (1U24TR001608–03); she also has a consulting agreement in place with Swedish Orphan Biovitrium for pharmacokinetic consultation for anakinra in the pediatric population.
C.T. received support for research from the Empire Clinical Research Investigator Program, Cures Within Reach, and the Gerber Foundation.
P.B.S. receives support from the National Institutes of Health (5U2COD023375–03).
K.O.Z. receives support from the National Institutes of Health (National Institute of Child Health and Human Development (K23 HD091398, HHSN275201000003I), the Duke Clinical and Translational Science Award (KL2TR001115–03), and industry for neonatal and pediatric drug development, https://scholars.duke.edu/person/kanecia.obie.
› Further Information
    Permissions and Reprints

Abstract

Adverse drug events are common in critically ill children and often result from systemic or target organ drug exposure. Methods of drug dosing and titration that consider pharmacokinetic alterations may improve our ability to optimally dose critically ill patients and reduce the risk for drug-related adverse events. To demonstrate this possibility, we explored the exposure-response relationship between midazolam and delirium in critically ill children. We retrospectively examined electronic health records (EHRs) of critically ill children <18 years of age hospitalized in the pediatric intensive care unit at Duke University; these children were administered midazolam during mechanical ventilation and had ≥1 Cornell Assessment of Pediatric Delirium (CAPD) score. We used individual-level data extracted from the EHR and a previously published population pharmacokinetic (PK) model developed in critically ill children to simulate plasma concentrations at the time of CAPD scores in 1,000 representative datasets. We used multilevel repeated measures models, with clustering at patient and simulation levels, to evaluate the associations between measures of drug exposure (e.g., concentration and area under concentration time curve) and delirium scores. We included 61 children, median age 1.5 years (range = 0.1–16.3), with 181 CAPD assessments. We identified similarities between simulated Empirical Bayesian parameter estimates from the EHR cohort and those from the PK model population. We identified a stronger association between drug concentration at the time of score and CAPD scores (coefficient 1.78; 95% confidence interval: 1.66–1.90) compared with cumulative dose per kilogram and CAPD scores (coefficient −0.01; 95% confidence interval: −0.01 to −0.01). EHR and PK models can be leveraged to investigate exposure-response relationships in critically ill children.

Keywords

critically ill children - delirium - midazolam

Supplementary Material



Publication History

Received: 10 November 2020

Accepted: 21 January 2021

Article published online:
17 March 2021

© 2021. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

  • References

  • 1 Alghamdi AA, Keers RN, Sutherland A, Ashcroft DM. Prevalence and nature of medication errors and preventable adverse drug events in paediatric and neonatal intensive care settings: a systematic review. Drug Saf 2019; 42 (12) 1423-1436
    CrossrefPubMedGoogle Scholar
  • 2 Eulmesekian PG, Alvarez JP, Ceriani Cernadas JM, Pérez A, Berberis S, Kondratiuk Y. The occurrence of adverse events is associated with increased morbidity and mortality in children admitted to a single pediatric intensive care unit. Eur J Pediatr 2020; 179 (03) 473-482
    CrossrefPubMedGoogle Scholar
  • 3 Kunac DL, Kennedy J, Austin N, Reith D. Incidence, preventability, and impact of Adverse Drug Events (ADEs) and potential ADEs in hospitalized children in New Zealand: a prospective observational cohort study. Paediatr Drugs 2009; 11 (02) 153-160
    CrossrefPubMedGoogle Scholar
  • 4 Zuppa AF, Curley MAQ. Sedation analgesia and neuromuscular blockade in pediatric critical care: overview and current landscape. Pediatr Clin North Am 2017; 64 (05) 1103-1116
    CrossrefPubMedGoogle Scholar
  • 5 Giachetto GA, Telechea HM, Speranza N, Oyarzun M, Nanni L, Menchaca A. Vancomycin pharmacokinetic-pharmacodynamic parameters to optimize dosage administration in critically ill children. Pediatr Crit Care Med 2011; 12 (06) e250-e254
    CrossrefPubMedGoogle Scholar
  • 6 Kramer L, Jordan B, Druml W, Bauer P, Metnitz PG. Austrian Epidemiologic Study on Intensive Care, ASDI Study Group. Incidence and prognosis of early hepatic dysfunction in critically ill patients--a prospective multicenter study. Crit Care Med 2007; 35 (04) 1099-1104
    CrossrefPubMedGoogle Scholar
  • 7 Jenniskens M, Langouche L, Vanwijngaerden YM, Mesotten D, Van den Berghe G. Cholestatic liver (dys)function during sepsis and other critical illnesses. Intensive Care Med 2016; 42 (01) 16-27
    CrossrefPubMedGoogle Scholar
  • 8 Milbrandt EB, Deppen S, Harrison PL. et al. Costs associated with delirium in mechanically ventilated patients. Crit Care Med 2004; 32 (04) 955-962
    CrossrefPubMedGoogle Scholar
  • 9 Colville G, Kerry S, Pierce C. Children's factual and delusional memories of intensive care. Am J Respir Crit Care Med 2008; 177 (09) 976-982
    CrossrefPubMedGoogle Scholar
  • 10 Prugh DG, Wagonfeld S, Metcalf D, Jordan K. A clinical study of delirium in children and adolescents. Psychosom Med 1980; 42 (1, Suppl): 177-195
    CrossrefPubMedGoogle Scholar
  • 11 Traube C, Mauer EA, Gerber LM. et al. Cost associated with pediatric delirium in the ICU. Crit Care Med 2016; 44 (12) e1175-e1179
    CrossrefPubMedGoogle Scholar
  • 12 Saczynski JS, Marcantonio ER, Quach L. et al. Cognitive trajectories after postoperative delirium. N Engl J Med 2012; 367 (01) 30-39
    CrossrefPubMedGoogle Scholar
  • 13 Serafim RB, Dutra MF, Saddy F. et al. Delirium in postoperative nonventilated intensive care patients: risk factors and outcomes. Ann Intensive Care 2012; 2 (01) 51
    CrossrefPubMedGoogle Scholar
  • 14 Pandharipande P, Shintani A, Peterson J. et al. Lorazepam is an independent risk factor for transitioning to delirium in intensive care unit patients. Anesthesiology 2006; 104 (01) 21-26
    CrossrefPubMedGoogle Scholar
  • 15 Pandharipande P, Cotton BA, Shintani A. et al. Prevalence and risk factors for development of delirium in surgical and trauma intensive care unit patients. J Trauma 2008; 65 (01) 34-41
    CrossrefPubMedGoogle Scholar
  • 16 Traube C, Silver G, Gerber LM. et al. Delirium and mortality in critically ill children: epidemiology and outcomes of pediatric delirium. Crit Care Med 2017; 45 (05) 891-898
    CrossrefPubMedGoogle Scholar
  • 17 Traube C, Silver G, Reeder RW. et al. Delirium in critically ill children: an international point prevalence study. Crit Care Med 2017; 45 (04) 584-590
    CrossrefPubMedGoogle Scholar
  • 18 Zaal IJ, Devlin JW, Hazelbag M. et al. Benzodiazepine-associated delirium in critically ill adults. Intensive Care Med 2015; 41 (12) 2130-2137
    CrossrefPubMedGoogle Scholar
  • 19 Pandharipande PP, Pun BT, Herr DL. et al. Effect of sedation with dexmedetomidine vs lorazepam on acute brain dysfunction in mechanically ventilated patients: the MENDS randomized controlled trial. JAMA 2007; 298 (22) 2644-2653
    CrossrefPubMedGoogle Scholar
  • 20 Dubois MJ, Bergeron N, Dumont M, Dial S, Skrobik Y. Delirium in an intensive care unit: a study of risk factors. Intensive Care Med 2001; 27 (08) 1297-1304
    CrossrefPubMedGoogle Scholar
  • 21 Fraser GL, Devlin JW, Worby CP. et al. Benzodiazepine versus nonbenzodiazepine-based sedation for mechanically ventilated, critically ill adults: a systematic review and meta-analysis of randomized trials. Crit Care Med 2013; 41 (09, Suppl 1): S30-S38
    CrossrefPubMedGoogle Scholar
  • 22 Seymour CW, Pandharipande PP, Koestner T. et al. Diurnal sedative changes during intensive care: impact on liberation from mechanical ventilation and delirium. Crit Care Med 2012; 40 (10) 2788-2796
    CrossrefPubMedGoogle Scholar
  • 23 Ince I, de Wildt SN, Wang C. et al. A novel maturation function for clearance of the cytochrome P450 3A substrate midazolam from preterm neonates to adults. Clin Pharmacokinet 2013; 52 (07) 555-565
    CrossrefPubMedGoogle Scholar
  • 24 Shelly MP, Mendel L, Park GR. Failure of critically ill patients to metabolise midazolam. Anaesthesia 1987; 42 (06) 619-626
    CrossrefPubMedGoogle Scholar
  • 25 Traube C, Silver G, Kearney J. et al. Cornell assessment of pediatric delirium: a valid, rapid, observational tool for screening delirium in the PICU*. Crit Care Med 2014; 42 (03) 656-663
    CrossrefPubMedGoogle Scholar
  • 26 Food and Drug Administration (FDA). Drug development and drug interactions: table of substrates, inhibitors and inducers. Updated March 10, 2020. Accessed October 21, 2020 at: https://www.fda.gov/drugs/drug-interactions-labeling/drug-development-and-drug-interactions-table-substrates-inhibitors-and-inducers
    PubMedGoogle Scholar
  • 27 Graciano AL, Balko JA, Rahn DS, Ahmad N, Giroir BP. The Pediatric Multiple Organ Dysfunction Score (P-MODS): development and validation of an objective scale to measure the severity of multiple organ dysfunction in critically ill children. Crit Care Med 2005; 33 (07) 1484-1491
    CrossrefPubMedGoogle Scholar
  • 28 de Wildt SN, de Hoog M, Vinks AA, van der Giesen E, van den Anker JN. Population pharmacokinetics and metabolism of midazolam in pediatric intensive care patients. Crit Care Med 2003; 31 (07) 1952-1958
    CrossrefPubMedGoogle Scholar
  • 29 Mould DR, Upton RN. Basic concepts in population modeling, simulation, and model-based drug development. CPT Pharmacometrics Syst Pharmacol 2012; 1 (09) e6
    CrossrefPubMedGoogle Scholar
  • 30 Mould DR, Upton RN. Basic concepts in population modeling, simulation, and model-based drug development-part 2: introduction to pharmacokinetic modeling methods. CPT Pharmacometrics Syst Pharmacol 2013; 2 (04) e38
    CrossrefPubMedGoogle Scholar
  • 31 Hartman SJF, Brüggemann RJ, Orriëns L, Dia N, Schreuder MF, de Wildt SN. Pharmacokinetics and target attainment of antibiotics in critically ill children: a systematic review of current literature. Clin Pharmacokinet 2020; 59 (02) 173-205
    CrossrefPubMedGoogle Scholar
  • 32 Cies JJ, Moore II WS, Enache A, Chopra A. β-lactam therapeutic drug management in the PICU. Crit Care Med 2018; 46 (02) 272-279
    CrossrefPubMedGoogle Scholar
  • 33 Balch AH, Constance JE, Thorell EA. et al. Pediatric vancomycin dosing: trends over time and the impact of therapeutic drug monitoring. J Clin Pharmacol 2015; 55 (02) 212-220
    CrossrefPubMedGoogle Scholar
  • 34 Roberts JA, Abdul-Aziz MH, Lipman J. et al; International Society of Anti-Infective Pharmacology and the Pharmacokinetics and Pharmacodynamics Study Group of the European Society of Clinical Microbiology and Infectious Diseases. Individualised antibiotic dosing for patients who are critically ill: challenges and potential solutions. Lancet Infect Dis 2014; 14 (06) 498-509
    CrossrefPubMedGoogle Scholar
  • 35 Blot SI, Pea F, Lipman J. The effect of pathophysiology on pharmacokinetics in the critically ill patient--concepts appraised by the example of antimicrobial agents. Adv Drug Deliv Rev 2014; 77: 3-11
    CrossrefPubMedGoogle Scholar
  • 36 Smith HAB, Gangopadhyay M, Goben CM. et al. Delirium and benzodiazepines associated with prolonged ICU stay in critically ill infants and young children. Crit Care Med 2017; 45 (09) 1427-1435
    CrossrefPubMedGoogle Scholar
  • 37 Mody K, Kaur S, Mauer EA. et al. Benzodiazepines and development of delirium in critically ill children: estimating the causal effect. Crit Care Med 2018; 46 (09) 1486-1491
    CrossrefPubMedGoogle Scholar
  • 38 Rizk ML, Zou L, Savic RM, Dooley KE. Importance of drug pharmacokinetics at the site of action. Clin Transl Sci 2017; 10 (03) 133-142
    CrossrefPubMedGoogle Scholar
  • 39 de Wildt SN, de Hoog M, Vinks AA, Joosten KF, van Dijk M, van den Anker JN. Pharmacodynamics of midazolam in pediatric intensive care patients. Ther Drug Monit 2005; 27 (01) 98-102
    CrossrefPubMedGoogle Scholar
  • 40 DRUGBANK. DRUGBANK database. Accessed October 21, 2020 at: https://www.drugbank.ca/
    PubMedGoogle Scholar
  • 41 Wishart DS, Feunang YD, Guo AC. et al. DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res 2018; 46 (D1): D1074-D1082
    Google Scholar
  • 42 Law V, Knox C, Djoumbou Y. et al. DrugBank 4.0: shedding new light on drug metabolism. Nucleic Acids Res 2014; 42 (Database issue): D1091-D1097
    CrossrefPubMedGoogle Scholar