Covariates in population pharmacokinetic studies of critically ill adults receiving β-lactam antimicrobials: a systematic review and narrative synthesis

Author:

Hansel Jan12ORCID,Mannan Fahmida3ORCID,Robey Rebecca1ORCID,Kumarendran Mary2,Bladon Siân4ORCID,Mathioudakis Alexander G15ORCID,Ogungbenro Kayode6ORCID,Dark Paul17ORCID,Felton Timothy W12

Affiliation:

1. Division of Immunology, Immunity to Infection and Respiratory Medicine, School of Biological Sciences, University of Manchester , Oxford Road , Manchester M13 9PL, UK

2. Acute Intensive Care Unit, Wythenshawe Hospital, Manchester University NHS Foundation Trust , Southmoor Road, Wythenshawe , Manchester M23 9LT, UK

3. Division of Cardiovascular Sciences, School of Medical Sciences, University of Manchester , Oxford Road , Manchester M13 9PL, UK

4. Division of Informatics, Imaging & Data Sciences, School of Health Sciences, University of Manchester , Oxford Road , Manchester M13 9PL, UK

5. North West Lung Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust , Southmoor Road, Wythenshawe , Manchester M23 9LT, UK

6. Division of Pharmacy & Optometry, School of Health Sciences, University of Manchester , Oxford Road , Manchester M13 9PL, UK

7. Critical Care Unit, Northern Care Alliance NHS Foundation Trust, Salford Care Organisation , Greater Manchester M6 8HD , UK

Abstract

Abstract Introduction Population pharmacokinetic studies of β-lactam antimicrobials in critically ill patients derive models that inform their dosing. In non-linear mixed-effects modelling, covariates are often used to improve model fit and explain variability. We aimed to investigate which covariates are most commonly assessed and which are found to be significant, along with global patterns of publication. Methods We conducted a systematic review, searching MEDLINE, Embase, CENTRAL and Web of Science on 01 March 2023, including studies of critically ill adults receiving β-lactam antimicrobials who underwent blood sampling for population pharmacokinetic studies. We extracted and categorized all reported covariates and assessed reporting quality using the ClinPK checklist. Results Our search identified 151 studies with 6018 participants. Most studies reported observational cohorts (120 studies, 80%), with the majority conducted in high-income settings (136 studies, 90%). Of the 1083 identified covariate instances, 237 were unique; the most common categories were patient characteristics (n = 404), biomarkers (n = 206) and physiological parameters (n = 163). Only seven distinct commonly reported covariates (CLCR, weight, glomerular filtration rate, diuresis, need for renal replacement, serum albumin and C-reactive protein) were significant more than 20% of the time. Conclusions Covariates are most commonly chosen based on biological plausibility, with patient characteristics and biomarkers the most frequently investigated. We developed an openly accessible database of reported covariates to aid investigators with covariate selection when designing population pharmacokinetic studies. Novel covariates, such as sepsis subphenotypes, have not been explored yet, leaving a research gap for future work.

Funder

NIHR Manchester Biomedical Research Centre

Publisher

Oxford University Press (OUP)

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