Jan Hansel, Fahmida Mannan, Rebecca Robey, Mary Kumarendran, Siân Bladon, Alexander G Mathioudakis, Kayode Ogungbenro, Paul Dark, Timothy W Felton
{"title":"接受β-内酰胺类抗菌药物治疗的重症成人群体药代动力学研究中的变量:系统综述和叙述性综述。","authors":"Jan Hansel, Fahmida Mannan, Rebecca Robey, Mary Kumarendran, Siân Bladon, Alexander G Mathioudakis, Kayode Ogungbenro, Paul Dark, Timothy W Felton","doi":"10.1093/jacamr/dlae030","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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 (<i>n</i> = 404), biomarkers (<i>n</i> = 206) and physiological parameters (<i>n</i> = 163). Only seven distinct commonly reported covariates (CL<sub>CR</sub>, weight, glomerular filtration rate, diuresis, need for renal replacement, serum albumin and C-reactive protein) were significant more than 20% of the time.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":14594,"journal":{"name":"JAC-Antimicrobial Resistance","volume":"6 1","pages":"dlae030"},"PeriodicalIF":3.7000,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10895699/pdf/","citationCount":"0","resultStr":"{\"title\":\"Covariates in population pharmacokinetic studies of critically ill adults receiving β-lactam antimicrobials: a systematic review and narrative synthesis.\",\"authors\":\"Jan Hansel, Fahmida Mannan, Rebecca Robey, Mary Kumarendran, Siân Bladon, Alexander G Mathioudakis, Kayode Ogungbenro, Paul Dark, Timothy W Felton\",\"doi\":\"10.1093/jacamr/dlae030\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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 (<i>n</i> = 404), biomarkers (<i>n</i> = 206) and physiological parameters (<i>n</i> = 163). Only seven distinct commonly reported covariates (CL<sub>CR</sub>, weight, glomerular filtration rate, diuresis, need for renal replacement, serum albumin and C-reactive protein) were significant more than 20% of the time.</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":14594,\"journal\":{\"name\":\"JAC-Antimicrobial Resistance\",\"volume\":\"6 1\",\"pages\":\"dlae030\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2024-02-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10895699/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JAC-Antimicrobial Resistance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/jacamr/dlae030\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/2/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"INFECTIOUS DISEASES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JAC-Antimicrobial Resistance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/jacamr/dlae030","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/2/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
Covariates in population pharmacokinetic studies of critically ill adults receiving β-lactam antimicrobials: a systematic review and narrative synthesis.
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.