{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T15:14:48Z","timestamp":1781190888722,"version":"3.54.1"},"reference-count":82,"publisher":"The Pediatric Pharmacy Association","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:sec id=\"st1\">\n                    <jats:title>OBJECTIVES<\/jats:title>\n                    <jats:p>\n                      The primary objectives were to identify the correlation between various estimated glomerular filtration rate (eGFR) methods and observed meropenem clearance (CL\n                      <jats:sub>MERO<\/jats:sub>\n                      ) in hospitalized children on meropenem and to identify patients with acute kidney injury (AKI) or augmented renal clearance (ARC).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"st2\">\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>We prospectively assessed children aged 4 weeks to 21 years who received meropenem 20mg\/kg IV every 8 hours from 2019 to 2023. Cases with sepsis were compared with controls without sepsis. Plasma meropenem concentrations and renal function biomarkers (serum creatinine [SCr], cystatin C [SCys]) were measured. GFR was estimated using: eGFR-MS (modified Schwartz for &lt;18 years old and CKD-EPI for \u2265 18 years old), 3 equations by Pierce using SCr (eGFR-Cr) or SCys (eGFR-Cys) or their average (eGFR-Avg), and eGFR-Pot (Pottel).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"st3\">\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>\n                      Analysis included 27 subjects (n = 19 cases and n = 8 controls) with 309 meropenem serum concentrations. Median age was 11.8 (range 0.6\u201319.6) years, weight 36.3 (7.2\u201398.0) kg, CL\n                      <jats:sub>MERO<\/jats:sub>\n                      122.7 (35.7\u2013422.3), eGFR-MS 138.9 (22.9\u2013364.8), eGFR-Cr 122.1 (24.0\u2013601.8), eGFR-Cys 163.0 (47.5\u2013432.4), eGFR-Avg 143.06 (35.75\u2013395.7), and eGFR-Pot 138.92 (25.98\u2013614.09) mL\/min\/1.73 m\n                      <jats:sup>2<\/jats:sup>\n                      . The correlation between all eGFR methods to CL\n                      <jats:sub>MERO<\/jats:sub>\n                      was weak (Spearman Rho ranged from 0.073 to 0.14). SCr-based eGFR and SCys-based eGFR had a discordance in identifying ARC and AKI in 41% of patients.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"st4\">\n                    <jats:title>CONCLUSIONS<\/jats:title>\n                    <jats:p>\n                      The renal function of critically ill children, especially with sepsis, was extremely diverse and variable by day. Current eGFR methods had weak correlation to CL\n                      <jats:sub>MERO<\/jats:sub>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.5863\/jppt-25-00065","type":"journal-article","created":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T14:47:03Z","timestamp":1781189223000},"page":"380-389","source":"Crossref","is-referenced-by-count":0,"title":["Correlation Between Renal Biomarkers, Glomerular Filtration Rate, and Meropenem Clearance in Pediatric Septic Shock"],"prefix":"10.5863","volume":"31","author":[{"given":"Brandon","family":"Vo","sequence":"first","affiliation":[{"name":"Department of Biochemistry (BV), University of California Riverside, Riverside, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julie","family":"Huynh","sequence":"additional","affiliation":[{"name":"School of Pharmacy and Pharmaceutical Sciences (JH, JL, JM, EC) and School of Medicine (RM, EC, JB), University of California San Diego, La Jolla, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert H.","family":"Mak","sequence":"additional","affiliation":[{"name":"School of Pharmacy and Pharmaceutical Sciences (JH, JL, JM, EC) and School of Medicine (RM, EC, JB), University of California San Diego, La Jolla, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeremiah D.","family":"Momper","sequence":"additional","affiliation":[{"name":"School of Pharmacy and Pharmaceutical Sciences (JH, JL, JM, EC) and School of Medicine (RM, EC, JB), University of California San Diego, La Jolla, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sean N.","family":"Avedissian","sequence":"additional","affiliation":[{"name":"Department of Pharmacy Practice and Science (SA), University of Nebraska Medical Center, NE"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Edmund V.","family":"Capparelli","sequence":"additional","affiliation":[{"name":"School of Pharmacy and Pharmaceutical Sciences (JH, JL, JM, EC) and School of Medicine (RM, EC, JB), University of California San Diego, La Jolla, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Helen","family":"Harvey","sequence":"additional","affiliation":[{"name":"Department of Infectious Disease (JB) and Critical Care (EB, HH, NR), Rady Children\u2019s Hospital, San Diego, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Erin","family":"Bradley","sequence":"additional","affiliation":[{"name":"Department of Infectious Disease (JB) and Critical Care (EB, HH, NR), Rady Children\u2019s Hospital, San Diego, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nanda","family":"Ramchandar","sequence":"additional","affiliation":[{"name":"Department of Infectious Disease (JB) and Critical Care (EB, HH, NR), Rady Children\u2019s Hospital, San Diego, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Su Jin","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Pediatrics (SJK), Inha University College of Medicine and Inha University Hospital, Incheon, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eun Mi","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Pediatrics (EMY), Chonnam National University College of Medicine and Hospital, Gwangju, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John S.","family":"Bradley","sequence":"additional","affiliation":[{"name":"School of Pharmacy and Pharmaceutical Sciences (JH, JL, JM, EC) and School of Medicine (RM, EC, JB), University of California San Diego, La Jolla, CA"},{"name":"Department of Infectious Disease (JB) and Critical Care (EB, HH, NR), Rady Children\u2019s Hospital, San Diego, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jennifer","family":"Le","sequence":"additional","affiliation":[{"name":"School of Pharmacy and Pharmaceutical Sciences (JH, JL, JM, EC) and School of Medicine (RM, EC, JB), University of California San Diego, La Jolla, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"3883","reference":[{"issue":"4","key":"JPPT-25-00065-b01","series-title":"Pediatr Nephrol","first-page":"1087","article-title":"Glomerular filtration rate in critically ill neonates and children: creatinine-based estimations versus iohexol-based measurements","volume":"38","author":"Smeets","year":"2023","unstructured":"Smeets NJL, Teunissen EMM, van der Velden K, et al. Glomerular filtration rate in critically ill neonates and children: creatinine-based estimations versus iohexol-based measurements. Pediatr Nephrol. 2023;38(4):1087\u20131097."},{"issue":"4","key":"JPPT-25-00065-b02","series-title":"Pediatr Crit Care Med","first-page":"e507","article-title":"Subtherapeutic meropenem antibiotic exposure in children with septic shock assessed by noncompartmental pharmacokinetic analysis in a prospective dataset","volume":"26","author":"Bradley","year":"2025","unstructured":"Bradley JS, Harvey H, Stout D, et al. Subtherapeutic meropenem antibiotic exposure in children with septic shock assessed by noncompartmental pharmacokinetic analysis in a prospective dataset. 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