{"doi":"10.1002/prp2.1002","title":"Comparison of 24‐hour urinary creatinine clearance and estimated glomerular filtration rate based on a panel of filtration markers in patients with chronic kidney disease","abstract":"<jats:title>Abstract</jats:title><jats:p>Diagnosis and management of chronic kidney disease (CKD) requires accurate assessment of glomerular filtration rate (GFR). In practice, GFR is typically estimated by equations based on creatinine concentration in blood, but creatinine is affected by non‐GFR factors such as age and sex. Alternative filtration markers such as cystatin C, beta‐trace protein (BTP), and beta‐2 microglobulin (B2M) may be less dependent on age and sex, but equations combining these markers have not been investigated in patients with chronic kidney disease (CKD). In this cross‐sectional study of 50 patients with CKD stage 3–4, we compared kidney function estimates based on creatinine, cystatin C, BTP, B2M, or a combination of markers. Compared to the creatinine/cystatin C combination equation, the panel equation yielded a mean difference of only 2.8 ml/min/1.73 m<jats:sup>2</jats:sup>, indicating that switching to the panel equation would be unlikely to affect management.</jats:p>","journal":"Pharmacology Research &amp; Perspectives","year":2022,"id":629319,"datarank":0.24141568686511508,"base_score":1.6094379124341003,"endowment":1.6094379124341003,"self_citation_contribution":0.24141568686511508,"citation_network_contribution":0.0,"self_endowment_contribution":0.24141568686511508,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":4,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1629722,"name":"Lene Boesby","orcid":"0000-0002-6326-3671","position":1,"is_corresponding":false},{"id":964848,"name":"Ditte Hansen","orcid":"0000-0003-4929-7901","position":2,"is_corresponding":false},{"id":1202749,"name":"Morten Baltzer Houlind","orcid":"0000-0003-4058-3012","position":3,"is_corresponding":false},{"id":1629721,"name":"Esben Iversen","orcid":"0000-0002-7558-9257","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Comparison of 24‐hour urinary creatinine clearance and estimated glomerular filtration rate based on a panel of filtration markers in patients with chronic kidney disease","abstract":"<jats:title>Abstract</jats:title><jats:p>Diagnosis and management of chronic kidney disease (CKD) requires accurate assessment of glomerular filtration rate (GFR). In practice, GFR is typically estimated by equations based on creatinine concentration in blood, but creatinine is affected by non‐GFR factors such as age and sex. Alternative filtration markers such as cystatin C, beta‐trace protein (BTP), and beta‐2 microglobulin (B2M) may be less dependent on age and sex, but equations combining these markers have not been investigated in patients with chronic kidney disease (CKD). In this cross‐sectional study of 50 patients with CKD stage 3–4, we compared kidney function estimates based on creatinine, cystatin C, BTP, B2M, or a combination of markers. Compared to the creatinine/cystatin C combination equation, the panel equation yielded a mean difference of only 2.8 ml/min/1.73 m<jats:sup>2</jats:sup>, indicating that switching to the panel equation would be unlikely to affect management.</jats:p>","is_dataset_classified":null,"base_score":1.6094379124341003,"endowment":1.6094379124341003,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"36069238","pmcid":"PMC9449817","openalex_id":"https://openalex.org/W4294867737","authors":[],"funders":[{"funder_name":"Novo Nordisk Fonden","grant_id":"NNF20SA0064340","title":null}],"total_grants":1,"fwci":0.3698,"citation_percentile":0.54009319,"influential_citations":0,"citation_trend":[{"year":2022,"count":1},{"year":2024,"count":1},{"year":2025,"count":1},{"year":2026,"count":1}],"oa_status":"gold","license":"cc-by-nc-nd","oa_locations":[{"url":"https://doi.org/10.1002/prp2.1002","host_type":"journal"},{"url":"https://doi.org/10.1002/prp2.1002","host_type":"publisher"},{"url":"https://onlinelibrary.wiley.com/doi/pdf/10.1002/prp2.1002","host_type":"publisher"},{"url":"https://onlinelibrary.wiley.com/doi/full-xml/10.1002/prp2.1002","host_type":"publisher"},{"url":"https://bpspubs.onlinelibrary.wiley.com/doi/pdf/10.1002/prp2.1002","host_type":"publisher"},{"url":"https://pubmed.ncbi.nlm.nih.gov/36069238","host_type":"repository"},{"url":"https://doaj.org/article/df839a74557d4737af8f7992d1af5eb0","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9449817","host_type":"repository"},{"url":"https://researchprofiles.ku.dk/da/publications/00455838-0660-4f6f-ac2a-1dd48206b170","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC9449817","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC9449817?pdf=render","host_type":"Europe_PMC"}],"fields_of_study":["Chronic Kidney Disease and Diabetes","Dialysis and Renal Disease Management","Renal Diseases and Glomerulopathies"],"mesh_terms":["Creatinine","Cross-Sectional Studies","Glomerular Filtration Rate","Humans","Biomarkers","Renal Insufficiency, Chronic","Cystatin C"],"keywords":["Renal function","Creatinine","Cystatin C","Kidney disease","Urology","Medicine","Internal medicine","Beta-2 microglobulin","Cystatin","Urinary system","Endocrinology","Chronic Kidney Disease","Estimated Glomerular Filtration Rate","Beta-trace Protein","Panel Equation"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Good health and well-being"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[{"name":"nct"}],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-05T18:05:07.987958Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}