{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T19:59:46Z","timestamp":1793131186816,"version":"4.5.0"},"reference-count":50,"publisher":"Walter de Gruyter GmbH","issue":"11","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,27]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec id=\"j_cclm-2025-0330_abs_001\">\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>Haemolysis is a major preanalytical issue that affects potassium measurements, often leading to sample rejection and delayed clinical management. This study proposes a novel corrective model for accurate unhaemolysed potassium prediction.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_cclm-2025-0330_abs_002\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Blood samples from 14 healthy volunteers were used to prepare a range of haemolysates via freeze-thaw method. First, the relationship between potassium variation and haemolysis variation (\u0394K\/\u0394HI) was studied both individually and globally to assess inter-individual variability. Then, to achieve a more personalised unhaemolysed potassium prediction, a novel corrective model was developed based on: potassium levels in paired unhaemolysed and gradually haemolysed samples, measured haemolysis index,\u00a0mean corpuscular haemoglobin concentration, mean corpuscular volume and intraerythrocytic potassium level. The bias between true and model-predicted unhaemolysed potassium values was calculated and compared to the reference change value (RCV%).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_cclm-2025-0330_abs_003\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Global data showed a strong correlation between \u0394K and \u0394HI (Pearson r=0.97, p&lt;0.0001), following a linear\u00a0relationship: \u0394K=0.33*\u0394HI (p&lt;0.0001). However, individual data revealed substantial inter-individual variation (min\u00a0\u0394K=0.23*\u0394HI and max \u0394K=0.39*\u0394HI). The correction model achieved 100\u202f% accuracy for the 116 prepared samples, with predicted unhaemolysed potassium values falling within a\u00a0\u00b1\u00a010\u202f% bias range (mean\u00a0\u00b1\u00a0standard deviation of bias =\u00a0\u22120.5\u00a0\u00b1\u00a02.8\u202f%).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_cclm-2025-0330_abs_004\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>We propose a novel, reliable, and cost-effective corrective model to predict unhaemolysed potassium from haemolysed samples. Compared with previously published models, the integration of red blood cells indices allows for a more personalised, patient-centred approach with high efficiency.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1515\/cclm-2025-0330","type":"journal-article","created":{"date-parts":[[2025,8,8]],"date-time":"2025-08-08T04:57:06Z","timestamp":1754629026000},"page":"2198-2208","source":"Crossref","is-referenced-by-count":1,"title":["A novel corrective model based on red blood cells indices and haemolysis index enables accurate unhaemolysed potassium determination in haemolysed samples\u00a0\u2013\u00a0Hemokalc project"],"prefix":"10.1515","volume":"63","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8887-376X","authenticated-orcid":false,"given":"Charles R.","family":"Lef\u00e8vre","sequence":"first","affiliation":[{"name":"Clinical Biochemistry and Toxicology Laboratory , Rennes University Hospital Centre , Rennes , France"},{"name":"INSERM, INRAE, Univ Rennes, Institut NUMECAN, UMR_S1317 Rennes , France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"B\u00e9r\u00e9nice","family":"Vigier","sequence":"additional","affiliation":[{"name":"Clinical Biochemistry and Toxicology Laboratory , Rennes University Hospital Centre , Rennes , France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mathilde","family":"Favalelli","sequence":"additional","affiliation":[{"name":"Clinical Biochemistry and Toxicology Laboratory , Rennes University Hospital Centre , Rennes , France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jordan","family":"Garnier","sequence":"additional","affiliation":[{"name":"Clinical Biochemistry and Toxicology Laboratory , Rennes University Hospital Centre , Rennes , France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexandre","family":"Scanff","sequence":"additional","affiliation":[{"name":"Centre d\u2019investigation clinique de Rennes (CIC1414) , Univ Rennes, CHU Rennes, Inserm, EHESP, Irset (Institut de recherche en sant\u00e9, environnement et travail)\u00a0\u2013\u00a0UMR_S 1085 , Rennes , France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maxime","family":"Pawlowski","sequence":"additional","affiliation":[{"name":"Clinical Biochemistry and Toxicology Laboratory , Rennes University Hospital Centre , Rennes , France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicolas","family":"Collet","sequence":"additional","affiliation":[{"name":"Clinical Biochemistry and Toxicology Laboratory , Rennes University Hospital Centre , Rennes , France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Claude","family":"Bendavid","sequence":"additional","affiliation":[{"name":"Clinical Biochemistry and Toxicology Laboratory , Rennes University Hospital Centre , Rennes , France"},{"name":"INSERM, INRAE, Univ Rennes, Institut NUMECAN, UMR_S1317 Rennes , France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"374","published-online":{"date-parts":[[2025,8,8]]},"reference":[{"key":"2025103114402222235_j_cclm-2025-0330_ref_001","doi-asserted-by":"crossref","unstructured":"Gumz, ML, Rabinowitz, L, Wingo, CS. 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