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Background and ObjectivesKappa free light chains (KFLC) seem to efficiently diagnose MS. However, extensive cohort studies are lacking to establish consensus cut-offs, notably to rule out non-MS autoimmune CNS disorders. Our objectives were to (1) determine diagnostic performances of CSF KFLC, KFLC index, and KFLC intrathecal fraction (IF) threshold values that allow us to separate MS from different CNS disorder control populations and compare them with oligoclonal bands' (OCB) performances and (2) to identify independent factors associated with KFLC quantification in MS.MethodsWe conducted a retrospective multicenter study involving 13 French MS centers. Patients were included if they had a noninfectious and nontumoral CNS disorder, eligible data concerning CSF and serum KFLC, albumin, and OCB. Patients were classified into 4 groups according to their diagnosis: MS, clinically isolated syndrome (CIS), other inflammatory CNS disorders (OIND), and noninflammatory CNS disorder controls (NINDC).ResultsOne thousand six hundred twenty-one patients were analyzed (675 MS, 90 CIS, 297 OIND, and 559 NINDC). KFLC index and KFLC IF had similar performances in diagnosing MS from nonselected controls and OIND (p= 0.123 andp= 0.991 for area under the curve [AUC] comparisons) and performed better than CSF KFLC (p< 0.001 for all AUC comparisons). A KFLC index of 8.92 best separated MS/CIS from the entire nonselected control population, with better performances than OCB (p< 0.001 for AUC comparison). A KFLC index of 11.56 best separated MS from OIND, with similar performances than OCB (p= 0.065). In the multivariate analysis model, female gender (p= 0.003), young age (p= 0.013), and evidence of disease activity (p< 0.001) were independent factors associated with high KFLC index values in patients with MS, whereas MS phenotype, immune-modifying treatment use at sampling, and the FLC analyzer type did not influence KFLC index.DiscussionKFLC biomarkers are efficient tools to separate patients with MS from controls, even when compared with other patients with CNS autoimmune disorder. Given these results, we suggest using KFLC index or KFLC IF as a criterion to diagnose MS.Classification of EvidenceThis study provides Class III evidence that KFLC index or IF can be used to differentiate patients with MS from nonselected controls and from patients with other autoimmune CNS disorders.

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BackgroundTotal blood calcium (TCa) is routinely used to diagnose and manage mineral and bone metabolism disorders. Numerous laboratories adjust TCa by albumin, though literature suggests there are some limits to this approach. Here we report a large retrospective study on agreement rate between ionized calcium (iCa) measurement and TCa or albumin-adjusted calcium measurements.MethodsWe retrospectively selected 5055 samples with simultaneous measurements of iCa, TCa, albumin and pH. We subgrouped our patients according to their estimated glomerular filtration rate (eGFR), albumin levels and pH. We analyzed each patient’s calcium state with iCa as reference to determine agreement rate with TCa and albumin-adjusted calcium using Payne, Clase, Jain and Ridefelt formulas.ResultsThe Payne formula performed poorly in patients with abnormal albumin, eGFR or pH levels. In patients with low albumin levels or blood pH disorders, Payne-adjusted calcium may overestimate the calcium state in up to 80% of cases. Similarly, TCa has better agreement with iCa in the case of hypoalbuminemia, but performed similarly to the Payne formula in patients with physiological albumin levels. The global agreement rate for Clase, Jain and Ridefelt formulas suggests significant improvement compared to Payne calcium adjustment but no significant improvement compared to TCa.ConclusionsTotal and albumin-adjusted calcium measurement leads to a misclassification of calcium status. Moreover, accurate calcium state determination depends on blood pH levels, whose measurement requires the same pre-analytical restrictions as iCa measurement. We propose that iCa should instead become the reference method to determine the real calcium state.

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