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  1. Fulltext A Novel Algorithm Using Cell Population Data (VCS Parameters) as a Screening Discriminant between Alpha and Beta Thalassemia Traits
    Ambayya A, Sahibon S, Yang TW, Zhang QY, Hassan R, Sathar J
    Diagnostics (Basel), 2021 Nov 22;11(11).
    PMID: 34829510 DOI: 10.3390/diagnostics11112163
    Thalassemia is one of the major inherited haematological disorders in the Southeast Asia region. This study explored the potential utility of red blood cell (RBC) parameters and reticulocyte cell population data (CPD) parameters in the differential diagnosis of α and β-thalassaemia traits as a rapid and cost-effective tool for screening of thalassemia traits. In this study, a total of 1597 subjects (1394 apparently healthy subjects, 155 subjects with α-thalassaemia trait, and 48 subjects with β-thalassaemia trait) were accrued. The parameters studied were the RBC parameters and reticulocyte CPD parameters derived from Unicel DxH800. A novel algorithm named αβ-algorithm was developed: (MN-LMALS-RET × RDW) - MCH) to discriminate α from β-thalassaemia trait with a cut-off value of 1742.5 [AUC = 0.966, sensitivity = 92%, specificity = 90%, 95% CI = 0.94-0.99]. Two prospective studies were carried: an in-house cohort to assess the specificity of this algorithm in 310 samples comprising various RBC disorders and in an interlaboratory cohort of 65 α-thalassemia trait, and 30 β-thalassaemia trait subjects to assess the reproducibility of the findings. We propose the αβ-algorithm to serve as a rapid, inexpensive surrogate evaluation tool of α and β-thalassaemia in the population screening of thalassemia traits in geographic regions with a high burden of these inherited blood disorders.
  2. Development of the clinical assessment scale in autoimmune encephalitis
    Lim JA, Lee ST, Moon J, Jun JS, Kim TJ, Shin YW, et al.
    Ann Neurol, 2019 03;85(3):352-358.
    PMID: 30675918 DOI: 10.1002/ana.25421
    OBJECTIVE: There is no scale for rating the severity of autoimmune encephalitis (AE). In this study, we aimed to develop a novel scale for rating severity in patients with diverse AE syndromes and to verify the reliability and validity of the developed scale.

    METHODS: The key items were generated by a panel of experts and selected according to content validity ratios. The developed scale was initially applied to 50 patients with AE (development cohort) to evaluate its acceptability, reproducibility, internal consistency, and construct validity. Then, the scale was applied to another independent cohort (validation cohort, n = 38).

    RESULTS: A new scale consisting of 9 items (seizure, memory dysfunction, psychiatric symptoms, consciousness, language problems, dyskinesia/dystonia, gait instability and ataxia, brainstem dysfunction, and weakness) was developed. Each item was assigned a value of up to 3 points. The total score could therefore range from 0 to 27. We named the scale the Clinical Assessment Scale in Autoimmune Encephalitis (CASE). The new scale showed excellent interobserver (intraclass correlation coefficient [ICC] = 0.97) and intraobserver (ICC = 0.96) reliability for total scores, was highly correlated with modified Rankin scale (r = 0.86, p

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