Selected article for: "blood type and logistic regression analysis"

Author: Beksac, Meral; Akin, Hasan Yalim; Gencer-Oncul, Emine Begum; Yousefzadeh, Mahsa; Cengiz Seval, Guldane; Gulten, Ezgi; Akdemir Kalkan, Irem; Cinar, Gule; Memikoglu, Osman; Karaagaoglu, Ergun; Dalva, Klara
Title: A model integrating Killer Immunoglobulin-like Receptor (KIR) haplotypes for risk prediction of COVID-19 clinical disease severity
  • Cord-id: 5s8cmb4n
  • Document date: 2021_9_18
  • ID: 5s8cmb4n
    Snippet: Associations between inherited Killer Immunoglobulin-like Receptor (KIR) genotypes and the severity of multiple RNA virus infections have been reported. This prospective study was initiated to investigate if such an association exists for COVID-19. In this cohort study performed at Ankara University, 132 COVID-19 patients (56 asymptomatic, 51 mild-intermediate, and 25 patients with severe disease) were genotyped for KIR and ligands. Ankara University Donor Registry (n:449) KIR data was used for
    Document: Associations between inherited Killer Immunoglobulin-like Receptor (KIR) genotypes and the severity of multiple RNA virus infections have been reported. This prospective study was initiated to investigate if such an association exists for COVID-19. In this cohort study performed at Ankara University, 132 COVID-19 patients (56 asymptomatic, 51 mild-intermediate, and 25 patients with severe disease) were genotyped for KIR and ligands. Ankara University Donor Registry (n:449) KIR data was used for comparison. Clinical parameters (age, gender, comorbidities, blood group antigens, inflammation biomarkers) and KIR genotypes across cohorts of asymptomatic, mild-intermediate, or severe disease were compared to construct a risk prediction model based on multivariate binary logistic regression analysis with backward elimination method. Age, blood group, number of comorbidities, CRP, D-dimer, and telomeric and centromeric KIR genotypes (tAA, tAB1, and cAB1) along with their cognate ligands were found to differ between cohorts. Two prediction models were constructed; both included age, number of comorbidities, and blood group. Inclusion of the KIR genotypes in the second prediction model exp (-3.52 + 1.56 age group - 2.74 blood group (type A vs others) + 1.26 number of comorbidities - 2.46 tAB1 with ligand + 3.17 tAA with ligand) increased the predictive performance with a 92.9% correct classification for asymptomatic and 76% for severe cases (AUC: 0.93; P < 0.0001, 95% CI 0.88, 0.99). This novel risk model, consisting of KIR genotypes with their cognate ligands, and clinical parameters but excluding earlier published inflammation-related biomarkers allow for the prediction of the severity of COVID-19 infection prior to the onset of infection. This study is listed in the National COVID-19 clinical research studies database. [Image: see text]

    Search related documents:
    Co phrase search for related documents
    • acute phase and logistic regression: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
    • acute phase and low albumin: 1
    • acute phase and low frequency: 1, 2
    • acute phase and low lymphocyte count: 1, 2
    • acute phase and low specificity: 1, 2, 3
    • acute phase and lymphocyte count: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15
    • acute phase reactant and logistic model: 1
    • acute phase reactant and logistic regression: 1
    • acute phase reactant and lymphocyte count: 1, 2, 3
    • logistic model and low albumin: 1, 2
    • logistic model and low albumin level: 1
    • logistic model and low frequency: 1
    • logistic model and low lymphocyte count: 1
    • logistic model and low specificity: 1, 2
    • logistic model and low specificity high sensitivity: 1
    • logistic model and lymphocyte count: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
    • logistic regression and low albumin: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18
    • logistic regression and low albumin level: 1, 2, 3, 4
    • logistic regression and low frequency: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16