Graphical abstract 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.
Objective: Non-compliance with antibiotic use is a major cause of treatment failure, increased adverse effects, higher healthcare costs and antibiotic resistance. In this study, our objective was to investigate the factors affecting non-compliance with antibiotic use in Dursunbey, to define preventive measures, and to design content of educational activities. Methods: 129 volunteers who have used antibiotics in the last 3 months were involved in the study. A brief questionnaire with 14 questions was applied through face to face interview. A cross-sectional study was performed on the basis of volunteers' replies. The data were evaluated by bivariate analysis and a logistic regression model. Results: Non-compliance in antibiotic use was detected to be 35%. Bivariate analysis revealed that female sex, age, antibiotic prescription in family medicine centers, antibiotic consumption for upper respiratory tract complaints, feeling better on the first days of antibiotic course, low education level were significantly related to non-compliance in antibiotic use. Multivariate analysis showed that "feeling better on the first days of antibiotic course" (Odds ratio: 5.05) and "female sex" (Odds ratio: 14.38) were significantly related to noncompliance in antibiotic use. Conclusions:Compliance with antibiotic use can be increased by physicians and pharmacists giving satisfactory and appropriate information, performing rapid diagnostic tests, thorough evaluation of antibiotic necessity in each patient with upper respiratory tract complaints by physicians and designing educational activities about antibiotics in schools and maternal healthcare centers. Klimik Dergisi 2016; 29(3): 125-9.
Comparative validation data and clinical performance data are essential for the reliable interpretation of SARS-CoV-2 antibody test results. This study aimed to assess the performance of six SARS-CoV-2 IgG immunoassays in different disease severity settings.Four automated chemiluminescence immunoassays Access (Beckman Coulter), Architect (Abbott), Atellica-IM (Siemens) and Elecsys (Roche) and two ELISA assays (SARS-CoV-2 IgG-S1-based and NCP IgG, Euroimmun) were evaluated in 143 patients and 50 pre-pandemic control sera. Accuracy and precision tests were performed for validation. Overall sensitivity differed between 73.38-88.65%, being higher in spike protein-based assays.Specificity was > 98% in all immunoassays. IgG response was lower for the samples taken <20 days post-symptom onset (87.30%) than for the samples taken >20 days postsymptom onset (94.80%). Higher rate of antibody was detected in the clinically moderate disease group. In the asymptomatic and mild group more antibody positivity was detected with spike protein-based assays. Clinical performance of the immunoassays differs according to disease severity and antigen targeted; moderate disease leading to highest rate of IgG response. All the assays tested were eligible for the detection of SARS-CoV-2 IgG however, spike-based assays revealed relatively higher sensitivity than the nucleoprotein-based assays particularly in the asymptomatic and mild disease severity.
Introduction Guidelines recommend using a pulse oximeter rather than arterial blood gas (ABG) for COVID‐19 patients. However, significant differences can be observed between oxygen saturation measured by pulse oximetry (SpO 2 ) and arterial oxygen saturation (SaO 2 ) in some clinical conditions. We aimed to assess the reliability of the pulse oximeter in patients with COVID‐19. Methods We retrospectively reviewed ABG analyses and SpO 2 levels measured simultaneously with ABG in patients hospitalised in COVID‐19 wards. Results We categorised total 117 patients into two groups, in whom the difference between SpO 2 and SaO 2 was ≤4% (acceptable difference) and >4% (large difference). A large difference group exhibited higher neutrophil count, C‐reactive protein, ferritin, fibrinogen, D‐dimer and lower lymphocyte count. Multivariate analyses revealed that increased fibrinogen, increased ferritin and decreased lymphocyte count were independent risk factors for a large difference between SpO 2 and SaO 2 . The total study group demonstrated the negative bias of 4.02% with the limits of agreement of −9.22% to 1.17%. The bias became significantly higher in patients with higher ferritin, fibrinogen levels and lower lymphocyte count. Conclusion Pulse oximeters may not be sufficient to assess actual oxygen saturation, especially in COVID‐19 patients with high ferritin and fibrinogen levels and low lymphocyte count with low SpO 2 measurements.
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