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Against the background of the current COVID-19 infection dynamics with its rapid spread of SARS-CoV-2 variants of concern (VOC), the immunity and the vaccine prevention of healthcare workers (HCWs) against SARS-CoV-2 continues to be of high importance. This observational cross-section study assesses factors influencing the level of anti-SARS-CoV-2-spike IgG after SARS-CoV-2 infection or vaccination. One thousand seven hundred and fifty HCWs were recruited meeting the following inclusion criteria: age ≥18 years, PCR-confirmed SARS-CoV-2 infection convalescence and/or at least one dose of COVID-19 vaccination. anti-SARS-CoV-2-spike IgG titers were determined by SERION ELISA agile SARS-CoV-2 IgG. Mean anti-SARS-CoV-2-spike IgG levels increased significantly by number of COVID-19 vaccinations (92.2 BAU/ml for single, 140.9 BAU/ml for twice and 1144.3 BAU/ml for threefold vaccination). Hybrid COVID-19 immunized respondents (after infection and vaccination) had significantly higher antibody titers compared with convalescent only HCWs. Anti-SARS-CoV-2-spike IgG titers declined significantly with time after the second vaccination. Smoking and high age were associated with lower titers. Both recovered and vaccinated HCWs presented a predominantly good humoral immune response. Smoking and higher age limited the humoral SARS-CoV-2 immunity, adding to the risk of severe infections within this already health impaired collective.
Background
Published models predicting nasal colonization with Methicillin-resistant Staphylococcus aureus among hospital admissions predominantly focus on separation of carriers from non-carriers and are frequently evaluated using measures of discrimination. In contrast, accurate estimation of carriage probability, which may inform decisions regarding treatment and infection control, is rarely assessed. Furthermore, no published models adjust for MRSA prevalence.
Methods
Using logistic regression, a scoring system (values from 0 to 200) predicting nasal carriage of MRSA was created using a derivation cohort of 3091 individuals admitted to a European tertiary referral center between July 2007 and March 2008. The expected positive predictive value of a rapid diagnostic test (GeneOhm, Becton & Dickinson Co.) was modeled using non-linear regression according to score. Models were validated on a second cohort from the same hospital consisting of 2043 patients admitted between August 2008 and January 2012. Our suggested correction score for prevalence was proportional to the log-transformed odds ratio between cohorts. Calibration before and after correction, i.e. accurate classification into arbitrary strata, was assessed with the Hosmer-Lemeshow-Test.
Results
Treating culture as reference, the rapid diagnostic test had positive predictive values of 64.8% and 54.0% in derivation and internal validation corhorts with prevalences of 2.3% and 1.7%, respectively. In addition to low prevalence, low positive predictive values were due to high proportion (> 66%) of mecA-negative Staphylococcus aureus among false positive results. Age, nursing home residence, admission through the medical emergency department, and ICD-10-GM admission diagnoses starting with “A” or “J” were associated with MRSA carriage and were thus included in the scoring system, which showed good calibration in predicting probability of carriage and the rapid diagnostic test’s expected positive predictive value. Calibration for both probability of carriage and expected positive predictive value in the internal validation cohort was improved by applying the correction score.
Conclusions
Given a set of patient parameters, the presented models accurately predict a) probability of nasal carriage of MRSA and b) a rapid diagnostic test’s expected positive predictive value. While the former can inform decisions regarding empiric antibiotic treatment and infection control, the latter can influence choice of screening method.