SummaryRituximab (RTX) treatment in rheumatoid arthritis (RA) patients severely hampers humoral response after influenza vaccination as determined by haemagglutination inhibition assay (HI). It is not known whether HI reflects both immunoglobulin (Ig)M and IgG (subclass) influenza response, and whether IgM antibodies contribute to the low rate of influenza infection seen in RA patients. Twenty RA patients on methotrexate (MTX), 23 on RTX and 28 healthy controls (HC) received trivalent influenza subunit vaccination. Before and 28 days after vaccination, H1N1-and H3N2-specific antibodies were measured by HI and by IgM and IgG (subclass) enzyme-linked immunosorbent assay (ELISA). B cell activating factor (BAFF) levels were determined in serum samples before vaccination. Vaccination induced a significant increase of IgM and IgG (IgG1 and IgG3) antibodies against both strains in the HC and MTX groups (all P < 0·01), but not in the RTX group. HI correlated significantly in all cases with IgG (IgG1) but not with IgM. In RTX late patients (RTX treatment 6-10 months before vaccination), IgG (IgG1 and IgG3) response to vaccination was restored, but not IgM response. BAFF levels were significantly increased in RA-RTX patients and correlated with total IgG levels. Haemagglutination inhibition assay, used as gold standard, detects primarily IgG (IgG1) responses. IgM-and IgG influenza-specific antibodies increase after vaccination in HC and RA patients except in patients on RTX treatment. BAFF levels are increased in both early and late RTX-treated patients, but do not correlate with an influenza-specific antibody response.

BackgroundIn order to stimulate appropriate antimicrobial use and thereby lower the chances of resistance development, an Antibiotic Stewardship Team (A-Team) has been implemented at the University Medical Center Groningen, the Netherlands. Focus of the A-Team was a pro-active day 2 case-audit, which was financially evaluated here to calculate the return on investment from a hospital perspective.MethodsEffects were evaluated by comparing audited patients with a historic cohort with the same diagnosis-related groups. Based upon this evaluation a cost-minimization model was created that can be used to predict the financial effects of a day 2 case-audit. Sensitivity analyses were performed to deal with uncertainties. Finally, the model was used to financially evaluate the A-Team.ResultsOne whole year including 114 patients was evaluated. Implementation costs were calculated to be €17,732, which represent total costs spent to implement this A-Team. For this specific patient group admitted to a urology ward and consulted on day 2 by the A-Team, the model estimated total savings of €60,306 after one year for this single department, leading to a return on investment of 5.9.ConclusionsThe implemented multi-disciplinary A-Team performing a day 2 case-audit in the hospital had a positive return on investment caused by a reduced length of stay due to a more appropriate antibiotic therapy. Based on the extensive data analysis, a model of this intervention could be constructed. This model could be used by other institutions, using their own data to estimate the effects of a day 2 case-audit in their hospital.

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