Lipid changes in HIV-patients switching to the coformulated single tablet FTC/RPV/TDF (Eviplera®). Efficacy and safety analysis. GeSida Study 8114.

INTRODUCTION Rilpivirine (RPV) has a better lipid profile than efavirenz (EFV) in naïve patients (1). Switching to RPV may be convenient for many patients, while maintaining a good immunovirological control (2). The aim of this study was to analyze lipid changes in HIV-patients at 24 weeks after switching to Eviplera® (emtricitabine/RPV/tenofovir disoproxil fumarate [FTC/RPV/TDF]). MATERIALS AND METHODS Retrospective, multicentre study of a cohort of asymptomatic HIV-patients who switched from a regimen based on 2 nucleoside reverse transcriptase inhibitors (NRTI)+protease inhibitor (PI)/non nucleoside reverse transcriptase inhibitor (NNRTI) or ritonavir boosted PI monotherapy to Eviplera® during February-December, 2013; all had undetectable HIV viral load for ≥3 months prior to switching. Patients with previous failures on antiretroviral therapy (ART) including TDF and/or FTC/3TC, with genotype tests showing resistance to components of Eviplera®, or who had changed the third drug of the ART during the study period were excluded. Changes in lipid profile and cardiovascular risk (CVR), and efficacy and safety at 24 weeks were analyzed. RESULTS Among 305 patients included in the study, 298 were analyzed (7 cases were excluded due to lack of data). Men 81.2%, mean age 44.5 years, 75.8% of HIV sexually transmitted. 233 (78.2%) patients switched from a regimen based on 2 NRTI+NNRTI (90.5% EFV/FTC/TDF). The most frequent reasons for switching were central nervous system (CNS) adverse events (31.0%), convenience (27.6%) and metabolic disorders (23.2%). At this time, 293 patients have reached 24 weeks: 281 (95.9%) have continued Eviplera®, 6 stopped it (3 adverse events, 2 virologic failures, 1 discontinuation) and 6 have been lost to follow up. Lipid profiles of 283 cases were available at 24 weeks and mean (mg/dL) baseline vs 24 weeks are: total cholesterol (193 vs 169; p=0.0001), HDL-c (49 vs 45; p=0.0001), LDL-c (114 vs 103; p=0.001), tryglycerides (158 vs 115; p=0.0001), total cholesterol to HDL-c ratio (4.2 vs 4.1; p=0.3). CVR decreased (8.7 vs 7.5%; p= 0.0001). CD4 counts were similar to baseline (653 vs 674 cells/µL; p=0.08), and 274 (96.8%) patients maintained viral suppression. CONCLUSIONS At 24 weeks after switching to Eviplera®, lipid profile and CVR improved while maintaining a good immunovirological control. Most subjects switched to Eviplera® from a regimen based on NNRTI, mainly EFV/FTC/TDF. CNS adverse events, convenience and metabolic disorders were the most frequent reasons for switching.

Evaluation of the new advanced 15-loci MIRU-VNTR genotyping tool in Mycobacterium tuberculosis molecular epidemiology studies

Background. During the last few years, PCR-based methods have been developed to simplify and reduce the time required for genotyping Mycobacterium tuberculosis (MTB) by standard approaches based on IS6110-Restriction Fragment Length Polymorphism (RFLP). Of these, MIRU-12-VNTR (Mycobacterial interspersed repetitive units- variable number of tandem repeats) (MIRU-12) has been considered a good alternative. Nevertheless, some limitations and discrepancies with RFLP, which are minimized if the technique is complemented with spoligotyping, have been found. Recently, a new version of MIRU-VNTR targeting 15 loci (MIRU-15) has been proposed to improve the MIRU-12 format. Results. We evaluated the new MIRU-15 tool in two different samples. First, we analyzed the same convenience sample that had been used to evaluate MIRU-12 in a previous study, and the new 15-loci version offered higher discriminatory power (Hunter-Gaston discriminatory index [HGDI]: 0.995 vs 0.978; 34.4% of clustered cases vs 57.5%) and better correlation (full or high correlation with RFLP for 82% of the clusters vs 47%). Second, we evaluated MIRU-15 on a population-based sample and, once again, good correlation with the RFLP clustering data was observed (for 83% of the RFLP clusters). To understand the meaning of the discrepancies still found between MIRU-15 and RFLP, we analyzed the epidemiological data for the clustered patients. In most cases, splitting of RFLP-clustered patients by MIRU-15 occurred for those without epidemiological links, and RFLP-clustered patients with epidemiological links were also clustered by MIRU-15, suggesting a good epidemiological background for clustering defined by MIRU-15. Conclusion. The data obtained by MIRU-15 suggest that the new design is very efficient at assigning clusters confirmed by epidemiological data. If we add this to the speed with which it provides results, MIRU-15 could be considered a suitable tool for real-time genotyping.

Prognostic factors in left-sided endocarditis: results from the andalusian multicenter cohort

Despite medical advances, mortality in infective endocarditis (IE) is still very high. Previous studies on prognosis in IE have observed conflicting results. The aim of this study was to identify predictors of in-hospital mortality in a large multicenter cohort of left-sided IE.Methods An observational multicenter study was conducted from January 1984 to December 2006 in seven hospitals in Andalusia, Spain. Seven hundred and five left-side IE patients were included. The main outcome measure was in-hospital mortality. Several prognostic factors were analysed by univariate tests and then by multilogistic regression model. Results.The overall mortality was 29.5% (25.5% from 1984 to 1995 and 31.9% from 1996 to 2006; Odds Ratio 1.25; 95% Confidence Interval: 0.97-1.60; p = 0.07). In univariate analysis, age, comorbidity, especially chronic liver disease, prosthetic valve, virulent microorganism such as Staphylococcus aureus, Streptococcus agalactiae and fungi, and complications (septic shock, severe heart failure, renal insufficiency, neurologic manifestations and perivalvular extension) were related with higher mortality. Independent factors for mortality in multivariate analysis were: Charlson comorbidity score (OR: 1.2; 95% CI: 1.1-1.3), prosthetic endocarditis (OR: 1.9; CI: 1.2-3.1), Staphylococcus aureus aetiology (OR: 2.1; CI: 1.3-3.5), severe heart failure (OR: 5.4; CI: 3.3-8.8), neurologic manifestations (OR: 1.9; CI: 1.2-2.9), septic shock (OR: 4.2; CI: 2.3-7.7), perivalvular extension (OR: 2.4; CI: 1.3-4.5) and acute renal failure (OR: 1.69; CI: 1.0-2.6). Conversely, Streptococcus viridans group etiology (OR: 0.4; CI: 0.2-0.7) and surgical treatment (OR: 0.5; CI: 0.3-0.8) were protective factors.Conclusions Several characteristics of left-sided endocarditis enable selection of a patient group at higher risk of mortality. This group may benefit from more specialised attention in referral centers and should help to identify those patients who might benefit from more aggressive diagnostic and/or therapeutic procedures.

Expert study: A bolus calculator improves glycemic control and quality of life of type 1 diabetic patients (T1DM) (preliminary results)

Aims: To evaluate the impact on glycemic control and quality of life of a bolus calculator. Methods: Multicentre randomized prospective crosssectional study. Patients were randomized to control phase (3 months; calculation of prandial insulin according to insulinto-carbohydrate ratio and insulin sensitivity factor using a single strip meter) or intervention phase (3 months; calculation of prandial insulin with a bolus advisor), with a washout period (3 months). Patients wore a continuous glucosensor (7 days) and answered a quality of life questionnaire at the beginning and at the end of each phase. A questionnaire of satisfaction was obtained at the end of both phases. Inclusion criteria: Adults; T1DM> 1 year, HbA1c > 7.5%, basal-bolus therapy with insulin analogs, experience with carbohydrate Results: Data from the first 32 subjects with at least 1 ended phase (27 females, age 38 – 11 years, diabetes duration 16.8 – 7.5 years). Basal characteristics were comparable independently of the starting phase. No differences were found between phases in terms of mean blood glucose, standard deviation (from meter neither from sensor) and satisfaction. Conclusions: The use of a bolus calculator improves glycemic control and quality of life of T1DM subjects.