4 research outputs found
Outcome prediction following transcatheter aortic valve implantation: Multiple risk scores comparison
Background: The aim of the study was to compare 7 available risk models in the prediction of 30-day mortality following transcatheter aortic valve implantation (TAVI). Heart team decision supported by different risk score calculations is advisable to estimate the individual procedural risk before TAVI.
Methods: One hundred and fifty-six consecutive patients (n = 156, 48% female, mean age 80.03 ± 8.18 years) who underwent TAVI between March 2010 and October 2014 were inÂcluded in the study. Thirty-day follow-up was performed and available in each patient. BaseÂline risk was calculated according to EuroSCORE I, EuroSCORE II, STS, ACEF, Amblerâs, OBSERVANT and SURTAVI scores.
Results: In receiver operating characteristics analysis, neither of the investigated scales was able to distinguish between patients with or without an endpoint with areas under the curve (AUC) not exceeding 0.6, as follows: EuroSCORE I, AUC 0.55; 95% confidence intervals (CI) 0.47â0.63, p = 0.59; EuroSCORE II, AUC 0.59; 95% CI 0.51â0.67, p = 0.23; STS, AUC 0.55; 95% CI 0.47â0.63, p = 0.52; ACEF, AUC 0.54; 95% CI 0.46â0.62, p = 0.69; Amblerâs, AUC 0.54; 95% CI 0.46â0.62, p = 0.70; OBSERVANT, AUC 0.597; 95% CI 0.52â0.67, p = 0.21; SURTAVI, AUC 0.535; 95% CI 0.45â0.62, p = 0.65. SURTAVI model was calibrated best in high-risk patients showing coherence between expected and observed mortality (10.8% vs. 9.4%, p = 0.982). ACEF demonstrated best classification accuracy (17.5% vs. 6.9%, p = 0.053, observed mortality in high vs. non-high-risk cohort, respectively).
Conclusions: None of the investigated risk scales proved to be optimal in predicting 30-day mortality in unselected, real-life population with aortic stenosis referred to TAVI. This data supports primary role of heart team in decision process of selecting patients for TAVI
Systematic review and network meta-analysis (NMA) for cladribine tablets in achieving sustained disability improvement (SDI) in multiple sclerosis
Introduction. This study was performed to compare probabilities of SDI on the Expanded Disability Status Scale (EDSS) in patients with relapsing-remitting multiple sclerosis (RRMS), treated with cladribine tablets (CT) or fingolimod (FTY), natalizumab (NAT), alemtuzumab (ALE) and ocrelizumab (OCR).
Clinical rationale for the study. Progression of neurological disability as measured by the EDSS has been a common endpoint in multiple sclerosis (MS) trials. Novel therapies can not only slow this process, but in some patients even reverse it. This effect can be measured by the sustained disability improvement (SDI) â an endpoint that seems to continuously gain importance in clinical practice. Despite that, SDI has rarely been explored as an outcome in MS clinical studies, mostly as post-hoc analyses from randomised trials or as retrospective analyses based on patient registry records.
Material and methods. A systematic review was conducted in Medline, Embase and Cochrane to identify clinical trials (RCT or non-RCT) evaluating 6-month SDI. An indirect comparison via network meta-analysis (NMA) was performed. Bayesian inference with Markov chains Monte Carlo methods were applied.
Results. Eight trials presenting SDI results and applicable for NMA were included: six non-RCTs, with control groups selected by propensity score matching, and two RCTs. NMA results revealed that probability of achieving 6-month SDI with CT was significantly higher compared to all other high efficacy disease-modifying drugs with available data â HR (95% Crl - Bayesian Credibility Interval) vs. FTY: 4.98 (2.11â11.79); vs. NAT: 3.12 (1.31â7.27); vs. ALE: 9.29 (3.40â25.21). The main results were confirmed in the sensitivity analyses.
Conclusions. Of all considered therapies, treatment with cladribine tablets was associated with a higher probability of sustained disability improvement in RRMS patients. As this conclusion is based on available clinical data of limited quality, future studies, as well as real-world data, would be valuable to provide further evidence regarding the comparative effectiveness of RRMS therapies