Rivaroxaban versus aspirin on functional and cognitive outcomes after embolic stroke of undetermined source: NAVIGATE ESUS trial

The standard assessment of global everyday activities is a valid and reliable scale to assess both physical and cognitive functionality in Turkish older adults

AIM

This study aims to evaluate the reliability and validity of the Turkish version of the Standard Assessment of Global Everyday Activities (SAGEA) scale in older adults.

METHODS

The study employed a cross-sectional, methodological design. The SAGEA scale was administered twice, with a two-week interval for test-retest reliability. The study examined correlations between the SAGEA and other functional measures including the Activities of Daily Living (BADL), Instrumental Activities of Daily Living (IADL), the Timed Up and Go Test (TUGT), and the Mini-Mental State Examination (MMSE).

RESULTS

The participants were 307 community-dwelling older adults who underwent a comprehensive geriatric assessment at a university hospital. The average age of the participants was 74.93 years. SAGEA scores showed strong correlations with BADL (-.620), IADL (-.802), TUGT (.613), and MMSE (-.784). The Cronbach alpha for internal consistency was .79, and the test-retest reliability was high (r=.99, p<.001).

CONCLUSION

The Turkish version of SAGEA (TSAGEA) is a quick, reliable, and validated scale that can be easily used in clinical practice without additional training. It effectively assesses both physical and cognitive functionality in older adults, aiding in early intervention and disability prevention.

Improving analysis of cognitive outcomes in cardiovascular trials using different statistical approaches

BACKGROUND

The Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) questionnaires are commonly used to measure global cognition in clinical trials. Because these scales are discrete and bounded with ceiling and floor effects and highly skewed, their analysis as continuous outcomes presents challenges. Normality assumptions of linear regression models are usually violated, which may result in failure to detect associations with variables of interest.

METHODS

Alternative approaches to analyzing the results of these cognitive batteries include transformations (standardization, square root, or log transformation) of the scores in the multivariate linear regression (MLR) model, the use of nonlinear beta-binomial regression (which is not dependent on the assumption of normality), or Tobit regression, which adds a latent variable to account for bounded data. We aim to empirically compare the model performance of all proposed approaches using four large randomized controlled trials (ORIGIN, TRANSCEND, COMPASS, and NAVIGATE-ESUS), and using as metrics the Akaike information criterion (AIC). We also compared the treatment effects for the methods that have the same unit of measure (i.e., untransformed MLR, beta-binomial, and Tobit).

RESULTS

The beta-binomial consistently demonstrated superior model performance, with the lowest AIC values among nearly all the approaches considered, followed by the MLR with square root and log transformations across all four studies. Notably, in ORIGIN, a substantial AIC reduction was observed when comparing the untransformed MLR to the beta-binomial, whereas other studies had relatively small AIC reductions. The beta-binomial model also resulted in a significant treatment effect in ORIGIN, while the untransformed MLR and Tobit regression showed no significance. The other three studies had similar and insignificant treatment effects among the three approaches.

CONCLUSION

When analyzing discrete and bounded outcomes, such as cognitive scores, as continuous variables, a beta-binomial regression model improves model performance, avoids spurious significance, and allows for a direct interpretation of the actual cognitive measure.

TRIALS REGISTRATION

ORIGIN (NCT00069784). Registered on October 1, 2003; TRANSCEND (NCT00153101). Registered on September 9, 2005; COMPASS (NCT01776424). Registered on January 24, 2013; NAVIGATE-ESUS (NCT02313909). Registered on December 8, 2014.

An update on novel therapies for treating patients with arterial thrombosis

INTRODUCTION

Antithrombotic therapy field is undergoing rapid and significant changes during the past decade. In addition to new therapeutic strategies with existing targets, investigators are exploring the potential use of new targets to address unmet needs to treat patients with arterial diseases.

AREAS COVERED

We aim to provide an update on and a comprehensive review of the antithrombic agents that are being explored in patients with arterial diseases. We discuss latest developments with respect to upstream antiplatelet agents, and collagen and thrombin pathway inhibitors. We searched PubMed databases for English language articles using keywords: antiplatelet agents, thrombin pathway inhibitors, collagen receptors, arterial disease.

EXPERT OPINION

Despite implementation of potent P2Y12 inhibitors, there are numerous unmet needs in the treatment of arterial diseases including ceiling effect of currently available antiplatelet agents along with and an elevated risk of bleeding. The latter observations encouraged investigators to explore new targets that can attenuate the generation of platelet-fibrin clot formation and subsequent ischemic event occurrences with minimal effect on bleeding. These targets include collagen receptors on platelets and thrombin generation including FXa, FXIa, and FXIIa. In addition, investigators are studying novel antiplatelet agents/strategies to facilitate upstream therapy in high-risk patients.