9 research outputs found

    Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

    Get PDF
    Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

    Using task network modeling to predict human error

    Get PDF
    Human error taxonomies have been implemented in numerous safety critical industries. These taxonomies have provided invaluable insight into understanding the underlying causes of human error; however, their utility for actually predicting future errors remains in question. A need has been identified for another approach to supplement what we can extrapolate from taxonomies and better predict human error. Task network modeling is a promising approach to human error prediction that had yet to be empirically evaluated. This study tested a task network modeling approach to predicting human error in the context of automotive assembly. The task network modeling architecture was expanded to include a set of predictors from the human error literature, and used to model part of an operational automotive assembly plant. This manuscript contains three studies. Study 1 tested separate task network models for two different target areas of an active automotive assembly line. Study 2 tested the validity of predictions made by the models from Study 1, both within and across samples. Study 3 tested predictions across both models on a larger sample of vehicles. The expanded architecture accounted for 21.9% to 36.5% of the variance in human error and identified 12 explanatory variables that significantly predicted the occurrence of human error. Model outputs were used to compute prediction equations that were tested using binary logistic regression and then cross-validated twice using both split-half and cross-sample validation. The predictors of Time Pressure, Visual Workload, Auditory Workload, Cognitive Workload, Psychomotor Workload, Task Frequency, Information Flow, Teamwork, and Equipment Feedback were significant predictors of human error in all three models that were tested. The variables of Information Presentation and Task Dependency varied in significance across samples, but both were significant in two out of the three models. The variables of Shift and Hour into Shift were never significant in any of the three models. The variables that were greatly stable across studies were all related to the tasks being performed by each worker at each station. The variables related to the timing of errors, on the other hand, were never significant. The results indicate that an expanded task network architecture is a great tool for predicting the situations and circumstances in which human errors will occur, but not the timing of when they will occur. Nevertheless, task network modeling demonstrated to provide useful, valid, and accurate predictions of human error and should continue to be developed as an error prediction tool.Ph.D

    Evidence-Based Human Factors Guidelines For Powerpoint Presentations

    No full text
    For decades, the vehicle of choice for idea transfer has been Microsoft\u27s PowerPoint. PowerPoint gives the orator a plethora of options in the design of a presentation. Choosing configurations for the most effective presentation can prove daunting, and even professional presentations bear witness to the difficulty of choosing wisely. Guidelines based on a collection of basic human factors/ergonomics principles and a few empirical studies are presented for effective PowerPoint presentations. © 2011 Human Factors and Ergonomics Society

    Dulaglutide and cardiovascular outcomes in type 2 diabetes (REWIND): a double-blind, randomised placebo-controlled trial

    No full text

    Health-status outcomes with invasive or conservative care in coronary disease

    No full text
    BACKGROUND In the ISCHEMIA trial, an invasive strategy with angiographic assessment and revascularization did not reduce clinical events among patients with stable ischemic heart disease and moderate or severe ischemia. A secondary objective of the trial was to assess angina-related health status among these patients. METHODS We assessed angina-related symptoms, function, and quality of life with the Seattle Angina Questionnaire (SAQ) at randomization, at months 1.5, 3, and 6, and every 6 months thereafter in participants who had been randomly assigned to an invasive treatment strategy (2295 participants) or a conservative strategy (2322). Mixed-effects cumulative probability models within a Bayesian framework were used to estimate differences between the treatment groups. The primary outcome of this health-status analysis was the SAQ summary score (scores range from 0 to 100, with higher scores indicating better health status). All analyses were performed in the overall population and according to baseline angina frequency. RESULTS At baseline, 35% of patients reported having no angina in the previous month. SAQ summary scores increased in both treatment groups, with increases at 3, 12, and 36 months that were 4.1 points (95% credible interval, 3.2 to 5.0), 4.2 points (95% credible interval, 3.3 to 5.1), and 2.9 points (95% credible interval, 2.2 to 3.7) higher with the invasive strategy than with the conservative strategy. Differences were larger among participants who had more frequent angina at baseline (8.5 vs. 0.1 points at 3 months and 5.3 vs. 1.2 points at 36 months among participants with daily or weekly angina as compared with no angina). CONCLUSIONS In the overall trial population with moderate or severe ischemia, which included 35% of participants without angina at baseline, patients randomly assigned to the invasive strategy had greater improvement in angina-related health status than those assigned to the conservative strategy. The modest mean differences favoring the invasive strategy in the overall group reflected minimal differences among asymptomatic patients and larger differences among patients who had had angina at baseline

    Initial invasive or conservative strategy for stable coronary disease

    No full text
    BACKGROUND Among patients with stable coronary disease and moderate or severe ischemia, whether clinical outcomes are better in those who receive an invasive intervention plus medical therapy than in those who receive medical therapy alone is uncertain. METHODS We randomly assigned 5179 patients with moderate or severe ischemia to an initial invasive strategy (angiography and revascularization when feasible) and medical therapy or to an initial conservative strategy of medical therapy alone and angiography if medical therapy failed. The primary outcome was a composite of death from cardiovascular causes, myocardial infarction, or hospitalization for unstable angina, heart failure, or resuscitated cardiac arrest. A key secondary outcome was death from cardiovascular causes or myocardial infarction. RESULTS Over a median of 3.2 years, 318 primary outcome events occurred in the invasive-strategy group and 352 occurred in the conservative-strategy group. At 6 months, the cumulative event rate was 5.3% in the invasive-strategy group and 3.4% in the conservative-strategy group (difference, 1.9 percentage points; 95% confidence interval [CI], 0.8 to 3.0); at 5 years, the cumulative event rate was 16.4% and 18.2%, respectively (difference, 121.8 percentage points; 95% CI, 124.7 to 1.0). Results were similar with respect to the key secondary outcome. The incidence of the primary outcome was sensitive to the definition of myocardial infarction; a secondary analysis yielded more procedural myocardial infarctions of uncertain clinical importance. There were 145 deaths in the invasive-strategy group and 144 deaths in the conservative-strategy group (hazard ratio, 1.05; 95% CI, 0.83 to 1.32). CONCLUSIONS Among patients with stable coronary disease and moderate or severe ischemia, we did not find evidence that an initial invasive strategy, as compared with an initial conservative strategy, reduced the risk of ischemic cardiovascular events or death from any cause over a median of 3.2 years. The trial findings were sensitive to the definition of myocardial infarction that was used
    corecore