Irbesartan in Marfan syndrome (AIMS): a double-blind, placebo-controlled randomised trial

BACKGROUND: Irbesartan, a long acting selective angiotensin-1 receptor inhibitor, in Marfan syndrome might reduce aortic dilatation, which is associated with dissection and rupture. We aimed to determine the effects of irbesartan on the rate of aortic dilatation in children and adults with Marfan syndrome. METHODS: We did a placebo-controlled, double-blind randomised trial at 22 centres in the UK. Individuals aged 6-40 years with clinically confirmed Marfan syndrome were eligible for inclusion. Study participants were all given 75 mg open label irbesartan once daily, then randomly assigned to 150 mg of irbesartan (increased to 300 mg as tolerated) or matching placebo. Aortic diameter was measured by echocardiography at baseline and then annually. All images were analysed by a core laboratory blinded to treatment allocation. The primary endpoint was the rate of aortic root dilatation. This trial is registered with ISRCTN, number ISRCTN90011794. FINDINGS: Between March 14, 2012, and May 1, 2015, 192 participants were recruited and randomly assigned to irbesartan (n=104) or placebo (n=88), and all were followed for up to 5 years. Median age at recruitment was 18 years (IQR 12-28), 99 (52%) were female, mean blood pressure was 110/65 mm Hg (SDs 16 and 12), and 108 (56%) were taking β blockers. Mean baseline aortic root diameter was 34·4 mm in the irbesartan group (SD 5·8) and placebo group (5·5). The mean rate of aortic root dilatation was 0·53 mm per year (95% CI 0·39 to 0·67) in the irbesartan group compared with 0·74 mm per year (0·60 to 0·89) in the placebo group, with a difference in means of -0·22 mm per year (-0·41 to -0·02, p=0·030). The rate of change in aortic Z score was also reduced by irbesartan (difference in means -0·10 per year, 95% CI -0·19 to -0·01, p=0·035). Irbesartan was well tolerated with no observed differences in rates of serious adverse events. INTERPRETATION: Irbesartan is associated with a reduction in the rate of aortic dilatation in children and young adults with Marfan syndrome and could reduce the incidence of aortic complications

How Random Noise and a Graphical Convention Subverted Behavioral Scientists\u27 Explanations of Self-Assessment Data: Numeracy Underlies Better Alternatives

Despite nearly two decades of research, researchers have not resolved whether people generally perceive their skills accurately or inaccurately. In this paper, we trace this lack of resolution to numeracy, specifically to the frequently overlooked complications that arise from the noisy data produced by the paired measures that researchers employ to determine self-assessment accuracy. To illustrate the complications and ways to resolve them, we employ a large dataset (N = 1154) obtained from paired measures of documented reliability to study self-assessed proficiency in science literacy. We collected demographic information that allowed both criterion-referenced and normative-based analyses of self-assessment data. We used these analyses to propose a quantitatively based classification scale and show how its use informs the nature of self-assessment. Much of the current consensus about peoples\u27 inability to self-assess accurately comes from interpreting normative data presented in the Kruger-Dunning type graphical format or closely related (y - x) vs. (x) graphical conventions. Our data show that peoples\u27 self-assessments of competence, in general, reflect a genuine competence that they can demonstrate. That finding contradicts the current consensus about the nature of self-assessment. Our results further confirm that experts are more proficient in self-assessing their abilities than novices and that women, in general, self-assess more accurately than men. The validity of interpretations of data depends strongly upon how carefully the researchers consider the numeracy that underlies graphical presentations and conclusions. Our results indicate that carefully measured self-assessments provide valid, measurable and valuable information about proficiency

Random Number Simulations Reveal How Random Noise Affects the Measurements and Graphical Portrayals of Self-Assessed Competency

Self-assessment measures of competency are blends of an authentic self-assessment signal that researchers seek to measure and random disorder or noise that accompanies that signal. In this study, we use random number simulations to explore how random noise affects critical aspects of self-assessment investigations: reliability, correlation, critical sample size, and the graphical representations of self-assessment data. We show that graphical conventions common in the self-assessment literature introduce artifacts that invite misinterpretation. Troublesome conventions include: (y minus x) vs. (x) scatterplots; (y minus x) vs. (x) column graphs aggregated as quantiles; line charts that display data aggregated as quantiles; and some histograms. Graphical conventions that generate minimal artifacts include scatterplots with a best-fit line that depict (y) vs. (x) measures (self-assessed competence vs. measured competence) plotted by individual participant scores, and (y) vs. (x) scatterplots of collective average measures of all participants plotted item-by-item. This last graphic convention attenuates noise and improves the definition of the signal. To provide relevant comparisons across varied graphical conventions, we use a single dataset derived from paired measures of 1154 participants\u27 self-assessed competence and demonstrated competence in science literacy. Our results show that different numerical approaches employed in investigating and describing self-assessment accuracy are not equally valid. By modeling this dataset with random numbers, we show how recognizing the varied expressions of randomness in self-assessment data can improve the validity of numeracy-based descriptions of self-assessment

Random Number Simulations Reveal How Random Noise Affects the Measurements and Graphical Portrayals of Self-Assessed Competency

Self-assessment measures of competency are blends of an authentic self-assessment signal that researchers seek to measure and random disorder or noise that accompanies that signal. In this study, we use random number simulations to explore how random noise affects critical aspects of self-assessment investigations: reliability, correlation, critical sample size, and the graphical representations of self-assessment data. We show that graphical conventions common in the self-assessment literature introduce artifacts that invite misinterpretation. Troublesome conventions include: (y minus x) vs. (x) scatterplots; (y minus x) vs. (x) column graphs aggregated as quantiles; line charts that display data aggregated as quantiles; and some histograms. Graphical conventions that generate minimal artifacts include scatterplots with a best-fit line that depict (y) vs. (x) measures (self-assessed competence vs. measured competence) plotted by individual participant scores, and (y) vs. (x) scatterplots of collective average measures of all participants plotted item-by-item. This last graphic convention attenuates noise and improves the definition of the signal. To provide relevant comparisons across varied graphical conventions, we use a single dataset derived from paired measures of 1154 participants\u27 self-assessed competence and demonstrated competence in science literacy. Our results show that different numerical approaches employed in investigating and describing self-assessment accuracy are not equally valid. By modeling this dataset with random numbers, we show how recognizing the varied expressions of randomness in self-assessment data can improve the validity of numeracy-based descriptions of self-assessment

Pathology pots; linking educational value

A large, accumulated collection of pathology specimens without descriptions and with minimal labelling is being developed as a shared, multi-centre teaching resource. The aims are to create a system simple to implement over a long period of time, simple to transfer between institutions, and simple for learners to work with. We are linking the physical pathology specimen with Internet-based information by tagging the pot with machine readable code. Pathologists review pathological specimens and make a short audio recording for each, describing the visible pathology, their causes, and often including a fictitious case that aids linking of symptoms to pathology for the learner. The audio recording and relevant links are added to a custom website’s database, generating a new dynamic web-page and a unique QR code that is printed and applied to the specimen’s case. Students can use a mobile device with a QR code scanning application to scan the code and be directed to a mobile-optimised website that holds the title for the pot, a small image and a 3–5 min audio description of the visible pathology. In this way the emphasis is applied to the pathology specimen itself, aiming to encourage students to engage with the physical tissue and not solely the internet-based information

Pathological pots: a valuable physical and virtual resource

net based audio recordings were an innovation in the second year medical student respiratory morbid anatomy teaching. Short auditory stimuli were linked with a case study questions and photographs of anatomical specimens. These link pathological lesions directly to the signs and symptoms of disease. These were extremely popular with learners and accessible outside the laboratory environment. They were made to ensure all learners had equable access to the resources and an awareness of learner and pathologist teaching time being pressurised. They link pathological lesions directly to the signs and symptoms of disease. Evolution of this teaching compared favourably with previous 2 years evaluation of resource heavy teaching with physical interaction in the laboratory with the three dimensional specimen. Pod casts are a way of giving distilled and thoughtful stimuli in a resource conscious and accessible way. However, interaction with the physical three dimensional specimen is still invaluable and must be encouraged. This evaluation has encouraged the development of similar resources for different body systems

Paired Measures of Competence and Confidence Illuminate Impacts of Privilege on College Students

We seek to understand how the experiences of groups that differ in gender, ethnicity, and sexual orientation produce college-level educational performances that differ from the experiences of the dominant majority group. We employ two datasets: a National Database of 24,701 participants and a Paired-Measures Database with 3,323 participants. Both datasets provide demographic information, socioeconomic conditions of status as first-generation student, English as a first language, and interest in majoring in science, and competency scores on understanding science as a way of knowing obtained from the Science Literacy Concept Inventory. The Paired-Measures Database includes additional self-assessed competence ratings that enabled quantifying affective confidence. We meld the ways of knowing of ethics, numeracy, and social justice, especially the social justice concept of Othering, to interpret our data. Two of three competing hypotheses about self-assessment encourage Othering. Our data strongly support the third—that all groups are good at self-assessment and merit equal respect. Women and men are equally competent in science literacy. Women, on average, are more accurate in their self-assessments whereas men, on average, are overconfident. Those with minority sexual orientations register higher competence than the binary-sexual majority but are less confident of their competency. Minority ethnicities, on average, produce significantly lower science literacy scores. With one exception (Middle Eastern), groups produce mean self-assessed competence ratings that are remarkably accurate predictors of their mean competence scores. The three socioeconomic conditions exert significant and unequal impacts across ethnic groups, with Hispanic, Middle Eastern and Pacific Islander data providing some unique results