Learning from Failure – An Important Step in Innovation

There is a reluctance to publish “negative” data in many fields. However, there is so much to be learned from what did not work! Failure can be an important step in innovation. Health professional educators around the world strive to deliver effective SP-based interventions for their learners by leveraging on the strengths and opportunities whilst mitigating any challenges they face in their local context. The pandemic has created unprecedented pressure to “try something new” as we navigate the prevailing safe management measures and restrictions imposed at various levels (government, organizational, personal preference). Whilst many adaptations result in effective interventions, sometimes we learn more from the innovations that did not go quite as planned. The ability to see failure as a stepping-stone to success is a quality we should celebrate. The Association of SP Educators (ASPE) International Committee is charged with building member networks, identifying cultural differences in context and approach to SP simulation, and outlining needs of international SP programs. In this spirit, SP educators from the ASPE International Committee, representing several countries, will present examples of times they learned a great deal through trial and error. They will offer suggestions for adaptations of SP practice and describe lessons learned with reference to the ASPE Standards of Best Practice and with particular emphasis on ethical components, including safe work practices. Workshop Objectives Describe ways in which the COVID-19 pandemic has been a driver for change Explore examples of innovations and adaptations to practice Reflect on the value of failure as a steppingstone in innovation Planned Format Through a series of micro presentations interspersed with large and small group discussions, we will hear examples of lessons learned through innovation during a time of unprecedented change

Enhancing 3D Mesh Topological Skeletons with Discrete Contour Constrictions

International audienceThis paper describes a unified and fully automatic algorithm for Reeb graph construction and simplification as well as constriction approximation on triangulated surfaces. The key idea of the algorithm is that discrete contours - curves carried by the edges of the mesh and approximating the continuous contours of a mapping function - encode both topological and geometrical shape characteristics. Therefore, a new concise shape representation, enhanced topological skeletons, is proposed, encoding contours' topological and geometrical evolution. Firstly, mesh feature points are computed. Then they are used as geodesic origins for the computation of an invariant mapping function that reveals the shape most significant features. Secondly, for each vertex in the mesh, its discrete contour is computed. As the set of discrete contours recovers the whole surface, each of them can be analyzed, both to detect topological changes and constrictions. Constriction approximations enable Reeb graphs refinement into more visually meaningful skeletons, that we refer as enhanced topological skeletons. Extensive experiments showed that, without preprocessing stage, proposed algorithms are fast in practice, affine-invariant and robust to a variety of surface degradations (surface noise, mesh sampling and model pose variations). These properties make enhanced topological skeletons interesting shape abstractions for many computer graphics applications

Statin Use and Risk of Diabetes Mellitus in Postmenopausal Women in the Women\u27s Health Initiative

BACKGROUND: This study investigates whether the incidence of new-onset diabetes mellitus (DM) is associated with statin use among postmenopausal women participating in the Women\u27s Health Initiative (WHI). METHODS: The WHI recruited 161 808 postmenopausal women aged 50 to 79 years at 40 clinical centers across the United States from 1993 to 1998 with ongoing follow-up. The current analysis includes data through 2005. Statin use was captured at enrollment and year 3. Incident DM status was determined annually from enrollment. Cox proportional hazards models were used to estimate the risk of DM by statin use, with adjustments for propensity score and other potential confounding factors. Subgroup analyses by race/ethnicity, obesity status, and age group were conducted to uncover effect modification. RESULTS: This investigation included 153 840 women without DM and no missing data at baseline. At baseline, 7.04% reported taking statin medication. There were 10 242 incident cases of self-reported DM over 1 004 466 person-years of follow-up. Statin use at baseline was associated with an increased risk of DM (hazard ratio [HR], 1.71; 95% CI, 1.61-1.83). This association remained after adjusting for other potential confounders (multivariate-adjusted HR, 1.48; 95% CI, 1.38-1.59) and was observed for all types of statin medications. Subset analyses evaluating the association of self-reported DM with longitudinal measures of statin use in 125 575 women confirmed these findings. CONCLUSIONS: Statin medication use in postmenopausal women is associated with an increased risk for DM. This may be a medication class effect. Further study by statin type and dose may reveal varying risk levels for new-onset DM in this population

Statin Use and Risk of Diabetes in Postmenopausal Women in the Women’s Health Initiative

BACKGROUND: This study investigates whether the incidence of new-onset diabetes mellitus (DM) is associated with statin use among postmenopausal women participating in the Women\u27s Health Initiative (WHI). METHODS: The WHI recruited 161,808 postmenopausal women aged 50 to 79 years at 40 clinical centers across the United States from 1993 to 1998 with ongoing follow-up. The current analysis includes data through 2005. Statin use was captured at enrollment and year 3. Incident DM status was determined annually from enrollment. Cox proportional hazards models were used to estimate the risk of DM by statin use, with adjustments for propensity score and other potential confounding factors. Subgroup analyses by race/ethnicity, obesity status, and age group were conducted to uncover effect modification. RESULTS: This investigation included 153,840 women without DM and no missing data at baseline. At baseline, 7.04% reported taking statin medication. There were 10,242 incident cases of self-reported DM over 1,004,466 person-years of follow-up. Statin use at baseline was associated with an increased risk of DM (hazard ratio [HR], 1.71; 95% CI, 1.61-1.83). This association remained after adjusting for other potential confounders (multivariate-adjusted HR, 1.48; 95% CI, 1.38-1.59) and was observed for all types of statin medications. Subset analyses evaluating the association of self-reported DM with longitudinal measures of statin use in 125,575 women confirmed these findings. CONCLUSIONS: Statin medication use in postmenopausal women is associated with an increased risk for DM. This may be a medication class effect. Further study by statin type and dose may reveal varying risk levels for new-onset DM in this population