Designing comparative effectiveness trials of surgical ablation for atrial fibrillation: Experience of the Cardiothoracic Surgical Trials Network

ObjectiveSince the introduction of the cut-and-sew Cox maze procedure for atrial fibrillation, there has been substantial innovation in techniques for ablation. Use of alternative energy sources for ablation simplified the procedure and has resulted in dramatic increase in the number of patients with atrial fibrillation treated by surgical ablation. Despite its increasingly widespread adoption, there is lack of rigorous clinical evidence to establish this procedure as an effective clinical therapy.MethodsThis article describes a comparative effectiveness randomized trial, supported by the Cardiothoracic Surgical Clinical Trials Network, of surgical ablation with left atrial appendage closure versus left atrial appendage closure alone in patients with persistent and long-standing persistent atrial fibrillation undergoing mitral valve surgery. Nested within this trial is a further randomized comparison of 2 different lesions sets: pulmonary vein isolation and the full maze lesion set.ResultsThis article addresses trial design challenges, including how best to characterize the target population, operationalize freedom from atrial fibrillation as a primary end point, account for the impact of antiarrhythmic drugs, and measure and analyze secondary end points, such as postoperative atrial fibrillation load.ConclusionsThis article concludes by discussing how insights that emerge from this trial may affect surgical practice and guide future research in this area

A Novel Drill Set for the Enhancement and Assessment of Robotic Surgical Performance

Background: There currently exist several training modules to improve performance during video-assisted surgery. The unique characteristics of robotic surgery make these platforms an inadequate environment for the development and assessment of robotic surgical performance. Methods: Expert surgeons (n=4) (greater than 50 clinical robotic procedures and greater than 2 years of clinical robotic experience) were compared to novice surgeons (n=17) (less than 5 clinical cases and limited laboratory experience) using the da Vinci Surgical System. Seven drills were designed to simulate clinical robotic surgical tasks. Performance score was calculated by the equation Time to Completion + (minor error) x 5 + (major error) x 10. The Robotic Learning Curve (RLC) was expressed as a trend line of the performance scores corresponding to each repeated drill. Results: Performance scores for experts were better than novices in all 7 drills (p less than 0.05). The RLC for novices reflected an improvement in scores (p less than 0.05). In contrast, experts demonstrated a flat RLC for 6 drills and an improvement in one drill (p=0.027). Conclusion: This new drill set provides a framework for performance assessment during robotic surgery. The inclusion of particular drills and their role in training robotic surgeons of the future awaits larger validation studies

CosmoDC2: A Synthetic Sky Catalog for Dark Energy Science with LSST

This paper introduces cosmoDC2, a large synthetic galaxy catalog designed to support precision dark energy science with the Large Synoptic Survey Telescope (LSST). CosmoDC2 is the starting point for the second data challenge (DC2) carried out by the LSST Dark Energy Science Collaboration (LSST DESC). The catalog is based on a trillion-particle, 4.225 Gpc^3 box cosmological N-body simulation, the `Outer Rim' run. It covers 440 deg^2 of sky area to a redshift of z=3 and is complete to a magnitude depth of 28 in the r-band. Each galaxy is characterized by a multitude of properties including stellar mass, morphology, spectral energy distributions, broadband filter magnitudes, host halo information and weak lensing shear. The size and complexity of cosmoDC2 requires an efficient catalog generation methodology; our approach is based on a new hybrid technique that combines data-driven empirical approaches with semi-analytic galaxy modeling. A wide range of observation-based validation tests has been implemented to ensure that cosmoDC2 enables the science goals of the planned LSST DESC DC2 analyses. This paper also represents the official release of the cosmoDC2 data set, including an efficient reader that facilitates interaction with the data

A data compression and optimal galaxy weights scheme for Dark Energy Spectroscopic Instrument and weak lensing datasets

Combining different observational probes, such as galaxy clustering and weak lensing, is a promising technique for unveiling the physics of the Universe with upcoming dark energy experiments. The galaxy redshift sample from the Dark Energy Spectroscopic Instrument (DESI) will have a significant overlap with major ongoing imaging surveys specifically designed for weak lensing measurements: the Kilo-Degree Survey (KiDS), the Dark Energy Survey (DES) and the Hyper Suprime-Cam (HSC) survey. In this work we analyse simulated redshift and lensing catalogues to establish a new strategy for combining high-quality cosmological imaging and spectroscopic data, in view of the first-year data assembly analysis of DESI. In a test case fitting for a reduced parameter set, we employ an optimal data compression scheme able to identify those aspects of the data that are most sensitive to the cosmological information, and amplify them with respect to other aspects of the data. We find this optimal compression approach is able to preserve all the information related to the growth of structure; we also extend this scheme to derive weights to be applied to individual galaxies, and show that these produce near-optimal results.Comment: 14 pages, 12 Figures, DESI collaboration articl

Mitigating the noise of DESI mocks using analytic control variates

In order to address fundamental questions related to the expansion history of the Universe and its primordial nature with the next generation of galaxy experiments, we need to model reliably large-scale structure observables such as the correlation function and the power spectrum. Cosmological $N$-body simulations provide a reference through which we can test our models, but their output suffers from sample variance on large scales. Fortunately, this is the regime where accurate analytic approximations exist. To reduce the variance, which is key to making optimal use of these simulations, we can leverage the accuracy and precision of such analytic descriptions using Control Variates (CV). We apply two control variate formulations to mock catalogs generated in anticipation of upcoming data from the Dark Energy Spectroscopic Instrument (DESI) to test the robustness of its analysis pipeline. Our CV-reduced measurements, of the power spectrum and correlation function, both pre- and post-reconstruction, offer a factor of 5-10 improvement in the measurement error compared with the raw measurements from the DESI mock catalogs. We explore the relevant properties of the galaxy samples that dictate this reduction and comment on the improvements we find on some of the derived quantities relevant to Baryon Acoustic Oscillation (BAO) analysis. We also provide an optimized package for computing the power spectra and other two-point statistics of an arbitrary galaxy catalog as well as a pipeline for obtaining CV-reduced measurements on any of the AbacusSummit cubic box outputs. We make our scripts, notebooks, and benchmark tests against existing software publicly available and report a speed improvement of a factor of $\sim$10 for a grid size of $N_{\rm mesh} = 256^3$ compared with $\texttt{nbodykit}$.Comment: 15 pages, 9 figures, public package (for power spectrum and control variates estimation

A Spectroscopic Road Map for Cosmic Frontier: DESI, DESI-II, Stage-5

In this white paper, we present an experimental road map for spectroscopic experiments beyond DESI. DESI will be a transformative cosmological survey in the 2020s, mapping 40 million galaxies and quasars and capturing a significant fraction of the available linear modes up to z=1.2. DESI-II will pilot observations of galaxies both at much higher densities and extending to higher redshifts. A Stage-5 experiment would build out those high-density and high-redshift observations, mapping hundreds of millions of stars and galaxies in three dimensions, to address the problems of inflation, dark energy, light relativistic species, and dark matter. These spectroscopic data will also complement the next generation of weak lensing, line intensity mapping and CMB experiments and allow them to reach their full potential.Comment: Contribution to Snowmass 202