Clinical and functional impairment after nonoperative treatment of distal biceps ruptures

© 2018 Journal of Shoulder and Elbow Surgery Board of Trustees Background: Clinical and functional impairment after nonoperative treatment of distal biceps ruptures is not well understood. The goal of this study was to measure patients’ perceived disability, kinematic adjustment, and forearm supination power after nonoperative treatment of distal biceps ruptures. Methods: Fourteen individuals after nonoperative treatment of distal biceps ruptures were matched to a control group of 18 uninjured volunteers. Both groups prospectively completed the Disabilities of the Arm, Shoulder and Hand (DASH), Single Assessment Numerical Evaluation (SANE), and Biceps Disability Questionnaire. Both performed a new timed isotonic supination test that was designed to simulate activities of daily life. The isotonic torque dynamometer measures the supination arc, center of supination arc, torque, angular velocity, and power. Motion analysis quantifies forearm and shoulder contributions to the arc of supination. Results: The nonoperative treated group\u27s DASH (23.2 ± 10.3) and SANE (59.6 ± 16.2) scores demonstrated a clinical meaningful impairment. The control group showed no significant differences in kinematic values between dominant and nondominant arms (P =.854). The nonoperative biceps ruptured arms, compared with their uninjured arms, changed supination motion by decreasing the supination arc (P ≤.036), shifting the center of supination arc to a more pronated position (P ≤.030), and increasing the shoulder contribution to rotation (P ≤.001); despite this adaptation, their average corrected power of supination decreased by 47% (P =.001). Conclusion: Patients should understand that nonoperative treatment for distal biceps ruptures will result in varying degrees of functional loss as measured by the DASH, SANE, and Biceps Disability Questionnaire, change their supination kinematics during repetitive tasks, and that they will lose 47% of their supination power

The Eighth Data Release of the Sloan Digital Sky Survey: First Data from SDSS-III

The Sloan Digital Sky Survey (SDSS) started a new phase in August 2008, with new instrumentation and new surveys focused on Galactic structure and chemical evolution, measurements of the baryon oscillation feature in the clustering of galaxies and the quasar Ly alpha forest, and a radial velocity search for planets around ~8000 stars. This paper describes the first data release of SDSS-III (and the eighth counting from the beginning of the SDSS). The release includes five-band imaging of roughly 5200 deg^2 in the Southern Galactic Cap, bringing the total footprint of the SDSS imaging to 14,555 deg^2, or over a third of the Celestial Sphere. All the imaging data have been reprocessed with an improved sky-subtraction algorithm and a final, self-consistent photometric recalibration and flat-field determination. This release also includes all data from the second phase of the Sloan Extension for Galactic Understanding and Evolution (SEGUE-2), consisting of spectroscopy of approximately 118,000 stars at both high and low Galactic latitudes. All the more than half a million stellar spectra obtained with the SDSS spectrograph have been reprocessed through an improved stellar parameters pipeline, which has better determination of metallicity for high metallicity stars.Comment: Astrophysical Journal Supplements, in press (minor updates from submitted version

The Ninth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-III Baryon Oscillation Spectroscopic Survey

The Sloan Digital Sky Survey III (SDSS-III) presents the first spectroscopic data from the Baryon Oscillation Spectroscopic Survey (BOSS). This ninth data release (DR9) of the SDSS project includes 535,995 new galaxy spectra (median z=0.52), 102,100 new quasar spectra (median z=2.32), and 90,897 new stellar spectra, along with the data presented in previous data releases. These spectra were obtained with the new BOSS spectrograph and were taken between 2009 December and 2011 July. In addition, the stellar parameters pipeline, which determines radial velocities, surface temperatures, surface gravities, and metallicities of stars, has been updated and refined with improvements in temperature estimates for stars with T_eff<5000 K and in metallicity estimates for stars with [Fe/H]>-0.5. DR9 includes new stellar parameters for all stars presented in DR8, including stars from SDSS-I and II, as well as those observed as part of the SDSS-III Sloan Extension for Galactic Understanding and Exploration-2 (SEGUE-2). The astrometry error introduced in the DR8 imaging catalogs has been corrected in the DR9 data products. The next data release for SDSS-III will be in Summer 2013, which will present the first data from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) along with another year of data from BOSS, followed by the final SDSS-III data release in December 2014.Comment: 9 figures; 2 tables. Submitted to ApJS. DR9 is available at http://www.sdss3.org/dr

SDSS-III: Massive Spectroscopic Surveys of the Distant Universe, the Milky Way Galaxy, and Extra-Solar Planetary Systems

Building on the legacy of the Sloan Digital Sky Survey (SDSS-I and II), SDSS-III is a program of four spectroscopic surveys on three scientific themes: dark energy and cosmological parameters, the history and structure of the Milky Way, and the population of giant planets around other stars. In keeping with SDSS tradition, SDSS-III will provide regular public releases of all its data, beginning with SDSS DR8 (which occurred in Jan 2011). This paper presents an overview of the four SDSS-III surveys. BOSS will measure redshifts of 1.5 million massive galaxies and Lya forest spectra of 150,000 quasars, using the BAO feature of large scale structure to obtain percent-level determinations of the distance scale and Hubble expansion rate at z<0.7 and at z~2.5. SEGUE-2, which is now completed, measured medium-resolution (R=1800) optical spectra of 118,000 stars in a variety of target categories, probing chemical evolution, stellar kinematics and substructure, and the mass profile of the dark matter halo from the solar neighborhood to distances of 100 kpc. APOGEE will obtain high-resolution (R~30,000), high signal-to-noise (S/N>100 per resolution element), H-band (1.51-1.70 micron) spectra of 10^5 evolved, late-type stars, measuring separate abundances for ~15 elements per star and creating the first high-precision spectroscopic survey of all Galactic stellar populations (bulge, bar, disks, halo) with a uniform set of stellar tracers and spectral diagnostics. MARVELS will monitor radial velocities of more than 8000 FGK stars with the sensitivity and cadence (10-40 m/s, ~24 visits per star) needed to detect giant planets with periods up to two years, providing an unprecedented data set for understanding the formation and dynamical evolution of giant planet systems. (Abridged)Comment: Revised to version published in The Astronomical Journa

Flu Near You: An Online Self-reported Influenza Surveillance System in the USA

In order to simultaneously learn about influenza activity and epidemiology across the nation, we harnessed the Internet and volunteers from around the nation to develop a participatory system for monitoring influenza-like-illness, called Flu Near You. Building on the work of participatory systems in other countries, we created a platform for weekly collection of the prevalence of 10 symptoms from volunteers. A freely available website provides an illustration of the distribution of users and their symptoms, by week. After a year of operation and with user feedback, we are able to evaluate design of the platform. Subsequent years will focus on expanding the system and detailed analysis of the data

Creating a Global Dialogue on Infectious Disease Surveillance: Connecting Organizations for Regional Disease Surveillance (CORDS)

Connecting Organizations for Regional Disease Surveillance (CORDS) is an international non-governmental organization focused on information exchange between disease surveillance networks in different areas of the world. By linking regional disease surveillance networks, CORDS builds a trust-based social fabric of experts who share best practices, surveillance tools and strategies, training courses, and innovations. CORDS exemplifies the shifting patterns of international collaboration needed to prevent, detect, and counter all types of biological dangers -- not just naturally occurring infectious diseases, but also terrorist threats. Representing network-of-networks approach, the mission of CORDS is to link regional disease surveillance networks to improve global capacity to respond to infectious diseases. CORDS is an informal governance cooperative with six founding regional disease surveillance networks, with plans to expand; it works in complement and cooperatively with the World Health Organization (WHO), the World Organization for Animal Health (OIE), and the Food and Animal Organization of the United Nations (FAO). As described in detail elsewhere in this special issue of merging Health Threats, each regional network is an alliance of a small number of neighboring countries working across national borders to tackle emerging infectious diseases that require unified regional efforts. Here we describe the history, culture, and commitment of CORDS; and the novel and necessary role that CORDS serves in the existing international infectious disease surveillance framework

Participatory Disease Surveillance: Engaging Communities Directly in Reporting, Monitoring, and Responding to Health Threats

Background: Since 2012, the International Workshop on Participatory Surveillance (IWOPS) has served as an informal network to share best practices, consult on analytic methods, and catalyze innovation to advance the burgeoning method of direct engagement of populations in voluntary monitoring of disease. Objective: This landscape provides an overview of participatory disease surveillance systems in the IWOPS network and orients readers to this growing field of practice.Methods: Authors reviewed participatory approaches that include human and animal health surveillance, both syndromic (self- reported symptoms) and event-based, and how these tools have been leveraged for disease modeling and forecasting. The authors also discuss benefits, challenges, and future directions for participatory disease surveillance.Results: There are at least 23 distinct participatory surveillance tools or programs represented in the IWOPS network across 18 countries. Organizations supporting these tools are diverse in nature. Conclusions: Participatory disease surveillance is a promising method to complement both traditional, facility-based surveillance and newer digital epidemiology systems

Decreased Seasonal Influenza Rates Detected in a Crowdsourced Influenza-Like Illness Surveillance System During the COVID-19 Pandemic: Prospective Cohort Study

BackgroundSeasonal respiratory viruses had lower incidence during their 2019-2020 and 2020-2021 seasons, which overlapped with the COVID-19 pandemic. The widespread implementation of precautionary measures to prevent transmission of SARS-CoV-2 has been seen to also mitigate transmission of seasonal influenza. The COVID-19 pandemic also led to changes in care seeking and access. Participatory surveillance systems have historically captured mild illnesses that are often missed by surveillance systems that rely on encounters with a health care provider for detection. ObjectiveThis study aimed to assess if a crowdsourced syndromic surveillance system capable of detecting mild influenza-like illness (ILI) also captured the globally observed decrease in ILI in the 2019-2020 and 2020-2021 influenza seasons, concurrent with the COVID-19 pandemic. MethodsFlu Near You (FNY) is a web-based participatory syndromic surveillance system that allows participants in the United States to report their health information using a brief weekly survey. Reminder emails are sent to registered FNY participants to report on their symptoms and the symptoms of household members. Guest participants may also report. ILI was defined as fever and sore throat or fever and cough. ILI rates were determined as the number of ILI reports over the total number of reports and assessed for the 2016-2017, 2017-2018, 2018-2019, 2019-2020, and 2020-2021 influenza seasons. Baseline season (2016-2017, 2017-2018, and 2018-2019) rates were compared to the 2019-2020 and 2020-2021 influenza seasons. Self-reported influenza diagnosis and vaccination status were captured and assessed as the total number of reported events over the total number of reports submitted. CIs for all proportions were calculated via a 1-sample test of proportions. ResultsILI was detected in 3.8% (32,239/848,878) of participants in the baseline seasons (2016-2019), 2.58% (7418/287,909) in the 2019-2020 season, and 0.27% (546/201,079) in the 2020-2021 season. Both influenza seasons that overlapped with the COVID-19 pandemic had lower ILI rates than the baseline seasons. ILI decline was observed during the months with widespread implementation of COVID-19 precautions, starting in February 2020. Self-reported influenza diagnoses decreased from early 2020 through the influenza season. Self-reported influenza positivity among ILI cases varied over the observed time period. Self-reported influenza vaccination rates in FNY were high across all observed seasons. ConclusionsA decrease in ILI was detected in the crowdsourced FNY surveillance system during the 2019-2020 and 2020-2021 influenza seasons, mirroring trends observed in other influenza surveillance systems. Specifically, the months within seasons that overlapped with widespread pandemic precautions showed decreases in ILI and confirmed influenza. Concerns persist regarding respiratory pathogens re-emerging with changes to COVID-19 guidelines. Traditional surveillance is subject to changes in health care behaviors. Systems like FNY are uniquely situated to detect disease across disease severity and care seeking, providing key insights during public health emergencies

Determinants of Participants’ Follow-Up and Characterization of Representativeness in Flu Near You, A Participatory Disease Surveillance System

Background: Flu Near You (FNY) is an Internet-based participatory surveillance system in the United States and Canada that allows volunteers to report influenza-like symptoms using a brief weekly symptom report. Objective: Our objective was to evaluate the representativeness of the FNY population compared with the general population of the United States, explore the demographic and behavioral characteristics associated with FNY’s high-participation users, and summarize results from a user survey of a cohort of FNY participants. Methods: We compared (1) the representativeness of sex and age groups of FNY participants during the 2014-2015 flu season versus the general US population and (2) the distribution of Human Development Index (HDI) scores of FNY participants versus that of the general US population. We analyzed associations between demographic and behavioral factors and the level of participant follow-up (ie, high vs low). Finally, descriptive statistics of responses from FNY’s 2015 and 2016 end-of-season user surveys were calculated. Results: During the 2014-2015 influenza season, 47,234 unique participants had at least one FNY symptom report that was either self-reported (users) or submitted on their behalf (household members). The proportion of female FNY participants was significantly higher than that of the general US population (n=28,906, 61.2% vs 51.1%, P5.0, signaling that the FNY user distribution was more affluent and educated than the US population baseline. We found that high-participation use (ie, higher participation in follow-up symptom reports) was associated with sex (females were 25% less likely than men to be high-participation users), higher HDI, not reporting an influenza-like illness at the first symptom report, older age, and reporting for household members (all differences between high- and low-participation users P<.001). Approximately 10% of FNY users completed an additional survey at the end of the flu season that assessed detailed user characteristics (3217/33,324 in 2015; 4850/44,313 in 2016). Of these users, most identified as being either retired or employed in the health, education, and social services sectors and indicated that they achieved a bachelor’s degree or higher. Conclusions: The representativeness of the FNY population and characteristics of its high-participation users are consistent with what has been observed in other Internet-based influenza surveillance systems. With targeted recruitment of underrepresented populations, FNY may improve as a complementary system to timely tracking of flu activity, especially in populations that do not seek medical attention and in areas with poor official surveillance data