Can Clinical and Surgical Parameters Be Combined to Predict How Long It Will Take a Tibia Fracture to Heal? A Prospective Multicentre Observational Study: The FRACTING Study

Healing of tibia fractures occurs over a wide time range of months, with a number of risk factors contributing to prolonged healing. In this prospective, multicentre, observational study, we investigated the capability of FRACTING (tibia FRACTure prediction healING days) score, calculated soon after tibia fracture treatment, to predict healing time. Methods: The study included 363 patients. Information on patient health, fracture morphology, and surgical treatment adopted were combined to calculate the FRACTING score. Fractures were considered healed when the patient was able to fully weight-bear without pain. Results: 319 fractures (88%) healed within 12 months from treatment. Forty-four fractures healed after 12 months or underwent a second surgery. FRACTING score positively correlated with days to healing: r = 0.63 (p < 0.0001). Average score value was 7.3 ± 2.5; ROC analysis showed strong reliability of the score in separating patients healing before versus after 6 months: AUC = 0.823. Conclusions: This study shows that the FRACTING score can be employed both to predict months needed for fracture healing and to identify immediately after treatment patients at risk of prolonged healing. In patients with high score values, new pharmacological and nonpharmacological treatments to enhance osteogenesis could be tested selectively, which may finally result in reduced disability time and health cost savings

Observed changes in the Earth’s dynamic oblateness from GRACE data and geophysical models

A new methodology is proposed to estimate changes in the Earth’s dynamic oblateness (?J2 or equivalently, ?5??C20) on a monthly basis. The algorithm uses monthly Gravity Recovery and Climate Experiment (GRACE) gravity solutions, an ocean bottom pressure model and a glacial isostatic adjustment (GIA) model. The resulting time series agree remarkably well with a solution based on satellite laser ranging (SLR) data. Seasonal variations of the obtained time series show little sensitivity to the choice of GRACE solutions. Reducing signal leakage in coastal areas when dealing with GRACE data and accounting for self-attraction and loading effects when dealing with water redistribution in the ocean is crucial in achieving close agreement with the SLR-based solution in terms of de-trended solutions. The obtained trend estimates, on the other hand, may be less accurate due to their dependence on the GIA models, which still carry large uncertainties.Geoscience & Remote SensingCivil Engineering and Geoscience

Separating Geophysical Signals Using GRACE and High-Resolution Data: A Case Study in Antarctica

To fully exploit data from the Gravity Recovery and Climate Experiment (GRACE), we separate geophysical signals observed by GRACE in Antarctica by deriving high-spatial resolution maps for present-day glacial isostatic adjustment (GIA) and ice-mass changes with the least possible noise level. For this, we simultaneously (i) improve the postprocessing of gravity data and (ii) consistently combine them with high-resolution data from Ice Cloud and land Elevation Satellite altimeter (ICESat) and Regional Atmospheric Climate Model 2.3 (RACMO). We use GPS observations to discriminate between various candidate spatial patterns of vertical motions caused by GIA. The ICESat-RACMO combination determines the spatial resolution of estimated ice-mass changes. The results suggest the capability of the developed approach to retrieve the complex spatial pattern of present-day GIA, such as a pronounced subsidence in the proximity of the Kamb Ice Stream and pronounced uplift in the Amundsen Sea Sector.Physical and Space Geodes

Geocentre motion and Earth's dynamic oblateness time-series derived from GRACE CSR RL06 solutions and geophysical models

With the launch of the Gravity Recovery and Climate Experiment (GRACE) satellite mission in 2002 (http://www.csr.utexas.edu/grace), Satellite Gravimetry has become a unique tool to estimate hydrological water balance and mass balance of ice sheets, as well as to monitor mass re-distribution in the oceans and the solid Earth. However, satellite gravimetry still suffers from a poor estimation of temporal variations in the spherical harmonic coefficient C20 (which is associated with the Earth's dynamic oblateness). Therefore, these variations are typically extracted from Satellite Laser Ranging (SLR) data. Furthermore, satellite gravimetry is not sensitive to variations of degree-1 spherical harmonic coefficients (i.e., C10, C11, and S11), which are associated with the geocentre motion. Swenson et al (2008) proposed to restore those coefficients using as a reference an area where the mass anomalies are known. Such an area was chosen as the entire world ocean; mass anomalies there were defined as variations of the Ocean Bottom Pressure based on an ocean circulation model. The Glacial Isostatic Adjustment signal was corrected for by applying a remove-restore approach.Sun et al (2016) further developed the technique by Swenson et al (2008). First, the Self-Attraction and Loading (SAL) effects were additionally modelled in order to estimate water re-distribution in the ocean more accurately. Second, a buffer zone around the continents was excluded from the reference area in order to suppress the effect of “signal leakage” caused by a limited spatial resolution of satellite gravimetry. It was shown that the modified technique allows for an accurate estimation of both degree-1 and C20 variations.Physical and Space Geodes

Postseismic GRACE and GPS observations indicate a rheology contrast above and below the Sumatra slab

More than 7 years of observations of postseismic relaxation after the 2004 Sumatra-Andaman earthquake provide an improving view on the deformation in the wide vicinity of the 2004 rupture. We include both Gravity Recovery and Climate Experiment (GRACE) gravity field data that show a large postseismic signal over the rupture area and GPS observations in the back arc region. With increasing time GPS and GRACE show contrasting relaxation styles that were not easily discernible on shorter time series. We investigate whether mantle creep can simultaneously explain the far-field surface displacements and the long-wavelength gravity changes. We interpret contrasts in the temporal behavior of the GPS-GRACE observations in terms of lateral variations in rheological properties of the asthenosphere below and above the slab. Based on 1-D viscoelastic models, our results support an (almost) order of magnitude contrast between oceanic lithosphere viscosity and continental viscosity, which likely means that the low viscosities frequently found from postseismic deformation after subduction earthquakes are valid only for the mantle wedge. Next to mantle creep, we also consider afterslip as an alternative mechanism for postseismic deformation. We investigate how the combination of GRACE and GPS data can better discriminate between different mechanisms of postseismic relaxation: distributed deformation (mantle creep) versus localized deformation (afterslip). We conclude that the GRACE-observed gravity changes rule out afterslip as the dominant mechanism explaining long-wavelength deformation even over the first year after the event.Geoscience & Remote SensingCivil Engineering and Geoscience

An approach for estimating time-variable rates from geodetic time series

There has been considerable research in the literature focused on computing and forecasting sea-level changes in terms of constant trends or rates. The Antarctic ice sheet is one of the main contributors to sea-level change with highly uncertain rates of glacial thinning and accumulation. Geodetic observing systems such as the Gravity Recovery and Climate Experiment (GRACE) and the Global Positioning System (GPS) are routinely used to estimate these trends. In an effort to improve the accuracy and reliability of these trends, this study investigates a technique that allows the estimated rates, along with co-estimated seasonal components, to vary in time. For this, state space models are defined and then solved by a Kalman filter (KF). The reliable estimation of noise parameters is one of the main problems encountered when using a KF approach, which is solved by numerically optimizing likelihood. Since the optimization problem is non-convex, it is challenging to find an optimal solution. To address this issue, we limited the parameter search space using classical least-squares adjustment (LSA). In this context, we also tested the usage of inequality constraints by directly verifying whether they are supported by the data. The suggested technique for time-series analysis is expandedPhysical and Space Geodes

DEOS mass transport model (DMT-1) based on GRACE satellite data: Methodology and validation

DEOSAerospace Engineerin

A comparison of coincident GRACE and ICESat data over Antarctica

In this study, we present a comparison of coincident GRACE and ICESat data over Antarctica. The analysis focused on the secular changes over a 4-year period spanning from 2003 to 2007, using the recently reprocessed and publicly available data sets for both missions. The results show that the two independent data sets possess strong spatial correlations, but that there are several factors that can significantly impact the total derived ice mass variability from both missions. For GRACE, the primary source of uncertainty comes from the modelling of glacial isostatic adjustment, along with the estimates of C 2,0 and the degree one terms. For ICESat, it is shown that assumptions about firn density, rate biases, and the sampling interval of the various laser campaigns can have large effects on the results. Despite these uncertainties, the similarities that do exist indicate a strong potential for the future refinement of both GIA and mass balance estimates of Antarctica.Earth Observation and Space SystemsAerospace Engineerin

Brief communication: The global signature of post-1900 land ice wastage on vertical land motion

Melting glaciers, ice caps and ice sheets have made an important contribution to sea-level rise through the last century. Self-attraction and loading effects driven by shrinking ice masses cause a spatially varying redistribution of ocean waters that affects reconstructions of past sea level from sparse observations. We model the solid-earth response to ice mass changes and find significant vertical deformation signals over large continental areas. We show how deformation rates have been strongly varying through the last century, which implies that they should be properly modelled before interpreting and extrapolating recent observations of vertical land motion and sea-level change.Physical and Space Geodes

A comparison of coincident GRACE and ICESat data over Antarctica

In this study, we present a comparison of coincident GRACE and ICESat data over Antarctica. The analysis focused on the secular changes over a 4-year period spanning from 2003 to 2007, using the recently reprocessed and publicly available data sets for both missions. The results show that the two independent data sets possess strong spatial correlations, but that there are several factors that can significantly impact the total derived ice mass variability from both missions. For GRACE, the primary source of uncertainty comes from the modelling of glacial isostatic adjustment, along with the estimates of C 2,0 and the degree one terms. For ICESat, it is shown that assumptions about firn density, rate biases, and the sampling interval of the various laser campaigns can have large effects on the results. Despite these uncertainties, the similarities that do exist indicate a strong potential for the future refinement of both GIA and mass balance estimates of Antarctica.Earth Observation and Space SystemsAerospace Engineerin