Satellite laser ranging to GPS and GLONASS

Satellite laser ranging (SLR) to the satellites of the global navigation satellite systems (GNSS) provides substantial and valuable information about the accuracy and quality of GNSS orbits and allows for the SLR-GNSS co-location in space. In the framework of the NAVSTAR-SLR experiment two GPS satellites of Block-IIA were equipped with laser retroreflector arrays (LRAs), whereas all satellites of the GLONASS system are equipped with LRAs in an operational mode. We summarize the outcome of the NAVSTAR-SLR experiment by processing 20 years of SLR observations to GPS and 12 years of SLR observations to GLONASS satellites using the reprocessed microwave orbits provided by the center for orbit determination in Europe (CODE). The dependency of the SLR residuals on the size, shape, and number of corner cubes in LRAs is studied. We show that the mean SLR residuals and the RMS of residuals depend on the coating of the LRAs and the block or type of GNSS satellites. The SLR mean residuals are also a function of the equipment used at SLR stations including the single-photon and multi-photon detection modes. We also show that the SLR observations to GNSS satellites are important to validate GNSS orbits and to assess deficiencies in the solar radiation pressure models. We found that the satellite signature effect, which is defined as a spread of optical pulse signals due to reflection from multiple reflectors, causes the variations of mean SLR residuals of up to 15 mm between the observations at nadir angles of 0∘ and 14∘. in case of multi-photon SLR stations. For single-photon SLR stations this effect does not exceed 1 mm. When using the new empirical CODE orbit model (ECOM), the SLR mean residual falls into the range 0.1–1.8 mm for high-performing single-photon SLR stations observing GLONASS-M satellites with uncoated corner cubes. For best-performing multi-photon stations the mean SLR residuals are between −12.2 and −25.6 mm due to the satellite signature effect.

Chronic postsurgical pain in Europe: An observational study.

BACKGROUND Chronic postsurgical pain (CPSP) is an important clinical problem. Prospective studies of the incidence, characteristics and risk factors of CPSP are needed. OBJECTIVES The objective of this study is to evaluate the incidence and risk factors of CPSP. DESIGN A multicentre, prospective, observational trial. SETTING Twenty-one hospitals in 11 European countries. PATIENTS Three thousand one hundred and twenty patients undergoing surgery and enrolled in the European registry PAIN OUT. MAIN OUTCOME MEASURES Pain-related outcome was evaluated on the first postoperative day (D1) using a standardised pain outcome questionnaire. Review at 6 and 12 months via e-mail or telephonic interview used the Brief Pain Inventory (BPI) and the DN4 (Douleur Neuropathique four questions). Primary endpoint was the incidence of moderate to severe CPSP (numeric rating scale, NRS ≥3/10) at 12 months. RESULTS For 1044 and 889 patients, complete data were available at 6 and 12 months. At 12 months, the incidence of moderate to severe CPSP was 11.8% (95% CI 9.7 to 13.9) and of severe pain (NRS ≥6) 2.2% (95% CI 1.2 to 3.3). Signs of neuropathic pain were recorded in 35.4% (95% CI 23.9 to 48.3) and 57.1% (95% CI 30.7 to 83.4) of patients with moderate and severe CPSP, respectively. Functional impairment (BPI) at 6 and 12 months increased with the severity of CPSP (P < 0.01) and presence of neuropathic characteristics (P < 0.001). Multivariate analysis identified orthopaedic surgery, preoperative chronic pain and percentage of time in severe pain on D1 as risk factors. A 10% increase in percentage of time in severe pain was associated with a 30% increase of CPSP incidence at 12 months. CONCLUSION The collection of data on CPSP was feasible within the European registry PAIN OUT. The incidence of moderate to severe CPSP at 12 months was 11.8%. Functional impairment was associated with CPSP severity and neuropathic characteristics. Risk factors for CPSP in the present study were chronic preoperative pain, orthopaedic surgery and percentage of time in severe pain on D1. TRIAL REGISTRATION Clinicaltrials.gov identifier: NCT01467102.

Earth system commitments due to delayed mitigation

As long as global CO₂ emissions continue to increase annually, long-term committed Earth system changes grow much faster than current observations. A novel metric linking this future growth to policy decisions today is the mitigation delay sensitivity (MDS), but MDS estimates for Earth system variables other than peak temperature (ΔT max) are missing. Using an Earth System Model of Intermediate Complexity, we show that the current emission increase rate causes a ΔT max increase roughly 3–7.5 times as fast as observed warming, and a millenial steric sea level rise (SSLR) 7–25 times as fast as observed SSLR, depending on the achievable rate of emission reductions after the peak of emissions. These ranges are only slightly affected by the uncertainty range in equilibrium climate sensitivity, which is included in the above values. The extent of ocean acidification at the end of the century is also strongly dependent on the starting time and rate of emission reductions. The preservable surface ocean area with sufficient aragonite supersaturation for coral reef growth is diminished globally at an MDS of roughly 25%–80% per decade. A near-complete loss of this area becomes unavoidable if mitigation is delayed for a few years to decades. Also with respect to aragonite, 12%–18% of the Southern Ocean surface become undersaturated per decade, if emission reductions are delayed beyond 2015–2040. We conclude that the consequences of delaying global emission reductions are much better captured if the MDS of relevant Earth system variables is communicated in addition to current trends and total projected future changes.

External validation of the Hospital-patient One-year Mortality Risk (HOMR) model for predicting death within 1 year after hospital admission

BACKGROUND Predicting long-term survival after admission to hospital is helpful for clinical, administrative and research purposes. The Hospital-patient One-year Mortality Risk (HOMR) model was derived and internally validated to predict the risk of death within 1 year after admission. We conducted an external validation of the model in a large multicentre study. METHODS We used administrative data for all nonpsychiatric admissions of adult patients to hospitals in the provinces of Ontario (2003-2010) and Alberta (2011-2012), and to the Brigham and Women's Hospital in Boston (2010-2012) to calculate each patient's HOMR score at admission. The HOMR score is based on a set of parameters that captures patient demographics, health burden and severity of acute illness. We determined patient status (alive or dead) 1 year after admission using population-based registries. RESULTS The 3 validation cohorts (n = 2,862,996 in Ontario, 210 595 in Alberta and 66,683 in Boston) were distinct from each other and from the derivation cohort. The overall risk of death within 1 year after admission was 8.7% (95% confidence interval [CI] 8.7% to 8.8%). The HOMR score was strongly and significantly associated with risk of death in all populations and was highly discriminative, with a C statistic ranging from 0.89 (95% CI 0.87 to 0.91) to 0.92 (95% CI 0.91 to 0.92). Observed and expected outcome risks were similar (median absolute difference in percent dying in 1 yr 0.3%, interquartile range 0.05%-2.5%). INTERPRETATION The HOMR score, calculated using routinely collected administrative data, accurately predicted the risk of death among adult patients within 1 year after admission to hospital for nonpsychiatric indications. Similar performance was seen when the score was used in geographically and temporally diverse populations. The HOMR model can be used for risk adjustment in analyses of health administrative data to predict long-term survival among hospital patients.

The virtual patient in dental medicine

OBJECTIVES The aim of this Short Communication was to present a workflow for the superimposition of intraoral scan (IOS), cone-beam computed tomography (CBCT), and extraoral face scan (EOS) creating a 3D virtual dental patient. MATERIAL AND METHODS As a proof-of-principle, full arch IOS, preoperative CBCT, and mimic EOS were taken and superimposed to a unique 3D data pool. The connecting link between the different files was to detect existing teeth as constant landmarks in all three data sets. RESULTS This novel application technique successfully demonstrated the feasibility of building a craniofacial virtual model by image fusion of IOS, CBCT, and EOS under 3D static conditions. CONCLUSIONS The presented application is the first approach that realized the fusion of intraoral and facial surfaces combined with skeletal anatomy imaging. This novel 3D superimposition technique allowed the simulation of treatment planning, the exploration of the patients' expectations, and the implementation as an effective communication tool. The next step will be the development of a real-time 4D virtual patient in motion.

Cognitive rehabilitation of working memory in juvenile multiple sclerosis-effects on cognitive functioning, functional MRI and network related connectivity.

PURPOSE To assess possible effects of working memory (WM) training on cognitive functionality, functional MRI and brain connectivity in patients with juvenile MS. METHODS Cognitive status, fMRI and inter-network connectivity were assessed in 5 cases with juvenile MS aged between 12 and 18 years. Afterwards they received a computerized WM training for four weeks. Primary cognitive outcome measures were WM (visual and verbal) and alertness. Activation patterns related to WM were assessed during fMRI using an N-Back task with increasing difficulty. Inter-network connectivity analyses were focused on fronto-parietal (left and right), default-mode (dorsal and ventral) and the anterior salience network. Cognitive functioning, fMRI and inter-network connectivity were reassessed directly after the training and again nine months following training. RESULTS Response to treatment was seen in two patients. These patients showed increased performance in WM and alertness after the training. These behavioural changes were accompanied by increased WM network activation and systematic changes in inter-network connectivity. The remaining participants were non-responders to treatment. Effects on cognitive performance were maintained up to nine months after training, whereas effects observed by fMRI disappeared. CONCLUSIONS Responders revealed training effects on all applied outcome measures. Disease activity and general intelligence may be factors associated with response to treatment.