A high-resolution Antarctic grounding zone product from ICESat-2 laser altimetry

The Antarctic grounding zone, which is the transition between the fully grounded ice sheet to freely floating ice shelf, plays a critical role in ice sheet stability, mass budget calculations, and ice sheet model projections. It is therefore important to continuously monitor its location and migration over time. Here we present the first ICESat-2-derived high-resolution grounding zone product of the Antarctic Ice Sheet, including three important boundaries: the inland limit of tidal flexure (Point F), inshore limit of hydrostatic equilibrium (Point H), and the break in slope (Point Ib). This dataset was derived from automated techniques developed in this study, using ICESat-2 laser altimetry repeat tracks between 30 March 2019 and 30 September 2020. The new grounding zone product has a near-complete coverage of the Antarctic Ice Sheet with a total of 21 346 Point F, 18 149 Point H, and 36 765 Point Ib locations identified, including the difficult-to-survey grounding zones, such as the fast-flowing glaciers draining into the Amundsen Sea embayment. The locations of newly derived ICESat-2 landward limit of tidal flexure agree well with the most recent differential synthetic aperture radar interferometry (DInSAR) observations in 2018, with a mean absolute separation and standard deviation of 0.02 and 0.02 km, respectively. By comparing the ICESat-2-derived grounding zone with the previous grounding zone products, we find a grounding line retreat of up to 15 km on the Crary Ice Rise of Ross Ice Shelf and a pervasive landward grounding line migration along the Amundsen Sea embayment during the past 2 decades. We also identify the presence of ice plains on the Filchner–Ronne Ice Shelf and the influence of oscillating ocean tides on grounding zone migration. The product derived from this study is available at https://doi.org/10.5523/bris.bnqqyngt89eo26qk8keckglww (Li et al., 2021) and is archived and maintained at the National Snow and Ice Data Center

The scope of the Kalman filter for spatio-temporal applications in environmental science

The Kalman filter is a workhorse of dynamical modeling. But there are challenges when using the Kalman filter in environmental science: the complexity of environmental processes, the complicated and irregular nature of many environmental datasets, and the scale of environmental datasets, which may comprise many thousands of observations per time-step. We show how these challenges can be met within the Kalman filter, identifying some situations which are relatively easy to handle, such as datasets which are high-resolution in time, and some which are hard, like areal observations on small contiguous polygons. Overall, we conclude that many applications in environmental science are within the scope of the Kalman filter, or its generalizations

Incidence, nature and causes of avoidable significant harm in primary care in England:retrospective case note review

Objective To estimate the incidence of avoidable significant harm in primary care in England; describe and classify the associated patient safety incidents and generate suggestions to mitigate risks of ameliorable factors contributing to the incidents. Design Retrospective case note review. Patients with significant health problems were identified and clinical judgements were made on avoidability and severity of harm. Factors contributing to avoidable harm were identified and recorded. Setting Primary care. Participants Thirteen general practitioners (GPs) undertook a retrospective case note review of a sample of 14 407 primary care patients registered with 12 randomly selected general practices from three regions in England (total list size: 92 255 patients). Main outcome measures The incidence of significant harm considered at least ‘probably avoidable’ and the nature of the safety incidents. Results The rate of significant harm considered at least probably avoidable was 35.6 (95% CI 23.3 to 48.0) per 100 000 patient-years (57.9, 95% CI 42.2 to 73.7, per 100 000 based on a sensitivity analysis). Overall, 74 cases of avoidable harm were detected, involving 72 patients. Three types of incident accounted for more than 90% of the problems: problems with diagnosis accounted for 45/74 (60.8%) primary incidents, followed by medication-related problems (n=19, 25.7%) and delayed referrals (n=8, 10.8%). In 59 (79.7%) cases, the significant harm could have been identified sooner (n=48) or prevented (n=11) if the GP had taken actions aligned with evidence-based guidelines. Conclusion There is likely to be a substantial burden of avoidable significant harm attributable to primary care in England with diagnostic error accounting for most harms. Based on the contributory factors we found, improvements could be made through more effective implementation of existing information technology, enhanced team coordination and communication, and greater personal and informational continuity of care

Understanding the epidemiology of avoidable significant harm in primary care:Protocol for a retrospective cross-sectional study

Introduction: Most patient safety research has focused on specialist-care settings where there is an appreciation of the frequency and causes of medical errors, and the resulting burden of adverse events. There have, however, been few large-scale robust studies that have investigated the extent and severity of avoidable harm in primary care. To address this, we will conduct a 12-month retrospective cross-sectional study involving case note review of primary care patients. Methods and Analysis: We will conduct electronic searches of general practice (GP) clinical computer systems to identify patients with avoidable significant harm. Up to sixteen general practices from three areas of England (East Midlands, London and the North West) will be recruited based on practice size, to obtain a sample of around 100,000 patients. Our investigations will include an ‘enhanced sample’ of patients with the highest risk of avoidable significant harm. We will estimate the incidence of avoidable significant harm and express this as ‘per 100,000 patients per year’. Univariate and multivariate analysis will be conducted to identify the factors associated with avoidable significant harm. Ethics/Dissemination: The decision regarding participation by general practices in the study is entirely voluntary; the consent to participate may be withdrawn at any time. We will not seek individual patient consent for the retrospective case note review, but if patients respond to publicity about the project and say they do not wish their records to be included we will follow these instructions. We will produce a report for the Department of Health’s Policy Research Programme and several high-quality peer-reviewed publications in scientific journals. The study has been granted a favourable opinion by the East Midlands Nottingham 2 Research Ethics Committee (reference 15/EM/0411) and Confidentiality Advisory Group approval for access to medical records without consent under section 251 of the NHS Act 2006 (reference 15/CAG/0182)

A patient safety toolkit for family practices

Objectives: Major gaps remain in our understanding of primary care patient safety. We describe a toolkit for measuring patient safety in family practices. Methods: Six tools were used in 46 practices. These tools were: NHS Education for Scotland Trigger Tool, NHS Education for Scotland Medicines Reconciliation Tool, Primary Care Safequest, Prescribing Safety Indicators, PREOS-PC, and Concise Safe Systems Checklist. Results: PC-Safequest showed that most practices had a well-developed safety climate. However, the Trigger Tool revealed that a quarter of events identified were associated with moderate or substantial harm, with a third originating in primary care and avoidable. Although medicines reconciliation was undertaken within 2 days in >70% of cases, necessary discussions with a patient/carer did not always occur. The prescribing safety indicators identified 1,435 instances of potentially hazardous prescribing or lack of recommended monitoring (from 92,649 patients). The Concise Safe Systems Checklist found that 25% of staff thought their practice provided inadequate follow-up for vulnerable patients discharged from hospital and inadequate monitoring of non-collection of prescriptions. Most patients had a positive perception of the safety of their practice although 45% identified at least one safety problem in the past year. Conclusions: Patient safety is complex and multidimensional. The Patient Safety Toolkit is easy to use and hosted on a single platform with a collection of tools generating practical and actionable information. It enables family practices to identify safety deficits that they can review and change procedures to improve their patient safety across a key sets of patient safety issues

Factors Associated with Revision Surgery after Internal Fixation of Hip Fractures

Background: Femoral neck fractures are associated with high rates of revision surgery after management with internal fixation. Using data from the Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trial evaluating methods of internal fixation in patients with femoral neck fractures, we investigated associations between baseline and surgical factors and the need for revision surgery to promote healing, relieve pain, treat infection or improve function over 24 months postsurgery. Additionally, we investigated factors associated with (1) hardware removal and (2) implant exchange from cancellous screws (CS) or sliding hip screw (SHS) to total hip arthroplasty, hemiarthroplasty, or another internal fixation device. Methods: We identified 15 potential factors a priori that may be associated with revision surgery, 7 with hardware removal, and 14 with implant exchange. We used multivariable Cox proportional hazards analyses in our investigation. Results: Factors associated with increased risk of revision surgery included: female sex, [hazard ratio (HR) 1.79, 95% confidence interval (CI) 1.25-2.50; P = 0.001], higher body mass index (fo

Increasing frailty is associated with higher prevalence and reduced recognition of delirium in older hospitalised inpatients: results of a multi-centre study

Purpose: Delirium is a neuropsychiatric disorder delineated by an acute change in cognition, attention, and consciousness. It is common, particularly in older adults, but poorly recognised. Frailty is the accumulation of deficits conferring an increased risk of adverse outcomes. We set out to determine how severity of frailty, as measured using the CFS, affected delirium rates, and recognition in hospitalised older people in the United Kingdom. Methods: Adults over 65 years were included in an observational multi-centre audit across UK hospitals, two prospective rounds, and one retrospective note review. Clinical Frailty Scale (CFS), delirium status, and 30-day outcomes were recorded. Results: The overall prevalence of delirium was 16.3% (483). Patients with delirium were more frail than patients without delirium (median CFS 6 vs 4). The risk of delirium was greater with increasing frailty [OR 2.9 (1.8–4.6) in CFS 4 vs 1–3; OR 12.4 (6.2–24.5) in CFS 8 vs 1–3]. Higher CFS was associated with reduced recognition of delirium (OR of 0.7 (0.3–1.9) in CFS 4 compared to 0.2 (0.1–0.7) in CFS 8). These risks were both independent of age and dementia. Conclusion: We have demonstrated an incremental increase in risk of delirium with increasing frailty. This has important clinical implications, suggesting that frailty may provide a more nuanced measure of vulnerability to delirium and poor outcomes. However, the most frail patients are least likely to have their delirium diagnosed and there is a significant lack of research into the underlying pathophysiology of both of these common geriatric syndromes

Constructing large nonstationary spatio-temporal covariance models via compositional warpings

Understanding and predicting environmental phenomena often requires the construction of spatio-temporal statistical models, which are typically Gaussian processes. A common assumption made on Gaussian processes is that of covariance stationarity, which is unrealistic in many geophysical applications. In this article, we introduce a deep-learning-inspired approach to construct descriptive nonstationary spatio-temporal models by modeling stationary processes on warped spatio-temporal domains. The warping functions we use are constructed using several simple injective warping units which, when combined through composition, can induce complex warpings. A stationary spatio-temporal covariance function on the warped domain induces covariance nonstationarity on the original domain. Sparse linear algebraic methods are used to reduce the computational complexity when fitting the model in a big data setting. We show that our proposed nonstationary spatio-temporal model can capture covariance nonstationarity in both space and time, and provide better probabilistic predictions than conventional stationary models in both simulation studies and on a real-world data set