Can co-authorship networks be used to predict author research impact? A machine-learning based analysis within the field of degenerative cervical myelopathy research.

INTRODUCTION: Degenerative Cervical Myelopathy (DCM) is a common and disabling condition, with a relatively modest research capacity. In order to accelerate knowledge discovery, the AO Spine RECODE-DCM project has recently established the top priorities for DCM research. Uptake of these priorities within the research community will require their effective dissemination, which can be supported by identifying key opinion leaders (KOLs). In this paper, we aim to identify KOLs using artificial intelligence. We produce and explore a DCM co-authorship network, to characterise researchers' impact within the research field. METHODS: Through a bibliometric analysis of 1674 scientific papers in the DCM field, a co-authorship network was created. For each author, statistics about their connections to the co-authorship network (and so the nature of their collaboration) were generated. Using these connectedness statistics, a neural network was used to predict H-Index for each author (as a proxy for research impact). The neural network was retrospectively validated on an unseen author set. RESULTS: DCM research is regionally clustered, with strong collaboration across some international borders (e.g., North America) but not others (e.g., Western Europe). In retrospective validation, the neural network achieves a correlation coefficient of 0.86 (p<0.0001) between the true and predicted H-Index of each author. Thus, author impact can be accurately predicted using only the nature of an author's collaborations. DISCUSSION: Analysis of the neural network shows that the nature of collaboration strongly impacts an author's research visibility, and therefore suitability as a KOL. This also suggests greater collaboration within the DCM field could help to improve both individual research visibility and global synergy

Bayesian Inference and Data Augmentation Schemes for Spatial, Spatiotemporal and Multivariate Log-Gaussian Cox Processes in R

Log-Gaussian Cox processes are an important class of models for spatial and spatiotemporal point-pattern data. Delivering robust Bayesian inference for this class of models presents a substantial challenge, since Markov chain Monte Carlo (MCMC) algorithms require careful tuning in order to work well. To address this issue, we describe recent advances in MCMC methods for these models and their implementation in the R package lgcp. Our suite of R functions provides an extensible framework for inferring covariate effects as well as the parameters of the latent field. We also present methods for Bayesian inference in two further classes of model based on the log-Gaussian Cox process. The first of these concerns the case where we wish to fit a point process model to data consisting of event-counts aggregated to a set of spatial regions: we demonstrate how this can be achieved using data-augmentation. The second concerns Bayesian inference for a class of marked-point processes specified via a multivariate log-Gaussian Cox process model. For both of these extensions, we give details of their implementation in R

Exploratory Analysis of Preoperative and Postoperative Risk Stratification Tools to Identify Acute Kidney and Myocardial Injury in Patients Undergoing Surgery for Chronic Subdural Haematoma.

Perioperative statistical risk stratification is widespread. Such tools inform intraoperative and postoperative care as part of the National Emergency Laparotomy Audit (NELA)1. Patients with chronic subdural haematomas (cSDH) are often elderly with significant comorbidity2. Despite this, there is a paucity of literature pertaining to risk stratification models in this cohort3. At our centre, as part of a multidisciplinary improvement initiative (the ‘Improving Care in Elderly Neurosurgery Initiative’ (ICENI)4) (Project ID:PRN7705) we demonstrated a significant association between postoperative complications and length of stay2. As a further analysis within this cohort of operated cSDH, we explore the potential of using retrospective electronic health record (EHR) data to generate prognostic statistical models for the identification of two end-organ complications (myocardial injury –troponin above the upper limit of normal and acute kidney injury (AKI) –a rise in serum creatinine of ≥ 1.5 times baseline). Outcomes were chosen based on data availability and veracity as well as clinical relevance. The integrated nature of our EHR permitted incorporation of variables reflecting intraoperative management. This enabled an exploratory analysis of models that, analogous to NELA, could be used preoperatively and updated postoperatively

Development and validation of a MEDLINE search filter/hedge for degenerative cervical myelopathy

Abstract Background Degenerative cervical myelopathy (DCM) is a common condition with many unmet clinical needs. Pooled analysis of studies is an important tool for advancing medical understanding. This process starts with a systematic search of the literature. Identification of studies in DCM is challenged by a number of factors, including non-specific terminology and index terms. Search filters or HEDGEs, are search strings developed and validated to optimise medical literature searches. We aimed to develop a search filter for DCM for the MEDLINE database. Methods The diagnostic test assessment framework of a “development dataset” and seperate “validation dataset” was used. The development dataset was formed by hand searching four leading spinal journals (Spine, Journal of Neurosurgery Spine, Spinal Cord and Journal of Spinal Disorders and Techniques) in 2005 and 2010. The search filter was initially developed focusing on sensitivity and subsequently refined using NOT functions to improve specificity. One validation dataset was formed from DCM narrative and systematic review articles and the second, articles published in April of 1989, 1993, 1997, 2001, 2005, 2009, 2013 and 2017 retrieved via the search MeSH term ‘Spine’. Metrics of sensitivity, specificity, precision and accuracy were used to test performance. Results Hand searching identified 77/1094 relevant articles for 2005 and 55/1199 for 2010. We developed a search hedge with 100% sensitivity and a precision of 30 and 29% for the 2005 and 2010 development datasets respectively. For the selected time periods, EXP Spine returned 2113 publications and 30 were considered relevant. The search filter identified all 30 relevant articles, with a specificity of 94% and precision of 20%. Of the 255 references listed in the narrative index reviews, 225 were indexed in MEDLINE and 165 (73%) were relevant articles. All relevant articles were identified and accuracy ranged from 67 to 97% over the three reviews. Of the 42 articles returned from 3 recent systematic reviews, all were identified by the filter. Conclusions We have developed a highly sensitive hedge for the research of DCM. Whilst precision is similarly low as other hedges, this search filter can be used as an adjunct for DCM search strategies

Comparative endurance testing of the Biomet Matthews Nail and the Dynamic Compression Screw, in simulated condylar and supracondylar femoral fractures

<p>Abstract</p> <p>Background</p> <p>The dynamic compression screw is a plate and screws implant used to treat fractures of the distal femur. The Biomet Matthews Nail is a new retrograde intramedullary nail designed as an alternative surgical option to treat these fractures. The objective of this study was to assess the comparative endurance of both devices.</p> <p>Method</p> <p>The dynamic compression screw (DCS) and Biomet Matthews Nail (BMN) were implanted into composite femurs, which were subsequently cyclically loaded using a materials testing machine. Simulated fractures were applied to each femur prior to the application of load. Either a Y type fracture or a transverse osteotomy was prepared on each composite femur using a jig to enable consistent positioning of cuts.</p> <p>Results</p> <p>The Biomet Matthews Nail demonstrated a greater endurance limit load over the dynamic compression screw in both fracture configurations.</p> <p>Conclusion</p> <p>The distal locking screws pass through the Biomet Matthews Nail in a unique "cruciate" orientation. This allows for greater purchase in the bone of the femoral condyle and potentially improves the stability of the fracture fixation. As these fractures are usually in weak osteoporotic bone, the Biomet Matthews Nail represents a favourable surgical option in these patients.</p

Descriptors for Electron and Hole Charge Carriers in Metal Oxides

Metal oxides can act as insulators, semiconductors, or metals depending on their chemical composition and crystal structure. Metal oxide semiconductors, which support equilibrium populations of electron and hole charge carriers, have widespread applications including batteries, solar cells, and display technologies. It is often difficult to predict in advance whether these materials will exhibit localized or delocalized charge carriers upon oxidation or reduction. We combine data from first-principles calculations of the electronic structure and dielectric response of 214 metal oxides to predict the energetic driving force for carrier localization and transport. We assess descriptors based on the carrier effective mass, static polaron binding energy, and Fröhlich electron–phonon coupling. Numerical analysis allows us to assign p- and n-type transport of a metal oxide to three classes: (i) band transport with high mobility; (ii) small polaron transport with low mobility; and (iii) intermediate behavior. The results of this classification agree with observations regarding carrier dynamics and lifetimes and are used to predict 10 candidate p-type oxides

Research Inefficiency in Degenerative Cervical Myelopathy: Findings of a Systematic Review on Research Activity Over the Past 20 Years.

STUDY DESIGN: Scoping review. OBJECTIVE: To describe activity, themes and trends in degenerative cervical myelopathy (DCM) research over the past 20 years with a view to considering DCM research inefficiency. METHODS: A systematic review of MEDLINE and Embase for "Cervical" AND "Myelopathy" was conducted following PRISMA guidelines. Full-text papers in English, exclusively studying DCM, published between January 1, 1995 and December 31, 2015 were considered eligible. Country of origin, number of papers published, number of patients studied, research theme, and year of publication were assessed. Comparison was made between developed and developing countries. RESULTS: A total of 1485 papers and 4 117 051 patients were included. Japan published more papers (450) than any other country while the United States studied the greatest number of patients (3 674 737). Over 99.4% of papers and 78.6% of patients were from developed countries. The number of papers (r = 0.96, P < .001) and patients (r = 0.83 P < .001) studied each year increased significantly overall and for both developed (r = 0.93, P < .001; r = 0.81, P < .001) and developing countries (r = 0.90, P < .001; r = 0.87, P < .001). Surgery was the most prevalent theme (58.3% papers; 55.7% patients) for developed and developing countries. Research from developing countries showed greater thematic variability. CONCLUSIONS: DCM research activity is increasing internationally, with surgery remaining the focus. Research output has predominantly been from developed countries; however, the rate of growth for developed and developing countries is comparable

A third red supergiant rich cluster in the Scutum-Crux arm

Aims. We aim to characterise the properties of a third massive, red supergiant dominated galactic cluster. Methods. To accomplish this we utilised a combination of near/mid-IR photometry and spectroscopy to identify and classify the properties of cluster members, and statistical arguments to determine the mass of the cluster. Results. We found a total of 16 strong candidates for cluster membership, for which formal classification of a subset yields spectral types from K3-M4 Ia and luminosities between log(L/L-circle dot) similar to 4.5-4.8 for an adopted distance of 6 +/- 1 kpc. For an age in the range of 16-20 Myr, the implied mass is 2-4 x 10(4) M-circle dot, making it one of the most massive young clusters in the Galaxy. This discovery supports the hypothesis that a significant burst of star formation occurred at the base of Scutum-Crux arm between 10-20 Myr ago, yielding a stellar complex comprising at least similar to 10(5) M-circle dot of stars (noting that since the cluster identification criteria rely on the presence of RSGs, we suspect that the true stellar yield will be significantly higher). We highlight the apparent absence of X-ray binaries within the star formation complex and finally, given the physical association of at least two pulsars with this region, discuss the implications of this finding for stellar evolution and the production and properties of neutron stars