Financial Metrics In Wide-Moat Firms

According to Morningstar companies with certain structural characteristics enjoy economic moats. Compared to benchmark indices, Morningstar hypothesizes that over a ten-year time frame these firms will evidence superior price appreciation. Based on analysis of 1360 companies, this study supports the thesis of historical performance among wide-moat firms

On the Injection Energy Distibution of Ultra-High-Energy Cosmic Rays

We investigate the injection spectrum of ultra-high-energy (>10^{15} eV) cosmic rays under the hypotheses that (1) these cosmic rays are protons and (2) the sources of these cosmic rays are extra-galactic and are homogeneously distributed in space. The most puzzling aspect of the observed ultra-high-energy cosmic ray spectrum is the apparent nonexistence of a ``Greisen cut-off'' at about 10^{19.8} eV. We show that this fact could be naturally explained if most (or all) of the cosmic rays presently observed above about 10^{19.6} eV were initially injected with energy above the Greisen cut-off. However, we find that the injection of cosmic rays above the Greisen cut-off cannot account for the observed flux below about 10^{19.6} eV unless the injection rate of these particles was enormously higher in the past, as would be the case if the injection resulted from the decay of an ultra-massive particle with lifetime of order 10^{9} yr. Even with such a rapid source evolution, the observed cosmic ray spectrum below about 10^{18.5} eV cannot be explained in this manner. However, we show that a 1/E^3 injection spectrum can account for the observed spectrum below 10^{18.5} eV}, with the steepening observed by the Fly's Eye group between 10^{17.6} eV and 10^{18.5} eV being very naturally explained by e+ - e- production effects. This latter fact lends support to the hypothesis that the cosmic rays in this energy regime are protons. However, due to e+ - e- production effects, a 1/E^3 injection spectrum cannot account for the observed flux above about 10^{18.5} eV.Comment: 23 pages, REVTeX, 5 Postscript figures available by anonymous FTP at ftp://rainbow.uchicago.edu/pub/relativity/cosmicray

Occurrence rate of delirium in acute stroke settings

Background and Purpose— Delirium is associated with increased mortality, length of stay, and poor functional outcome following critical illness. The epidemiology of delirium in stroke is poorly described. We sought to collate evidence around occurrence (incidence or prevalence) of delirium in acute stroke. Methods— We searched multiple cross-disciplinary electronic databases using a prespecified search strategy, complemented by hand searching. Eligible studies described delirium in acute (first 6 weeks) stroke. We compared delirium occurrence using random-effects models to describe summary estimates. We assessed risk of bias using the Newcastle-Ottawa tool, incorporating this in sensitivity analyses. We performed subgroup analyses for delirium diagnostic method (confusion assessment method scoring, clinical diagnosis, other), duration and timing of delirium assessment (>1 or <1 week), and performed meta-regression based on the year of publication. Results— Of 8822 titles, we included 32 papers (6718 participants) in the quantitative analysis. Summary estimate for occurrence of delirium was 25% (95% CI, 20%–30%; moderate quality evidence). Limiting to studies at low risk of bias (22 studies, 4422 participants), the occurrence rate was 23% (95% CI, 17%–28%). Subgroup summary estimates suggest that delirium occurrence may vary with assessment method: confusion assessment method, 21% (95% CI, 16%–27%); clinical diagnosis, 27% (95% CI, 19%–38%); other, 32% (95% CI, 22%–43%) but not with duration and timing of assessment. Meta-regression suggested decline in occurrence of delirium comparing historical to more recent studies (slope, 0.03 [SE, 0.004]; P<0.0001). Conclusions— Delirium is common, affecting 1 in 4 acute stroke patients. Reported rates of delirium may be dependent on assessment method. Our estimate of delirium occurrence could be used for audit, to plan intervention studies, and inform clinical practice. Clinical Trial Registration— URL: http://www.crd.york.ac.uk/PROSPERO/. Unique identifier: CRD42015029251

Public interest in hyaluronic acid injections for knee osteoarthritis in the United States and Europe: An international Google Trends analysis

BACKGROUND: Hyaluronic acid injections remain a common nonsurgical alternative for the treatment of knee osteoarthritis despite limited clinical evidence and varying global recommendations regarding its use. We used the Google Trends tool to provide a quantitative analysis of public interest in hyaluronic acid injections for knee osteoarthritis in the United States and Europe. METHODS: We customized Google Trends parameters to obtain search data from January 2009 to December 2019 in both the United States and Europe. Combinations of arthritis , osteoarthritis , hyaluronic acid , knee arthritis , knee osteoarthritis , and knee injection were entered into the Google Trends tool, and trend analyses were performed. RESULTS: The models generated to describe public interest in hyaluronic acid for knee injections in both the United States and Europe showed increased Google queries as time progressed ( CONCLUSIONS: Our results indicate a significant increase in Google queries related to hyaluronic acid injections for knee osteoarthritis since 2009 in both the United States and Europe. Our models suggest that despite mixed evidence supporting its use, orthopedic surgeons should expect continued public interest in hyaluronic acid for knee osteoarthritis. The results of our study may help to prepare surgeons for patient inquiries, inform the creation of evidence-based shared decision-making tools, and direct future research

Who is classified as untestable on brief cognitive screens in an acute stroke setting?

Full completion of cognitive screening tests can be problematic in the context of a stroke. Our aim was to examine the completion of various brief cognitive screens and explore reasons for untestability. Data were collected from consecutive stroke admissions (May 2016–August 2018). The cognitive assessment was attempted during the first week of admission. Patients were classified as partially untestable (≥1 test item was incomplete) and fully untestable (where assessment was not attempted, and/or no questions answered). We assessed univariate and multivariate associations of test completion with: age (years), sex, stroke severity (National Institutes of Health Stroke Scale (NIHSS)), stroke classification, pre-morbid disability (modified Rankin Scale (mRS)), previous stroke and previous dementia diagnosis. Of 703 patients admitted (mean age: 69.4), 119 (17%) were classified as fully untestable and 58 (8%) were partially untestable. The 4A-test had 100% completion and the clock-draw task had the lowest completion (533/703, 76%). Independent associations with fully untestable status had a higher NIHSS score (odds ratio (OR): 1.18, 95% CI: 1.11–1.26), higher pre-morbid mRS (OR: 1.28, 95% CI: 1.02–1.60) and pre-stroke dementia (OR: 3.35, 95% CI: 1.53–7.32). Overall, a quarter of patients were classified as untestable on the cognitive assessment, with test incompletion related to stroke and non-stroke factors. Clinicians and researchers would benefit from guidance on how to make the best use of incomplete test data

Orbits for the Impatient: A Bayesian Rejection Sampling Method for Quickly Fitting the Orbits of Long-Period Exoplanets

We describe a Bayesian rejection sampling algorithm designed to efficiently compute posterior distributions of orbital elements for data covering short fractions of long-period exoplanet orbits. Our implementation of this method, Orbits for the Impatient (OFTI), converges up to several orders of magnitude faster than two implementations of MCMC in this regime. We illustrate the efficiency of our approach by showing that OFTI calculates accurate posteriors for all existing astrometry of the exoplanet 51 Eri b up to 100 times faster than a Metropolis-Hastings MCMC. We demonstrate the accuracy of OFTI by comparing our results for several orbiting systems with those of various MCMC implementations, finding the output posteriors to be identical within shot noise. We also describe how our algorithm was used to successfully predict the location of 51 Eri b six months in the future based on less than three months of astrometry. Finally, we apply OFTI to ten long-period exoplanets and brown dwarfs, all but one of which have been monitored over less than 3% of their orbits, producing fits to their orbits from astrometric records in the literature.Comment: 32 pages, 28 figures, Accepted to A

Cardiovascular risk factors indirectly affect acute post-stroke cognition through stroke severity and prior cognitive impairment: A moderated mediation analysis

Abstract: Background: Cognitive impairment is an important consequence of stroke and transient ischaemic attack, but its determinants are not fully understood. Simple univariable or multivariable models have not shown clinical utility for predicting cognitive impairment. Cardiovascular risk factors may influence cognition through multiple, direct, and indirect pathways, including effects on prior cognition and stroke severity. Understanding these complex relationships may help clinical teams plan intervention and follow-up strategies. Methods: We analysed clinical and demographic data from consecutive patients admitted to an acute stroke ward. Cognitive assessment comprised Abbreviated Mental Test and mini-Montreal Cognitive Assessment. We constructed bias-corrected confidence intervals to test indirect effects of cardiovascular risk factors (hypertension, vascular disease, atrial fibrillation, diabetes mellitus, previous stroke) on cognitive function, mediated through stroke severity and history of dementia, and we assessed moderation effects due to comorbidity. Results: From 594 eligible patients, we included 587 in the final analysis (age range 26–100; 45% female). Our model explained R2 = 62.10% of variance in cognitive test scores. We found evidence for an indirect effect of previous stroke that was associated with increased risk of prevalent dementia and in turn predicted poorer cognitive score (estimate = − 0.39; 95% bias-corrected CI, − 0.75 to − 0.13; p = 0.02). Atrial fibrillation was associated with greater stroke severity and in turn with a poorer cognitive score (estimate = − 0.27; 95% bias-corrected CI, − 0.49 to − 0.05; p = 0.02). Conversely, previous TIA predicted decreased stroke severity and, through that, lesser cognitive impairment (estimate = 0.38; 95% bias-corrected CI, 0.08 to 0.75; p = 0.02). Through an association with reduced stroke severity, vascular disease was associated with lesser cognitive impairment, conditional on presence of hypertension and absence of diabetes mellitus (estimate = 0.36; 95% bias-corrected CI, 0.03 to 0.68; p = 0.02), although the modelled interaction effects did not reach statistical significance. Conclusions: We have shown that relationships between cardiovascular risk factors and cognition are complex and simple multivariable models may be overly reductionist. Including direct and indirect effects of risk factors, we constructed a model that explained a substantial proportion of variation in cognitive test scores. Models that include multiple paths of influence and interactions could be used to create dementia prognostic tools for use in other healthcare settings