The Glasgow outcome at discharge scale: an inpatient assessment of disability after brain injury

This study assesses the validity and reliability of the Glasgow Outcome at Discharge Scale (GODS), which is a tool that is designed to assess disability after brain injury in an inpatient setting. It is derived from the Glasgow Outcome Scale-Extended (GOS-E), which assesses disability in the community after brain injury. Inter-rater reliability on the GODS is high (quadratic-weighted kappa 0.982; 95% confidence interval [CI] 0.968, 0.996) as is concurrent validity with the Disability Rating Scale (DRS) (Spearman correlation −0.728; 95% CI −0.819, −0.601). The GODS is significantly associated with physical and fatigue subscales of the short form (SF)-36 in hospital. In terms of predictive validity the GODS is highly associated with the GOS-E after discharge (Spearman correlation 0.512; 95% CI 0.281, 0.687), with the DRS, and with physical, fatigue, and social subscales of the SF-36. The GODS is recommended as an assessment tool for disability after brain injury pre-discharge and can be used in conjunction with the GOS-E to monitor disability between hospital and the community

Divergent confidence intervals among pre-specified analyses in the HiSTORIC stepped wedge trial:an exploratory post-hoc investigation

BACKGROUND: The high-sensitivity cardiac troponin on presentation to rule out myocardial infarction (HiSTORIC) study was a stepped-wedge cluster randomised trial with long before-and-after periods, involving seven hospitals across Scotland. Results were divergent for the binary safety endpoint (type 1 or type 4b myocardial infarction or cardiac death) across certain pre-specified analyses, which warranted further investigation. In particular, the calendar-matched analysis produced an odds ratio in the opposite direction to the primary logistic mixed-effects model analysis. METHODS: Several post-hoc statistical models were fitted to each of the co-primary outcomes of length of hospital stay and safety events, which included adjusting for exposure time, incorporating splines, and fitting a random time effect. We improved control of patient characteristics over time by adjusting for multiple additional covariates using different methods: direct inclusion, regression adjustment for propensity score, and weighting. A data augmentation approach was also conducted aiming to reduce the effect of sparse data bias. Finally, the raw data was examined. RESULTS: The new statistical models confirmed the results of the pre-specified trial analysis. In particular, the observed divergence between the calendar-matched and other analyses remained, even after performing the covariate adjustment methods, and after using data augmentation. Divergence was particularly acute for the safety endpoint, which had an event rate of 0.36% overall. Examining the raw data was particularly helpful to assess the sensitivity of the results to small changes in event rates and identify patterns in the data. CONCLUSIONS: Our experience reveals the importance of conducting multiple pre-specified sensitivity analyses and examining the raw data, particularly for stepped wedge trials with low event rates or with a small number of sites. Before-and-after analytical approaches that adjust for differences in patient populations but avoid direct modelling of the time trend should be considered in future stepped wedge trials with similar designs

Towards a theoretical determination of the geographical probability distribution of meteoroid impacts on Earth

Tunguska and Chelyabinsk impact events occurred inside a geographical area of only 3.4\% of the Earth's surface. Although two events hardly constitute a statistically significant demonstration of a geographical pattern of impacts, their spatial coincidence is at least tantalizing. To understand if this concurrence reflects an underlying geographical and/or temporal pattern, we must aim at predicting the spatio-temporal distribution of meteoroid impacts on Earth. For this purpose we designed, implemented and tested a novel numerical technique, the "Gravitational Ray Tracing" (GRT) designed to compute the relative impact probability (RIP) on the surface of any planet. GRT is inspired by the so-called ray-casting techniques used to render realistic images of complex 3D scenes. In this paper we describe the method and the results of testing it at the time of large impact events. Our findings suggest a non-trivial pattern of impact probabilities at any given time on Earth. Locations at $60-90\deg$ from the apex are more prone to impacts, especially at midnight. Counterintuitively, sites close to apex direction have the lowest RIP, while in the antapex RIP are slightly larger than average. We present here preliminary maps of RIP at the time of Tunguska and Chelyabinsk events and found no evidence of a spatial or temporal pattern, suggesting that their coincidence was fortuitous. We apply the GRT method to compute theoretical RIP at the location and time of 394 large fireballs. Although the predicted spatio-temporal impact distribution matches marginally the observed events, we successfully predict their impact speed distribution.Comment: 16 pages, 11 figures. Accepted for publication in MNRA