Comparative Evaluation of Stroke Triage Algorithms for Emergency Medical Dispatchers (MeDS): Prospective Cohort Study Protocol

<p>Abstract</p> <p>Background</p> <p>Stroke is a major cause of death and leading cause of disability in the United States. To maximize a stroke patient's chances of receiving thrombolytic treatment for acute ischemic stroke, it is important to improve prehospital recognition of stroke. However, it is known from published reports that emergency medical dispatchers (EMDs) using Card 28 of the Medical Priority Dispatch System protocols recognize stroke poorly. Therefore, to improve EMD's recognition of stroke, the National Association of Emergency Medical Dispatchers recently designed a new diagnostic stroke tool (Cincinnati Stroke Scale -CSS) to be used with Card 28. The objective of this study is to determine whether the addition of CSS improves diagnostic accuracy of stroke triage.</p> <p>Methods/Design</p> <p>This prospective experimental study will be conducted during a one-year period in the 911 call center of Santa Clara County, CA. We will include callers aged ≥ 18 years with a chief complaint suggestive of stroke and second party callers (by-stander or family who are in close proximity to the patient and can administer the tool) ≥ 18 years of age. Life threatening calls will be excluded from the study. Card 28 questions will be administered to subjects who meet study criteria. After completion of Card 28, CSS tool will be administered to all calls. EMDs will record their initial assessment of a cerebro-vascular accident (stroke) after completion of Card 28 and their final assessment after completion of CSS. These assessments will be compared with the hospital discharge diagnosis (ICD-9 codes) recorded in the Office of Statewide Health Planning and Development (OSHPD) database after linking the EMD database and OSHPD database using probabilistic linkage. The primary analysis will compare the sensitivity of the two stroke protocols using logistic regression and generalizing estimating equations to account for clustering by EMDs. To detect a 15% difference in sensitivity between the two groups with 80% power, we will enroll a total of 370 subjects in this trial.</p> <p>Discussion</p> <p>A three week pilot study was performed which demonstrated the feasibility of implementation of the study protocol.</p

Short-term earthquake hazard assessment for the San Andreas Fault in southern California

The southernmost 200 km of the San Andreas fault in California, from Cajon Pass southeast to Bombay Beach on the Salton Sea (Figure 1), has not produced a major earthquake within the historic record. Both geodetic evidence of continuing strain accumulation (Savage et al, 1986) and the occurrence of recent prehistoric large earthquakes (Sieh, 1986; Sieh and Williams, 1990), however, lead us to conclude that this fault segment will eventually produce great earthquakes that pose one of the greatest hazards to southern California. An estimated 1.0-1.5 million people now live adjacent to the San Andreas fault within the projected zone of severe shaking for such an earthquake. A magnitude 7.5 to 8.0 earthquake on this segment would also cause widespread damage to San Bernardino, Imperial, Riverside, Orange, and Los Angeles counties, which together have over 12 million inhabitants. For these reasons, the Southern San Andreas Fault Working Group was formed in 1989 to recommend how the scientific community might best respond to anomalous geophysical activity along the fault, increase our understanding of regional seismotectonics, and offer timely scientific advice to state and local governments

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Race and Sex Disparities in Prehospital Recognition of Acute Stroke

ObjectivesThe objective of this study was to examine prehospital provider recognition of stroke by race and sex.MethodsDiagnoses at emergency department (ED) and hospital discharge from a statewide database in California were linked to prehospital diagnoses from an electronic database from two counties in Northern California from January 2005 to December 2007 using probabilistic linkage. All patients 18 years and older, transported by ambulances (n = 309,866) within the two counties, and patients with hospital-based discharge diagnoses of stroke (n = 10,719) were included in the study. Logistic regression was used to analyze the independent association of race and sex with the correct prehospital diagnosis of stroke.ResultsThere were 10,719 patients discharged with primary diagnoses of stroke. Of those, 3,787 (35%) were transported by emergency medical services providers. Overall, 32% of patients ultimately diagnosed with stroke were identified in the prehospital setting. Correct prehospital recognition of stroke was lower among Hispanic patients (odds ratio [OR] = 0.77, 95% confidence interval [CI] 0.61 to 0.96), Asians (OR = 0.66, 95% CI 0.55 to 0.80), and others (OR = 0.71, 95% CI = 0.53 to 0.94), when compared with non-Hispanic whites, and in women compared with men (OR = 0.82, 95% CI = 0.71 to 0.94). Specificity for recognizing stroke was lower in females than males (OR = 0.84, 95% CI = 0.78 to 0.90).ConclusionsSignificant disparities exist in prehospital stroke recognition