Novel Screening Tool for Stroke Using Artificial Neural Network.

BACKGROUND AND PURPOSE: The timely diagnosis of stroke at the initial examination is extremely important given the disease morbidity and narrow time window for intervention. The goal of this study was to develop a supervised learning method to recognize acute cerebral ischemia (ACI) and differentiate that from stroke mimics in an emergency setting. METHODS: Consecutive patients presenting to the emergency department with stroke-like symptoms, within 4.5 hours of symptoms onset, in 2 tertiary care stroke centers were randomized for inclusion in the model. We developed an artificial neural network (ANN) model. The learning algorithm was based on backpropagation. To validate the model, we used a 10-fold cross-validation method. RESULTS: A total of 260 patients (equal number of stroke mimics and ACIs) were enrolled for the development and validation of our ANN model. Our analysis indicated that the average sensitivity and specificity of ANN for the diagnosis of ACI based on the 10-fold cross-validation analysis was 80.0% (95% confidence interval, 71.8-86.3) and 86.2% (95% confidence interval, 78.7-91.4), respectively. The median precision of ANN for the diagnosis of ACI was 92% (95% confidence interval, 88.7-95.3). CONCLUSIONS: Our results show that ANN can be an effective tool for the recognition of ACI and differentiation of ACI from stroke mimics at the initial examination.

Sensorimotor and psychosocial determinants of 3-year incident mobility disability in middle-aged and older adults.

OBJECTIVE: to identify sensorimotor and psychosocial determinants of 3-year incident mobility disability. DESIGN: prospective. SETTING: population-based sample of community-dwelling older persons. PARTICIPANTS: community-living middle-aged and older persons (age: 50-85 years) without baseline mobility disability (n = 622). MEASUREMENTS: mobility disability, defined as self-reported inability to walk a quarter mile without resting or inability to walk up a flight of stairs unsupported, was ascertained at baseline and 3-year follow-up. Potential baseline determinant characteristics included demographics, education, social support, financial condition, knee extensor strength, visual contrast sensitivity, cognition, depression, presence of chronic conditions and history of falls. RESULTS: a total of 13.5% participant reported 3-year incident mobility disability. Age ≥75 years, female sex, knee extensor strength in the lowest quartile, visual contrast sensitivity <1.7 on the Pelli-Robson chart or significant depressive symptoms (CESD score >16) were independent determinants of 3-year incident mobility disability (ORs 1.84-16.51). CONCLUSIONS: low visual contrast sensitivity, poor knee extensor strength and significant depressive symptoms are independent determinants of future onset of mobility disability.

Prognostication via early computed tomography head in patients treated with targeted temperature management after cardiac arrest.

BACKGROUND: We evaluated computed tomography head (CTH) imaging obtained prior to targeted temperature management (TTM) in patients after cardiac arrest, and its role in prognostication. METHODS: In this retrospective cohort study in a tertiary-care hospital, 341 adults presenting with out-of-hospital cardiac arrest received a CTH prior to TTM. Associations between outcomes and neuroimaging variables were evaluated with Chi-square analysis for significant associations that yielded a composite neuroimaging score-Tennessee Early Neuroimaging Score (TENS). Univariable and multivariable logistic regression analysis including TENS as an independent variable and the four outcome dependent variables were analyzed. RESULTS: Four of the neuroimaging variables-sulcal effacement, partial gray-white matter effacement, total gray-white matter effacement, deep nuclei effacement-had significant associations with each of the four outcome variables and yielded TENS. In multivariable logistic regression models adjusted for potential confounders, TENS was associated with poor discharge CPC (OR 2.15, 95%CI 1.16-3.98, p = .015), poor disposition (OR 2.62, 95%CI 1.37-5.02, p = .004), in-hospital mortality (OR 1.99, 95%CI 1.09-3.62, p = .024), and ICU mortality (OR 1.89, 95%CI 1.12-3.20, p = .018). CONCLUSION: Imaging prior to TTM may help identify post-cardiac arrest patients with severe anoxic brain injury and poor outcomes.

Modulation of genetic associations with serum urate levels by body-mass-index in humans.

We tested for interactions between body mass index (BMI) and common genetic variants affecting serum urate levels, genome-wide, in up to 42569 participants. Both stratified genome-wide association (GWAS) analyses, in lean, overweight and obese individuals, and regression-type analyses in a non BMI-stratified overall sample were performed. The former did not uncover any novel locus with a major main effect, but supported modulation of effects for some known and potentially new urate loci. The latter highlighted a SNP at RBFOX3 reaching genome-wide significant level (effect size 0.014, 95% CI 0.008-0.02, Pinter= 2.6 x 10-8). Two top loci in interaction term analyses, RBFOX3 and ERO1LB-EDARADD, also displayed suggestive differences in main effect size between the lean and obese strata. All top ranking loci for urate effect differences between BMI categories were novel and most had small magnitude but opposite direction effects between strata. They include the locus RBMS1-TANK (men, Pdifflean-overweight= 4.7 x 10-8), a region that has been associated with several obesity related traits, and TSPYL5 (men, Pdifflean-overweight= 9.1 x 10-8), regulating adipocytes-produced estradiol. The top-ranking known urate loci was ABCG2, the strongest known gout risk locus, with an effect halved in obese compared to lean men (Pdifflean-obese= 2 x 10-4). Finally, pathway analysis suggested a role for N-glycan biosynthesis as a prominent urate-associated pathway in the lean stratum. These results illustrate a potentially powerful way to monitor changes occurring in obesogenic environment.