IMPORTANCE Informing patients and providers of the likelihood of survival after in-hospital cardiac arrest (IHCA), neurologically intact or with minimal deficits, may be useful when discussing do-not-attempt-resuscitation orders. OBJECTIVE To develop a simple prearrest point score that can identify patients unlikely to survive IHCA, neurologically intact or with minimal deficits. DESIGN, SETTING, AND PARTICIPANTS The study included 51 240 inpatients experiencing an index episode of IHCA between January 1, 2007, and December 31, 2009, in 366 hospitals participating in the Get With the Guidelines-Resuscitation registry. Dividing data into training (44.4%), test (22.2%), and validation (33.4%) data sets, we used multivariate methods to select the best independent predictors of good neurologic outcome, created a series of candidate decision models, and used the test data set to select the model that best classified patients as having a very low (<1%), low (1%-3%), average (>3%-15%), or higher than average (>15%) likelihood of survival after in-hospital cardiopulmonary resuscitation for IHCA with good neurologic status. The final model was evaluated using the validation data set. MAIN OUTCOMES AND MEASURES Survival to discharge after in-hospital cardiopulmonary resuscitation for IHCA with good neurologic status (neurologically intact or with minimal deficits) based on a Cerebral Performance Category score of 1. RESULTS The best performing model was a simple point score based on 13 prearrest variables. The C statistic was 0.78 when applied to the validation set. It identified the likelihood of a good outcome as very low in 9.4% of patients (good outcome in 0.9%), low in 18.9% (good outcome in 1.7%), average in 54.0% (good outcome in 9.4%), and above average in 17.7% (good outcome in 27.5%). Overall, the score can identify more than one-quarter of patients as having a low or very low likelihood of survival to discharge, neurologically intact or with minimal deficits after IHCA (good outcome in 1.4%). CONCLUSIONS AND RELEVANCE The Good Outcome Following Attempted Resuscitation (GO-FAR) scoring system identifies patients who are unlikely to benefit from a resuscitation attempt should they experience IHCA. This information can be used as part of a shared decision regarding do-not-attempt-resuscitation orders.

The adsorption behavior of 4-cyanobiphenyl (CNBP) has been investigated by means of surface-enhanced Raman scattering (SERS). CNBP appeared to assume a tilted orientation on silver and gold. The presence of the ring C-H band denoted a rather vertical orientation of the biphenyl ring on Ag and Au. On the other hand, considerable red shifts of the ring-breathing modes with the increase in their bandwidths indicated a substantial π-type interaction between the benzene rings and metal substrates. On gold, the concentrationdependent SERS experiment showed CNBP to have a slightly perpendicular stance at its high surface coverage. The presence of the BH4ion in sols was found to affect the adsorption reaction and surface orientation of CNBP. The spectral band analysis based on electromagnetic selection rule indicated that CNBP should have a slightly more vertical orientation on gold than on silver at the concentration of ∼10 -4 M.

Extreme heat is the leading weather-related killer in the United States. Vulnerability to extreme heat has previously been identified and mapped in urban areas to improve heat morbidity and mortality prevention efforts. However, only limited work has examined vulnerability outside of urban locations. This study seeks to broaden the geographic context of earlier work and compute heat vulnerability across the state of Georgia, which offers diverse landscapes and populations with varying sociodemographic characteristics. Here, a modified heat vulnerability index (HVI) developed by Reid et al. is used to characterize vulnerability by county. About half of counties with the greatest heat vulnerability index scores contain the larger cities in the state (i.e., Athens, Atlanta, Augusta, Columbus, Macon, and Savannah), while the other half of high-vulnerability counties are located in more rural counties clustered in southwestern and east-central Georgia. The source of vulnerability varied between the more urban and rural high-vulnerability counties, with poverty and population of nonwhite residents driving vulnerability in the more urban counties and social isolation/population of elderly/poor health the dominant factor in the more rural counties. Additionally, the effectiveness of the HVI in identifying vulnerable populations was investigated by examining the effect of modification of the vulnerability index score with mortality during extreme heat. Except for the least vulnerable categories, the relative risk of mortality increases with increasing vulnerability. For the highest-vulnerability counties, oppressively hot days lead to a 7.7% increase in mortality.