In the present study, patient condition was classified into seven categories in order to compare the estimated life threat risk to the patients’ state or severity: death confirmed at the

scene (they were not transported to hospital), resulted in death at emergency departments, life-threatening condition with CPA, life-threatening condition without CPA, serious but not life-threatening condition, moderate condition, and mild condition. The data used in this study did not include personal information such as the patients’ names and addresses. Use of data from the city’s computer-based record system was in accordance with two EX 527 municipal ordinances enacted Inhibitors,research,lifescience,medical by the Yokohama municipal assembly: the Free Access to Information Ordinance (enacted February 25, 2000); and the Protection of Personal Information Inhibitors,research,lifescience,medical Ordinance (enacted February 25, 2000). The study was approved by the ethics committee of the Yokohama City University School of Medicine. Algorithm for estimating a patient’s life threat risk A computer algorithm estimates a patient’s life threat risk. The algorithm was constructed with a logistic model [15]. The probability, P, of the life threat risk as assessed from an emergency

call was expressed as: where β reflects the impact of information x obtained via interview with the caller; ‘x’ consists of information regarding the patient’s consciousness level, breathing status, walking ability, position (standing, Inhibitors,research,lifescience,medical sitting, Inhibitors,research,lifescience,medical or lying) and other signs such as cyanosis and sweating. Coefficient β differs by the type of caller: a family member, nursing home staff, or third party (not patients themselves, nor family members, nor nursing home staff). If the value of P was higher than 0.1 (10%), patients were categorized Inhibitors,research,lifescience,medical as A+. The values of the coefficients used in the logistic

models in the computer algorithm are shown in Table ​Table1.1. The coefficients of variables were estimated from a trial (sample size was 4,301) prior to the start of the new system with multivariate logistic analyses, in which the independent variables equals 1 if the patient’s condition resulted in death or was recognized as life-threatening at the ED, and 0 if classified under one of the less serious categories [14]. In the analyses, age strata, consciousness level, breathing status, and walking ability were treated as categorical variables and other variables were treated as dummy variables. Levetiracetam No model exists to estimate the life threat risk from calls made by patients themselves. The algorithm had been used under the Yokohama New Emergency System, which started from October 1st, 2008. Table 1 Coefficients of variables in the logistic model applied for estimating the patient’s life threat risk Review of the algorithm for estimating a patient’s life threat risk First, the patient’s estimated life threat risk at the moment of the emergency call was compared with the state or severity of the patient’s condition.