External Validation of Updated Prediction Models for Neurological Outcomes at 90 Days in Patients With Out-of-Hospital Cardiac Arrest.

BACKGROUND: Few prediction models for individuals with early-stage out-of-hospital cardiac arrest (OHCA) have undergone external validation. This study aimed to externally validate updated prediction models for OHCA outcomes using a large nationwide dataset. METHODS AND RESULTS: We performed a secondary analysis of the JAAM-OHCA (Comprehensive Registry of In-Hospital Intensive Care for Out-of-Hospital Cardiac Arrest Survival and the Japanese Association for Acute Medicine Out-of-Hospital Cardiac Arrest) registry. Previously developed prediction models for patients with cardiac arrest who achieved the return of spontaneous circulation were updated. External validation was conducted using data from 56 institutions from the JAAM-OHCA registry. The primary outcome was a dichotomized 90-day cerebral performance category score. Two models were updated using the derivation set (n=3337). Model 1 included patient demographics, prehospital information, and the initial rhythm upon hospital admission; Model 2 included information obtained in the hospital immediately after the return of spontaneous circulation. In the validation set (n=4250), Models 1 and 2 exhibited a C-statistic of 0.945 (95% CI, 0.935-0.955) and 0.958 (95% CI, 0.951-0.960), respectively. Both models were well-calibrated to the observed outcomes. The decision curve analysis showed that Model 2 demonstrated higher net benefits at all risk thresholds than Model 1. A web-based calculator was developed to estimate the probability of poor outcomes (https://pcas-prediction.shinyapps.io/90d_lasso/). CONCLUSIONS: The updated models offer valuable information to medical professionals in the prediction of long-term neurological outcomes for patients with OHCA, potentially playing a vital role in clinical decision-making processes.

Rapid analysis of gasoline-contaminated soil using multiphoton ionization/time-of-flight mass spectrometry.

Multiphoton ionization/time-of-flight mass spectrometry (MPI/TOFMS) was modified for the rapid analysis of gasoline-contaminated soil. This technique uses a nanosecond laser emitting at 266 nm, and has the potential to produce the mass spectrum for gasoline 30 min after sampling. The rapidity and robustness of the method can be applied to the screening of gasoline-contaminated soils while minimizing the risk of contamination when gas chromatograph (GC) is used. GC/MPI/TOFMS was used for a simultaneous determination of aromatic compounds of gasoline in a soil sample, and this was achieved without interference. A peak for toluene can be observed from 0.02 ng of gasoline, and ten peaks of aromatic hydrocarbons, which are sensitive to measurement by a laser, can be observed from 0.65 ng of gasoline. The MPI/TOFMS had good sensitivity and selectivity, and was therefore useful for the rapid analysis of gasoline-contaminated soils.