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Background: Disasters burden on hospital emergency intensive care units (ICUs). This burden is increased in Latin America (LATAM) where hospital resources, intrahospital disaster simulations, and perceived level of preparedness vary greatly among different communities. The objective of the study was to assess LATAM ICU leaders' knowledge and attitudes regarding disaster preparedness., Methods: We developed a ten-item, web-based knowledge and attitude survey administered via LATAM ICU leaders online forums. Descriptive statistics were used. Epi Info™ software was used for analysis. Chi-square and Fisher's exact test with P < 0.05 were implemented for statistical significance, and odds ratio was used to measure the strength of association among variables., Results: There were 68 respondents in the survey. 13/68 respondents felt prepared for disasters. 16/68 worked at hospitals with 250+ beds and 52/68 represented hospitals with <250 beds. 23/68 participated in hospital committees for disaster, 24/68 participated in simulations or drills, and 22/68 participated in trainings or courses for disasters. Feeling prepared for disasters did not correlate with hospital size (odds ratio [OR] = 2.87 [95% confidence interval (CI): 0.83-9.92], P = 0.91), participation in hospital committees for disaster (OR = 3.10 [95% CI: 1.02-9.26], P = 0.08), and participation in simulations or drills (OR = 2.78 [95% CI: 0.93-8.29], P = 0.11), but participation in disaster trainings and courses appeared to directly correlate with the perception of being prepared (OR = 3.43 [95% CI: 1.13-10.41], P = 0.03)., Conclusion: Among the 68 centers represented, the majority did not feel their institution to be adequately prepared for disasters, but training appeared to change that perception. A small sample size represents the major limitation of this study., Competing Interests: There are no conflicts of interest., (Copyright: © 2019 International Journal of Critical Illness and Injury Science.)

Objective: We sought out to determine the correlation between the injury severity score (ISS) and multiple organ dysfunction syndrome (MODS) between severely injured young adults (18-54 years) and elderly (>55 years) patients., Materials and Methods: This was a cross-sectional observational study. We included all adult cases (>18 years) diagnosed with trauma defined by the International Classification of Diseases, Ninth Revision. For significance testing, Chi-square test and odds ratio were used. Severe injuries were defined by an ISS >15. The presence of MODS was based on the definitions proposed by society for critical care medicine., Results: A total of 469 young and 173 elderly patients were included in the study. Among the 469 young adults, 193 had ISS >15, whereas out of the 173 elderly patients, 88 had an ISS >15. Severely injured young and elderly groups were more likely to develop MODS compared with those with an ISS <15 ( P < 0.001 and P < 0.001, respectively). The elderly had a higher likelihood of developing MODS ( P < 0.001; odds ratio: 5.17; 95% confidence interval: 2.74-9.80)., Conclusion: This study demonstrated a direct relationship between an ISS >15 and the development of MODS. We also observed a five-fold increase in the development of MODS among severely injured elderly patients., Competing Interests: There are no conflicts of interest.

Background: Bayes' theorem describes the probability of an event, based on conditions that might be related to the event.[1] We developed the Bayesian Diagnostic Gains (BDG) method as a simple tool for interpreting diagnostic impact.[234567]., Aim: We aimed to evaluate the clinical diagnostic impact of contrast-enhanced ultrasound (CEUS) compared to traditional abdominal computed tomography (CT) and standard ultrasound (US) in a Bayesian Clinical Decision Scheme., Materials and Methods: Our mathematical method uses Bayesian Diagnostic Gains (BDG) model. For the purposes of our model, the EMTRAS was used as pretest probability and stratified as low risk (0-3 points = 10%), moderate risk (4-6 points = 42%), and high risk (7-12 points = 80%) based on mortality risk. Sensitivity and specificity for US, CT, and CEUS were obtained from pooled data and used to calculate LR- and LR+. Bayesian/Fagan nomogram was used to attain posttest probabilities using baseline probability of an event on the first axis (PRE), with LR on the second axis, and read off the pos-test probability (POST) on the third axis. For the nomogram analysis, the pretest probability (Pre) scoring for the EMTRAS score was obtained using the original EMTRAS data. Posttest probabilities were obtained based on the Bayes/Fagan Nomgram. Relative diagnostic gain (RDG) and absolute diagnostic gain (ADG) were calculated based on the differences deducted from pre- and post-test probabilities. IBM® SPSS® Statistics 20 was used for analysis and modeling. ANOVA was used for association between EMTRAS, CT scan, and CEUS, where P value set at 0.05., Results: Pooled data for Sensitivity (Se), Specificity (Sp), LR+, and LR- were obtained for US (Se = 45.7%, Sp = 91.8%, LR+ = 5.57, and LR- = 0.59), CEUS (Se 91.4%, Sp 100%, LR+ 91, and LR-0.09), and CT (Se = 94.8%, SP = 98.7%, LR+ = 73, and LR- =0.05). ANOVA analysis for LR+ and LR- showed no significant difference ( P < 0.8745 and P < 0.9841). Comparison of CT and CEUS did not yield statistically significant differences for LR+ ( P < 0.1)., Conclusion: In this Bayesian model, the diagnostic performance of CEUS was found to be similar to traditional abdominal CT. The greatest diagnostic gain was observed in low pretest positive LR groups., Competing Interests: There are no conflicts of interest.