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Acute respiratory distress syndrome (ARDS) is the most severe form of acute lung injury, responsible for high mortality and long-term morbidity. As a dynamic syndrome with multiple etiologies, its timely diagnosis is difficult as is tracking the course of the syndrome. Therefore, there is a significant need for early, rapid detection and diagnosis as well as clinical trajectory monitoring of ARDS. Here, we report our work on using human breath to differentiate ARDS and non-ARDS causes of respiratory failure. A fully automated portable 2-dimensional gas chromatography device with high peak capacity (> 200 at the resolution of 1), high sensitivity (sub-ppb), and rapid analysis capability (~30 min) was designed and made in-house for on-site analysis of patients' breath. A total of 85 breath samples from 48 ARDS patients and controls were collected. Ninety-seven elution peaks were separated and detected in 13 min. An algorithm based on machine learning, principal component analysis (PCA), and linear discriminant analysis (LDA) was developed. As compared to the adjudications done by physicians based on the Berlin criteria, our device and algorithm achieved an overall accuracy of 87.1% with 94.1% positive predictive value and 82.4% negative predictive value. The high overall accuracy and high positive predicative value suggest that the breath analysis method can accurately diagnose ARDS. The ability to continuously and non-invasively monitor exhaled breath for early diagnosis, disease trajectory tracking, and outcome prediction monitoring of ARDS may have a significant impact on changing practice and improving patient outcomes. Keywords Breath analysis. Acute respiratory distress syndrome gas chromatography. 2D GC. Machine learning Menglian Zhou and Ruchi Sharma contributed equally to this work.

Surgical resident experience on most trauma services is heavily weighted to nonoperative management, with a relatively low number of procedures, little experience with DPL, and highly variable experience with ultrasound. These data have serious implications for resident training and recruitment into the specialty.

BACKGROUND Interfacility transfer of patients from Level III/IV to Level I/II (tertiary) trauma centers has been associated with improved outcomes. However, little data are available classifying the specific subsets of patients that derive maximal benefit from transfer to a tertiary trauma center. Drawbacks to transfer include increased secondary overtriage. Here, we ask which injury patterns are associated with improved survival following interfacility transfer. METHODS Data from the National Trauma Data Bank was utilized. Inclusion criteria were adults (≥16 years). Patients with Injury Severity Score of 10 or less or those who arrived with no signs of life were excluded. Patients were divided into two cohorts: those admitted to a Level III/IV trauma center versus those transferred into a tertiary trauma center. Multiple imputation was performed for missing values, and propensity scores were generated based on demographics, injury patterns, and disease severity. Using propensity score–stratified Cox proportional hazards regression, the hazard ratio for time to death was estimated. RESULTS Twelve thousand five hundred thirty-four (5.2%) were admitted to Level III/IV trauma centers, and 227,315 (94.8%) were transferred to a tertiary trauma center. Patients transferred to a tertiary trauma center had reduced mortality (hazard ratio, 0.69; p < 0.001). We identified that patients with traumatic brain injury with Glasgow Coma Scale score less than 13, pelvic fracture, penetrating mechanism, solid organ injury, great vessel injury, respiratory distress, and tachycardia benefited from interfacility transfer to a tertiary trauma center. In this sample, 56.8% of the patients benefitted from transfer. Among those not transferred, 49.5% would have benefited from being transferred. CONCLUSION Interfacility transfer is associated with a survival benefit for specific patients. These data support implementation of minimum evidence-based criteria for interfacility transfer. LEVEL OF EVIDENCE Therapeutic/Care Management, Level IV.