Trauma resource pit stop: increasing efficiency in the evaluation of lower severity trauma patients

Background Overtriage of trauma patients is unavoidable and requires effective use of hospital resources. A ‘pit stop’ (PS) was added to our lowest tier trauma resource (TR) triage protocol where the patient stops in the trauma bay for immediate evaluation by the emergency department (ED) physician and trauma nursing. We hypothesized this would allow for faster diagnostic testing and disposition while decreasing cost.Methods We performed a before/after retrospective comparison after PS implementation. Patients not meeting trauma activation (TA) criteria but requiring trauma center evaluation were assigned as a TR for an expedited PS evaluation. A board-certified ED physician and trauma/ED nurse performed an immediate assessment in the trauma bay followed by performance of diagnostic studies. Trauma surgeons were readily available in case of upgrade to TA. We compared patient demographics, Injury Severity Score, time to physician evaluation, time to CT scan, hospital length of stay, and in-hospital mortality. Comparisons were made using 95% CI for variance and SD and unpaired t-tests for two-tailed p values, with statistical difference, p<0.05.Results There were 994 TAs and 474 TRs in the first 9 months after implementation. TR’s preanalysis versus postanalysis of the TR group shows similar mean door to physician evaluation times (6.9 vs. 8.6 minutes, p=0.1084). Mean door to CT time significantly decreased (67.7 vs. 50 minutes, p<0.001). 346 (73%) TR patients were discharged from ED; 2 (0.4%) were upgraded on arrival. When admitted, TR patients were older (61.4 vs. 47.2 years, p<0.0001) and more often involved in a same-level fall (59.5% vs. 20.1%, p<0.0001). Undertriage was calculated using the Cribari matrix at 3.2%.Discussion PS implementation allowed for faster door to CT time for trauma patients not meeting activation criteria without mobilizing trauma team resources. This approach is safe, feasible, and simultaneously decreases hospital cost while improving allocation of trauma team resources.Level of evidence Level II, economic/decision therapeutic/care management study

Fine-mapping genomic loci refines bipolar disorder risk genes

Bipolar disorder (BD) is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 BD risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci, and prioritized 22 likely causal SNPs for BD. We mapped these SNPs to genes, and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci, and results from rare variant exome sequencing in BD. Convergent lines of evidence supported the roles of SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, PLCB3, PRDX5, KCNK4, AP001453.3, TRPT1, FKBP2, DNAJC4, RASGRP1, FURIN, FES, YWHAE, DPH1, GSDMB, MED24, THRA, EEF1A2, and KCNQ2 in BD. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance and transferability of BD polygenic risk scores across ancestrally diverse populations, and present a high-throughput fine-mapping pipeline (https://github.com/mkoromina/SAFFARI)