External validation of novel Revised Intensity Battle Score and comparison of static rib fracture scoring systems.

BACKGROUND: This study aims to compare and externally validate the previously developed Revised Intensity Battle Score (RIBS) against other proposed scores for predicting poor outcomes after rib fractures. METHODS: An external validation set was assembled retrospectively, comprising 1,493 adult patients with one or more rib fractures admitted to a Level 1 trauma center between 2019 and 2022. The following rib fracture scores were calculated for each patient: RIBS, Injury Severity Score, Rib Fracture Score, Chest Trauma Score, and Battle score. Each was investigated to assess utility in predicting mortality, intensive care unit upgrade, unplanned intubation and ventilator days. Performance was measured by area under the receiver operating characteristic curve. RESULTS: Of the 1,493 patients who met inclusion criteria, 239 patients (16%) experienced one of more of the investigated outcomes. Generally, scores performed best at predicting mortality and ventilator days. The RIBS stood out as best predicting "any complication" (AUC = 0.735) and ">7 ventilator days" (AUC = 0.771). CONCLUSION: The RIBS represents an externally validated triage score in patients with rib fractures and compares favorably to other static scoring systems. Use of this score as a triage tool may allow stratifying patients who may benefit from direct intensive care unit admission, neuraxial anesthesia and aggressive respiratory care. Next steps include prospective investigation of how pairing these interventions with score directed triage impacts outcomes. LEVEL OF EVIDENCE: Prognostic and Epidemiological; Level IV.

Revised Intensity Battle Score (RIBS): Development of a Clinical Score for Predicting Poor Outcomes After Rib Fractures.

BACKGROUND: Patients with rib fractures have variable clinical courses and it is difficult to predict which patients will do poorly. Ideally this prediction would happen at the time of admission to facilitate effective triage. One scoring system devised to this end, is the Battle score. This study aims to evaluate the efficacy of the Battle score as triage tool, and to re-tool it for performance in an inpatient trauma setting. METHODS: A multivariate logistic regression model was trained on patients admitted to a level one trauma center with at least one rib fracture. A composite outcome was used to classify those who had poor outcomes. Eighteen candidate predictors were analyzed in univariate analysis, then the most promising fed into the logistic model until a triage score was built and internally validated by bootstrapping. RESULTS: Of the 838 patients who met the inclusion criteria, 145 (17.3%) patients had a defined poor outcome. The relevant predictors included in the final scoring system were number of ribs fractured, chest tube, pulmonary contusions, chronic obstructive pulmonary disease, and Glasgow coma score. Age was not found to be predictive. This score was found to have higher fidelity in predicting poor outcomes than the original Battle score (AUROC .858 vs .649.). DISCUSSION: An easy to calculate clinical scoring system was created to triage patients with rib fractures at the time of admission. Age may be of less importance than previously thought, while injury burden and history of lung disease may play a larger role.

Mapping the BH3 Binding Interface of Bcl-xL, Bcl-2, and Mcl-1 Using Split-Luciferase Reassembly.

The recognition of helical BH3 domains by Bcl-2 homology (BH) receptors plays a central role in apoptosis. The residues that determine specificity or promiscuity in this interactome are difficult to predict from structural and computational data. Using a cell free split-luciferase system, we have generated a 276 pairwise interaction map for 12 alanine mutations at the binding interface for three receptors, Bcl-xL, Bcl-2, and Mcl-1, and interrogated them against BH3 helices derived from Bad, Bak, Bid, Bik, Bim, Bmf, Hrk, and Puma. This panel, in conjunction with previous structural and functional studies, starts to provide a more comprehensive portrait of this interactome, explains promiscuity, and uncovers surprising details; for example, the Bcl-xL R139A mutation disrupts binding to all helices but the Bad-BH3 peptide, and Mcl-1 binding is particularly perturbed by only four mutations of the 12 tested (V220A, N260A, R263A, and F319A), while Bcl-xL and Bcl-2 have a more diverse set of important residues depending on the bound helix.