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Introduction: The cooccurrence of a traumatic hemothorax (HTX) and pneumothorax (PTX) is extremely common (70%). Prior work shows the safety of observing small HTX (≤300 cubic centimeters) and PTX (≤35 mm) in isolation. Accordingly, we sought to assess the safety of observation of concurrent small hemopneumothorax(HPTX)., Methods: We conducted a single-center retrospective study from 2015 to 2021 at a level I trauma center. Patients with a computed tomography (CT) scan confirmed that HPTXwas included in the study. Exclusion criteria included tube thoracostomy (TT) prior to CT scan, TT placement for rib fixation, PTX>35 mm, HTX>300 cubic centimeters, and death within 72 h of admission. The study group was stratified into either initial observation or early TT, which is defined as TT placement immediately after initial CT scan. Primary outcome was observation failure., Results: A total of 353 patients met the inclusion criteria, of whom 261 (74%) were initially observed. The initial observation cohort had a lower pulmonary morbidity rate (9% versus 14%; P = 0.04) and a shorter hospital (7 versus 10 d, P < 0.001) and intensive care unit (2 versus 4 d, P = 0.01) length of stay (LOS) when compared to those with initial TT placement. Sixty-eight (26%) patients failed observation, with a worsening HTXon repeat imaging (45%) being the most common reason. Compared to those who received an early TT, those who failed observation had a similar pulmonary morbidity and need for video-assisted thoracoscopic surgery, TT duration, LOS, readmission, and mortality rates., Conclusions: Initial observation of concurrent small traumatic HPTX had a lower pulmonary morbidity and LOS but was found to have a clinically significant failure rate. Patients who failed observation had similar outcomes to those who received an early TT., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Introduction: Gallstone disease is one of the most common surgical diagnoses in the United States. Notably absent from the literature is the patient's perspective on priorities in management. Understanding patient values will assist surgeons and systems in achieving high-quality, patient-focused care for biliary disease., Methods: Patients who underwent elective or urgent cholecystectomy were invited to participate in a semistructured interview to assess their experience. Interviews were performed over the phone or in person and recordings were transcribed. Each transcription was analyzed independently by two authors using the MAXQDA software, and a mixed deductive-inductive approach was used to develop themes. Anonymized quotes were used to illustrate themes and subthemes regarding the patient's experiences and priorities surrounding gallstone disease., Results: A total of 29 interviews were completed. Most participants were female, but represented a diverse racial and educational group. The most common diagnosis was acute cholecystitis (48%), and 76% of patients underwent an emergency operation. Patients indicated that their main priority regarding treatment was prompt pain control with definitive management so they could return to their previous quality of life. Most patients wanted face-to-face communication with the surgical team both pre and postoperatively. Patients wished they had more information about postoperative care and expectations in the preoperative setting., Conclusions: Patients' priorities in their care for gallstone disease are centered around definitive management and quality of life. Improvements in communication were identified regarding meeting the surgeon, and postoperative communication. These results can inform surgeons how to prioritize patient perspectives in an acute care surgical system that was not designed with patient input., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Introduction: The Traumatic Brain Injury - Patient Reported Outcome (TBI-PRO) model was previously derived to predict long-term patient satisfaction as assessed by the Quality of Life After Brain Injury (QOLIBRI) score. The aim of this study is to externally and prospectively validate the TBI-PRO model to predict long-term patient-reported outcomes and to derive a new model using a larger dataset of older adults with TBI., Methods: Patients admitted to a Level I trauma center with TBI were prospectively followed for 1 y after injury. Outcomes predicted by the TBI-PRO model based on admission findings were compared to actual QOLIBRI scores reported by patients at 3,6, and 12 mo. When deriving a new model, Collaborative European NeuroTrauma Effectiveness Research in TBI and the Transforming Research and Clinical Knowledge in Traumatic Brain Injury databases were used to identify older adults (≥50 y) with TBI from 2014 to 2018. Bayesian additive regression trees were used to identify predictive admission covariates. The coefficient of determination was used to identify the fitness of the model., Results: For prospective validation, a total of 140 patients were assessed at 3 mo, with follow-up from 69 patients at 6 mo and 13 patients at 12 mo postinjury. The area under receiver operating curve of the TBI-PRO model for predicting favorable outcomes at 3, 6, and 12 mo were 0.65, 0.57, and 0.62, respectively. When attempting to derive a novel predictive model, a total of 1521 patients (80%) was used in the derivation dataset while 384 (20%) were used in the validation dataset. A past medical history of heart conditions, initial hospital length of stay, admission systolic blood pressure, age, number of reactive pupils on admission, and the need for craniectomy were most predictive of long-term QOLIBRI-Overall Scale. The coefficient of determination for the validation model including only the most predictive variables were 0.28, 0.19, and 0.27 at 3, 6, and 12 mo, respectively., Conclusions: In the present study, the prospective validation of a previously derived TBI-PRO model failed to accurately predict a long-term patient reported outcome measures in TBI. Additionally, the derivation of a novel model in older adults using a larger database showed poor accuracy in predicting long-term health-related quality of life. This study demonstrates limitations to current targeted approaches in TBI care. This study provides a framework for future studies and more targeted datasets looking to assess long-term quality of life based upon early hospital variables and can serve as a starting point for future predictive analysis., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Introduction: The decision to withdraw life sustaining treatment (WDLST) in older adults with traumatic brain injury is subject to wide variability leading to nonbeneficial interventions and unnecessary use of hospital resources. We hypothesized that patient and hospital factors are associated with WDLST and WDLST timing., Methods: All traumatic brain injury patients ≥65 with Glasgow coma scores (GCS) of 4-11 from 2018 to 2019 at level I and II centers were selected from the National Trauma Data Bank. Patients with head abbreviated injury scores 5-6 or death within 24 h were excluded. Bayesian additive regression tree analysis was performed to identify the cumulative incidence function (CIF) and the relative risks (RR) over time for withdrawal of care, discharge to hospice (DH), and death. Death alone (no WDLST or DH) served as the comparator group for all analyses. A subanalysis of the composite outcome WDLST/DH (defined as end-of-life-care), with death (no WDLST or DH) as a comparator cohort was performed., Results: We included 2126 patients, of whom 1957 (57%) underwent WDLST, 402 (19%) died, and 469 (22%) were DH. 60% of patients were male, and the mean age was 80 y. The majority of patients were injured by fall (76%, n = 1644). Patients who were DH were more often female (51% DH versus 39% WDLST), had a past medical history of dementia (45% DH versus 18% WDLST), and had lower admission injury severity score (14 DH versus 18.6 WDLST) (P < 0.001). Compared to those who DH, those who underwent WDLST had a lower GCS (9.8 versus 8.4, P < 0.001). CIF of WDSLT and DH increased with age, stabilizing by day 3. At day 3, patients ≥90 y had an increased RR of DH compared to WDLST (RR 2.5 versus 1.4). As GCS increased, CIF and RR of WDLST decreased, while CIF and RR of DH increased (RR on day 3 for GCS 12: WDLST 0.42 versus DH 1.31).Patients at nonprofit institutions were more likely to undergo WDLST (RR 1.15) compared to DH (0.68). Compared to patients of White race, patients of Black race had a lower RR of WDLST at all timepoints., Conclusions: Patient and hospital factors influence the practice of end-of-life-care (WDLST, DH, and death), highlighting the need to better understand variability to target palliative care interventions and standardize care across populations and trauma centers., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Background: The ability to reliably predict outcomes after trauma in older adults (age ≥ 65 y) is critical for clinical decision making. Using novel machine-learning techniques, we sought to design a nonlinear, competing risks paradigm for prediction of older adult discharge disposition following injury., Materials and Methods: The National Trauma Databank (NTDB) was used to identify patients 65+ y between 2007 and 2014. Training was performed on an enriched cohort of diverse patients. Factors included age, comorbidities, length of stay, and physiologic parameters to predict in-hospital mortality and discharge disposition (home versus skilled nursing/long-term care facility). Length of stay and discharge status were analyzed via competing risks survival analysis with Bayesian additive regression trees and a multinomial mixed model., Results: The resulting sample size was 47,037 patients. Admission GCS and age were important in predicting mortality and discharge disposition. As GCS decreased, patients were more likely to die (risk ratio increased by average of 1.4 per 2-point drop in GCS, P < 0.001). As GCS decreased, patients were also more likely to be discharged to a skilled nursing or long-term care facility (risk ratio decreased by 0.08 per 2-point decrease in GCS, P< 0.001). The area under curve for prediction of discharge home was improved in the competing risks model 0.73 versus 0.43 in the traditional multinomial mixed model., Conclusions: Predicting older adult discharge disposition after trauma is improved using machine learning over traditional regression analysis. We confirmed that a nonlinear, competing risks paradigm enhances prediction on any given hospital day post injury., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: A tiered trauma team activation (TTA) system aims to allocate resources proportional to the patient's need based upon injury burden. The current metrics used to evaluate appropriateness of TTA are the trauma triage matrix (TTM), need for trauma intervention (NFTI), and secondary triage assessment tool (STAT)., Materials and Methods: In this retrospective study, we compared the effectiveness of the need for an emergent intervention within 6 h (NEI-6) with existing definitions. Data from the Michigan Trauma Quality Improvement Program was utilized. The dataset contains information from 31 level 1 and 2 trauma centers from 2011 to 2017. Inclusion criteria were: adult patients (≥16 y) and ISS ≥5., Results: 73,818 patients were included in the study. Thirty percentage of trauma patients met criteria for STAT, 21% for NFTI, 20% for TTM, and 13% for NEI-6. NEI-6 was associated with the lowest rate of undertriage at 6.5% (STAT 22.3%, NFTI 14.0%, TTM 14.3%). NEI-6 best predicted undertriage mortality, early mortality, in-hospital mortality, and late (>60 h) mortality. Most patients who met criteria for TTM (58%), NFTI (51%), and STAT (62%) did not require emergent intervention. All four methods had similar rates of early mortality for patients who did not meet criteria (0.3%-0.5%)., Conclusions: NEI-6 performs better than TTM, NFTI, and STAT in terms of undertriage, mortality and need for resource utilization. Other methods resulted in significantly more full TTAs than NEI-6 without identifying patients at risk for early mortality. NEI-6 represents a novel tool to determine trauma activation appropriateness., (Crown Copyright © 2019. Published by Elsevier Inc. All rights reserved.)

Background: Peritoneal carcinomatosis represents widespread metastatic disease throughout the abdomen and/or pelvis. Cytoreductive surgery/hyperthermic intraperitoneal chemotherapy (CRS/HIPEC) improves the overall survival compared to standard therapy alone. The role palliative care (PC) plays however, remains poorly studied among these patients., Methods: Patients who had previously undergone HIPEC and who underwent an inpatient admission from 7/1/2013 to 6/30/2014 were identified to determine which patients were referred for inpatient or outpatient palliative consultation. Multivariable logistic regression analysis was performed to identify risk factors associated with the use of PC., Results: Of the 60 patients analyzed, 23 (38.3%) had a PC consultation with a median time to PC referral of 310 (IQR: 151-484 days). Patients who were prescribed opioids (no PC referral versus PC referral: 46.0% versus 91.3%, P < 0.001), patients who reported the use of a cancer-related emetic (35.1% versus 87.0%, P < 0.001), patients reporting the use of total parenteral nutrition (16.2% versus 39.1%, P = 0.046), and patients dependent on a gastric tube for nutrition (5.4% versus 43.5%, P < 0.001) were more likely to be referred to a PC consultation. On multivariable analysis, use of opioids, use of a cancer-related antiemetic, and the use of a G-tube were independently associated with a greater odds for being referred to PC (all P < 0.05)., Conclusions: Approximately one-third of patients were referred to PC following cytoreductive surgery/hyperthermic intraperitoneal chemotherapy. Palliative care referrals were most commonly used for patients with chronic symptoms, which are difficult to manage, especially toward the end of life., (Copyright © 2016 Elsevier Inc. All rights reserved.)