BACKGROUND:Due to significant injury heterogeneity, outcome prediction following traumatic brain injury (TBI) is challenging. This study aimed to develop a simple model for high-accuracy mortality risk prediction after TBI. STUDY DESIGN:Data from the American College of Surgeons (ACS) Trauma Quality Program (TQP) from 2019 to 2021 was used to develop a summary score based on age, the Glasgow Coma Scale (GCS) component subscores, and pupillary reactivity data. We then compared the predictive accuracy to that of the Corticosteroid Randomisation After Significant Head Injury Trial (CRASH)-Basic and International Mission for Prognosis and Analysis of Clinical Trial in TBI (IMPACT)-Core models. Two separate series of sensitivity analyses were conducted to further assess our model's generalizability. We evaluated predictive performance of the models with discrimination [the area under the receiver-operating characteristic curves (AUC), sensitivity, specificity] and calibration (Brier score). Discriminative ability was compared with DeLong tests. RESULTS:259,404 patients were included in the present study (mean age, 60 years; 93,495 (36 %) female). The mortality score after TBI (MOST) model (AUC = 0.875) had better discrimination (DeLong test p values < 0.00001) than CRASH-Basic (AUC = 0.837) and IMPACT-Core (AUC = 0.821) models, and superior calibration (MOST = 0.02729, CRASH-Basic = 0.02962, IMPACT-Core = 0.02962) in predicting in-hospital mortality. The MOST model similarly outperformed in predicting 3-, 7-, 14-, and 30-day mortality. CONCLUSION:The MOST model can be rapidly calculated and outperforms two widely used models for predicting mortality in TBI patients. It utilizes a larger, contemporaneous dataset that reflects modern trauma care.

Introduction: Alcohol intoxication is a common patient presentation to urban emergency departments (ED). There is limited data on the healthcare financial impact of caring for alcohol-intoxicated patients in the ED. In this study we examined the facility-based financial billings and collections related to ED visits for alcohol intoxication. Methods: Using a retrospective cohort analysis of two large, urban EDs, with a combined yearly census of approximately 150,000 patient visits, we included all encounters between June 2018–December 2021 with a discharge diagnosis consistent with acute alcohol intoxication. We reviewed records of patient encounters with a final diagnosis consistent with acute alcohol intoxication who only had minimal or no interventions performed, implying the visit was solely consistent with acute alcohol intoxication. We reviewed the facility charges of these patients, along with insurance status and average payment by status to understand the financial impact. Results: Of 495,436 patient presentations to the EDs during the study period, 13,454 met study criteria (2.7% of total patients). Patient length of stay in the ED had an average of 254 minutes and median of 240 minutes. In total, this cohort of patients occupied ED beds for 56,505 hours cumulatively, or an average of 43.2 bed hours per day for alcohol intoxication-related visits, representing 3.14% of all ED bed hours across both sites. The majority of patient encounters were billed as a level 3 facility code (76%). Facility charges for the cohort totaled $22,590,000. The estimated reimbursement based on the percentage reimbursed by payor mix was $1.7 million (7.5%), or an average of $126 per patient visit—less than one quarter of the general average visit collection. Conclusion: Patients with acute alcohol intoxication and no other complaints are a minority of ED patients, yet their care results in substantial charges and ED resources. Based on the known facility collection rates per insurer, the weighted prevalence of insurers among this cohort yields an estimated collection rate of 7.5%. Opportunities to provide proven alcohol-related interventions should consider the unreimbursed costs of these visits when determining cost effectiveness.

Background:This study primarily aimed to assess the volumetric attributes of the midbrain and perimesencephalic structures preoperatively and following surgical interventions in patients diagnosed with brain herniation secondary to traumatic brain injury (TBI). Methods:We evaluated patients based on radiological findings and clinical symptoms indicative of brain herniation. We performed semi-automated segmentation of the intracranial structures most relevant to trauma and of interest for the current study, such as hematoma, ventricles, midbrain, and perimesencephalic cisterns. Using preoperative and postoperative computed tomography scans, we measured and analyzed the volume of these structures. Patients were grouped based on their discharge Glasgow Coma Scale (GCS) scores: GCS 15 and non-GCS 15. Results:From May 2018 to February 2020, we included 20 patients in the study. Our volumetric analysis revealed that preoperative midbrain volume (5.84 cc vs. 4.37 cc, P = 0.034) was a significant differentiator between GCS 15 and non-GCS 15 groups. Preoperative midbrain volume remained significant in univariate (odds ratio [OR] = 2.280, 95% confidence interval (CI) = 1.126-5.929, P = 0.04) and multivariate logistic regression analysis (adjusted OR = 3.204, 95% CI = 1.228-12.438, P = 0.038) even after adjusting for age, sex, and admission GCS score. We identified a cut-off point of 4.86 ccs in preoperative midbrain volume, which demonstrated a discriminatory performance of 0.788 area under the receiver operating characteristic curve, 80.0% accuracy, 77.8% sensitivity, and 81.8% specificity between the two groups. Conclusion:Our findings suggest that patients presenting with lesser midbrain compression preoperatively tended to have improved clinical outcomes postsurgery. Thus, we propose that this preoperative midbrain volume cut-off point holds predictive value for clinical outcomes within our cohort.

BACKGROUND:The EQUIPPED (Enhancing Quality of Prescribing Practices for Older Adults Discharged from the Emergency Department) medication safety program is an evidence-informed quality improvement initiative to reduce potentially inappropriate medications (PIMs) prescribed by Emergency Department (ED) providers to adults aged 65 and older at discharge. We aimed to scale-up this successful program using (1) a traditional implementation model at an ED with a novel electronic medical record and (2) a new hub-and-spoke implementation model at three new EDs within a health system that had previously implemented EQUIPPED (hub). We hypothesized that implementation speed would increase under the hub-and-spoke model without cost to PIM reduction or site engagement. METHODS:We evaluated the effect of the EQUIPPED program on PIMs for each ED, comparing their 12-month baseline to 12-month post-implementation period prescribing data, number of months to implement EQUIPPED, and facilitators and barriers to implementation. RESULTS:The proportion of PIMs at all four sites declined significantly from pre- to post-EQUIPPED: at traditional site 1 from 8.9% (8.1-9.6) to 3.6% (3.6-9.6) (p < 0.001); at spread site 1 from 12.2% (11.2-13.2) to 7.1% (6.1-8.1) (p < 0.001); at spread site 2 from 11.3% (10.1-12.6) to 7.9% (6.4-8.8) (p = 0.045); and at spread site 3 from 16.2% (14.9-17.4) to 11.7% (10.3-13.0) (p < 0.001). Time to implement was equivalent at all sites across both models. Interview data, reflecting a wide scope of responsibilities for the champion at the traditional site and a narrow scope at the spoke sites, indicated disproportionate barriers to engagement at the spoke sites. CONCLUSIONS:EQUIPPED was successfully implemented under both implementation models at four new sites during the COVID-19 pandemic, indicating the feasibility of adapting EQUIPPED to complex, real-world conditions. The hub-and-spoke model offers an effective way to scale-up EQUIPPED though a speed or quality advantage could not be shown.

Background: Venous thromboembolism (VTE) is a significant complication in patients with traumatic brain injury (TBI), but the optimal timing of pharmacological prophylaxis in operative cases remains controversial. Methods: This retrospective study aimed to describe the timing of pharmacological prophylaxis initiation in operative TBI cases, stratified by surgery type, and to report the frequency of worsening postoperative intracranial pathology. Results: Data from 90 surgical TBI patients were analyzed, revealing that 87.8% received VTE pharmacological prophylaxis at a mean of 85 hours postsurgery. The timing of initiation varied by procedure, with burr holes having the earliest start at a mean of 66 h. Craniotomy and decompressive craniectomy had the longest delay, with means of 116 and 109 h, respectively. Worsening intracranial pathology occurred in 5.6% of patients, with only one case occurring after VTE pharmacological prophylaxis initiation. The overall VTE rate was 3.3%. Conclusion: These findings suggest that initiating VTE pharmacological prophylaxis between 3 and 5 days postsurgery may be safe in operative TBI patients, with the timing dependent on the procedure’s invasiveness. The low frequencies of worsening intracranial pathology and VTE support the safety of these proposed timeframes. However, the study’s limitations, including its single-center retrospective nature and lack of a standardized protocol, necessitate further research to confirm these findings and establish evidence-based guidelines for VTE pharmacological prophylaxis in operative TBI patients.

INTRODUCTION: Both unfractionated heparin (UH) and low-molecular weight heparin (LMWH) are routinely used prophylactically after traumatic brain injury (TBI) to prevent deep vein thrombosis. Their comparative risk for intracranial hemorrhage (ICH) development or worsening necessitating cranial decompression after prophylaxis initiation is unclear. Furthermore, the absence of a specific antidote for LMWH may lead to UH being used more often for high-risk patients. METHODS: We compared the incidence of delayed cranial decompression occurring after initiation of prophylactic UH vs. LMWH using the National Trauma Data Bank. Cranial decompression procedures included craniotomy, craniectomy, and external ventricular drain placement. Multiple imputation was utilized for missing data. To account for selection bias between UH and LMWH, we conducted propensity score matching using factors that were significantly different between the two groups. The matched UH and LMWH groups were then compared using logistic regression for the primary outcome of post-prophylaxis cranial decompression. RESULTS: A total of 218,594 TBI patients were included, with 61,998 (28.3%) receiving UH and 156,596 (71.7%) receiving LMWH as DVT prophylaxis. The UH group had significantly higher patient age, BMI, comorbidity rates, injury severity score, and worse motor Glasgow coma scale. After matching the UH and LMWH groups for these factors, logistic regression demonstrated lower rates of post-prophylaxis cranial decompression for the LMWH group (OR 0.13, 95% CI 0.11-0.16, P < 0.001). CONCLUSION: Despite the absence of a specific antidote, LMWH was associated with substantially lower rates of post-DVT-prophylaxis cranial decompression. This indicates that UH may not be the safer alternative in TBI patients at high risk for intracranial hemorrhagic complications.

BACKGROUND: Stage 3 acute kidney injury (AKI) has been observed to develop after serious traumatic brain injury (TBI) and is associated with worse outcomes, though its incidence is not consistently established. This study aims to report the incidence of stage 3 AKI in serious isolated TBI in a large, national trauma database and explore associated predictive factors. METHODS: This was a retrospective cohort study using 2015-2018 data from the American College of Surgeons Trauma Quality Improvement Program, a national database of trauma patients. Adult trauma patients admitted to the hospital with isolated serious TBI were included. Variables relating to demographics, comorbidities, vitals, hospital presentation, and course of stay were assessed. Imputed multivariable logistic regression assessed factors predictive of stage 3 AKI development. RESULTS: A total of 342,675 patients with isolated serious TBI were included, 1585 (0.5%) of whom developed stage 3 AKI. Variables associated with stage 3 AKI in multivariable analysis were older age, male sex, Black race, higher body mass index, history of hypertension, diabetes, peripheral artery disease, chronic kidney disease, higher injury severity score, higher heart rate on arrival, lower oxygen saturation and motor Glasgow Coma Scale, admission to the intensive care unit or operating room, development of catheter-associated urinary tract infections or acute respiratory distress syndrome, longer intensive care unit stay, and ventilation duration. CONCLUSIONS: Stage 3 AKI occurred in 0.5% of serious TBI cases. Complications of acute respiratory distress syndrome and catheter-associated urinary tract infections are more likely to co-occur with stage 3 AKI in patients with serious TBI.

Coronavirus disease (COVID-19), caused by the SARS-CoV-2 virus, originated in Wuhan, Hubei Province, China in late 2019 and grew rapidly into a pandemic. As of the writing of this monograph, there are over 100 million confirmed cases worldwide and 2.3 million deaths.1 New York City, with over 630,000 COVID-19-positive patients and over 27,000 deaths, became the infection epicenter in the United States. The Mount Sinai Health System, with 8 hospitals spread across New York City and Long Island, has been on the forefront of the pandemic. This compendium summarizes the lessons learned through interdisciplinary collaborations to meet the varied challenges created by the explosive appearance of the infection in our community, and will be updated continuously as new research and best practices emerge. It is our hope is that the collaborations and lessons learned that went into creating these guidelines and protocols can serve as a useful template for other systems to adapt to their fight against COVID-19.

Coronavirus disease (COVID-19), caused by the SARS-CoV-2 virus, originated in Wuhan, Hubei Province, China in late 2019 and grew rapidly into a pandemic. As of the writing of this monograph, there are over 2 million confirmed cases worldwide and 147,000 deaths. New York City, with over 120,000 COVID-19-positive patients and over 11,000 deaths, has become the infection epicenter in the United States. The Mount Sinai Health System, with 8 hospitals spread across New York City and Long Island, has been on the forefront of the pandemic. This compendium summarizes the lessons learned through interdisciplinary collaborations to meet the varied challenges created by the explosive appearance of the infection in our community, and will be updated continuously as new research and best practices emerge. It is our hope is that the collaborations and lessons learned that went into creating these guidelines and protocols can serve as a useful template for other systems to adapt to their fight against COVID-19.