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Nonpenetrating, blunt chest trauma is a serious medical condition with varied clinical presentations and implications. This can be the result of a dense projectile during competitive and recreational sports but may also include other etiologies such as motor vehicle accidents or traumatic falls. In this setting, the manifestation of ventricular arrhythmias has been observed both acutely and chronically. This is based on two entirely separate mechanisms and etiologies requiring different treatments. Ventricular fibrillation can occur immediately after chest wall injury (commotio cordis) and requires rapid defibrillation. Monomorphic ventricular tachycardia can develop in the chronic stage due to underlying structural heart disease long after blunt chest injury. The associated arrhythmogenic tissue may be complex and provides the necessary substrate to form a reentrant VT circuit. Ventricular tachycardia in the absence of overt structural heart disease appears to be focal in nature with rapid termination during ablation. Regardless of the VT mechanism, patients with recurrent episodes, despite antiarrhythmic medication in the chronic stage following blunt chest injury, are likely to require ablation to achieve VT control. This review article will describe the mechanisms, pathophysiology, and treatment of ventricular arrhythmias that occur in both the acute and chronic stages following blunt chest trauma.

(CBEMS) organizations. Background: University campuses are unique, typically selfcontained environments. In North America over the past twenty years, CBEMS organizations have proliferated on campuses. Today, hundreds of university-funded, student-run organizations perform prehospital medical care for the campus population of our universities. Methods: We performed a retrospective observational study of 200 CBEMS organizations in North America. The NCEMSF has aggregated data from 1993 to 2015 from an annual survey of all CBEMS organizations. Of those, 329 organizations selfidentified themselves to the NCEMSF and completed the survey. We excluded 129 organizations who were either not operational or who had not completed significant portions of the survey. Results: In North America, the mean response time for CBEMS organizations is 3.09 minutes. The mean annual budget reported is $38,333. The mean annual call volume is 516 calls, while the mean number of total vehicles per organization is 3.8. Looking at the level of service provided by the CBEMS organization, 15.50% (31/200) are classified as first responder only organizations, 69.50% (139/200) are basic life support (BLS) capable, 3% (6/200) provide intermediate level of care, 8.5% (17/200) provide Advanced Life Support (ALS) care, while the remaining 3.5% (7/200) were classified as 'other'. For the type of response provided, 10.5% (21/200) provide 'event only' coverage, 54.5% (109/200) provide quick response services (QRS) only, 23% (46/200) provide ambulance response, 5.5% (11/200) provide a response type classified as 'other', while the remaining 6.5% (13/200) provide nonemergent response (see Table 1). Conclusion: Collegiate EMS organizations are diverse, with the majority being urban Basic Life Support (BLS) Quality Rescue Services (QRS) services. CBEMS organizations are a relatively recent development in the history of EMS, paralleling other specialty EMS agencies, such as wilderness and tactical medicine.

Background: Poor preoperative health-related quality of life (HRQoL) has been associated with reduced short-term survival after coronary artery bypass graft surgery (CABG); however, it’s impact on long-term mortality is unknown. This study’s objective was to determine if baseline HRQoL status predicts five-year post-CABG mortality. Methods: This pre-specified, Randomized On/Off Bypass Follow-up Study (ROOBY-FS) sub-analysis compared baseline patient characteristics and HRQoL scores, obtained from the Seattle Angina Questionnaire (SAQ) and Veterans Rand Short Form 36 (VR-36), between five-year post-CABG survivors and non-survivors. Standardized sub-scores were calculated for each questionnaire. Multivariable logistic regression assessed whether HRQoL survey sub-components independently predicted five-year mortality (p < 0.05). Results: Of the 2,203 ROOBY-FS enrollees, 2,104 (95.5%) completed baseline surveys. Significant differences between five-years post-CABG deaths (n = 286) and survivors (n = 1818) included age, history of chronic obstructive pulmonary disease, stroke, peripheral vascular disease, renal dysfunction, diabetes, lower left ventricular ejection fraction, atrial fibrillation, depression, non-white race/ethnicity, lower education status, and off-pump CABG. Adjusting for these factors, baseline VR-36 Physical Component Summary score (PCS) [p = 0.01], VR-36 Mental Component Summary score (MCS) (p < 0.001) and SAQ Physical Limitation score (SAQ-PL) (p = 0.003) were all associated with five-year all-cause mortality. Conclusions: Pre-CABG HRQoL scores may provide clinically relevant prognostic information beyond traditional risk models and prove useful for patient-provider shared decision making and enhancing pre-CABG informed consent.

Study Objectives: One measure of the quality of emergency medical services (EMS) is response time to the patient's location. Collegiate-based emergency medical services (CBEMS) are unique EMS services that are dedicated to providing out-ofhospital care on specific college or university campus. It is unknown what factors affect response time for CBEMS organizations. Our objective is to determine which organizational characteristics are associated with response times, and thus the quality of out-of-hospital care provided on university campuses.Methods: We performed a retrospective study of 200 CBEMS organizations in the United States and Canada. Survey data was collected between 1993 and 2015 by the National Collegiate Emergency Medical Services Foundation (NCEMSF). Regression modeling was utilized to predict mean response times from covariates. Log transformations of variables were taken where appropriate. Covariates that had an P > 0.1 were dropped from the stepwise multiple regression model. Analyses were conducted with Stata v. 13 software (Austin, Texas) with a 2-sided significance threshold of P < .05.Results: Annual call volume, population increases, annual budget, and student enrollment are associated with response time. When there is a 10% increase in their annual call volume, the data predicts that a CBEMS organization will experience a 5% increase in their mean response time. An annual budget increase of 10% will lead to a 1.3% decrease in response time. A population increase of 10% will increase the average response time by 9.5%, while an increase in student enrollment at the institution of 10% will lead to a decrease the response time by 12.3% (see Table 1). There was a statistically significant correlation with a one-unit increase in automated external defibrillators (AEDs) and a 10.8% decrease in average response times. The remaining characteristics of the CBEMS organizations, like number of ambulances and number of members, have no statistically significant predictive value on the average response time.Conclusion: There are multiple factors that affect response times for CBEMS organizations. Both population increases and annual call volume increases lead to longer response times, and are likely directly related to one another. CBEMS organizations may be able to mitigate this effect by increasing their annual budget. Student enrollment was also associated with decreasing response times, likely because of an increase in the number of responders geographically distributed throughout campuses. This study provides insight into factors affecting the quality of out-of-hospital care provided by CBEMS organizations.