Diagnostic Adjunct Techniques in the Assessment of Hypovolemia: A Prospective Pilot Project.

INTRODUCTION: Measuring the hypovolemic resuscitation end point remains a critical care challenge. Our project compared clinical hypovolemia (CH) with three diagnostic adjuncts: 1) noninvasive cardiac output monitoring (NICOM), 2) ultrasound (US) static IVC collapsibility (US-IVC), and 3) US dynamic carotid upstroke velocity (US-C). We hypothesized US measures would correlate more closely to CH than NICOM. METHODS: Adult trauma/surgical intensive care unit patients were prospectively screened for suspected hypovolemia after acute resuscitation, excluding patients with burns, known heart failure, or severe liver/kidney disease. Adjunct measurements were assessed up to twice a day until clinical improvement. Hypovolemia was defined as: 1) NICOM: ≥10% stroke volume variation with passive leg raise, 2) US-IVC: <2.1 cm and >50% collapsibility (nonventilated) or >18% collapsibility (ventilated), 3) US-C: peak systolic velocity increase 15 cm/s with passive leg raise. Previously unknown cardiac dysfunction seen on US was noted. Observation-level data were analyzed with a Cohen's kappa (κ). RESULTS: 44 patients (62% male, median age 60) yielded 65 measures. Positive agreement with CH was 47% for NICOM, 37% for US-IVC and 10% for US-C. None of the three adjuncts correlated with CH (κ -0.045 to 0.029). After adjusting for previously unknown cardiac dysfunction present in 10 patients, no adjuncts correlated with CH (κ -0.036 to 0.031). No technique correlated with any other (κ -0.118 to 0.083). CONCLUSIONS: None of the adjunct measurements correlated with CH or each other, highlighting that fluid status assessment remains challenging in critical care. US should assess for right ventricular dysfunction prior to resuscitation.

Variations in Discharge Destination Following Severe Traumatic Brain Injury across the United States.

BACKGROUND: Discharge destination after traumatic brain injury (TBI) may be influenced by non-patient factors such as regional or institutional practice patterns. We hypothesized that non-patient factors would be associated with discharge destination in severe TBI patients. METHODS: All patients in the ACS Trauma Quality Improvement Program 2016 data set with severe TBI, defined as head Abbreviated Injury Scale ≥3, were categorized by discharge destination. Logistic regression was used to assess factors associated with each destination; odds ratios and 95% confidence level are reported. Regressions were adjusted for age, gender, race, insurance, GCS, ISS, polytrauma, mechanism, neurosurgical procedure, geographic region, teaching status, trauma center level, hospital size, and neurosurgeon group size. RESULTS: 75,690 patients met inclusion criteria. 51% were discharged to home, 16% to rehab, 14% to SNF, and 11% deceased. Mortality was similar across geographic region, teaching status, and hospital size. Southern patients were more likely to be discharged to home while Northeastern patients were more likely to be discharged to rehab. Treatment by groups of 3 or more neurosurgeons was associated with SNF discharge as was treatment at community or non-teaching hospitals. Patients treated at larger hospitals were less likely to be discharged to rehab and more likely to go to SNF. CONCLUSIONS: Geographic region, neurosurgeon group size, teaching status, and hospital size are significantly associated with variation in discharge destination following severe TBI. Regional and institutional variation in practice patterns may play important roles in recovery for some patients with severe TBI.

Factors Influencing Nonadherence to Recommended Postdischarge Follow-Up After Trauma.

INTRODUCTION: Historically, trauma patients have low adherence to recommended outpatient follow-up plans, which is crucial for improved long-term clinical outcomes. We sought to identify characteristics associated with nonadherence to recommended outpatient follow-up visits. METHODS: This is a single-center retrospective examination of inpatient trauma survivors admitted to a level 1 trauma center (March 2017-March 2018). Patients with known alternative follow-up were excluded. All outpatient visits within 1 y from the index admission were identified. The primary outcome was nonadherence, which was noted if a patient failed to follow-up for any specialty recommended in the discharge instructions. Factors for nonadherence studied included age, injury severity score, mechanism, length of stay, number of referrals made, and involvement with a Trauma Recovery Services program. Bivariate and logistic regression analyses were performed. RESULTS: A total of498 patients were identified (69% men, median age 43 y [range, 26-58 y], median injury severity score 14 [range, 9-19]). Among them, 240 (47%) were nonadherent. The most common specialties recommended were orthopedic surgery (56% referred, 19% nonadherent), trauma (54% referred, 35% nonadherent), and neurosurgery (127 referred, 35% nonadherent). Lowest levels of follow-up were seen for nonsurgical referrals. In adjusted analysis, a higher number of referrals made (odds ratio [OR], 2.45; 95% confidence interval [CI], 1.95-3.05) and older age (OR, 1.01; 95% CI, 1.00-1.02) were associated with nonadherence. Trauma Recovery Service participants and penetrating trauma patients were more likely to be adherent (OR, 0.60; 95% CI, 0.37-0.97). CONCLUSIONS: The largest contributor to nonadherence was the number of referrals made; patients who were referred to multiple specialists were more likely to be nonadherent. Peer support services may lower barriers to follow-up.

Post-Trauma Discharge Instructions: Are We Dropping the Ball?

INTRODUCTION: Complex follow-up plans for polytrauma patients are compiled at the end of hospitalization into discharge instructions. We sought to identify how often patient discharge instructions incorrectly communicated specialist recommendations. We hypothesized that patients with more complex hospitalizations would have more discharge instruction errors (DI-errors). METHODS: We reviewed adult trauma inpatients (March 2017-March 2018), excluding those who left against medical advice or were expected to follow up outside our system. Complex hospitalizations were represented using injury severity (ISS), hospital length of stay (LOS), intensive care unit length of stay (iLOS), and number of consultants (NC). We recorded the type of consultant (surgical or nonsurgical), and consultant recommendations for follow-up. DI-errors were defined as either follow-up necessary but omitted or follow-up not necessary yet present on the instructions. Patients with DI-errors were compared to patients without DI-errors. Groups were compared using Wilcoxon rank sum or chi-square (alpha <.05). RESULTS: We included 392 patients (median age 45 [IQR 26-58], ISS 14 [10-21], LOS 6 [3-11]). 55 patients (14%) had DI-errors. Factors associated with DI-errors included the total number of consultants and use of nonsurgical consultants. ISS, LOS, iLOS, were not associated with DI-errors. CONCLUSION: Common measures of admission complexity were not associated with DI-errors, although the number and type of consultants were associated with DI-errors. Non-surgical specialty consultant recommendations were more likely to be omitted. It is crucial for patients to receive accurate discharge instructions, and systematic processes are needed to improve communication with the patients at discharge.

Predictors for Withdrawal of Life-Sustaining Therapies in Patients With Traumatic Brain Injury: A Retrospective Trauma Quality Improvement Program Database Study.

Many patients with severe traumatic brain injuries (TBIs) undergo withdrawal of life-sustaining therapies (WLSTs) or transition to comfort measures, but noninjury factors that influence this decision have not been well characterized. We hypothesized that WLST would be associated with institutional and geographic noninjury factors. All patients with a head Abbreviated Injury Scale score ≥3 were identified from 2016 Trauma Quality Improvement Program data. We analyzed factors that might be associated with WLST, including procedure type, age, sex, race, insurance, Glasgow Coma Scale score, mechanism of injury, geographic region, and institutional size and teaching status. Adjusted logistic regression was performed to examine factors associated with WLST. Sixty-nine thousand fifty-three patients were identified: 66% male, 77% with isolated TBI, and 7.8% had WLST. The median age was 56 years (34-73). A positive correlation was found between increasing age and WLST. Women were less likely to undergo WLST than men (odds ratio 0.91 [0.84-0.98]) and took more time to for WLST (3 vs 2 days, P < .001). African Americans underwent WLST at a significantly lower rate (odds ratio 0.66 [0.58-0.75]). Variations were also discovered based on US region, hospital characteristics, and neurosurgical procedures. WLST in severe TBI is independently associated with noninjury factors such as sex, age, race, hospital characteristics, and geographic region. The effect of noninjury factors on these decisions is poorly understood; further study of WLST patterns can aid health care providers in decision making for patients with severe TBI.

Is more better? Do statewide increases in trauma centers reduce injury-related mortality?

OBJECTIVES: Trauma centers are inconsistently distributed throughout the United States. It is unclear if new trauma centers improve care and decrease mortality. We tested the hypothesis that increases in trauma centers are associated with decreases in injury-related mortality (IRM) at the state level. METHODS: We used data from the American Trauma Society to geolocate every state-designated or American College of Surgeons-verified trauma center in all 50 states and the District of Columbia from 2014 to 2018. These data were merged with publicly available IRM data from the Centers for Disease Control and Prevention. We used geographic information systems methods to map and study the relationships between trauma center locations and state-level IRM over time. Regression analysis, accounting for state-level fixed effects, was used to calculate the effect of total statewide number of trauma center on IRM and year-to-year changes in statewide trauma center with the IRM (shown as deaths per additional trauma center per 100,000 population, p value). RESULTS: Nationwide between 2014 and 2018, the number of trauma center increased from 2,039 to 2,153. Injury-related mortality also increased over time. There was notable interstate variation, from 1 to 284 trauma centers. Four patterns in statewide trauma center changes emerged: static (12), increased (29), decreased (5), or variable (4). Of states with trauma center increases, 26 (90%) had increased IRM between 2014 and 2017, while the remaining 3 saw a decline. Regression analysis demonstrated that having more trauma centers in a state was associated with a significantly higher IRM rate (0.38, p = 0.03); adding new trauma centers was not associated with changes in IRM (0.02, p = 0.8). CONCLUSION: Having more trauma centers and increasing the number of trauma center within a state are not associated with decreases in state-level IRM. In this case, more is not better. However, more work is needed to identify the optimal number and location of trauma centers to improve IRM. LEVEL OF EVIDENCE: Epidemiologic, level III; Care management, level III.

Opioids and Injury Deaths: A population-based analysis of the United States from 2006 to 2017.

INTRODUCTION: In the United States, the opioid epidemic claims over 130 lives per day due to overdoses. While the use of opioids in trauma patients has been well-described in the literature, it is unknown whether prescription opioid use is associated with mortality after trauma. We hypothesized that legally obtained prescription opioid consumption would be positively associated with injury-related deaths in the United States. METHODS: Cross-sectional time-series data was compiled using state-level mortality data from the Centers for Disease Control and Prevention Multiple Causes of Death database and prescription opioid shipping data to each state using the US Department of Justice Automated Reports and Consolidated Ordering System Retail Drug Summary reports from 2006 to 2017, with opioids shipped used as a proxy for local opioid consumption. Oxycodone and hydrocodone amounts were converted to morphine equivalent doses (MEDs). Our primary outcome was an association between MEDs and injury mortality rates at the state-level. We analyzed total injury-related deaths and subgroups of unintentional deaths, suicides, and homicides. We modeled the data using fixed effects regression to reduce bias from unmeasured differences between states. RESULTS: Data were available for all states and the District of Columbia. Opioid deliveries increased through 2012 and then declined. Total injury-related mortalities have been increasing steadily since 2012. Opioid MEDs did not show a consistent or statistically significant relationship with injury-related mortality, including with any subgroups of unintentional deaths, suicides, and homicides. CONCLUSION: In every state examined, there was no consistent relationship between the amount of prescription opioids delivered and total injury-related mortality or any subgroups, suggesting that there is not a direct association between prescription opioids and injury-related mortality. This is the first study to combine national mortality and opioid data to investigate the relationship between legally obtained opioids and injury-related mortality. The US opioid epidemic remains a significant challenge that requires ongoing attention from all stakeholders in our medical and public health systems.

Variation in neurosurgical intervention for severe traumatic brain injury: The challenge of measuring quality in trauma center verification.

BACKGROUND: Intracranial pressure monitor (ICPm) procedure rates are a quality metric for American College of Surgeons trauma center verification. However, ICPm procedure rates may not accurately reflect the quality of care in TBI. We hypothesized that ICPm and craniotomy/craniectomy procedure rates for severe TBI vary across the United States by geography and institution. METHODS: We identified all patients with a severe traumatic brain injury (head Abbreviated Injury Scale, ≥3) from the 2016 Trauma Quality Improvement Program data set. Patients who received surgical decompression or ICPm were identified via International Classification of Diseases codes. Hospital factors included neurosurgeon group size, geographic region, teaching status, and trauma center level. Two multiple logistic regression models were performed identifying factors associated with (1) craniotomy with or without ICPm or (2) ICPm alone. Data are presented as medians (interquartile range) and odds ratios (ORs) (95% confidence interval). RESULTS: We identified 75,690 patients (66.4% male; age, 59 [36-77] years) with a median Injury Severity Score of 17 (11-25). Overall, 6.1% had surgical decompression, and 4.8% had ICPm placement. Logistic regression analysis showed that region of the country was significantly associated with procedure type: hospitals in the West were more likely to use ICPm (OR, 1.34 [1.20-1.50]), while Northeastern (OR, 0.80 [0.72-0.89]), Southern (OR, 0.84 [0.78-0.92]), and Western (OR, 0.88 [0.80-0.96]) hospitals were less likely to perform surgical decompression. Hospitals with small neurosurgeon groups (<3) were more likely to perform surgical intervention. Community hospitals are associated with higher odds of surgical decompression but lower odds of ICPm placement. CONCLUSION: Both geographic differences and hospital characteristics are independent predictors for surgical intervention in severe traumatic brain injury. This suggests that nonpatient factors drive procedural decisions, indicating that ICPm rate is not an ideal quality metric for American College of Surgeons trauma center verification. LEVEL OF EVIDENCE: Epidemiological, level III; Care management/Therapeutic level III.

Pro-Con Perspectives on Ethics in Surgical Research: Update from the 39th Annual Surgical Infection Society Meeting.

Background: Surgical research is potentially invasive, high-risk, and costly. Research that advances medical dogma must justify both its ends and its means. Although ethical questions do not always have simple answers, it is critically important for the clinician, researcher, and patient to approach these dilemmas and surgical research in a thoughtful, conscientious manner. Methods: We present four ethical issues in surgical research and discuss the opposing viewpoints. These topics were presented and discussed at the 39th Annual Meeting of the Surgical Infection Society as pro-con debates. The presenters of each opinion developed a succinct summary of their respective reviews for this publication. Results: The key subjects for these pro-con debates were: (1) Should patients be enrolled for time-sensitive surgical infection research using an opt-out or an opt-in strategy? (2) Should patients who are being enrolled in a randomized controlled trial (RCT) comparing surgery with a non-operative intervention pay the costs of their treatment arm? (3) Should the scientific community embrace open access journals as the future of scientific publishing? (4) Should the majority of funding go to clinical or basic science research? Important points were illustrated in each of the pro-con presentations and illustrated the difficulties that are facing the performance and payment of infection research in the future. Conclusions: Surgical research is ethically complex, with conflicting demands between individual patients, society, and healthcare economics. At present, there are no clear answers to these and the many other ethical issues facing research in the future. Answers will only come from continued robust dialogue among all stakeholders in surgical research.