Rapid Critical Care Training for Nurses Deployed to Intensive Care Units During the COVID-19 Surge.

BACKGROUND: During the first COVID-19 pandemic wave, non-intensive care unit (non-ICU) nurses were deployed to temporary ICUs to provide critical care for the patient surge. A rapid critical care training program was designed to prepare them to care for patients in either temporary or permanent ICUs. OBJECTIVE: To evaluate the effectiveness of this training program in preparing non-ICU nurses to provide critical care for COVID-19 patients in temporary ICUs. METHODS: A survey was used to evaluate the impact of rapid critical care training on nurses' critical care skills and compare the experiences of nurses deployed to temporary versus permanent ICUs. Data were analyzed with χ2 and Spearman ρ tests with α = .05. RESULTS: Compared with nurses in other locations, nurses deployed to temporary ICUs were less likely to report improved capability in managing mechanical ventilation; infusions of sedative, vasoactive, and paralytic agents; and continuous renal replacement therapy. Nurses in temporary ICUs also reported being less prepared to care for critically ill patients (all P < .05). CONCLUSIONS: The rapid training program provided basic critical care knowledge for nurses in temporary ICUs, but experiences differed significantly between those deployed to temporary versus permanent ICUs. Although participants believed they provided safe care, nurses with no critical care experience cannot be expected to learn comprehensive critical care from expedited instruction; more formal clinical support is needed for nurses in temporary ICUs. Rapid critical care training can meet emergency needs for nurses capable of providing critical care.

A Decade of Firearm Injuries: Have We Improved?

BACKGROUND: Firearm injuries are a growing public health issue, with marked increases coinciding with the coronavirus disease 2019 (COVID-19) pandemic. This study evaluates temporal trends over the past decade, hypothesizing that despite a growing number of injuries, mortality would be unaffected. In addition, the study characterizes the types of centers affected disproportionately by the reported firearm injury surge in 2020. METHODS: Patients aged 18 years and older with firearm injuries from 2011-2020 were identified retrospectively using the National Trauma Data Bank (NTDB®). Trauma centers not operating for the entirety of the study period were excluded to allow for temporal comparisons. Joinpoint regression and risk-standardized mortality ratios (SMR) were used to evaluate injury counts and adjusted mortality over time. Subgroup analysis was performed to describe centers with the largest increases in firearm injuries in 2020. RESULTS: A total of 238,674 patients, treated at 420 unique trauma centers, met inclusion criteria. Firearm injuries increased by 31.1% in 2020, compared to an annual percent change of 2.4% from 2011-2019 (p = 0.01). Subset analysis of centers with the largest changes in firearm injuries in 2020 found that they were more often level I centers, with higher historic trauma volumes and percentages of firearm injuries (p < 0.001). Unadjusted mortality decreased by 0.9% from 2011-2020, but after controlling for demographics, injury characteristics and physiology, there was no difference in adjusted mortality over the same time period. However, among patients with injury severity scores ≥25, adjusted mortality improved compared to 2011 (SMR of 0.950 in 2020, 95% CI 0.916 - 0.986). CONCLUSIONS: Firearm injuries pose an increasing burden to trauma systems, with level I and high-volume centers seeing the largest growth in 2020. Despite increasing numbers of firearm injuries, mortality has remained unchanged over the past decade. LEVEL OF EVIDENCE: Level III, Prognostic/Epidemiologic.

Current patterns of trauma center proliferation have not led to proportionate improvements in access to care or mortality after injury: An ecologic study.

BACKGROUND: Timely access to high-level (I/II) trauma centers (HLTCs) is essential to minimize mortality after injury. Over the last 15 years, there has been a proliferation of HLTC nationally. The current study evaluates the impact of additional HLTC on population access and injury mortality. METHODS: A geocoded list of HLTC, with year designated, was obtained from the American Trauma Society, and 60-minute travel time polygons were created using OpenStreetMap data. Census block group population centroids, county population centroids, and American Communities Survey data from 2005 and 2020 were integrated. Age-adjusted nonoverdose injury mortality was obtained from CDC Wide-ranging Online Data for Epidemiologic Research and the Robert Wood Johnson Foundation. Geographically weighted regression models were used to identify independent predictors of HLTC access and injury mortality. RESULTS: Over the 15-year (2005-2020) study period, the number of HLTC increased by 31.0% (445 to 583), while population access to HLTC increased by 6.9% (77.5-84.4%). Despite this increase, access was unchanged in 83.1% of counties, with a median change in access of 0.0% (interquartile range, 0.0-1.1%). Population-level age-adjusted injury mortality rates increased by 5.39 per 100,000 population during this time (60.72 to 66.11 per 100,000). Geographically weighted regression controlling for population demography and health indicators found higher median income and higher population density to be positively associated with majority (≥50%) HLTC population coverage and negatively associated with county-level nonoverdose mortality. CONCLUSION: Over the past 15 years, the number of HLTC increased 31%, while population access to HLTC increased only 6.9%. High-level (I/II) trauma center designation is likely driven by factors other than population need. To optimize efficiency and decrease potential oversupply, the designation process should include population level metrics. Geographic information system methodology can be an effective tool to assess optimal placement. LEVEL OF EVIDENCE: Prognostic and Epidemiological; Level IV.

Performance-Based Assessment of Trauma Systems: Estimates for the State of Ohio.

OBJECTIVES: There are no widely accepted metrics to determine the optimal number and geographic distribution of trauma centers (TCs). We propose a Performance-based Assessment of Trauma System (PBATS) model to optimize the number and distribution of TCs in a region using key performance metrics. METHODS: The proposed PBATS approach relies on well-established mathematical programming approach to minimize the number of level I (LI) and level II (LII) TCs required in a region, constrained by prespecified system-related under-triage (srUT) and over-triage (srOT) rates and TC volume. To illustrate PBATS, we collected 6002 matched (linked) records from the 2012 Ohio Trauma and EMS registries. The PBATS-suggested network was compared to the 2012 Ohio network and also to the configuration proposed by the Needs-Based Assessment of Trauma System (NBATS) tool. RESULTS: For this data, PBATS suggested 14 LI/II TCs with a slightly different geographic distribution compared to the 2012 network with 21 LI and LII TC, for the same srUT≈.2 and srOT≈.52. To achieve UT ≤ .05, PBATS suggested 23 LI/II TCs with a significantly different distribution. The NBATS suggested fewer TCs (12 LI/II) than the Ohio 2012 network. CONCLUSION: The PBATS approach can generate a geographically optimized network of TCs to achieve prespecified performance characteristics such as srUT rate, srOT rate, and TC volume. Such a solution may provide a useful data-driven standard, which can be used to drive incremental system changes and guide policy decisions.

Thrombotic Events and Anticoagulation-Related Bleeding Complications in Critically Ill Patients with Coronavirus Disease 2019.

Background: Thrombosis (T) is common in coronavirus disease 2019 (COVID-19) patients, and d-dimer concentrations correlate with outcomes. Controversy exists with regards to anticoagulation (AC) for patients. We implemented a full-heparinization AC protocol from the onset of the pandemic and hypothesized that a safety signal would be undetectable. Patients and Methods: Prospective evaluation of 111 patients with COVID-19 critical illness hospitalized from March to June 2020. All patients received therapeutic heparinoid-based AC from admission. Incidences of T, bleeding (B), or both (BT) were noted. The primary outcome was mortality. Kruskal-Wallis test and logistic regression were performed. Results are expressed as n (%), median (interquartile range) and odds ratios with 95% confidence intervals. Alpha was set at 0.05. Results: Thirty-two patients (28%) had T, 23 (20%) had B, and 14 (12%) had BT; 42 (40%) patients were unaffected. Two logistic regression models (outcome = mortality) evaluated BT as T, or BT as B. For BT as T, neither T, B, nor male gender predicted mortality; similarly, for BT as B, neither T, B, nor male gender predicted mortality. Factors associated with higher odds of death included higher Acute Physiology and Chronic Health Evaluation (APACHE) II score (odds ratio [OR], 1.06; 95% confidence interval [CI], 1.00-1.13; p = 0.0045), higher d-dimer concentration (OR, 1.00; 95% CI, 1.00-1.01; p = 0.043), and higher activated partial thromboplastin time (aPTT; OR, 1.09; 95% CI, 1.02-1.16; p = 0.010). Conclusions: Neither T nor B predicted mortality in this prospective cohort of anticoagulated patients with COVID-19 critical illness. These data support continued full-dose heparinoid prophylaxis.

Video-Based Stop the Bleed Training: A New Era in Education.

INTRODUCTION: Uncontrolled bleeding is a leading cause of preventable death. The "Stop the Bleed" (StB) program trains laypersons in hemorrhage control. This study evaluated the efficacy of video-based StB training. METHODS: Participants watched two different videos: a didactic video (DdV) and a technical video (TeV) demonstrating proper techniques for StB skills (i.e., direct pressure [DP], wound packing [WP], and tourniquet application [TA]). Then, they completed a standardized skills examination (SE). Participants were surveyed at three different time points (baseline, post-DdV, and post-SE) for comparison. We compared paired categorical and continuous variables with the McNemar-Bowker test and Wilcoxon signed-rank test, respectively. Alpha was set at 0.05. RESULTS: One hundred six participants were enrolled: 52% were female and the median age was 23 y (22, 24). At baseline, 29%, 8%, and 13% reported being somewhat or extremely confident with DP, WP, and TA, respectively. These percentages increased to 92%, 79%, and 76%, respectively, after the DdV (all, P < 0.0001). After the TeV and SE, percentages increased further to 100%, 96%, and 100% (all, P < 0.0001). During the SE, 96%, 99%, and 89% of participants were able to perform DP, WP, and TA without prompting. Among participants, 98% agreed that the video course was effective and 79% agreed that the DdV and TeV were engaging. CONCLUSIONS: We describe a novel paradigm of video-based StB learning combined with an in-person, standardized SE. Confidence scores in performing the three crucial StB tasks increased significantly during and after course completion. Through remote learning, StB could be disseminated more widely.

Improving Communication and Response to Clinical Deterioration to Increase Patient Safety in the Intensive Care Unit.

BACKGROUND: In the critical care setting, early recognition of clinical decompensation is imperative to trigger prompt intervention and optimize patient outcomes. LOCAL PROBLEM: In a 20-bed surgical intensive care unit of an urban academic medical center, cases of clinical deterioration that highlighted opportunities to improve the communication process prompted a reassessment of health care provider roles and responsibilities. METHODS: A quality improvement initiative was implemented to enhance communication among intensive care unit clinical staff members, improve the timeliness of reporting clinical deterioration, and ensure implementation of timely, appropriate interventions to eliminate adverse outcomes. INTERVENTIONS: Nurses were surveyed to determine their perceptions of communication and collaboration among providers. Education was provided that focused on familiarizing nurses with clinical conditions necessitating direct notification of the attending surgical intensivist and included review of a case in which escalation of care did not occur. Multidisciplinary rounds were expanded to engage night-shift nurses in clinical discussions and decision-making. A template was created to document episodes of escalation in the electronic health record. RESULTS: Since implementation of the quality improvement interventions, no incidents of patient harm or death related to failure to escalate have occurred to date. A total of 16 episodes of escalation for clinical deterioration were documented in the electronic health record. Most nurses reported an increased level of confidence in understanding when to escalate concerns about clinical deterioration. CONCLUSION: Implementing a multimodal program to empower nurses to escalate clinical concerns directly to the attending physician eliminated adverse events related to failure to escalate.

Disparity in Transport of Critically Injured Patients to Trauma Centers: Analysis of the National Emergency Medical Services Information System (NEMSIS).

BACKGROUND: Patient morbidity and mortality decrease when injured patients meeting CDC Field Triage Criteria (FTC) are transported by emergency medical services (EMS) directly to designated trauma centers (TCs). This study aimed to identify potential disparities in the transport of critically injured patients to TCs by EMS. STUDY DESIGN: We identified all patients in the National EMS Information System (NEMSIS) database in the National Association of EMS State Officials East region from January 1, 2018, to December 31, 2019, with a final prehospital acuity of critical or emergent by EMS. The cohort was stratified into patients transported to TCs or non-TCs. Analyses consisted of descriptive epidemiology, comparisons, and multivariable logistic regression analysis to measure the association of demographic features, vital signs, and CDC FTC designation by EMS with transport to a TC. RESULTS: A total of 670,264 patients were identified as sustaining an injury, of which 94,250 (14%) were critically injured. Of those 94,250 critically injured, 56.0% (52,747) were transported to TCs. Among all critically injured women (n = 41,522), 50.4% were transported to TCs compared with 60.4% of critically injured men (n = 52,728, p < 0.001). In a multivariable logistic regression model, critically injured women were 19% less likely to be taken to a TC compared with critically injured men (OR 0.81, 95% CI 0.71-0.93, p = 0.003). CONCLUSIONS: Critically injured female patients are less likely to be transported to TCs when compared with their male counterparts. Performance improvement processes that assess EMS compliance with field triage guidelines should explicitly evaluate for sex-based disparities. Further studies are warranted.

Factors associated with limitation of care after fatal injury.

BACKGROUND: There is variability in end-of-life care of trauma patients. Many survive resuscitation but die after limitation of care (LoC). This study investigated LoC at a level I center. METHODS: Adult trauma deaths between January 2016 and June 2020 were reviewed. Patients were stratified into "full code" versus any LoC (i.e., do not resuscitate, no escalation, or withdrawal of care) and by timing to LoC. Emergency department and "brain" deaths were excluded. Unadjusted logistic regression and Cox proportional hazards were used for analyses. Results include n (%) and odds ratios (ORs) with 95% confidence intervals (CIs), with α = 0.05. RESULTS: A total of 173 patients were included; 15 patients (8%) died full code and 158 (91%) died after LoC. Seventy-seven patients (48%) underwent incremental LoC. Age (OR, 1.05; 95% CI, 1.02-1.08; p = 0.0010) and female sex (OR, 3.71; 95% CI, 1.01-13.64; p = 0.0487) increased the odds of LoC; number of anatomic injuries (OR, 0.91; 95% CI, 0.85-0.98; p = 0.0146), chest injuries (Abbreviated Injury Scale [AIS] score chest, >3) (OR, 0.02; 95% CI, 0.01-0.26; p = 0.0021), extremity injury (AIS score, >3) (OR, 0.08; 95% CI, 0.01-0.64; p = 0.0170), and hospital complications equal to 1 (OR, 0.21; 95% CI, 0.06-0.78; p = 0.0201) or ≥2 (OR, 0.19; 95% CI, 0.04-0.87; p = 0.0319) decreased the odds of LoC. For those having LoC, final limitations were implemented in <14 days for 83% of patients; markers of injury severity (e.g., Injury Severity Score, Glasgow Coma Scale score, and AIS score) increased the odds of early LoC implementation. CONCLUSION: Most patients died after LoC was implemented in a timely fashion. Significant head injury increased the odds of LoC. The number of injuries, severe chest and extremity injuries, and increasing number of complications decreased the odds of LoC, presumably because patients died before LoCs were initiated. Understanding factors contributing to end-of-life care could help guide discussions regarding LoCs. LEVEL OF EVIDENCE: Prognostic and Epidemiologic; Level III.

Disparities in Insurance Status Are Associated With Outcomes but Not Timing of Trauma Care.

INTRODUCTION: Patient factors influence outcomes after injury. Delays in care have a crucial impact. We investigated the associations between patient characteristics and timing of transfer from the emergency department to definitive care. METHODS: This was a review of adult trauma patients treated between January 1, 2016, and December 31, 2018. Bivariate analyses were used to build Cox proportional hazards models. We built separate logistic and negative binomial regression models for secondary outcomes using mixed-step selection to minimize the Akaike information criterion c. RESULTS: A total of 1219 patients were included; 68.5% were male, 56.8% White, 11.2% Black, and 7.8% Asian/Pacific Islander. The average age was 51 ± 21 y. Overall, 13.7% of patients were uninsured. The average length of stay was 5 d and mortality was 5.9%. Shorter transfer time out of the emergency department was associated with higher tier of activation (relative risk [RR] 1.39, 95% confidence interval [CI] 1.09-1.77; P = 0.0074), Injury Severity Score between 16 and 24 points (RR 1.57, 95% CI 1.04-2.32; P = 0.0307) or ≥25 (RR 3.85, 95% CI 2.45-5.94; P = 0.0001), and penetrating injury. Longer time to event was associated with Glasgow coma scale score ≥14 points (RR 0.47, 95% CI 0.27-0.85; P = 0.0141). Uninsured patients were less likely to be admitted (odds ratio 0.29, 95% CI 0.17-0.48; P = 0.0001) and more likely to experience shorter length of stay (incidence rate ratio 0.34, 95% CI 0.24-0.51; P = 0.0001). CONCLUSIONS: Injury characteristics and insurance status were associated with patient outcomes in this retrospective, single-center study. We found no disparity in timing of intrafacility transfer, perhaps indicating that initial management protocols preserve equity.

Rotational thromboelastometry in patients with acute respiratory distress syndrome owing to coronavirus disease 2019: Is there a viscoelastic fingerprint and a role for predicting thrombosis?

OBJECTIVES: We evaluated rotational thromboelastometry tracings in 44 critically ill coronavirus disease 2019 patients, to determine whether there is a viscoelastic fingerprint and to test the hypothesis that the diagnosis and prediction of venous thromboembolism would be enhanced by the addition of rotational thromboelastometry testing. RESULTS: Rotational thromboelastometry values reflected an increase in clot strength for the EXTEM, INTEM, and FIBTEM assays beyond the reference range. No hyperfibrinolysis was noted. Fibrinolysis shutdown was present but did not correlate with thrombosis; 32% (14/44) of patients experienced a thrombotic episode. For every 1 mm increase of FIBTEM maximum clot formation, the odds of developing thrombosis increased 20% (95% confidence interval, 0-40%, P = .043), whereas for every 1,000 ng/mL increase in D-dimer, the odds of thrombosis increased by 70% (95% confidence interval, 20%-150%, P = .004), after adjustment for age and sex (AUC 0.96, 95% confidence interval, 0.90-1.00). There was a slight but significant improvement in model performance after adding FIBTEM maximum clot formation and EXTEM clot formation time to D-dimer in a multivariable model (P = .04). CONCLUSIONS: D-dimer concentrations were more predictive of thrombosis in our patient population than any other parameter. Rotational thromboelastometry confirmed the hypercoagulable state of coronavirus disease 2019 intensive care unit patients. FIBTEM maximum clot formation and EXTEM clot formation time increased the predictability for thrombosis compared with only using D-dimer. Rotational thromboelastometry analysis is most useful in augmenting the information provided by the D-dimer concentration for venous thromboembolism risk assessment when the D-dimer concentration is between 1,625 and 6,900 ng/dL, but the enhancement is modest. Fibrinolysis shutdown did not correlate with thrombosis.

Patient Factors Associated With Appendectomy Within 30 Days of Initiating Antibiotic Treatment for Appendicitis.

IMPORTANCE: Use of antibiotics for the treatment of appendicitis is safe and has been found to be noninferior to appendectomy based on self-reported health status at 30 days. Identifying patient characteristics associated with a greater likelihood of appendectomy within 30 days in those who initiate antibiotics could support more individualized decision-making. OBJECTIVE: To assess patient factors associated with undergoing appendectomy within 30 days of initiating antibiotics for appendicitis. DESIGN, SETTING, AND PARTICIPANTS: In this cohort study using data from the Comparison of Outcomes of Antibiotic Drugs and Appendectomy (CODA) randomized clinical trial, characteristics among patients who initiated antibiotics were compared between those who did and did not undergo appendectomy within 30 days. The study was conducted at 25 US medical centers; participants were enrolled between May 3, 2016, and February 5, 2020. A total of 1552 participants with acute appendicitis were randomized to antibiotics (776 participants) or appendectomy (776 participants). Data were analyzed from September 2020 to July 2021. EXPOSURES: Appendectomy vs antibiotics. MAIN OUTCOMES AND MEASURES: Conditional logistic regression models were fit to estimate associations between specific patient factors and the odds of undergoing appendectomy within 30 days after initiating antibiotics. A sensitivity analysis was performed excluding participants who underwent appendectomy within 30 days for nonclinical reasons. RESULTS: Of 776 participants initiating antibiotics (mean [SD] age, 38.3 [13.4] years; 286 [37%] women and 490 [63%] men), 735 participants had 30-day outcomes, including 154 participants (21%) who underwent appendectomy within 30 days. After adjustment for other factors, female sex (odds ratio [OR], 1.53; 95% CI, 1.01-2.31), radiographic finding of wider appendiceal diameter (OR per 1-mm increase, 1.09; 95% CI, 1.00-1.18), and presence of appendicolith (OR, 1.99; 95% CI, 1.28-3.10) were associated with increased odds of undergoing appendectomy within 30 days. Characteristics that are often associated with increased risk of complications (eg, advanced age, comorbid conditions) and those clinicians often use to describe appendicitis severity (eg, fever: OR, 1.28; 95% CI, 0.82-1.98) were not associated with odds of 30-day appendectomy. The sensitivity analysis limited to appendectomies performed for clinical reasons provided similar results regarding appendicolith (adjusted OR, 2.41; 95% CI, 1.49-3.91). CONCLUSIONS AND RELEVANCE: This cohort study found that presence of an appendicolith was associated with a nearly 2-fold increased risk of undergoing appendectomy within 30 days of initiating antibiotics. Clinical characteristics often used to describe severity of appendicitis were not associated with odds of 30-day appendectomy. This information may help guide more individualized decision-making for people with appendicitis.

Skin Failure Among Critically Ill Patients Afflicted with Coronavirus Disease 2019 (COVID-19).

Objective: To characterize skin integrity among coronavirus disease 2019 (COVID-19) patients treated in the intensive care unit (ICU), and identify risk factors for skin failure (SF) in these patients. Design: The characteristic, profound pro-inflammatory, hypercoagulable state of COVID-19 is manifested by the high severity of illness and extensive organ dysfunction observed in these patients. SF in critically ill patients, although described previously, exhibits a uniquely complex pathogenesis in this population. Patients: Retrospective review of all COVID-19 patients (confirmed positive for severe acute respiratory syndrome coronavirus-2 [SARS-CoV-2]) admitted to a single surgical ICU for at least 48 hours between March-June 2020. Interventions: Data were extracted from a COVID-19 institutional data repository that harvested data from electronic health records and other clinical data sources. Demographics; coagulation/inflammation biomarkers; number, location, and stage of SF lesions; resource utilization; and outcomes were captured. Measurements and Main Results: 64 patients met inclusion criteria; 51 (80%) developed SF (SF+ ). Forty-three (85%) developed stage 3 or higher SF (χ2 = 22.66, P < .0001). Thirty-nine of 51 (76%) SF+ patients developed more than one SF lesion (χ2 = 13.26, P = .0003). SF+ patients manifested a profound pro-inflammatory, hypercoagulable phenotype (lower serum albumin and higher ferritin, interleukin [IL]-6 and D-dimer concentrations [all, P < .001]). Durations of mechanical ventilation, vasopressor therapy, and ICU length of stay were significantly longer (all, P < .05) in the SF + patients. Conclusions: The unique characteristics of COVID-19 dermatopathology and the strong correlation between markers of inflammation and development of SF reflect COVID-19-related organ dysfunction and its deleterious effects on the microcirculation. Considering that skin is invaded directly by SARS-CoV-2 and affected by COVID-19-related immune complex deposition and microthrombosis, SF may reflect disease as opposed to pressure injuries related to processes of care. In the context of COVID-19 critical illness, SF should not be considered a "never event."

Cervical spinal cord infarction associated with coronavirus infectious disease (COVID)-19.

Coronavirus disease (COVID-19) has a number of emerging neurological manifestations in addition to pneumonia and respiratory distress. In what follows, we describe a case of a previously healthy young man with severe COVID-19 who subsequently developed an acute flaccid paralysis. Work up revealed a lesion in his cervical spinal cord concerning for spinal infarction or transverse myelitis. He received empiric pulsed steroids without improvement. Taken together, we felt his presentation was most consistent with spinal cord infarction in the setting of critical illness with COVID-19. We believe this is a rare case of spinal cord stroke associated with COVID-19.

Comparing geographic information system-based estimates with trauma center registry data to assess the effects of additional trauma centers on system access.

BACKGROUND: Geographic information systems (GISs) are often used to analyze trauma systems. Geographic information system-based approaches can model access to a trauma center (TC), including estimates of transport time and population coverage, when accurate trauma registry and emergency medical systems (EMS) data are not available. We hypothesized that estimates of trauma system performance calculated using a standard GIS method with public data would be comparable with trauma registry data. METHODS: A standardized GIS-based method was used to estimate metrics of TC access in a regional trauma system in which the number of TCs increased from one to three during a 3-year period. Registry data from the index TC in the system were evaluated for different periods during this evolution. The number of admissions to the TC in different periods was compared with changes predicted by the GIS-based model, and the distribution of observed ground-based transportation times was compared with the predicted distribution. RESULTS: With the addition of two TCs to the system, the volume of patients transported by ground to the index TC decreased by 30%. However, the model predicted a 68% decrease in population having the shortest predicted transport time to the index TC. The model predicted the geographic trend seen in the registry data, but many patients were transported to the index TC even though it was not the closest center. Observed transport times were uniformly shorter than predicted times. CONCLUSION: The GIS-based model qualitatively predicted changes in distribution of trauma patients, but registry data highlight that field triage decisions are more complex than model assumptions. Similarly, transport times were systematically overestimated. This suggests that model assumptions, such as vehicle speed, based on normal traffic may not fully reflect emergency medical systems (EMS) operations. There remains great need for metrics to guide policy based on widely available data. LEVEL OF EVIDENCE: Epidemiological, level III.

A Randomized Trial Comparing Antibiotics with Appendectomy for Appendicitis.

BACKGROUND: Antibiotic therapy has been proposed as an alternative to surgery for the treatment of appendicitis. METHODS: We conducted a pragmatic, nonblinded, noninferiority, randomized trial comparing antibiotic therapy (10-day course) with appendectomy in patients with appendicitis at 25 U.S. centers. The primary outcome was 30-day health status, as assessed with the European Quality of Life-5 Dimensions (EQ-5D) questionnaire (scores range from 0 to 1, with higher scores indicating better health status; noninferiority margin, 0.05 points). Secondary outcomes included appendectomy in the antibiotics group and complications through 90 days; analyses were prespecified in subgroups defined according to the presence or absence of an appendicolith. RESULTS: In total, 1552 adults (414 with an appendicolith) underwent randomization; 776 were assigned to receive antibiotics (47% of whom were not hospitalized for the index treatment) and 776 to undergo appendectomy (96% of whom underwent a laparoscopic procedure). Antibiotics were noninferior to appendectomy on the basis of 30-day EQ-5D scores (mean difference, 0.01 points; 95% confidence interval [CI], -0.001 to 0.03). In the antibiotics group, 29% had undergone appendectomy by 90 days, including 41% of those with an appendicolith and 25% of those without an appendicolith. Complications were more common in the antibiotics group than in the appendectomy group (8.1 vs. 3.5 per 100 participants; rate ratio, 2.28; 95% CI, 1.30 to 3.98); the higher rate in the antibiotics group could be attributed to those with an appendicolith (20.2 vs. 3.6 per 100 participants; rate ratio, 5.69; 95% CI, 2.11 to 15.38) and not to those without an appendicolith (3.7 vs. 3.5 per 100 participants; rate ratio, 1.05; 95% CI, 0.45 to 2.43). The rate of serious adverse events was 4.0 per 100 participants in the antibiotics group and 3.0 per 100 participants in the appendectomy group (rate ratio, 1.29; 95% CI, 0.67 to 2.50). CONCLUSIONS: For the treatment of appendicitis, antibiotics were noninferior to appendectomy on the basis of results of a standard health-status measure. In the antibiotics group, nearly 3 in 10 participants had undergone appendectomy by 90 days. Participants with an appendicolith were at a higher risk for appendectomy and for complications than those without an appendicolith. (Funded by the Patient-Centered Outcomes Research Institute; CODA ClinicalTrials.gov number, NCT02800785.).