Hypertension during transfer is associated with poor outcomes in unstable patients with ruptured abdominal aortic aneurysm.

OBJECTIVE: Limited data exist for optimal blood pressure (BP) management during transfer of patients with ruptured abdominal aortic aneurysm (rAAA). This study evaluates the effects of hypertension and severe hypotension during interhospital transfers in a cohort of patients with rAAA in hemorrhagic shock. METHODS: We performed a retrospective, single-institution review of patients with rAAA transferred via air ambulance to a quaternary referral center for repair (2003-2019). Vitals were recorded every 5 minutes in transit. Hypertension was defined as a systolic BP of ≥140 mm Hg. The primary cohort included patients with rAAA with hemorrhagic shock (≥1 episode of a systolic BP of <90 mm Hg) during transfer. The primary analysis compared those who experienced any hypertensive episode to those who did not. A secondary analysis evaluated those with either hypertension or severe hypotension <70 mm Hg. The primary outcome was 30-day mortality. RESULTS: Detailed BP data were available for 271 patients, of which 125 (46.1%) had evidence of hemorrhagic shock. The mean age was 74.2 ± 9.1 years, 93 (74.4%) were male, and the median total transport time from helicopter dispatch to arrival at the treatment facility was 65 minutes (interquartile range, 46-79 minutes). Among the cohort with shock, 26.4% (n = 33) had at least one episode of hypertension. There were no significant differences in age, sex, comorbidities, AAA repair type, AAA anatomic location, fluid resuscitation volume, blood transfusion volume, or vasopressor administration between the hypertensive and nonhypertensive groups. Patients with hypertension more frequently received prehospital antihypertensives (15% vs 2%; P = .01) and pain medication (64% vs 24%; P < .001), and had longer transit times (36.3 minutes vs 26.0 minutes; P = .006). Episodes of hypertension were associated with significantly increased 30-day mortality on multivariable logistic regression (adjusted odds ratio [aOR], 4.71; 95% confidence interval [CI], 1.54-14.39; P = .007; 59.4% [n = 19] vs 40.2% [n = 37]; P = .01). Severe hypotension (46%; n = 57) was also associated with higher 30-day mortality (aOR, 2.82; 95% CI, 1.27-6.28; P = .01; 60% [n = 34] vs 32% [n = 22]; P = .01). Those with either hypertension or severe hypotension (54%; n = 66) also had an increased odds of mortality (aOR, 2.95; 95% CI, 1.08-8.11; P = .04; 58% [n = 38] vs 31% [n = 18]; P < .01). Level of hypertension, BP fluctuation, and timing of hypertension were not significantly associated with mortality. CONCLUSIONS: Hypertensive and severely hypotensive episodes during interhospital transfer were independently associated with increased 30-day mortality in patients with rAAA with shock. Hypertension should be avoided in these patients, but permissive hypotension approaches should also maintain systolic BPs above 70 mm Hg whenever possible.

Death and End-of-Life Care in Emergency Departments in the US.

Importance: There are more than 140 million annual visits to emergency departments (EDs) in the US. The role of EDs in providing care at or near the end of life is not well characterized. Objective: To determine the frequency of death in the ED or within 1 month of an ED visit in an all-age, all-payer national database. Design, Setting, and Participants: The retrospective cohort study used patient-level data from the nationally representative Optum clinical electronic health record data set for 2010 to 2020. Data were analyzed from January to March 2022. Exposures: Age, Charlson Comorbidity Index (CCI), and year of ED encounter. Main Outcomes and Measures: The primary outcome was death in the ED, overall and stratified by age, CCI, or year. A key secondary outcome was death within 1 month of an ED encounter. We extrapolated to make national estimates using US Census and Nationwide Emergency Department Sample data. Results: Among a total of 104 113 518 individual patients with 96 239 939 ED encounters, 205 372 ED deaths were identified in Optum, for whom median (IQR) age was 72 (53 to >80) years, 114 582 (55.8%) were male, and 152 672 (74.3%) were White. ED death affected 0.20% of overall patients and accounted for 0.21% of ED encounters. An additional 603 273 patients died within 1 month of an ED encounter. Extrapolated nationally, ED deaths accounted for 11.3% of total deaths from 2010 to 2019, and 33.2% of all decedents nationally visited the ED within 1 month of their death. The proportion of total national deaths occurring in the ED decreased by 0.27% annually (P for trend = .003) but the proportion who died within 1 month of an ED visit increased by 1.2% annually (P for trend < .001). Compared with all ED encounters, patients with visits resulting in death were older, more likely to be White, male, and not Hispanic, and had higher CCI. Among ED encounters for patients aged older than 80 years, nearly 1 in 12 died within 1 month. Conclusions and Relevance: This retrospective cohort study found deaths during or shortly after ED care were common, especially among patients who are older and with chronic comorbidities. EDs must identify patients for whom end-of-life care is necessary or preferred and be equipped to deliver this care excellently.

The Effect of Blood Transfusion during Air Medical Transport on Transport Times in Patients with Ruptured Abdominal Aortic Aneurysm.

Background: Patients presenting with a diagnosis of ruptured abdominal aortic aneurysm (RAAA) to community hospitals must be transported to tertiary care centers, where necessary resources are available. Unfortunately, guidelines for treatment of RAAA lack high-level evidence on the optimal resuscitation of RAAA patients during transport. We hypothesized that transfusion of packed red blood cells (PRBCs) during transport would not delay transport times in patients with RAAA. Methods: We performed a retrospective analysis of a prospective registry including prehospital data of patients with RAAA presenting to a single academic hospital in Western Pennsylvania between 2001 and 2019. Our primary outcomes were prehospital transport times: "transport interval" and "total interval." "Transport interval" is the duration from patient pickup at the outside hospital (OSH) to arrival at the receiving facility. "Total interval" is the duration from dispatch of the air medical transport to arrival of the patient to the receiving facility. We then compared two groups of patients, stratified by the receipt of PRBCs in transit, by reporting mean difference (95% confidence interval: CI) for continuous variables and percent difference (95% CI) for categorical variables. We performed two multivariate linear regression models to test if there was any effect of the receipt of PRBCs in transit on transport times. Results: We included 271 patients with RAAA transported by our air ambulance system who underwent an operation at the receiving facility, 99 (37%) of whom received PRBCs in transit. Mean ± standard deviation (SD) of the total intervals were 67 ± 28 and 71 ± 42 minutes, among patients who received or did not receive PRBCs in transit respectively, with no significant difference (p = 0.437). Following adjusted analysis, the receipt of PRBCs during transport was not associated with increased transport times, after accounting for age, hypotension, endovascular aneurysm repair (EVAR), and PRBC transfusion at the OSH. Conclusion: PRBC transfusion during air medical transport in patients with RAAA did not delay transport times.

Relative Hyperlactatemia in the Emergency Department.

Objective: The clinical interpretation of lactate ≤ 2.00 mmol/L in emergency department (ED) patients is not well-characterized. This study aims to determine the optimal cutoff value for lactate within the reference range that predicts in-hospital mortality among ED patients. Methods: This was a retrospective study of adult patients presenting to a tertiary ED with an initial serum lactate level of <2.00 mmol/L. The primary outcome was in-hospital mortality. Youden's index was utilized to determine the optimal threshold that predicts mortality. Patients above the threshold were labeled as having relative hyperlactatemia. Results: During the study period, 1,638 patients were included. The mean age was 66.9 ± 18.6 years, 47.1% of the population were female, and the most prevalent comorbidity was hypertension (56.7%). The mean lactate level at presentation was 1.5 ± 0.3 mmol/L. In-hospital mortality was 3.8% in the overall population, and 16.2% were admitted to the ICU. A lactate level of 1.33 mmol/L was found to be the optimal cutoff that best discriminates between survivors and non-survivors. Relative hyperlactatemia was an independent predictor of in-hospital mortality (OR 1.78 C1.18-4.03; p = 0.02). Finally, relative hyperlactatemia was associated with increased mortality in patients without hypertension (4.7 vs. 1.1%; p = 0.008), as well as patients without diabetes or COPD. Conclusion: The optimal cutoff of initial serum lactate that discriminates between survivors and non-survivors in the ED is 1.33 mmol/L. Relative hyperlactatemia is associated with increased mortality in emergency department patients, and this interaction seems to be more important in healthy patients.

Data-driven classification of arrest location for emergency department cardiac arrests.

BACKGROUND: Resuscitation research is inconsistent in how emergency department (ED) arrests are classified. We tested whether clinical features of ED arrests more closely resembled out-of-hospital cardiac arrest (OHCA) or in-hospital cardiac arrest (IHCA). METHODS: We performed a retrospective study including all patients resuscitated from cardiac arrest at a single academic medical center from January 2010 to December 2019. We abstracted clinical information from our prospective registry. We used unsupervised learning (k-prototypes) to identify clusters within the OHCA and IHCA cohorts. We determined the number of subgroups using scree plots. We assigned individual ED arrest patients the nearest OHCA or IHCA cluster based on the shortest Gower distance from that patient to the nearest cluster center. In our secondary analysis, we determined the optimal number of clusters in each of the 3 arrest cohorts, and then calculated the mean Gower distances with the standard deviation (SD) between cluster centers (ED-IHCA, ED-OHCA, IHCA-OHCA). RESULTS: We included 2723 patients: 372 (14%) ED arrests, 1709 (63%) OHCA, and 642 (23%) IHCA. We identified 3 clusters of OHCA patients, and 4 clusters of IHCA patients. Of ED arrest cases, 292 (78%) most closely resembled an IHCA cluster and 80 (22%) most closely resembled an OHCA cluster. Mean (SD) Gower distance between ED arrest and IHCA centers was 0.33 (0.2). Mean Gower distances between ED arrest-OHCA centers and between IHCA-OHCA centers were 0.41 (0.11). CONCLUSION: Across multiple aggregated measures, ED arrests resemble IHCA more than OHCA.