Michele Moyer

Noninvasive Hemodynamic Monitoring in Emergency Patients with Suspected Heart Failure, Sepsis and Stroke: The Premium Registry

Introduction Noninvasive hemodynamic (HD) assessments in the emergency department (ED) might assist in the diagnosis, therapeutic plan development and risk stratification of acutely ill patients. This multinational observational study was designed to initiate noninvasive HD measurements prior to any ED patient therapeutic interventions and broadly evaluate them for potential diagnostic, therapeutic and predictive value. Methods We enrolled patients with suspected acute heart failure (AHF), sepsis or stroke. Continuous noninvasive HD monitoring was begun using the Nexfin finger cuff device (Edwards LifeSciences, BMEYE, Amsterdam, Netherlands). Beat-to-beat HD measurements were averaged for the initial 15 minutes, prior to therapeutic intervention. We performed suspected disease group comparisons and evaluated HD predictors of 30-day mortality. Results Of 510 patients enrolled: 185 (36%) AHF, 194 (38%) sepsis and 131 (26%) stroke. HD variables were significantly different (p<0.05) amongst the groups. Cardiac output and index and stroke volume index (SVI) were highest in sepsis (6.5, 3.5, 36), followed by stroke (5.5, 2.7, 35.8), and lowest in AHF (5.4, 2.7, 33.6). The in-group HD standard deviations and ranges measurements were large, indicating heterogeneous underlying HD profiles. Presenting SVI predicted 30-day mortality for all groups. Conclusion Presenting ED noninvasive HD data has not been previously reported in any large patient population. Our data suggest a potential role for early noninvasive HD assessments aiding in diagnosing of patients, individualizing therapy based on each person’s unique HD values and predicting 30-day mortality. Further studies and analyses are needed to determine how HD assessments should be best used in the ED.

Presenting phenotypes of acute heart failure patients in the ED: Identification and implications

Background: There is little known about the baseline hemodynamic (HD) profiles (beyond pulse/blood pressure) of patients presenting to the Emergency department (ED) with acute heart failure (AHF). Assessing these baseline parameters could help differentiate underlying HD phenotypes which could be used to develop specific phenotypic specific approaches to patient care. Methods: Patients with suspected AHF were enrolled in the PREMIUM (Prognostic Hemodynamic Profiling in the Acutely Ill Emergency Department Patient) multinational registry and continuous HD monitoring was initiated on ED presentation using noninvasive finger cuff technology (Nexfin, BMEYE, Edwards Lifesciences, Irvine, California). Individuals with clinically suspected and later confirmed AHF were included in this analysis and initial 15 minute averages for available HD parameters were calculated. K‐means clustering was performed to identify out of 23 HD variables a set that provided the greatest level of inter‐cluster discrimination and intra‐cluster cohesions. Results: A total of 127 patients had confirmed AHF. The final model, using mean normalized patient baseline HD values was able to differentiate these individuals into 3 distinct phenotypes. Cluster 1: normal cardiac index (CCI) and systemic vascular resistance index (SVRI); cluster 2: very low CI and markedly increased SVRI: and cluster 3: low CI and an elevated SVRI. These clusters were not differentiated using clinically available ED information. Conclusions: Three distinct clusters were defined using novel noninvasive presenting HD monitoring technology in this cohort of ED AHF patients. Further studies are needed to determine whether phenotypic specific therapies based on these clusters can improve outcomes.

Continuous hemodynamic monitoring in acute stroke: An exploratory analysis

Introduction Non-invasive, continuous hemodynamic monitoring is entering the clinical arena. The primary objective of this study was to test the feasibility of such monitoring in a pilot sample of Emergency Department (ED) stroke patients. Secondary objectives included analysis of hemodynamic variability and correlation of continuous blood pressure measurements with standard measurements. Methods This study was a secondary analysis of 7 stroke patients from a prospectively collected data set of patients that received 2 hours of hemodynamic monitoring in the ED. Stroke patients were included if hemorrhagic or ischemic stroke was confirmed by neuroimaging, and symptom onset was within 24 hours. They were excluded for the presence of a stroke mimic or transient ischemic attack. Monitoring was performed using the Nexfin device (Edwards Lifesciences, Irvine CA). Results The mean age of the cohort was 71 ± 17 years, 43% were male, and the mean National Institute of Health Stroke Scale (NIHSS) was 6.9 ± 5.5. Two patients had hemorrhagic stroke. We obtained 42,456 hemodynamic data points, including beat-to-beat blood pressure measurements with variability of 18 mmHg and cardiac indices ranging from 1.8 to 3.6 l/min/m2. The correlation coefficient between continuous blood pressure measurements with the Nexfin device and standard ED readings was 0.83. Conclusion This exploratory investigation revealed that continuous, noninvasive monitoring in the ED is feasible in acute stroke. Further research is currently underway to determine how such monitoring may impact outcomes in stroke or replace the need for invasive monitoring.

Hemodynamic characteristics of suspected stroke in the emergency department

Background Systemic hemodynamic characteristics of patients with suspected acute ischemic stroke are poorly described. The objective of this study was to identify baseline hemodynamic characteristics of emergency department (ED) patients with suspected acute stroke. Methods This was a planned analysis of the stroke cohort from a multicenter registry of hemodynamic profiling of ED patients. The registry prospectively collected non‐invasive hemodynamic measurements of patients with suspicion for acute stroke within 12 h of symptom onset. K‐means cluster analysis identified hemodynamic phenotypes of all suspected stroke patients, and we performed univariate hemodynamic comparisons based on final diagnoses. Results There were 72 patients with suspected acute stroke, of whom 38 (53%) had a final diagnosis of ischemic stroke, 10 (14%) had hemorrhagic stroke, and 24 (33%) had transient ischemic attack (TIA). Analysis defined three phenotypic clusters based on low or normal cardiac index (CI) and normal or high systemic vascular resistance index (SVRI). Patients with TIA had lower mean CI (2.3 L/min/m2) compared to hemorrhagic or ischemic stroke patients (p < 0.01). Conclusions The study demonstrates the feasibility of defining hemodynamic phenotypes of ED patients with suspected stroke.

Presenting hemodynamic phenotypes in ED patients with confirmed sepsis

OBJECTIVES To derive distinct clusters of septic emergency department (ED) patients based on their presenting noninvasive hemodynamic (HD) measurements and to determine if any clinical parameters could identify these groups. METHODS Prospective, observational, convenience study of individuals with confirmed systemic infection. Presenting, pretreatment noninvasive HD parameters were compiled using Nexfin (Bmeye/Edwards LifeSciences) from 127 cases. Based on normalized parameters, k-means clustering was performed to identify a set of variables providing the greatest level of intercluster discrimination and intracluster cohesion. RESULTS Our best HD clustering model used 2 parameters: the cardiac index (CI [L/min per square meter]) and systemic vascular resistance index (SVRI [dynes·s/cm5 per square meter]). Using this model, 3 different patient clusters were identified. Cluster 1 had high CI with normal SVRI (CI, 4.03 ± 0.61; SVRI, 1655.20 ± 348.08); cluster 2 low CI with increased vascular tone (CI, 2.50 ± 0.50; SVRI, 2600.83 ± 576.81); and cluster 3 very low CI with markedly elevated SVRI (CI, 1.37 ± 0.81; SVRI, 5951.49 ± 1480.16). Cluster 1 patients had the lowest 30-day overall mortality. Among clinically relevant variables available during the initial patient evaluation in the ED age, heart rate and temperature were significantly different across the 3 clusters. CONCLUSIONS Emergency department patients with confirmed sepsis had 3 distinct cluster groupings based on their presenting noninvasively derived CI and SVRI. Further clinical studies evaluating the effect of early cluster-specific therapeutic interventions are needed to determine if there are outcome benefits of ED HD phenotyping in these patients.

Ultrarapid Rule-out for Acute Myocardial Infarction Using the Generation 5 Cardiac Troponin T Assay: Results From the REACTION-US Study

Study objective: We determine how well a new Food and Drug Administration–approved single cardiac troponin T (cTnT) Generation 5 baseline measurement below the level of quantification (6 ng/L) and a novel study‐derived baseline and 30‐minute cTnT Generation 5 algorithm might adequately exclude acute myocardial infarction in patients with suspected acute coronary syndrome in a US emergency department (ED). Methods: Patients presenting with any symptoms suspicious for acute coronary syndrome were enrolled at a single US ED. Baseline and 30‐minute blood samples were obtained and cTnT Generation 5 levels were later batch analyzed in an independent core laboratory. Acute myocardial infarction diagnosis was adjudicated by a cardiologist and an emergency physician. Results: Of the 569 study patients, 44 (7.7%) had an acute myocardial infarction diagnosis. One hundred sixty‐four patients (28.8%) had a presentation cTnT Generation 5 level less than 6 ng/L, and none of these individuals had an acute myocardial infarction (negative predictive value of 100% [95% confidence interval 97.8% to 100.0%] and sensitivity of 100% [95% confidence interval 92.0% to 100.0%]). A baseline cTnT Generation 5 value of less than 8 ng/L and a 30‐minute &Dgr; of less than 3 ng/L were present in 221 patients (41.0%), and none had acute myocardial infarction (negative predictive value of 100% [95% confidence interval 98.3% to 100.0%] and sensitivity of 100% [95% confidence interval 92.0% to 100.0%]). Conclusion: In a single US ED, a single baseline cTnT Generation 5 measurement less than 6 mg/L and values at baseline less than 8 ng/L and a 30‐minute &Dgr; of less than 3 ng/L ruled out acute myocardial infarction in 28.8% and 41.0% of patients, respectively. Additional multicenter US studies evaluating these ultrarapid acute myocardial infarction rule‐out guidelines are needed, especially to narrow the confidence intervals.

Differentiating type 1 and 2 acute myocardial infarctions using the N-terminal pro B-type natriuretic peptide/cardiac troponin T ratio

Purpose Differentiation of type 1 (T1MI) from type 2 myocardial infarction (T2MI) is important as recommended treatments for each differ. Patients with T2MI may have more/earlier cardiac wall stress resulting in an increased N‐terminal pro B‐type natriuretic peptide (NT‐proBNP)/cTnT generation 5 ratio (cTnT Gen 5). Methods Emergency Department (ED) patients presenting with symptoms suspicious for acute coronary syndrome (ACS) were enrolled from 2013 to 2015. Baseline blood samples were collected within 60 min of a triage ECG, with additional draws at 30, 60 and 180 min. NT‐proBNP and cTnT Gen 5 levels were measured later in an independent laboratory. Acute myocardial infarction (AMI) was adjudicated using the Third Universal Definition of Myocardial Infarction. Results 575 patients were enrolled with 44 (7.7%) having AMI [25 T1MI (59.1%) and 18 T2MI (40.9%)]. Patient characteristics showed very few AMI type differences so accurate clinical differentiation was difficult. The median NT‐proBNP/cTnT Gen 5 ratios were significantly higher in T2MI when compared to T2MI at baseline and 30, 60 and 180 min later [7.3 v 53.0 (p = 0.003), 5.8 v 49.5 (p = 0.002), 6.3 v 47.5 (p = 0.003) and 4.3 v 33.7 (p = 0.016) respectively]. Conclusions The clinical determination of whether an AMI is type 1 or 2 is difficult as the ED patient characteristics of each are similar. The NT‐proBNP/cTnT Gen 5 ratio can aid in making this differentiation. Additional multicenter trials are needed to validate our results.