Presenting hemodynamic phenotypes in ED patients with confirmed sepsis
Nowak RM, Reed BP, Nanayakkara P, DiSomma S, Moyer ML, Millis S, and Levy P. Presenting hemodynamic phenotypes in ED patients with confirmed sepsis. Am J Emerg Med 2016.
The American journal of emergency medicine
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/cm 5 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.
Medical Subject Headings
Age Factors; Body Surface Area; Body Temperature; Cardiac Output; Cluster Analysis; Emergency Service, Hospital; Heart Rate; Hemodynamics; Humans; Phenotype; Prospective Studies; Sepsis; Vascular Resistance