Novel Prehospital Phenotypes and Outcomes in Adult-Patients with Acute Disease

Abstract

An early identification of prehospital phenotypes may allow health care workers to speed up and improve patients' treatment. To determine emergency phenotypes by exclusively using prehospital clinical data, a multicenter, prospective, and observational ambulance-based study was conducted with a cohort of 3,853 adult patients treated consecutively and transferred with high priority from the scene to the hospital emergency department. Cluster analysis determined three clusters with highly different outcome scores and pathological characteristics. The first cluster presented a 30-day mortality after the index event of 45.9%. The second cluster presented a mortality of 26.3%, while mortality of the third cluster was 5.1%. This study supports the detection of three phenotypes with different risk stages and with different clinical, therapeutic, and prognostic considerations. This evidence could allow adapting treatment to each phenotype thereby helping in the decision-making process.

Keywords: Clinical Decision-Making; Clinical Deterioration; Clinical Phenotypes; Emergency Medical Services; Pre-hospital Care.

Fig. 1

Patient selection flow chart. EMS: emergency medical services; BLS: basic life support unit

Fig. 2

Heatmap of the relative importance of continuous variables in each cluster. Intensity of colors represents the deviation, in terms of standard deviations, of the mean value of the variable in the cluster with respect to the mean value of that variable in the whole cohort. Reddish colors represent higher values and bluish colors represent lower values. Abbreviations: RR: respiratory rate; SpO2: pulse oximetry saturation; FiO2: fraction of inspired oxygen; SO2: supplemental oxygen in the scene; SaFi: pulse oximetry saturation/fraction of inspired oxygen ratio; AP: arterial pressure; HR: heart rate; ArT: arrival time; AsT: assistance time; TrT: transfer time; ToT total time; TrT: transfer time; TT: temperature; GCS.O: ocular Glasgow coma scale; GCS.V: verbal Glasgow coma scale; GCS.M: motor Glasgow coma scale; pNEWS2: prehospital National Early Warning Score 2; Lac: lactate; Glu: glucose; SAP: systolic arterial pressure; DAP: diastolic arterial pressure; PP: systolic-diastolic pressure

Fig. 3

Heatmap corresponding to the v-test applied to the whole set of 23 variables. For the case of numerical variables, red colors represent affinity or overrepresentation of high values with the corresponding cluster and yellow colors represent affinity of low values with the corresponding cluster. For the case of categorical variables, red colors represent the affinity or overrepresentation of the factor level with the corresponding cluster and the yellow colors represent an underrepresentation of the factor level with the corresponding cluster. Intensity of colors are proportional to the test significance, more intense, more significant. White colors represent non-significant values. Abbreviations: RR: respiratory rate; SpO2: pulse oximetry saturation; FiO2: fraction of inspired oxygen; SO2: supplemental oxygen in the scene; SaFi: pulse oximetry saturation/fraction of inspired oxygen ratio; AP: arterial pressure; HR: heart rate; ArT: arrival time; AsT: assistance time; TrT: transfer time; ToT total time; TrT: transfer time; TT: temperature; GCS.O: ocular Glasgow coma scale; GCS.V: verbal Glasgow coma scale; GCS.M: motor Glasgow coma scale; pNEWS2: prehospital National Early Warning Score 2; Lac: lactate; Glu: glucose; SAP: systolic arterial pressure; DAP: diastolic arterial pressure; PP: systolic-diastolic pressure

Fig. 4

Chord diagram of cluster distributions: Left upper panel. Distribution of patient’s pathologies corresponding to cluster #1, in red. Right upper panel. Distribution of patient pathologies corresponding to cluster #2, in blue color. Lower panel. Distribution of patient’s pathologies corresponding to cluster #3, in green