How Do Anesthesiologists Define Abnormal Heart Rate and Blood Pressure?

S192 INTRODUCTION: While anesthesiologists seek to achieve normal hemodynamic values in their patients, the definitions of normal and abnormal states are not established. By surveying a sample of anesthesiologists, this study sought to estimate the variability inherent in the ranges that clinicians use to define abnormal hemodynamics. METHODS: A surveyor interviewed 39 anesthesiologists and asked them the exact numbers that they used to categorize hemodynamic variables into mutually exclusive very low, low, normal, high, and very high categories. The very low and very high categories were defined as those values requiring immediate intervention. The participants were asked to define these parameters for a healthy ASA 1 patient undergoing a major abdominal procedure. The participants provided ranges for mean arterial pressure (MAP), systolic arterial pressure (SAP), and heart rate (HR). The data underwent descriptive analysis. RESULTS: Of the 39 anesthesiologists, 9 identified themselves as specialized in cardiothoracic, 4 as liver/vascular, 4 as pediatric, 4 as pain management, 2 as obstetrical, and 16 as not fitting any of the preceding categories. Twelve began their clinical training 10 years previously. The data are presented in Table 1 and MAP data are graphed in the figure.Table 1: Cutoff values for defining abnormal hemodynamics (median interquartile range)DISCUSSION: The true normal ranges for hemodynamics vary certainly according to age and co-existing diseases. The data from a broad range of anesthesiologists (according to specialty and seniority) from this single institution shows great variability in the definition of abnormal hemodynamic states. The overlapping of the categories is depicted well in the figure. Presumably, clinicians from one institution should have better agreement because of uniformity of practice. These data may therefore represent an underestimate of the true variability. Studies such as this one may help to define fuzzy logic sets that will enable improved automated detection of abnormal hemodynamics (e.g., smart alarms).