A new statistic has been developed to quantify the amount of regularity in data. This statistic, ApEn (approximate entropy), appears to have potential application throughout medicine, notably in electrocardiogram and related heart rate data analyses and in the analysis of endocrine hormone release pulsatility. The focus of this article is ApEn. We commence with a simple example of what we are trying to discern. We then discuss exact regularity statistics and practical difficulties of using them in data analysis. The mathematic formula development for ApEn concludes the Solution section. We next discuss the two key input requirements, followed by an account of a pilot study successfully applying ApEn to neonatal heart rate analysis. We conclude with the important topic of ApEn as a relative (not absolute) measure, potential applications, and some caveats about appropriate usage of ApEn. Appendix A provides example ApEn and entropy computations to develop intuition about these measures. Appendix B contains a Fortran program for computing ApEn. This article can be read from at least three viewpoints. The practitioner who wishes to use a "black box" to measure regularity should concentrate on the exact formula, choices for the two input variables, potential applications, and caveats about appropriate usage. The physician who wishes to apply ApEn to heart rate analysis should particularly note the pilot study discussion. The more mathematically inclined reader will benefit from discussions of the relative (comparative) property of ApEn and from Appendix A.

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Concern has been raised that altering the fraction of inspired O₂ (Fi(O₂)) could accelerate or decelerate microbubble dissolution time within the pulmonary vasculature and thereby invalidate the ability of saline contrast echocardiography to detect intrapulmonary arteriovenous shunt in subjects breathing either a low or a high Fi(O₂). The present study determined whether the gaseous component used for saline contrast echocardiography affects the detection of exercise-induced intrapulmonary arteriovenous shunt under varying Fi(O₂). Twelve healthy human subjects (6 men, 6 women) performed three 11-min bouts of cycle ergometer exercise at 60% peak O₂ consumption (Vo(2peak)) in normoxia, hypoxia (Fi(O₂) = 0.14), and hyperoxia (Fi(O₂) = 1.0). Five different gases were used to create saline contrast microbubbles by two separate methods and were injected intravenously in the following order at 2-min intervals: room air, 100% N₂, 100% O₂, 100% CO₂, and 100% He. Breathing hyperoxia prevented exercise-induced intrapulmonary arteriovenous shunt, whereas breathing hypoxia and normoxia resulted in a significant level of exercise-induced intrapulmonary arteriovenous shunt. During exercise, for any Fi(O₂) there was no significant difference in bubble score when the different microbubble gas compositions made with either method were used. The present results support our previous work using saline contrast echocardiography and validate the use of room air as an acceptable gaseous component for use with saline contrast echocardiography to detect intrapulmonary arteriovenous shunt during exercise or at rest with subjects breathing any Fi(O₂). These results suggest that in vivo gas bubbles are less susceptible to changes in the ambient external environment than previously suspected.