Pulmonary capillary wedge pressure (PCWP) measurements can be used to estimate left atrial pressure; the normal range is between 6-12 mm Hg, and recorded values are whole numbers. A patient in the intensive care unit has 20 serial PCWP measurements taken over the course of 2 hours. Among these 20 observations, the maximal recorded value is 12 mm Hg and the minimal recorded value is 10 mm Hg. If the next measurement is 26 mm Hg, which of the following is most likely to remain unchanged?

Question

Pulmonary capillary wedge pressure (PCWP) measurements can be used to estimate left atrial pressure; the normal range is between 6-12 mm Hg, and recorded values are whole numbers.  A patient in the intensive care unit has 20 serial PCWP measurements taken over the course of 2 hours.  Among these 20 observations, the maximal recorded value is 12 mm Hg and the minimal recorded value is 10 mm Hg.  If the next measurement is 26 mm Hg, which of the following is most likely to remain unchanged?

Quizplus · Accepted Answer

An outlier is defined as an extreme and unusual value observed in a dataset. It may be the result of a recording error, a measurement error, or a natural phenomenon. In this case, the value of 26 mm Hg is an outlier as all the other values lie between 10 and 12 mm Hg. An outlier can affect measures of central tendency (mean, median, mode) as well as measures of dispersion (standard deviation, variance). This patient had 20 initial measurements that were all between 10 and 12 mm Hg. Although it is not required to answer this question correctly, a numerical example can help to explain the effect of an outlier such as 26 mm Hg. Assume that the patient's 20 initial measurements were: 9 measurements of 10 mm Hg, 6 measurements of 11 mm Hg, and 5 measurements of 12 mm Hg. The mode is the most frequently observed data point, so the mode for this initial dataset is 10 mm Hg (because this value is observed 9 times whereas the other 2 values are observed 6 times and 5 times). If the next measurement is 26 mm Hg, the mode would remain 10 mm Hg because this would still be the most commonly observed value. Therefore, the mode would remain unchanged. The mode tends to be resistant to outliers because outliers are not likely to affect the most frequently observed value in a dataset. (Choice A) The mean (or average) can be quite sensitive to outliers, especially in the case of small datasets and extreme outliers. For instance, the mean of the 20 initial measurements is 10.8 mm Hg (obtained by calculating [9 × 10 mm Hg + 6 × 11 mm Hg + 5 × 12 mm Hg] / 20). With an additional measurement of 26 mm Hg, the mean would become 11.5 mm Hg (obtained by calculating [1 × 26 mm Hg + 9 × 10 mm Hg + 6 × 11 mm Hg + 5 × 12 mm Hg] / 21). (Choice C) The range is equal to the maximal value minus the minimal value and would clearly be affected by outliers. With the 20 initial measurements, the range is 12 mm Hg - 10 mm Hg = 2 mm Hg. If the next measurement is 26 mm Hg, then the range will be 26 mm Hg - 10 mm Hg = 16 mm Hg. (Choices D and E) The standard deviation and variance are measures of dispersion, which reflect how spread out the values in a dataset are from one another. The standard deviation and variance tend to be sensitive to outliers because outliers increase the dispersion of datasets. Educational objective: An outlier is defined as an extreme and unusual observed value in a dataset. It can affect measures of central tendency (mean, median, mode) as well as measures of dispersion (standard deviation, variance). Modes tend to be resistant to outliers.

Pulmonary Capillary Wedge Pressure (PCWP) Measurements Can Be Used to Estimate