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(Chest. 2006;130:754-765.)
© 2006 American College of Chest Physicians

Continuous Noninvasive Measurement of Pulsus Paradoxus Complements Medical Decision Making in Assessment of Acute Asthma Severity*

James Rayner, MD, MEng; Flor Trespalacios, BS; Jason Machan, PhD; Vijaya Potluri, BS; George Brown, MD; Linda M. Quattrucci, AS and Gregory D. Jay, MD, PhD

* From the Department of Emergency Medicine (Drs. Rayner, Brown, and Jay, Ms. Trespalacios, Ms. Potluri, and Ms. Quattrucci), Brown Medical School, Providence, RI; and the Center for Biostatistics (Dr. Machan), Rhode Island Hospital, Providence, RI.

Correspondence to: Gregory D. Jay, MD, PhD, Department of Emergency Medicine, Rhode Island Hospital, 1 Hoppin St, Coro West, Providence, RI 02903; e-mail: gregory_jay_MD{at}brown.edu

Abstract

Background: Pulsus paradoxus (PP) is a pathophysiologic parameter that is indicative of asthma severity. The ability of PP to categorize acutely asthmatic patients in accordance with the earlier National Asthma Education and Prevention Program (NAEPP) expert panel report 1 guidelines was determined.

Methods: An arterial tonometric BP monitor, which was interfaced to an analog-digital converter, executed a periodic amplitude analysis algorithm, which computed PP in real time. The PP measurement was compared to the criterion standard of emergency physicians in determining the hospital admission vs hospital discharge disposition following the NAEPP standardized treatment. Receiver operating characteristics (ROCs) were calculated, and the PP threshold, which maximized sensitivity and specificity, was identified. In a separate laboratory investigation, PP was induced in a healthy volunteer by inspiration through a fixed resistance. Plethysmographic waveform changes, induced by PP, were measured by a second analog-to-digital converter that was connected to a pulse oximeter.

Results: A total of 79 patients were enrolled in the study, of whom 63 met a priori inclusion criteria and had uninterrupted data acquisition. The mean PP for patients who were appropriately discharged from the hospital was 9.1 mm Hg (95% confidence interval [CI], 7.3 to 10.9 mm Hg) and differed from the PP of 17.6 mm Hg (95% CI, 13.5 to 21.8; p < 0.001) for patients admitted to the hospital/relapsed. The sensitivity and specificity for physician disposition were 0.83 and 0.89, respectively, and for PP values were 0.78 and 0.78, respectively. The Wilcoxon area under the ROC curve was 0.82 (95% CI, 0.64 to 0.99) following treatment. The risk ratio was 5.32 for hospital admission among patients with a PP of > 11.3 mm Hg. Changes in the photoplethysmography peak height were correlated to PP from the BP monitor by a regression line with a slope of 0.01V/mm Hg.

Conclusions: Continuous PP can aid in determining disposition among emergency department (ED) patients with acute asthma. ED physicians equipped with a PP monitor would be able to objectify the work of breathing and would more closely adhere to NAEPP guidelines. The possibility that a PP detection algorithm could reside in a pulse oximeter warrants further investigation.

Key Words: asthma • BP monitoring • emergency medicine • pulse oximetry • pulsus paradoxus

Pulsus paradoxus (PP) is a pathophysiologic vital sign that historically1 has been a cornerstone in the evaluation of patients with acute asthma.23 However, the measurement of PP is rarely performed, and the accuracy of its measurement via sphygmomanometry is questionable.4 Despite this, PP has been used in a number of asthma studies5 and continues to be a recommended metric by the National Asthma Education and Prevention Program (NAEPP) expert panel report 2.6 The value of PP as a pathophysiologic measure is well established.78 Acute asthma is attributable to airway inflammation and reversible airflow limitation leading to dynamic lung hyperinflation.910 PP is a measure of inspiratory impedance as it affects pleural pressure, left ventricular output, and right ventricular output.11 Therefore, the measurement of PP is pertinent to respiratory distress,12 inspiratory muscle elastic loading and fatigue, air leakage, and other mechanical consequences of dynamic hyperinflation during acute asthma.

Expert guidelines6 also support the utility of peak expiratory flow rate (PEFR) measurement in both patient self-monitoring and emergency department (ED) disposition of patients with acute asthma. However, because PEFR is highly dependent on patient technique and effort,13 values can change considerably from measure to measure. Further, PEFR diaries can be unreliable,14 which may lead to a misunderstanding of a patient’s personal best PEFR15 on which the emergent evaluation is based. PEFR also underestimates airway obstruction and the overall severity of an asthmatic exacerbation as air trapping results in dynamic hyperinflation.

A need exists for an objective criterion in evaluating acute asthma that is independent of effort, is well-validated, and is familiar to clinicians. The NAEPP expert panel report 1 guidelines in 199116 specified 12 mm Hg as the PP level that supported hospital admission. This threshold was not tested prospectively in a clinical study. An investigation17 conducted by our group showed that a PP of 11 mm Hg accurately identified acutely asthmatic pediatric patients who were in need of hospital admission. The PP values in that investigation were calculated post hoc by hand from digitized continuous noninvasive BP data and a respiratory strain gauge. The present study was undertaken to develop and test a signal-processing algorithm that would determine and display automated (AT) PP without the aid of a respiratory phase measure. This study was conducted in adult patients with acute asthma. Signal detection theory was used to identify the AT-PP threshold for hospital admission. Patient dispositions, as determined by the treating physicians, were compared to the AT-PP. A second part of this investigation, which was conducted in the laboratory, identified the reproducible alterations in oximetric plethysmography as a result of induced PP in a healthy adult volunteer. We hypothesize that inspiratory variation in plethysmography is the most logical and clinically appropriate way to measure PP in routine clinical practice.

Materials and Methods

Prospective Cohort
Patients and Protocol:
Adult patients who were 18 to 70 years of age, had a documented history of asthma, and were presenting with shortness of breath and probable asthma exacerbation were approached for study enrollment by trained clinical research assistants. Informed consent was obtained during the ED triage process or shortly thereafter, before ED treatment was initiated. Following patient consent, ED treatment was standardized and completed within 60 min according to NAEPP guidelines, as follows: three sequential nebulized albuterol treatments; and either IV solumedrol, 125 mg, or oral prednisone, 60 mg.6 Just prior to the initiation of ED treatment and at the end of ED treatment, patients’ AT-PP was measured, and both the treating physician and another physician performed objective asthma scoring. Physicians were blinded to the AT-PP values. Research assistants also measured patient vital signs during the AT-PP measurements. Following treatment, patient disposition was determined by the treating emergency physician, who was blinded to AT-PP measurements. A poor outcome was defined as either patient admission to the hospital or the relapse of a patient who had been discharged from the hospital within 72 h. All patients discharged from the hospital were contacted to determine whether they had made an unscheduled visit for their asthma exacerbation after ED discharge. This study was reviewed and approved by the Institutional Review Board.

The medical records of enrolled patients were analyzed to confirm that a prior diagnosis of asthma existed. Among patients who were admitted to the hospital, a physician who was blinded to AT-PP values and the ED record audited all inpatient records. Patients who had been inappropriately admitted to the hospital were identified as those whose level of care could have been accomplished as an outpatient. These patients were treated with oral steroids and metered-dose inhalers, and were not aggressively monitored.

Outcomes
Physician Objective Scoring:
Both physicians assessed each patient using eight visual analog scales measuring the following: accessory muscle use; wheezing; prolonged expiratory phase; objective dyspnea (OD); air entry; cyanosis; sternocleidomastoid muscle use; and mental status. Each scale ranged from 0 to 3, with anchor points at each integer. All of the scales were on the same side of a single sheet of paper. The physicians completed this assessment sequentially and filled in the form separately. They were instructed to mark the visual analog scale with an "X" along the continuum that best reflected the patients’ conditions for each of the above physical examination findings. The scoring of these data was accomplished with a ruler, measuring the distance of the X from the origin for each scale.

Measurement of AT-PP
Continuous BP measurements were obtained noninvasively with a wrist mounted arterial tonometer (NCAT; Nellcor; Pleasanton, CA). The analog output of this device was digitized via an eight-bit analog-to-digital converter (DAQ-500; National Instruments; Austin, TX) [Fig 1 ]. The sampling rate was 200 Hz. A peak-seeking periodic amplitude analysis algorithm was designed (LabVIEW; National Instruments) that would identify local maxima of the BP from the data stream. Beat-to-beat systolic BP (SBP) was identified using the algorithm recursively. Finally, the algorithm was applied again to the beat-to-beat SBP data to determine the variation in SBP with respiration. The algorithm calculates PP by keeping a moving average of the last five peak SBPs and an average of the last five trough SBPs. PP is then calculated by subtracting the average trough SBP from the average peak SBP. Since the algorithm is able to monitor the maxima and minima of SBP within a respiratory cycle, a derivation of respiratory rate was performed by measuring the elapsed time for the five SBPs.


Figure 1
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  		Figure 1. Photograph of a PP monitor setup consisting of a laptop computer equipped with an analog-to-digital conversion interface and a continuous noninvasive BP monitor.

 
Statistical Analysis
Accuracy of PP and Physician Scoring in Prediction of Admission Disposition:
Using the hospital discharge and admission/relapse results as the "gold standard," the sensitivity, specificity, and positive and negative predictive values of AT-PP and physician scoring were calculated. The exact binomial confidence intervals (CIs) were computed for each estimate. The measure of agreement between physician-determined and AT-PP-determined disposition was computed from the Cohen {kappa}-statistic. All analyses were conducted with a statistical software package (SAS, version 9.1 [the freely distributed "intracc" SAS macro]; SAS Institute; Cary, NC),18 and custom functions were developed internally (for MatLab, version 7.01; The MathWorks; Natick, MA); an {alpha}-level of 0.05 was deemed to be statistically significant unless otherwise noted. In addition, receiver operating characteristic (ROC) curves19 were constructed for AT-PP as a continuous variable for the prediction of hospital admission status using pretreatment and posttreatment values. The area under the curve (AUC) and 95% CI was computed as the c-statistic by the method of DeLong et al20 in estimating the overall ability of PP to distinguish between patients who were admitted to the hospital/relapsed and those who were discharged from the hospital. An optimized cutoff AT-PP threshold was selected based on optimized sensitivity and specificity, where sensitivity and specificity were equal.

All variable distributions were assessed for violation of the assumption of normality based on skewness, the Shapiro-Wilk statistic ({alpha} = 0.01), and visualization. Variables having a significant deviation from normal via the Shapiro-Wilk statistic were submitted to the following three linear transformations: square root; natural logarithm; and inverse. The linear transformation that improved the distribution the most was selected. In addition, both the untransformed and transformed distributions were visually inspected to verify normality.

Interrater Reliability of Physician Analog Scales
The interrater reliability of the objective scoring composite and subscales (transformed where necessary) was estimated using the intraclass correlation coefficients (ICCs) as described by Shrout and Fleiss.21 A mixed model was used, with "rater" treated as a random variable since each patient was rated by a pair of physicians who were pulled from a sample of possible physicians (the same two physicians were not always used for each patient, though the same two physicians were used for both pretreatment and posttreatment time points within a given patient). The ICC of the raters was used as an index of reliability of actual rater judgments. The estimated ICC of the mean of the two raters (n = 2) was used throughout the analysis.

Relationship Between Objective Scoring and PP
For objective scoring measures (composite and subscales) that met or exceeded an ICC of 0.80 for the mean of the ratings at both time points, the mean of the two raters for each patient was assessed for its relationship to AT-PP using a repeated measures (ie, pretreatment/posttreatment) general linear model with the score (continuous) as a fixed effect. In addition, each objective scoring measure (including those that failed to meet the ICC criterion) was evaluated for predicting AT-PP using hierarchical linear models (PROC MIXED, SAS Version 9.1; SAS Institute) to assess whether or not on average there was a relationship between observer ratings and AT-PP (ie, the mean slope within rater). Residuals were examined for systematic deviations and for overall model fit, and scatter-plots were examined to verify and assist in interpreting the model parameters.

Cost Effectiveness
The cost of care was based on hospital and physician charges for outpatient and inpatient treatment of asthma. The cost of appropriate inpatient care was determined by the average level of service, the cost of care per day, and the average length of stay for patients with conditions denoted by International Classification of Diseases, ninth revision, (ICD-9) codes 49390 and 49392 from inpatient billing records for 2004. This cost also included the ED charges. The cost of appropriate outpatient care was determined in the same way based on one ED visit without patient relapse, which was defined as an unscheduled medical office or ED visit within 72 h of hospital discharge. The cost of inappropriate inpatient care was based on the average cost in 2004 for conditions denoted by ICD-9 codes 49390 and 49392 for a 1-day hospital admission. This cost also included the ED charges. These patients were identified in the study cohort as those patients who had received a level of care that was low and could have been rendered as an outpatient. The cost of inappropriate outpatient care was based on the average 2004 costs for the initial ED visit and the cost of appropriate inpatient care described above (which included the second ED visit). The costs of inappropriate outpatient care do not contain the actuarial costs associated with the hypothetical risk of death as a result of asthma mistreatment. ICD-9 code 49391 was not utilized in this analysis as status asthmaticus is an infrequent diagnosis and is nonuniformly applied by hospital billing services.

Based on cost-of-care estimates, the estimated mean cost per patient was assessed for each possible AT-PP threshold. This was accomplished by first estimating the costs associated with each of the four possible combinations of decision (ie, patient AT-PP greater than the threshold value vs less than or equal to the threshold value) and outcome (ie, admitted to the hospital vs discharged from the hospital and inappropriately admitted to the hospital vs relapsed), as follows: (1) true-positive finding = $7,340; (2) true-negative finding = $1,002; (3) false-positive finding = $3,765; and (4) false-negative finding = $7,872. These four costs were multiplied by the number of patients in their matching decision/outcome combination (total cost per decision/outcome); these subsequent four values were then summed (total cost for all patients), and the sum was then divided by the total number of patients (mean cost per patient). The result produced the mean cost per patient as a function of threshold in patients with AT-PP.

Derived vs Observed Respiratory Rates
Respiratory rates from the AT-PP processing were compared to corresponding values obtained by the research assistants from direct visualization. Separate regression models were constructed for the pretreatment and posttreatment AT-PP measurement periods. These data were also pooled and analyzed in a Bland-Altman plot.22

Induced PP in Healthy Volunteer
PP was induced in a healthy adult using an established technique4 by having him breathe through a fixed resistance connected to a two-way nonrebreathing valve (Hans Rudolph; Kansas City, MO) that was attached to a manometer (OEM Medical; Marshalltown, IA). Airflow resistance occurred during inspiration, whereas expiration was unimpeded. The reference subject’s BP and oximetry plethysmograph findings were recorded continuously in the sitting position while he sequentially generated inspiratory mouth pressures from –5 to –20 mm Hg in 5-mm Hg increments. The subject controlled the generated mouth pressures by observing manometer readings. The respiratory rate was 20 breaths/min. Continuous BP was recorded noninvasively (FINAPRES; Ohmeda; Madison, WI). This device approximates invasive arterial BP23 monitoring as well as the mounted arterial tonometer (NCAT; Nellcor) and has been used previously by our group17 and others.24 Data from the BP monitoring device (FINAPRES; Ohmeda) was digitized by an analog-to-digital converter (MP-100; Biopac Systems; Santa Barbara, CA), which created a text file that could be analyzed by the AT-PP monitoring algorithm described previously. Pulse plethysmography findings were obtained from a pulse oximeter (model 395; Nellcor) that was specially configured to separately record plethysmograph signals from the visible red and infrared photodiodes. Data transfer from the oximeter was accomplished digitally in real time through its analog signal output. This aspect of the study was also approved by the institutional review board.

Evaluation of Oximeter Plethysmography Measuring PP (Volunteer Subject)
Data from continuous BP monitoring of the study subject were analyzed for PP by the dedicated AT-PP algorithm previously illustrated. Text files from the oximeter plethysmograph were analyzed (MP-100 software; Biopac Systems). A change in inspiratory and expiratory plethysmographic pulse amplitude caused by PP was calculated for at least 10 respirations in each induced PP data file, and the mean ± SD was calculated. Correlation of the percentage change in plethysmograph amplitude against the AT-PP for the same respirations was performed, and a linear regression model was constructed across the increasing degrees of negative inspiratory pressure and AT-PP.

Results

Descriptive Statistics
Seventy-nine patients were enrolled in this study from September 2003 to June 2005 as a convenience sample. Nine patients were excluded from the analysis as they failed to meet study asthma criteria following post hoc inspection of both outpatient and inpatient records. Of the remaining 70 patients, 19 (27.1%) were admitted to the hospital from the ED. Three patients relapsed within 72 h after hospital discharge and sought medical care. Thus, 48 patients (68.6%) had a good outcome, and 22 patients (31.4%) had a poor outcome. The median length of stay for admitted patients was 2 days. PP was successfully acquired from 63 patients during their treatment in the ED. Failure to acquire continuous BP data occurred in seven patients, resulting in no AT-PP values for these patients. Further analysis was conducted on these 63 patients. The demographic information comparing patients admitted to the hospital with those discharged from the hospital is illustrated in Table 1 , which shows no significant differences in gender, smoking, and pulse rate. However, the patients who were admitted to the hospital displayed statistically higher AT-PP values after treatment, as illustrated in Table 1. Patients who were admitted to the hospital also displayed higher respiratory rates pretreatment and posttreatment compared to patients who had been discharged from the hospital, and lower pulse oximetric saturation values posttreatment. The patients who were admitted to the hospital were older than those who had been discharged from the hospital. A significant difference in posttreatment AT-PP was observed between patients who had been discharged from the hospital and those who had been admitted.


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  		Table 1. ED Patient Demographics and Vital Signs*

 
ROC Curves
Signal detection theory-based analysis of the sensitivity and specificity of AT-PP in arriving at the hospital discharge/admit disposition was significant for the PP measurement at a time 60 min following standardized asthma treatment. The PP threshold, which maximized sensitivity and specificity, was 11.3 mm Hg (Fig 2 , top, A). The mean Wilcoxon AUC-ROC was 0.82 (95% CI, 0.69 to 0.99) [Fig 2, top, A, inset). The risk ratio was 5.32 for hospital admission among patients with PP, which exceeded this threshold. This is in contrast to the same analysis for the initial AT-PP measurement prior to standardized asthma treatment, in which the mean Wilcoxon AUC-ROC was 0.571 (95% CI, 0.27 to 0.87) [Fig 2, bottom, B, inset). The AT-PP threshold that maximized sensitivity and specificity was 9.6 mm Hg; patients’ AT-PP above this threshold had relative risk of 1.20 for hospital admission.


Figure 2
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  		Figure 2. Plots of AT-PP sensitivity and specificity as a function of PP threshold in asthma disposition during posttreatment (top, A) and pretreatment (bottom, B). The PP threshold, which maximized sensitivity and specificity, is identified. The cost of care is illustrated on the right-hand axis (inserts). Corresponding receiver operator curves are shown, in which the symbol "*" denotes the sensitivity and specificity, which maximized the AUC.

 
Accuracy of Tests
The specificity and sensitivity of the physicians in appropriately managing asthma in this study were 0.89 and 0.83, respectively (Table 2 ). There were eight cases in which physician management appeared to be correct on audit, but the AT-PP values failed to indicate a correct patient disposition. The specificity and sensitivity of AT-PP in appropriately managing asthma in this study were 0.78 and 0.78, respectively. The overall accuracy of AT-PP and physician disposition were 0.78 and 0.87, respectively. Interestingly, there were only two overlapping cases in which inappropriate dispositions by both physicians and AT-PP occurred, suggesting that each may have their relative strengths and that a combinatory approach would prove more effective than either alone. This is also supported by the {kappa}-statistic, which showed incomplete overlap between AT-PP and physician disposition (Table 2). A total of five patients who were admitted to the hospital may have been admitted unnecessarily judging from an audit of the inpatient medical records. These records indicate treatment for asthma but at an intensity level that could have been accomplished on an outpatient basis. In each case, the length of the hospital admission was for 1 day. The mean AT-PP measurement posttreatment for these patients was 6.0 mm Hg (95% CI, 2.6 to 9.5 mm Hg) compared to 17.6 mm Hg (95% CI, 13.5 to 21.8 mm Hg) for the remaining patients who were appropriately admitted to the hospital (Student t test = 2.95; p = 0.007). A total of three patients relapsed; two of these patients had posttreatment AT-PP values of 21.3 and 20.7 mm Hg. The mean AT-PP measurement for all patients who were appropriately discharged from the hospital was 9.1 mm Hg (95% CI, 7.3 to 10.5), which was significantly different from that for patients who were appropriately admitted to the hospital (Students t test = 4.51; p < 0.001). Assuming that the AT-PP threshold of 11.3 mm Hg was adhered to in a prospective manner, the PP measurement may have prevented five unnecessary hospital admissions and two inappropriate hospital discharges.


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  		Table 2. Comparison of AT-PP and Treating Physician-Assessed Disposition to Patient Chart Audit Data and Each Other*

 
Interrater Reliability and Relationship Between Objective Scoring and PP
The interrater reliabilities, as assessed with intraclass correlation, are listed in Table 3 . Neither the composite nor any of the subscales met our criterion for reliability (0.80). However, the estimated mean of the composite score did meet our criterion, as did the mean for OD at pretreatment. The mean total score, which was the only measure that met our criteria for reliability, was marginally predictive of AT-PP (Table 3), indicating that higher means generally predicted higher AT-PP. Examination using hierarchical linear modeling further revealed that while physicians did not show agreement in their absolute scores as measured by ICC, their composite score and one subscore (ie, OD) did significantly relate to AT-PP, as indicated by a significant mean slope (Table 4 ). This indicates that physicians agree on perceived changes in a composite assessment and OD, which are correlated to changes in AT-PP. This was almost also true for prolonged expiratory phase.


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  		Table 3. Interrater Reliability of Objective Scoring*

 

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  		Table 4. Bivariate Relationships Between Objective Scoring and AT-PP*

 
Cost-Effectiveness
Treating physician-based disposition was not error-free, contributing to increased costs. The actual mean cost per patient was approximately $3,057, compared to the $2,813 that would have been obtained with perfect sensitivity and specificity (ie, accuracy). Relying on AT-PP measurement alone in this study would have increased care costs to $3,285, which is reflected in Figure 2, top, A, in the cost-of-care function at the optimal AT-PP threshold of 11.3 mm Hg. However, the hypothetical cost for combined AT-PP and physician-based disposition was $2,838, assuming that physician-based disposition would have been improved with AT-PP.

Derived vs Observed Respiratory Rates
Figure 3 shows that the majority of both derived and observed respiratory rates fell within ± 5 breaths/min over a range of respiratory rates from 12 to 30 breaths/min from both the pretreatment and posttreatment data sets. However, the respiratory rate derived from the AT-PP monitor failed to predict those obtained by the research assistants, as indicated by the lack of a significant relationship between derived and observed respiratory rate during pretreatment (slope, 0.086; intercept, 21.13; F = 0.199; p = 0 0.66) and during posttreatment (slope, –0.147; intercept, 24.78; F = 1.178; p = 0.28).


Figure 3
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  		Figure 3. Bland-Altman plot of the respiratory rate measured by trained bedside observers compared to the predicted respiratory rate from the AT-PP monitor.

 
Oximeter Plethysmography Measures PP (Volunteer Subject)
Oximetry plethysmography also showed PP-like phenomena, which correspond to the BP measured PP events (Fig 4 , top, A). A linear regression model describes a transfer function, which relates AT-PP in units of millimeters of Hg to a decrease in plethysmographic amplitude (Fig 4, bottom, B). The slope of this relationship is roughly 0.01 V/mm Hg, where for each 1-mm Hg change in AT-PP, the oximeter plethysmograph peak amplitude would decrease by 0.01 V.


Figure 4
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  		Figure 4. Top, A: representative PP data from a BP monitor (FINAPRES; Ohmeda) and oximetry plethysmograph that were recorded simultaneously. Arrows indicate maxima and minima SBP values induced by a –20-mm Hg inspiratory pressure, which was identified by the PP algorithm. Arrowheads denote corresponding plethysmograph waveforms, which also indicate the presence of PP. In both panels A and B, PP was induced in a healthy subject by inspiration through a fixed resistance, while mouth pressure was monitored. Bottom, B: correlation of variable degrees of induced PP measured by a BP monitor, with changes in the plethysmographic waveforms from an oximeter shown ({circ}). NIBP = noninvasive BP monitoring.

 
Discussion

The measurement of PP, embedded and AT in a continuous noninvasive BP recorder (ie, AT-PP), discriminated asthmatic adult patients who had been admitted to the hospital/relapsed from asthmatic adult patients who had been discharged from the hospital and was a well-tolerated procedure. The optimized AT-PP threshold for hospital admission was > 11.3 mm Hg following standardized treatment. This value is near 11 mm Hg, which discriminated patients who had been admitted to the hospital/relapsed from patients who had been discharged from the hospital in a pediatric acute asthma study population.17 Both observed thresholds also compare favorably to the first NAEPP asthma guidelines,16 which recommended hospital admission at a PP of 12 mm Hg. The subsequent NAEPP guidelines continued to recommend PP measurement but have dropped actionable PP thresholds. Initial AT-PP measurements prior to standardized treatment failed to predict disposition in the present study. By contrast, our previous pediatric study17 showed that the groups of patients who had been admitted to the hospital/relapsed and had been discharged from the hospital were identifiable before treatment began. This discrepancy may be a manifestation of the loss of reserve effort in respiratory dyscrasias in children. Presenting asthmatic children who had tired (but still generated a high PP) needed more time to convalesce and thus required hospital admission.

Sensitivity and specificity after standardized therapy in determining correct disposition were higher overall for the treating physicians than for the AT-PP measure, reconfirming the treating physician as a "gold standard" in asthma management studies. However, overlapping errors were limited to two patients, suggesting that their combination could be of clinical and economic value. There were five patients admitted to the hospital with normal AT-PP measures who were considered to have been unnecessarily admitted to the hospital on a subsequent medical record audit, and there were two released patients who relapsed and were determined to have had high AT-PP values. The greater number of patients who had been unnecessarily admitted to the hospital may reflect the conservative approach that many physicians have in the management of asthma. The alternate disposition indicated by AT-PP supports its inclusion as an adjunct tool in patient assessment. Relapsing patients who had been discharged from the hospital are comparatively less common. As this study progresses, we anticipate observing additional relapsing asthmatic patients who were inappropriately discharged from the hospital, which would add to the cost of care for patients with an AT-PP of > 20 mm Hg, resulting in a cost-of-care curve (Fig 2, top, A) that looks more U-shaped. We further posit that these latter patients, who are discharged from the hospital with an AT-PP of > 15 mm Hg, could be managed differently if a bedside PP monitor suggested that either additional ED treatment or hospitalization was needed. Similarly, the cost of asthma care among patients admitted to the hospital could be decreased by a PP measure, which objectively confirms a physiologic response to therapy. The hypothetical mean cost per patient associated with dispositioning that is based on AT-PP measurement prior to treatment were comparatively higher at all thresholds. This was to be expected based on the poorer ability of AT-PP to disposition patients prior to treatment compared to after treatment, since there would have been more errors overall, and errors are costlier than correct dispositions.

Any agreement between physicians performing objective asthma scoring was lacking. For both the pretreatment and posttreatment periods, their scores had low intraclass correlations (Table 3) and little similarity in absolute objective asthma severity scores. However, while absolute scores varied, physicians did show similar trends in the ratings of some of the physical examination findings across the standardized treatment period (Table 4). Most notably, OD and, possibly, prolonged expiratory phase followed similar trends and appeared to be examination findings that physicians monitor, though they rate absolute magnitude differently. Ratings in OD also correlated with those in AT-PP. These results are indicative of the lack of consensus among treating physicians in appreciating asthma severity and also support previous observations that physicians underappreciate asthma-related symptoms.25

The results from this study are also supported by investigations26 that showed that PP is a suitable surrogate for work of breathing and predicted the need for hospital admission in pediatric patients. However, this conclusion was reached with the manual measurement of PP, which is imprecise in adult patients4 and therefore likely to be inaccurate in pediatric patients, who have a higher respiratory rate. Like other vital signs, PP offers the opportunity to follow disease progression and the response to therapy. As a unique pathophysiologic vital sign, PP can also be used as a screening vital sign in patients with undifferentiated dyspnea. The rapid evaluation for PP in ED triage could drive the differentiation of subjective dyspnea in the ED patient population. As a group, patients with dyspnea occupy 20% of this patient population. However, only those patients with asthma, pericardial effusions or tamponade,27 massive pulmonary embolus,28 tension pneumothorax,29 and severe dehydration will manifest PP. Patients with silent chest asthma could be more readily identified during triage evaluation. Continuous PP monitoring also offers the opportunity to assess the response of asthma and croup30 to pharmacotherapy. This will also be important in evaluating new products for the management of both diseases, as PP has been used in previous pharmacologic trials.31 It may also become possible to remotely monitor asthma severity via continuous PP, which would benefit many patients with a well-established diagnosis. Monitoring patients in this way could avoid unnecessary ED visits and hospitalizations, which account for the largest proportion of asthma care costs.32 Finally, continuous PP monitoring would add a new dimension in the identification of obstructive sleep apnea by identifying upper glottis closure and pathophysiologic dyscrasias before hypoxia occurs among patients undergoing sleep studies.

The AT-PP detection algorithm for continuous BP monitoring used in this study was accurate and precise, meeting the Association for the Advancement of Medical Instrumentation tolerance requirements for medical devices.33 This algorithm should also be transferable to other continuous and noninvasive BP monitors. In the event that continuous noninvasive BP monitoring becomes more available in acute care settings, we believe that PP could replace PEFR as the preferred metric of acute asthma severity. PEFR alone appears to be unpredictive of patient outcome in patients with acute asthma34 and is no longer recommended by the American College of Emergency Physicians.35 In a study of acute asthma in pediatric patients,26 PP appeared to be a surrogate for spirometry in evaluating asthma severity. Finally, PEFR meters, which are manufactured by a number of different companies, appear to have variable accuracy.36 Despite these and other limitations,1415 PEFR is widely used by patients as it appears to be superior to symptom self-monitoring37 and occupies a niche in monitoring asthmatic patients on an ongoing basis. However, the practice of having acutely dyspneic patients perform forcible expiratory maneuvers is also not without risk.3839

The discordance between the observed and derived respiratory rate is the focus of continued investigation. Lack of a "gold standard" in this aspect of the study limits further data analysis. Our research assistants were instructed to count the respiratory rate over 30 s and multiply by 2. This method may not have been sufficient, and direct observation for 1 min may be necessary. Respiratory rates collected by clinicians in triage40 and monitoring systems41 are frequently in error as suggested by direct observation. The phenomenon of respiratory rate collected by a pulse oximeter has been reported on previously.42 A PP monitor, if commercialized, could also display respiratory rate since the rate of the counted maxima and minima SBP peaks is equivalent to the respiratory rate. Rejected SBP peaks plagued by noise could still be counted, ensuring respiratory rate accuracy.

It is well-known that respirophasic changes in BP and perfusion are detectable in both pulse oximeters and plethysmographs. These devices are affected by the vagaries of perfusion, which are influenced by local peripheral extremity factors such as ambient temperature.43 Despite this, there are numerous reports4445 of detecting PP qualitatively by pulse oximetry and of detecting respiratory obstruction quantitatively by pulse oximetry.4647 Identifying the signature of PP in the presence of other confounding signals becomes an important task and is technically challenging. Pulse volume changes induced by respiratory events that are measured as the AUC may correlate with varying respiratory impedance.46 However, this study was limited by the lack of an external PP measure. Respiratory events generally follow a predictable pattern in relation to heart rate, which would help to negate interfering perfusion signals induced by local vascular events. Changes in plethysmographic volume, which reflect PP, can be quantitated by either a change in peak amplitude or area-under-the-curve calculations. Signal-processing schemes will require a look-up table correlating respirophasic pulse volume changes with known degrees of PP, measured in units of millimeters of Hg. In the present study, another commercially available plethysmograph was used, which demonstrated results that were similar to those in Figure 4 (data not shown). The scaling of the analog output of other instruments may vary, leading us to predict that plethysmograph amplitude varies by 1% for each millimeter of Hg of PP. In reality, the complexities of optical plethysmography, along with their inherent noise, may preclude the utility of a simple relationship in a pulse oximeter that also displays PP. Filtering and straightforward signal-processing methods like least mean squares approximation and best uniform approximation will be needed to take this next step.

Expert systems have appeared in many areas of health care. Examples include the bispectral index monitor,48 which gauges the depth of general anesthesia or conscious sedation,49 and the time-insensitive predictive instrument score, which measures the shape and elevation of the ST segment on 12-lead ECGs.50 These tools are especially useful in the context of emergency medicine by objectifying a subjective clinical assessment and reassessing a preconceived probability. An instrument like a PP monitor could serve as a patient management decision aid or in the detection of cardiopulmonary dyscrasias.

Limitations
The noninvasive continuous BP monitors used in this study measured BP to an acceptable degree of precision but tended to overestimate BP in the case of one monitor (FINAPRES; Ohmeda). However, the absolute difference in SBP between expiration and inspiration was calculated, which diminishes the significance of errors in the absolute values of BP. Continuous noninvasive BP monitors are not widely available clinically, which limits the ability to immediately deploy algorithms that calculate PP. In addition, arterial tonometry in this study was unable to acquire a continuous BP recording in 10% of patients due to motion artifacts or large wrist girth. Oscillometric BP monitors are unsuitable for this application as they do not provide a continuous measure of BP.

Some patients arriving at the hospital by ambulance were partially treated on study enrollment, which may have affected the analysis of the AT-PP ROC during the pretreatment phase. This could also have affected the posttreatment calculations as well, since these patients would have received larger amounts of inhaled ß-agonist agents than those patients arriving at the hospital by other means. However, this possibility is minimized by the fact that only 17% of patients arrived by ambulance, and in each case only one treatment was delivered prior to ED arrival. In addition, the main findings of this report remain clinically relevant as disposition is generally determined after standardized treatment is completed, which typically mirrors the NAEPP guidelines but may not be strictly adherent. Finally, physicians and raters were not held constant in keeping with clinical reality, thus warranting the calculation of intraclass correlation in lieu of interrater reliability.

Acknowledgements

The authors acknowledge Devraj Banerjee, BE, and Megan Wachs, BE, for their contribution in data collection.

Footnotes

Abbreviations: AT = automated; AUC = area under the curve; CI = confidence interval; ED = emergency department; ICC = intraclass correlation coefficients; ICD-9 = International Classification of Diseases, ninth revision; NAEPP = National Asthma Education and Prevention Program; OD = objective dyspnea; PEFR = peak expiratory flow rate; PP = pulsus paradoxus; ROC = receiver operator curve; SBP = systolic BP

Dr. Jay possesses two patents that relate to pulsus paradoxus.

This research was supported by National Heart, Lung, and Blood Institute grant R41 HL74633–01.

Received for publication December 12, 2005. Accepted for publication April 12, 2006.

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