A proposal for scientific validation of instruments for indirect blood pressure measurement at rest, during exercise, and in critical care

Peripheral venous pressure predicts central venous pressure poorly in pediatric patients

PURPOSE

Using peripheral venous pressure (PVP) instead of central venous pressure (CVP) as a volume monitor decreases patient risks and costs, and is convenient. This study was undertaken to determine if PVP predicts CVP in pediatric patients.

METHODS

With ethical approval and informed consent, 30 pediatric patients aged neonate to 12 yr requiring a central venous line were studied prospectively in a tertiary care teaching hospital. In the supine position, PVP and CVP were simultaneously transduced. Ninety-six paired recordings of CVP and PVP were made. Correlation and Bland-Altman analysis of agreement of end-expiratory measurements were performed.

RESULTS

The mean (SD; range) CVP was 10.0 mmHg (6.0; -1.0 to 27.0); the mean PVP was 13.7 mmHg (6.3; 0.0 to 33.0); offset (bias) of PVP > CVP was 3.7 mmHg with SD 2.6. The 95% confidence intervals (CI) for the bias were 3.2 to 4.1 mmHg. In the Bland-Altman analysis, lower and upper limits of agreement (LOA; CI in parentheses) were -1.5 (-2.3 to -0.7) and 8.8 (8.1 to 9.6) mmHg. Eight of 96 points were outside the limits of agreement. The correlation of PVP on CVP was r = 0.92, P < 0.0001. For a subset of ten patients (20 simultaneous recordings) with iv catheters proximal to the hand, limits of agreement were better - offset: 3.8 mmHg (+/- 1.4); lower LOA: 1.2 mmHg (0.25 to 2.1); upper LOA: 6.6 mmHg (5.7 to 7.5).

CONCLUSION

Peripheral venous pressure measured from an iv catheter in the hand predicts CVP poorly in pediatric patients.

Validation of a noninvasive blood pressure monitoring device in normotensive and hypertensive pediatric intensive care patients

OBJECTIVE

To evaluate the performance and to define limitations of a noninvasive blood pressure monitoring device in the critically ill pediatric population.

METHOD

Patients were included in the study if they were admitted to the Pediatric Intensive Care Unit, were between the ages of 1 month and 18 years with wrist circumferences of > or =10 cm, and had an indwelling arterial line. Patients were excluded if their systolic blood pressure differed by > or =7.5% between their upper extremities. The measurements were collected simultaneously with those from an arterial line by a computer interfaced with the noninvasive blood pressure monitoring system and the patient's monitor. Heart rates were calculated from the recorded pulse waveforms of the arterial lines. Comparison analyses were performed via bias and precision plots of the blood pressure and heart rate data in addition to calculation of Pearson's correlation coefficients and concordance correlation coefficients. As a nonparametric method of comparison, the proportion of measurements that differed by greater than 10% was calculated. Results. Blood pressures and heart rates of 20 patients between the ages of 12 months and 17 years were monitored by a noninvasive blood pressure monitor for 30 min per patient. This data collection resulted in 2015 data points for each blood pressure and heart rate for comparison of methods. Concordance correlation coefficients were the following: systolic blood pressure, 0.93; diastolic blood pressure, 0.93; mean blood pressure, 0.94; and heart rate, 0.85.

CONCLUSIONS

The noninvasive blood pressure monitor is capable of producing an accurate blood pressure measurement every 12-15 heartbeats in addition to providing a pulse waveform and digital display of the heart rate. Our study showed good agreement between the methods in the normotensive and hypertensive critically ill pediatric population with a wrist circumference limitation defined at > or =11 cm.

An arm phantom: a digital simulation system for testing sphygmomanometers

An arm phantom for testing non-invasive blood pressure measuring instruments under reproducible and real conditions has been developed. Signal records, recorded on patients and validated by a reference method, are played into the instruments to be tested using a combination of an electro-pneumatic and an electro-acoustic converter. For each of 90 patients a database contains records of at least three different kinds of signal: cuff pressure oscillations, Korotkoff sounds (except in neonates) and cuff pressure. As the inflation and deflation rate varies between different sphygmomanometers the control and synchronization of the signal output are ensured as a function of the instantaneous cuff pressure, measured continuously by the system. A segmented output procedure synchronizes the data flow during the test procedure. The records of blood pressure signals are separated in different signal groups, containing only one pressure oscillation and Korotkoff sound respectively, whereas the instantaneous cuff pressure determines the signal group to be selected. Suitable interfaces to the sphygmomanometers under test consist of two specifically developed signal converters, an electro-pneumatic converter and an electro-acoustic converter. The system generates both cuff pressure oscillations and Korotkoff sounds from real data earlier recorded on human subjects. It allows any inflation and deflation rate of the cuff pressure to be applied, considers the variability of the pulse rate occurring in the same data record and finally it allows the superposition of artefacts. The arm phantom can replace clinical trials. The possibility of testing the limits of the performance of sphygmomanometers has been considerably extended.

Assessing agreement between clinical measurement methods

Nursing practice and research often require the use of one measurement method in place of another, creating the need to know how well one clinical measurement method approximates another. The usual statistical analyses for assessing agreement between measurement methods are the correlation coefficient and the paired t test. This article suggests that these statistical methods do not address the question of agreement. It proposes the limits of agreement as a more informative analysis when a researcher is interested in replacing one measurement method with another. The application of limits of agreement analysis to assess repeatability of one measurement method is also introduced.