Agreement between continuous noninvasive finger cuff-derived and invasive arterial blood pressure measurements: Effect of data sampling and data processing

Abstract

BACKGROUND The effect of different methods for data sampling and data processing on the results of comparative statistical analyses in method comparison studies of continuous arterial blood pressure (AP) monitoring systems remains unknown. OBJECTIVE We sought to investigate the effect of different methods for data sampling and data processing on the results of statistical analyses in method comparison studies of continuous AP monitoring systems. DESIGN Prospective observational study. SETTING University Medical Center Hamburg-Eppendorf, Hamburg, Germany, from April to October 2019. PATIENTS 49 patients scheduled for neurosurgery with AP measurement using a radial artery catheter. MAIN OUTCOME MEASURES We assessed the agreement between continuous noninvasive finger cuff-derived (CNAP Monitor 500; CNSystems Medizintechnik, Graz, Austria) and invasive AP measurements in a prospective method comparison study in patients having neurosurgery using all beat-to-beat AP measurements (Methodall), 10-s averages (Methodavg), one 30-min period of 10-s averages (Method30), Method30 with additional offset subtraction (Method30off), and 10 30-s periods without (Methodiso) or with (Methodiso-zero) application of the zero zone. The agreement was analysed using Bland-Altman and error grid analysis. RESULTS For mean AP, the mean of the differences (95% limits of agreement) was 9.0 (−12.9 to 30.9) mmHg for Methodall, 9.2 (−12.5 to 30.9) mmHg for Methodavg, 6.5 (−9.3 to 22.2) mmHg for Method30, 0.5 (−9.5 to 10.5) mmHg for Method30off, 4.9 (−6.0 to 15.7) mmHg for Methodiso, and 3.4 (−5.9 to 12.7) mmHg for Methodiso-zero. Similar trends were found for systolic and diastolic AP. Results of error grid analysis were also influenced by using different methods for data sampling and data processing. CONCLUSION Data sampling and data processing substantially impact the results of comparative statistics in method comparison studies of continuous AP monitoring systems. Depending on the method used for data sampling and data processing, the performance of an AP test method may be considered clinically acceptable or unacceptable.

A new noninvasive finger sensor (NICCI system) for continuous blood pressure and pulse pressure variation monitoring

“…Therefore we included all available blood pressure measurements after exclusion of obvious artifacts. However, we averaged blood pressure measurements over 10 s episodes to avoid the potential for single outliers or differences in heart rates to influence comparative analyses 6 . Using 10 s averages does not alter the results of Bland–Altman analysis, and also reflects clinical practice, as most continuous blood pressure monitors do not display beat-to-beat measurements but moving averages.…”

“…Data sampling and processing can profoundly influence the results of comparative statistical analyses 6 . Therefore we included all available blood pressure measurements after exclusion of obvious artifacts.…”

“…Data sampling and processing can profoundly influence the results of comparative statistical analyses. 6 Therefore we included all available blood pressure measurements after exclusion of obvious artifacts. However, we averaged blood pressure measurements over 10 s episodes to avoid the potential for single outliers or differences in heart rates to influence comparative analyses.…”

“…For statistical analysis, the synchronised beat-to-beat blood pressure measurements were averaged over 10 s for further analysis ( i.e. consecutive, nonoverlapping 10-s averages) 6 …”

“…consecutive, nonoverlapping 10-s averages). 6 We compared PPV NICCI with PPV ART at 5 min intervals. PPV ART was calculated manually using the first 30 s episode of each 5 min interval using beat-to-beat blood pressure measurements from the radial arterial catheter after identification of pulse pressure maxima and minima of at least three visible respiratory swings using the formula: pulse pressure variation (%) ¼ 100 [2 x (pulse pressure maximum -pulse pressure minimum)] / (pulse pressure maximum þ pulse pressure minimum) %.…”