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The effect of baseline pressure errors on an intracranial pressure-derived index: results of a prospective observational study.

Eide PK, Sorteberg A, Meling TR, Sorteberg W - Biomed Eng Online (2014)

Bottom Line: We compared this approach with a method of calculating RAP using a 4-min moving window updated every 6 seconds (method 2).The two methods of calculating RAP produced similar results.As differences in RAP are of magnitudes that may alter patient management, we do not advocate the use of RAP in the management of neurosurgical patients.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Neurosurgery, Oslo University Hospital, Rikshospitalet, Oslo, Norway. p.k.eide@medisin.uio.no.

ABSTRACT

Background: In order to characterize the intracranial pressure-volume reserve capacity, the correlation coefficient (R) between the ICP wave amplitude (A) and the mean ICP level (P), the RAP index, has been used to improve the diagnostic value of ICP monitoring. Baseline pressure errors (BPEs), caused by spontaneous shifts or drifts in baseline pressure, cause erroneous readings of mean ICP. Consequently, BPEs could also affect ICP indices such as the RAP where in the mean ICP is incorporated.

Methods: A prospective, observational study was carried out on patients with aneurysmal subarachnoid hemorrhage (aSAH) undergoing ICP monitoring as part of their surveillance. Via the same burr hole in the scull, two separate ICP sensors were placed close to each other. For each consecutive 6-sec time window, the dynamic mean ICP wave amplitude (MWA; measure of the amplitude of the single pressure waves) and the static mean ICP, were computed. The RAP index was computed as the Pearson correlation coefficient between the MWA and the mean ICP for 40 6-sec time windows, i.e. every subsequent 4-min period (method 1). We compared this approach with a method of calculating RAP using a 4-min moving window updated every 6 seconds (method 2).

Results: The study included 16 aSAH patients. We compared 43,653 4-min RAP observations of signals 1 and 2 (method 1), and 1,727,000 6-sec RAP observations (method 2). The two methods of calculating RAP produced similar results. Differences in RAP ≥ 0.4 in at least 7% of observations were seen in 5/16 (31%) patients. Moreover, the combination of a RAP of ≥ 0.6 in one signal and <0.6 in the other was seen in ≥ 13% of RAP-observations in 4/16 (25%) patients, and in ≥ 8% in another 4/16 (25%) patients. The frequency of differences in RAP >0.2 was significantly associated with the frequency of BPEs (5 mmHg ≤ BPE <10 mmHg).

Conclusions: Simultaneous monitoring from two separate, close-by ICP sensors reveals significant differences in RAP that correspond to the occurrence of BPEs. As differences in RAP are of magnitudes that may alter patient management, we do not advocate the use of RAP in the management of neurosurgical patients.

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Trend plots of RAP [correlation coefficient (R) between the intracranial pressure (ICP) wave amplitude (A) and the mean ICP level (P)] of Signals 1 and 2 in patient 2. For patient 2, the trend plots of (a) RAP determined during 100 consecutive 4-min periods for signals 1 (blue line) and 2 (red line) show marked differences (average of RAPSignal 1 0.50; average of RAPSignal 2 -0.04). The horizontal lines at RAP 0.6 illustrate a commonly used upper normal threshold for RAP. The intracranial locations of the ICP sensors 1 and 2 are illustrated in (b).
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Figure 2: Trend plots of RAP [correlation coefficient (R) between the intracranial pressure (ICP) wave amplitude (A) and the mean ICP level (P)] of Signals 1 and 2 in patient 2. For patient 2, the trend plots of (a) RAP determined during 100 consecutive 4-min periods for signals 1 (blue line) and 2 (red line) show marked differences (average of RAPSignal 1 0.50; average of RAPSignal 2 -0.04). The horizontal lines at RAP 0.6 illustrate a commonly used upper normal threshold for RAP. The intracranial locations of the ICP sensors 1 and 2 are illustrated in (b).

Mentions: The software incorporates an automatic procedure for determining the correlation coefficient (R) between the ICP wave amplitude (A) and the ICP level (P), the RAP, during consecutive 4-min time periods. The RAP-index is the Pearson correlation coefficient between the MWA and the mean ICP during 40 6-sec time window periods. Computation of RAP has previously been described by others [6,12]. Since we compared the RAP of two simultaneous ICP signals, the RAP of Sensors 1 and 2 were derived from simultaneous 6-sec time windows (Figures 1a-b).The Pearson correlation coefficient is a measure of the strength of a relationship between two variables, ranging from -1 to +1. When one variable changes in the opposite direction of the other, the correlation coefficient becomes negative, whereas the correlation coefficient becomes positive when both variables change in the same direction (Figures 1d-f). The closer the correlation coefficient is to + or -1, the stronger is the relationship between the two variables. The assumptions for using the Pearson correlation coefficient during 4-min periods as performed in this study were fulfilled: Both the mean ICP and the MWA are continuous and independent observations that follow a normal distribution. Moreover, for intervals of 4-minute duration, the correlation coefficient between these two observations reflects a linear relationship.We further compared two different methods of calculating the RAP:(i) Method 1. According to method 1, a new RAP value was calculated every 4 min period. Hence, for every consecutive 4-min period the software determined the Pearson correlation coefficient (RAP) values of the two ICP signals (Figures 1c-d). The RAP scores could then be trended as shown in Figure 2.


The effect of baseline pressure errors on an intracranial pressure-derived index: results of a prospective observational study.

Eide PK, Sorteberg A, Meling TR, Sorteberg W - Biomed Eng Online (2014)

Trend plots of RAP [correlation coefficient (R) between the intracranial pressure (ICP) wave amplitude (A) and the mean ICP level (P)] of Signals 1 and 2 in patient 2. For patient 2, the trend plots of (a) RAP determined during 100 consecutive 4-min periods for signals 1 (blue line) and 2 (red line) show marked differences (average of RAPSignal 1 0.50; average of RAPSignal 2 -0.04). The horizontal lines at RAP 0.6 illustrate a commonly used upper normal threshold for RAP. The intracranial locations of the ICP sensors 1 and 2 are illustrated in (b).
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4125597&req=5

Figure 2: Trend plots of RAP [correlation coefficient (R) between the intracranial pressure (ICP) wave amplitude (A) and the mean ICP level (P)] of Signals 1 and 2 in patient 2. For patient 2, the trend plots of (a) RAP determined during 100 consecutive 4-min periods for signals 1 (blue line) and 2 (red line) show marked differences (average of RAPSignal 1 0.50; average of RAPSignal 2 -0.04). The horizontal lines at RAP 0.6 illustrate a commonly used upper normal threshold for RAP. The intracranial locations of the ICP sensors 1 and 2 are illustrated in (b).
Mentions: The software incorporates an automatic procedure for determining the correlation coefficient (R) between the ICP wave amplitude (A) and the ICP level (P), the RAP, during consecutive 4-min time periods. The RAP-index is the Pearson correlation coefficient between the MWA and the mean ICP during 40 6-sec time window periods. Computation of RAP has previously been described by others [6,12]. Since we compared the RAP of two simultaneous ICP signals, the RAP of Sensors 1 and 2 were derived from simultaneous 6-sec time windows (Figures 1a-b).The Pearson correlation coefficient is a measure of the strength of a relationship between two variables, ranging from -1 to +1. When one variable changes in the opposite direction of the other, the correlation coefficient becomes negative, whereas the correlation coefficient becomes positive when both variables change in the same direction (Figures 1d-f). The closer the correlation coefficient is to + or -1, the stronger is the relationship between the two variables. The assumptions for using the Pearson correlation coefficient during 4-min periods as performed in this study were fulfilled: Both the mean ICP and the MWA are continuous and independent observations that follow a normal distribution. Moreover, for intervals of 4-minute duration, the correlation coefficient between these two observations reflects a linear relationship.We further compared two different methods of calculating the RAP:(i) Method 1. According to method 1, a new RAP value was calculated every 4 min period. Hence, for every consecutive 4-min period the software determined the Pearson correlation coefficient (RAP) values of the two ICP signals (Figures 1c-d). The RAP scores could then be trended as shown in Figure 2.

Bottom Line: We compared this approach with a method of calculating RAP using a 4-min moving window updated every 6 seconds (method 2).The two methods of calculating RAP produced similar results.As differences in RAP are of magnitudes that may alter patient management, we do not advocate the use of RAP in the management of neurosurgical patients.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Neurosurgery, Oslo University Hospital, Rikshospitalet, Oslo, Norway. p.k.eide@medisin.uio.no.

ABSTRACT

Background: In order to characterize the intracranial pressure-volume reserve capacity, the correlation coefficient (R) between the ICP wave amplitude (A) and the mean ICP level (P), the RAP index, has been used to improve the diagnostic value of ICP monitoring. Baseline pressure errors (BPEs), caused by spontaneous shifts or drifts in baseline pressure, cause erroneous readings of mean ICP. Consequently, BPEs could also affect ICP indices such as the RAP where in the mean ICP is incorporated.

Methods: A prospective, observational study was carried out on patients with aneurysmal subarachnoid hemorrhage (aSAH) undergoing ICP monitoring as part of their surveillance. Via the same burr hole in the scull, two separate ICP sensors were placed close to each other. For each consecutive 6-sec time window, the dynamic mean ICP wave amplitude (MWA; measure of the amplitude of the single pressure waves) and the static mean ICP, were computed. The RAP index was computed as the Pearson correlation coefficient between the MWA and the mean ICP for 40 6-sec time windows, i.e. every subsequent 4-min period (method 1). We compared this approach with a method of calculating RAP using a 4-min moving window updated every 6 seconds (method 2).

Results: The study included 16 aSAH patients. We compared 43,653 4-min RAP observations of signals 1 and 2 (method 1), and 1,727,000 6-sec RAP observations (method 2). The two methods of calculating RAP produced similar results. Differences in RAP ≥ 0.4 in at least 7% of observations were seen in 5/16 (31%) patients. Moreover, the combination of a RAP of ≥ 0.6 in one signal and <0.6 in the other was seen in ≥ 13% of RAP-observations in 4/16 (25%) patients, and in ≥ 8% in another 4/16 (25%) patients. The frequency of differences in RAP >0.2 was significantly associated with the frequency of BPEs (5 mmHg ≤ BPE <10 mmHg).

Conclusions: Simultaneous monitoring from two separate, close-by ICP sensors reveals significant differences in RAP that correspond to the occurrence of BPEs. As differences in RAP are of magnitudes that may alter patient management, we do not advocate the use of RAP in the management of neurosurgical patients.

Show MeSH
Related in: MedlinePlus