First of all we would like to thank Cannesson et al
. for the positive critique and discussion of our recent study in Anesthesiology1
. Our motivation for performing the study was the increasing number of publications reporting that respiratory variations in the photoplethysmogram could predict fluid responsiveness in mechanically ventilated patients, based on correlation and agreement between respiratory variations in the photoplethysmographic waveform amplitude (ΔPOP) and in the invasive arterial pulse pressure (ΔPP). Because of our previous work on the complexity of human skin microcirculation these data surprised us, especially in intensive care unit (ICU) patients based on only a few measurements from each patient. Thus, we questioned the relationship between respiratory variations in ΔPOP and ΔPP in ICU patients, and found a large variability of ΔPOP and poor correlation between ΔPOP and ΔPP. We believe that the comments by Cannesson et al
. are highly relevant, and below we respond to the different issues.
First, our findings are in contradiction with several studies focusing on the relationship, agreement, and ability of ΔPP and ΔPOP to predict fluid responsiveness in mechanically ventilated patients in the operating room2
and in the ICU.3–6
were performed on deeply sedated ICU patients. The study by Wyffels et al
was performed on postoperative cardiac surgery patients, whereas Natalini et al
examined hypotensive ICU patients. Our study1
and three of the others3,4,6
were performed on heterogeneous ICU patients. Patient characteristics could explain some of the contradiction between the studies. However, we believe that the most important difference is how values of ΔPP and ΔPOP were selected. To be able to calculate inter- and intraindividual variability, we performed calculations continuously and time-synchronized over a period of approximately 15 min. By this continuous analysis system, we avoided potential bias in selection of data. Thus, we believe that our study illustrates the importance of performing analysis of repeatability when comparing methods.
Second, all pulse oximeters process the raw data in different ways. We agree that subtle differences in software may have a profound impact on the results.7
We used the analogue signal from an Oximax 451N5 (Nellcor, Boulder, CO) in our study, but do not have access to its signal algorithms. This could have given valuable information. However, details regarding signal algorithms are not given in other ICU studies.3–6
Cannesson et al
. suggested that our signal is less processed than in previous studies, and that including a high-pass filter would improve the agreement. By performing a high-pass filtering, one could remove the slower oscillations from the original signal. We agree that this could be an interesting approach. However, the important question is whether filtration improves the part of the signal related to fluid responsiveness. We filtered, with a Butterworth high-pass filter (Labview, National Instruments Corp., Austin, TX), signals from one patient in our study (Patient 3), who demonstrated large, slow oscillations (fig. 1
). The average values and the variability of ΔPOP and ΔPP were only modestly reduced. Even though only performed in one patient, this example illustrates that filtration of the photoplethysmogram is not a straightforward solution of the problem. In our paper we also showed that other, and probably more important, mechanisms than slow oscillations contribute to the great variability found in our study. Further investigations are needed in this field.
Third, we agree that more standardized conditions, as in the operating room during general anesthesia, monitoring depth of anesthesia, standardization of all aspects related to ventilation, temperature, and sites of measurements should be emphasized in future studies. We also agree that the key feature for future studies is the ability to predict fluid responsiveness and guide fluid therapy. However, before introducing a new method, it is imperative to demonstrate repeatability and agreement between the method and the present gold standard.
Finally, we believe that our findings in ICU patients relate to a combination of factors both in the patient (medication, diagnosis) and to the equipment, and how these factors affect the physiology and the measurement of the photoplethysmographic signal. We still believe that the photoplethysmogram has the potential to give valuable information about the volume status of patients. As the photoplethysmogram is more complex than the invasive blood pressure curve, we believe that an algorithm used in the photoplethysmogram should reflect this complexity. Regardless of algorithms, future studies comparing methods should include measurement of repeatability.
Svein A. Landsverk, M.D.*
Lars O. Hoiseth, M.D.,
Knut A. Kirkeboen, M.D., Ph.D.
*Ulleval University Hospital, Oslo, Norway. firstname.lastname@example.org
1. Landsverk SA, Hoiseth LO, Kvandal P, Hisdal J, Skare O, Kirkeboen KA: Poor agreement between respiratory variations in pulse oximetry photoplethysmographic waveform amplitude and pulse pressure in intensive care unit patients. Anesthesiology 2008; 109:849–55
2. Cannesson M, Attof Y, Rosamel P, Desebbe O, Joseph P, Metton O, Bastien O, Lehot JJ: Respiratory variations in pulse oximetry plethysmographic waveform amplitude to predict fluid responsiveness in the operating room. Anesthesiology 2007; 106:1105–11
3. Feissel M, Teboul JL, Merlani P, Badie J, Faller JP, Bendjelid K: Plethysmographic dynamic indices predict fluid responsiveness in septic ventilated patients. Intensive Care Med 2007; 33:993–9
4. Natalini G, Rosano A, Taranto M, Faggian B, Vittorielli E, Bernardini A: Arterial versus plethysmographic dynamic indices to test responsiveness for testing fluid administration in hypotensive patients: A clinical trial. Anesth Analg 2006; 103:1478–84
5. Wyffels PA, Durnez PJ, Helderweirt J, Stockman WM, De Kegel D: Ventilation-induced plethysmographic variations predict fluid responsiveness in ventilated postoperative cardiac surgery patients. Anesth Analg 2007; 105:448–52
6. Cannesson M, Besnard C, Durand PG, Bohé J, Jacques D: Relation between respiratory variations in pulse oximetry plethysmographic waveform amplitude and arterial pulse pressure in ventilated patients. Crit Care 2005; 9:R562–8
7. Feldman JM: Can clinical monitors be used as scientific instruments? Anesth Analg 2006; 103:1071–2
© 2009 American Society of Anesthesiologists, Inc.