212 L . Andersen et al .: J Extra Corpor Technol 2023 , 55 , 209 – 217
Figure 3 . Case example : ( A ) MAP ( grey curve ), rSO 2 ( blue curve ) and the COx index ( red curve ) from initiation of cardiopulmonary bypass until weaning ( 49 min ). ( B ) The MAP sorted from low to high based on the mean value over 2.5-minute intervals ( grey curve ). The red curve represents the corresponding trended average COx value including 20 registrations . Reference line COx = 0.4 ( green dotted line ).
the COx index for the surrogate data set , i . e ., the 90 truly unrelated MAP and rSO 2 signals . The results showed that 8 / 10 patients were located within the estimated confidence intervals , where the upper limit for the percentage of time with COx > 0.40 was 27 %. Interestingly , two patients presented with high COx values in 30 – 50 % of their total recording , which is a more frequent occurrence than expected if their MAP and rSO 2 signals had been unrelated .
If even short periods with high COx in the recordings from patients is a sign of e . g ., an abnormal CA , a phase shift between the signals , or only occurring randomly due to noise warrants further investigation . More studies are also required to evaluate if the surrogate data analysis method is a valid method to identify patients with signs of disturbed CA .
An alternative possible solution would be to combine or replace COx index analysis with either coherence [ 27 ] or transfer function analyses [ 28 ].
The
COx index from the observer ’ s eye
The observer ’ s real-time vision of the information presented in the clinical setting would typically include COx , MAP , and rSO 2 values shown in Figure 3A . In this example , the duration of CPB is 49 min , during which MAP has ranged from 37 to 67 mmHg , rSO 2 63 % to 69 %, and COx �0.86 to 0.94 , respectively . Of note is that both MAP and rSO 2 remain within acceptable physiological limits , despite a significant COx variation , with loss of CA occurring on eight occasions as defined by the COx > 0.4 criterion . In each case , CA is short-lived and mainly associated with minor changes in MAP , probably due to pharmacological interventions or changes in systemic blood flow or / and vascular resistance . The hypothetical question that remains to be answered is , can these events of abnormal CA be circumvented if the COx index is monitored in real-time ? COx values beyond 0.4 in Figure 3A appear during periods of hypotension , followed by a simultaneous elevation of MAP and rSO 2 . The interrogation of our data cannot isolate its cause , however most likely due to a vasoconstrictor intended to normalize the systemic blood pressure .
Adequate interventions related to COx index variations require several considerations . The calculated COx index is not truly instant , it is based on historical data ( 30 registrations collected over 2.5-minute periods ). Before a reliable trend can be visualized , a considerably longer period would be required . It makes instant therapeutic interventions difficult to accomplish , which limits the method ’ s applicability .
Clinically useful information derived from this method could be to display the COx index in reference to MAP ( Figure 3B ). This will once again be historical data , however , still possible to gradually build up during a CPB procedure . The rationale behind this would be to identify blood pressure limits (“ a safe window ”), within which the CA is preserved . Techniques are now available where the actual correlation between MAP and rSO 2 ( COx ) is presented online [ 19 , 29 , 30 ].
Characteristics of variables forming the COx index
Figure 4 shows differences in variability of the parameters used for the computation of the COx index . The variability is defined as the relationshipbetween the standard deviation
SD 100 [ SD ] and the mean value MV ) expressed as a percentage (%) of all recordings . The variability of MAP ( 13 %)
MV
overweighed the variability of rSO 2 ( 4 %) by more than 300 % based on the interpatient overall median values ( Figure 4A ). The difference is of note , as it means that the resulting COx index is more sensitive to changes in MAP than rSO 2 . This is also evident from the illustration in Figure 3 . Figure 4B further illustrates how MAP influences the COx index with the recorded interpatient variability ranging from 95 % to 2264 %, with a median value of 779 %. Posthoc analysis of the COx index
The COx index presented in publications is generally calculated posthoc , thus , it does not reflect real-time observations , and this is one of the main objections to using the method to monitor [ 19 , 29 ]. By plotting the COx index in consecutive bins of MAP ,