L . Andersen et al .: J Extra Corpor Technol 2023 , 55 , 209 – 217 211
Figure 1 . ( A ) A part of the Cox curve in one of the recordings , with a spread from �0.84 to 0.96 . ( B ) Data representing the blue dot with most positive Cox index . ( C ) Data representing the red dot with most negative COx index , depending on the independent relation between rSO 2 and the systemic MAP . Shaded area represents negative Cox index . Unshaded area represents positive COx index . Lines show corresponding linear regression line .
each combination of rSO 2 and MAP , where the length of the signals was set to the shortest signal length . Finally , the percentage of the total time when COx was above 0.40 or below �0.40 was calculated for each set of signals , and 90 % confidence intervals were constructed based on the 90 artificial COx values , as they represented truly uncorrelated signal pairs . Thus , if the total time with COx > 0.40 is higher than the upper limit of the CI , this would be more frequent than expected if the signals were unrelated , which in turn could indicate a loss of autoregulation .
Statistical
analyses
Calculation of central tendencies , correlations , and production of graphs was performed in Microsoft R 365 Excel for Mac ( Microsoft Corp , Redmond , WA ), SPSS statistical software version 27 ( IBM Corp , Armonk , NY ), and Matlab R2022a ( Mathworks Inc , Natick , MA ). Uses of the standard deviation and the median are annotated in the text . Correlations were analyzed using Pearson ’ s correlation coefficient ( r ).
Results and discussion Understanding the COx index
A typical COx curve configuration in the time domain representing the dynamic association [ 26 ] between slow wave fluctuations of the estimated CBF and MAP is shown in Figure 1A . Since the COx index is expressed as a correlation coefficient , the range can vary between ( �1 ) and ( 1 ). In this illustration , COx varies from (+ 0.96 ) to ( �0.84 ), with a sign change occurring after 2 min . A positive COx index appears , when MAP and rSO 2 are moving in the same direction , i . e ., both increase or decrease simultaneously , as indicated in Figure 1B . When CBF dependent on the MAP it implies loss of CA ; typically targeted by a COx index > 0.40 , while a COx index approaching 0 indicates preserved CA [ 18 ]. The paradox of a negative COx index occurs when CBF and MAP move in opposite directions ;
Figure
2 . The percent of time with COx > 0.40 or COx < �0.40 in each subject ( red dots ) related to results based on a unique mixture of 90 uncorrelated signals including all subjects ’ individual rSO 2 signals and a combination of MAP signals from the remaining cases . The 5 – 95 % interval is indicated by the shaded area and the median and quartiles with solid and dashed lines . The red dots represent the results based on the recorded signals in each subject . Two subjects presented more frequent COx > 0.40 than expected by the 95 % interval for uncorrelated signals .
MAP increases , while CBF decreases or vice versa ( Figure 1C ). Both these situations are difficult to explain from a physiological standpoint , especially in the case where there is a decrease in MAP and an increase in CBF . This would imply a disproportionable cerebral vascular dilatation to compensate for a cyclic drop in MAP .
The curve formations representing MAP and CBF appear at individual frequencies , which synchronize only occasionally , thus analysis in the time domain infers shifting of these phases [ 27 ]. The curve representing CBF is typically delayed in relation to MAP . The effect of phase shifts will inevitably produce significant COx index variations , which may explain why the COx index occasionally turns negative .
The percentage of the total time , when COx was above 0.40 or below �0.40 in individual registrations is presented in Figure 2 . Thefigure also shows the confidence intervals for the corresponding percentages based on the variation in