Does hypercapnic acidosis preserve mucosal oxygenation during hemorrhage?

As a researcher in the field of intensive care, I am interested in physiology and how its manipulations may alter both the phenotype of a disease and the outcome. I primarily start with experimental studies, preferentially in larger animals because I believe that these results are more likely to be reproducible in humans. Unfortunately, besides being expensive, such studies cause harm to the animals. Therefore, I try to keep the number of animals as low as possible. And I anesthetize the animals, although this interferes with physiology. Let’s assume that I want to evaluate the effects of two different manipulations of physiology on the pathophysiology of a disease. My options are either (a) to use three groups of animals, subject one group to the disease only and subject the remaining two groups to the disease and one of the manipulations, or (b) to use only one group of animals and expose each animal to all three conditions. It is difficult to judge whether three manipulations in one group of animals is less or more harmful than one manipulation in three times as many animals. Now let’s assume that I go for one group and three manipulations. This obviously will reduce the number of animals and the cost. How do I confirm that (a) I was able to reproduce the same disease three times, and (b) altering physiology in two different ways resulted in significant (and possibly different) changes in pathophysiology? Answering the first question becomes especially difficult if the manipulation starts before the disease has been establishedVand therefore, the answer to the second question is also not straightforward. In this issue of Shock, Dr Schwartges and coworkers (1) evaluate the effects of Bprophylactic[ and Btherapeutic[ hypoventilation (resulting in respiratory acidosis) on gastric mucosal tissue oxygenation in five dogs subjected to hemorrhage. Here, prophylactic and therapeutic mean that hypoventilation started before and after established hemorrhage, respectively. The main findings are shown in Figures 1 and 2 of this editorial (data derived from Table 1 in [1]). My informal interpretation of Figure 1 is the following: (a) hemorrhage reduced gastric mucosal oxygenation in all circumstances; (b) prophylactic hypoventilation helped increase the lower baseline values in this group to the level of the two other groups, and compared with the other two groups, kept mucosal oxygenation slightly higher during hemorrhage and recovery. As the overlapping SDs suggest, a (potential) difference between the groups cannot be shown with the small number of animals; (c) therapeutic hypoventilation has no significant effect. Hemorrhage produced a similar effect on systemic oxygen delivery (Fig. 2). It seems that the changes in controls and animals subjected to prophylactic hypoventilation parallel each otherV starting with slightly higher values in the latter group. In view of the difference between controls and the therapeutic hypoventilation group before hemorrhage (normovolemia)Vat a time point where both groups are still handled the same wayVthe small differences in changes between baseline and normovolemia and between hypovolemia 30 and hypovolemia 70 in controls and the prophylactic hypoventilation group, are certainly not significant. During the hypovolemia period, systemic oxygen delivery seems to increase in the therapeutic hypoventilation group. Again, significant changes between groups are hard to detect because the number of animals is small with respect to the variability of systemic oxygen delivery. What statistical test should I use to confirm or disprove my informal interpretation? Normally, nonparametric tests are used because normal distribution is difficult to prove with very small numbers. Non-normal distribution is suggested if the SD is equal to or more than half of the mean of a variable (2). This is certainly the case for the variable displayed in Figure 2 (change in mucosal oxygen saturation). Nevertheless, the authors used parametric tests, here a two-factor analysis of variance (ANOVA) for repeated measurements. The first factor is obviously hemorrhage (hypovolemia) and the second factor is hypoventilation. A significant interaction between the two factors indicates that hypoventilation (hypercapnic acidosis) alters the time course of a given variable (e.g., mucosal tissue oxygenation) during hemorrhage. The authors have not shown this. This does not mean that hypercapnia did not alter effects of hemorrhage on certain physiological parameters. It just means that potential changes are too small to be detected with the model used. Independent of the P, one can ask the question: are the differences clinically meaningful? We are all attracted to the idea of publishing significant findings. The chances of having a study published is much higher when the results are significant than when they are not (3Y5). I do not blame Dr Schwartges and coworkers (1) that they looked at their data from different angles to get significant P values. One option is to ignore the absolute values at baseline (I greatly acknowledge that the authors report all data) and display changes from there. This helps especially if baseline values in the group of interest are somewhat closer to the most aberrant values in the other group(s) in a situation where the hypothesis is Bno change[Vor the other way around if a significant difference is to be shown. The microvascular oxygen saturation in the article by Dr Schwartges and coworkers (1) is a prime example for it. It is very unlikely to detect a