Application of fiberoptic sensors for the study of hepatic dysoxia in swine hemorrhagic shock.

OBJECTIVES

To determine whether the simultaneous measurement of tissue pH, Pco2, and Po2 with a multiple-parameter fiberoptic sensor can be used to indicate the onset of hepatic dysoxia, to determine critical values, and to assess their use in predicting negative outcomes.

DESIGN

Prospective animal study.

SETTING

University research laboratory.

SUBJECTS

Fourteen Yorkshire swine.

INTERVENTIONS

Hemorrhagic shock (n = 11) was induced over 15 mins to lower systolic blood pressure to 40 mm Hg and was maintained for 30, 60, or 90 mins. Resuscitation was achieved with shed blood and warm saline to maintain mean pressure >60 mm Hg for 120 mins. Sham animals (n = 3) were subjected to 90 mins of sham shock, followed by a 120-min recovery period.

MEASUREMENTS AND MAIN RESULTS

The multiple-parameter sensor continuously measured tissue pH, Pco2, and Po2. pH and Pco2, indicators of anaerobic metabolism, were plotted against tissue Po2. All shocked animals, but no sham animals, showed a biphasic relationship between Po2 and both pH and Pco2. Curves were fit to both an exponential and a dual-line linear function to determine critical values for Po2, pH, and Pco2. The length of time the animal was dysoxic was evaluated as a predictor of negative outcome. Critical values determined from the exponential models were more sensitive indicators of negative outcome than values determined from the linear model and more sensitive than arterial lactate and tonometric intramucosal pH and Pco2.

CONCLUSIONS

The multiple-parameter sensor offers the unique opportunity to study solid as well as hollow organ dysoxia through the simultaneous measurement of interstitial pH, Pco2, and Po2 in a small tissue region. The gradual transition from sufficient oxygen availability to dysoxia as a result of hemorrhage was better described by an exponential equation. The length of time that pH was below or Pco2 was above the critical value determined from the exponential model was predictive of a negative outcome.