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

Objectives: To determine whether the simultaneous measurement of tissue pH, Pco(2), and Po-2 with a multiple-parameter fiberoptic sensor can be used t o 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 m ins. 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 m easured tissue pH, Pco(2), and Po-2 pH and Pco(2), indicators of anaerobic metabolism, were plotted against tissue Po-2. All shocked animals, but no s ham animals, showed a biphasic relationship between Po-2 and both pH and Pc o(2). Curves were fit to both an exponential and a dual-line linear functio n to determine critical values for Po-2, pH, and Pco(2). The length of time the animal was dysoxic was evaluated as a predictor of negative outcome. C ritical values determined from the exponential models were more sensitive i ndicators of negative outcome than values determined from the linear model and more sensitive than arterial lactate and tonometric intramucosal pH and Pco(2), Conclusions: The multiple-parameter sensor offers the unique opportunity to study solid as well as hollow organ dysoxia through the simultaneous measu rement of interstitial pH, Pco(2), and Po-2 in a small tissue region. The g radual transition from sufficient oxygen availability to dysoxia as a resul t of hemorrhage was better described by an exponential equation. The length of time that ph was below or Pco(2) was above the critical value determine d from the exponential model was predictive of a negative outcome.