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    Microdialysis is a clinical method used to detect ischemia after microvascular surgery. Microdialysis is easy to use and reliable, but its value in most clinical settings is hampered by a 1- to 2-h delay in the delivery of patient data. This study evaluated the effectiveness of an increase in the microdialysis perfusion rate from 0.3 to 1.0 µL/min on the diagnostic delay in the detection of ischemia.  In eight pigs, two symmetric pure muscle transfers were dissected based on one vascular pedicle each. In each muscle, two microdialysis catheters were placed. The two microdialysis catheters were randomized to a perfusion rate of 0.3 or 1.0 µL/min, and the two muscle transfers were randomized to arterial or venous ischemia, respectively. After baseline monitoring, arterial and venous ischemia was introduced by the application of vessel clamps. Microdialysis sampling was performed throughout the experiment. The ischemic cutoff values were based on clinical experience set as follows: CGlucose < 0.2 mmol/L, CLactate > 7 mmol/L, and the lactate/pyruvate ratio > 50.  The delay for the detection of 50% of arterial ischemia was reduced from 60 to 25 minutes, and for the detection of all cases of arterial ischemia, the delay was reduced from 75 to 40 minutes when the perfusion rate was increased from 0.3 to 1.0 µL/min. After the same increase in perfusion, the detection of 50% of venous ischemia was reduced from 75 to 40 minutes, and for all cases of venous ischemia, a reduction from 135 to 95 minutes was found.  When using microdialysis for the detection of ischemia in pure muscle transfers, an increase in the perfusion rate from 0.3 to 1.0 µL/min can reduce the detection delay of ischemia. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

    Citation

    Andreas Rauff-Mortensen, Mette Marie Berggren-Olsen, Hans Kirkegaard, Kim Houlind, Hanne Birke-Sørensen. Faster Detection of Ischemia in Free Muscle Transfer When Using Microdialysis. Journal of reconstructive microsurgery. 2020 Mar;36(3):228-234

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    PMID: 31858491

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