Power spectral analysis of the effects of epinephrine, norepinephrine, dobutamine and dopexamine on microcirculation following free tissue transfer.

BACKGROUND: The use of pressor drugs after microsurgical free tissue transfer remains controversial because of potential vasoconstrictor effects on the free flap. Noninvasive monitoring of free flaps with laser Doppler flowmetry may provide further information regarding the local regulation of blood flow in the flap tissues during pressor infusions. This study evaluated the effects of four commonly used pressor agents. METHODS: Twenty four patients (25 data sets) undergoing head and neck cancer resection and free flap reconstruction were recruited. Epinephrine, norepinephrine, dopexamine, and dobutamine were infused in a random order at four infusion rates, after surgery, with free flap and control area (deltoid region) laser Doppler skin blood flow monitoring. Frequency analysis of the Doppler waveform was performed utilizing the time period immediately before the first drug infusion for each patient as baseline. RESULTS: At baseline there was less power at the 0.002-0.6 Hz frequency in the flap compared with control tissue consistent with surgical denervation. At maximum epinephrine infusion rates, the control of blood flow moved toward (i.e., proportion of power increased in) the lower frequencies, as smooth muscle mediated (myogenic) control began to dominate blood flow, an effect most marked with norepinephrine. Dobutamine and dopexamine had little effect on control of blood flow. CONCLUSIONS: Denervation of free flap tissue is demonstrable using spectral analysis of laser Doppler blood flow signals. With norepinephrine the control of blood flow shifts toward low frequency vasomotion where blood flow depends mostly on average blood pressure, making it potentially the most suitable agent following free tissue transfer.

Non-contact physiological monitoring of post-operative patients in the intensive care unit.

Prolonged non-contact camera-based monitoring in critically ill patients presents unique challenges, but may facilitate safe recovery. A study was designed to evaluate the feasibility of introducing a non-contact video camera monitoring system into an acute clinical setting. We assessed the accuracy and robustness of the video camera-derived estimates of the vital signs against the electronically-recorded reference values in both day and night environments. We demonstrated non-contact monitoring of heart rate and respiratory rate for extended periods of time in 15 post-operative patients. Across day and night, heart rate was estimated for up to 53.2% (103.0 h) of the total valid camera data with a mean absolute error (MAE) of 2.5 beats/min in comparison to two reference sensors. We obtained respiratory rate estimates for 63.1% (119.8 h) of the total valid camera data with a MAE of 2.4 breaths/min against the reference value computed from the chest impedance pneumogram. Non-contact estimates detected relevant changes in the vital-sign values between routine clinical observations. Pivotal respiratory events in a post-operative patient could be identified from the analysis of video-derived respiratory information. Continuous vital-sign monitoring supported by non-contact video camera estimates could be used to track early signs of physiological deterioration during post-operative care.

The effects of precision, haematocrit, pH and oxygen tension on point-of-care glucose measurement in critically ill patients: a prospective study.

BACKGROUND: Critical care glycaemic control protocols commonly have treatment adjustment (target) ranges spanning ≤2 mmol/L. These require precise point-of-care glucose measurement, unaffected by other variables, to avoid measurement errors increasing glycaemic variability and hypoglycaemic episodes (both strongly associated with mortality in critically ill patients). METHODS: A prospective 206 intensive care patient study was carried out. Arterial glucose concentrations were measured in duplicate using three point-of-care instruments (MediSense Precision PCχ, HemoCue DM and Radiometer 700), a central laboratory instrument (Siemens ADVIA), and in whole blood and plasma using the Yellow Springs Instruments 2300 instrument. RESULTS: Coefficients of variation for the MediSense, HemoCue, Radiometer and Siemens instruments were 5.1%, 2.5%, 2.1% and 2.3%, respectively. Compared with the Siemens instrument, the bias (95% limits of agreement) for the MediSense, HemoCue and Radiometer instruments were 0.0 (-1.4 to 1.4), 0.0 (-1.2 to 1.1) and -0.2 (-0.9 to 0.6) mmol/L, respectively. The whole blood-plasma glucose concentration difference was significantly affected by the haematocrit. MediSense and HemoCue instrument performances were substantially affected by haematocrit. MediSense instrument performance was also affected by pH and PaO(2). Radiometer instrument performance was not affected by haematocrit, pH or PaO(2). CONCLUSIONS: The MediSense instrument was too imprecise for use in critically ill patients. The haematocrit range seen is too great to allow fixed-factor conversion between whole blood and plasma values, substantially affecting the accuracy of both glucose meters. However, the Radiometer instrument was unaffected by the haematocrit, pH or pO(2), resulting in a performance equivalent to the laboratory method. Instrument performance differences may therefore partially explain the differing results of tight glycaemic control therapy trials.