Intravital microscopy evaluation of angiogenesis and its effects on glucose sensor performance.

An optical window model for the rodent dorsum was used to perform chronic and quantitative intravital microscopy and laser Doppler flowmetry of microvascular networks adjacent to functional and non-functional glucose sensors. The one-sided configuration afforded direct, real-time observation of the tissue response to bare (unmodified, smooth surface) sensors and sensors coated with porous poly-L-lactic acid (PLLA). Microvessel length density and red blood cell flux (blood perfusion) within 1 mm of the sensors were measured bi-weekly over 2 weeks. When non-functional sensors were fully implanted beneath the windows, the porous coated sensors had two-fold more vasculature and significantly higher blood perfusion than bare sensors on Day 14. When functional sensors were implanted percutaneously, as in clinical use, no differences in baseline current, neovascularization, or tissue perfusion were observed between bare and porous coated sensors. However, percutaneously implanted bare sensors had two-fold more vascularity than fully implanted bare sensors by Day 14, indicating the other factors, such as micromotion, might be stimulating angiogenesis. Despite increased angiogenesis adjacent to percutaneous sensors, modest sensor current attenuation occurred over 14 days, suggesting that factors other than angiogenesis may play a dominant role in determining sensor function.

An evaluation of remifentanil-sevoflurane response surface models in patients emerging from anesthesia: model improvement using effect-site sevoflurane concentrations.

INTRODUCTION: We previously reported models that characterized the synergistic interaction between remifentanil and sevoflurane in blunting responses to verbal and painful stimuli. This preliminary study evaluated the ability of these models to predict a return of responsiveness during emergence from anesthesia and a response to tibial pressure when patients required analgesics in the recovery room. We hypothesized that model predictions would be consistent with observed responses. We also hypothesized that under non-steady-state conditions, accounting for the lag time between sevoflurane effect-site concentration (Ce) and end-tidal (ET) concentration would improve predictions. METHODS: Twenty patients received a sevoflurane, remifentanil, and fentanyl anesthetic. Two model predictions of responsiveness were recorded at emergence: an ET-based and a Ce-based prediction. Similarly, 2 predictions of a response to noxious stimuli were recorded when patients first required analgesics in the recovery room. Model predictions were compared with observations with graphical and temporal analyses. RESULTS: While patients were anesthetized, model predictions indicated a high likelihood that patients would be unresponsive (> or = 99%). However, after termination of the anesthetic, models exhibited a wide range of predictions at emergence (1%-97%). Although wide, the Ce-based predictions of responsiveness were better distributed over a percentage ranking of observations than the ET-based predictions. For the ET-based model, 45% of the patients awoke within 2 min of the 50% model predicted probability of unresponsiveness and 65% awoke within 4 min. For the Ce-based model, 45% of the patients awoke within 1 min of the 50% model predicted probability of unresponsiveness and 85% awoke within 3.2 min. Predictions of a response to a painful stimulus in the recovery room were similar for the Ce- and ET-based models. DISCUSSION: Results confirmed, in part, our study hypothesis; accounting for the lag time between Ce and ET sevoflurane concentrations improved model predictions of responsiveness but had no effect on predicting a response to a noxious stimulus in the recovery room. These models may be useful in predicting events of clinical interest but large-scale evaluations with numerous patients are needed to better characterize model performance.