Spectral tissue sensing to identify intra- and extravascular needle placement - A randomized single-blind controlled trial.

Safe vascular access is a prerequisite for intravenous drug admission. Discrimination between intra- and extravascular needle position is essential for procedure safety. Spectral tissue sensing (STS), based on optical spectroscopy, can provide tissue information directly from the needle tip. The primary objective of the trial was to investigate if STS can reliably discriminate intra-vascular (venous) from non-vascular punctures. In 20 healthy volunteers, a needle with an STS stylet was inserted, and measurements were performed for two intended locations: the first was subcutaneous, while the second location was randomly selected as either subcutaneous or intravenous. The needle position was assessed using ultrasound (US) and aspiration. The operators who collected the data from the spectral device were blinded to the insertion and ultrasonographic visualization procedure and the physician was blinded to the spectral data. Following offline spectral analysis, a prediction of intravascular or subcutaneous needle placement was made and compared with the "true" needle tip position as indicated by US and aspiration. Data for 19 volunteers were included in the analysis. Six out of 8 intended vascular needle placements were defined as intravascular according to US and aspiration. The remaining two intended vascular needle placements were negative for aspiration. For the other 11 final needle locations, the needle was clearly subcutaneous according to US examination and no blood was aspirated. The Mann-Whitney U test yielded a p-value of 0.012 for the between-group comparison. The differences between extra- and intravascular were in the within-group comparison computed with the Wilcoxon signed-rank test was a p-value of 0.022. In conclusion, STS is a promising method for discriminating between intravascular and extravascular needle placement. The information provided by this method may complement current methods for detecting an intravascular needle position.

Maximizing prediction probability PK as an alternative semiparametric approach to estimate the plasma effect-site equilibration rate constant ke0.

BACKGROUND: The k(e)(0) value is the first order rate constant determining the equilibration of drugs between plasma or end-tidal concentration and effect-site (e.g., brain) concentration. Parametric and semiparametric approaches have been used for estimating individual k(e)(0) values and describing the drug-response curve. In this study, we introduce a new semiparametric approach calculating k(e)(0) values for isoflurane, sevoflurane, and desflurane by maximizing the prediction probability P(K). METHODS: Data from 45 patients scheduled for a radical prostatectomy were analyzed. After lumbar epidural catheterization, patients received remifentanil and propofol solely for induction of anesthesia. Thereafter, epidural analgesia was initiated, and isoflurane, sevoflurane, or desflurane (15 patients each) was added to maintain unconsciousness. At least 45 min later, end-tidal concentrations were varied between 0.5 and 2 minimum alveolar anesthetic concentration. We estimated an individual k(e)(0) value for each patient by optimizing the prediction probability P(K) (P(K)-based k(e)(0)) or by minimizing the area within the hysteresis loop (area-based k(e)(0)). Data are mean +/- sd. RESULTS: Both semiparametric approaches led to comparable k(e)(0) values with 0.18 +/- 0.06 min(-1) (P(K) based) and 0.15 +/- 0.04 min(-1) (area based) for isoflurane and 0.17 +/- 0.08 min(-1) (P(K) based) and 0.16 +/- 0.11 min(-1) (area based) for sevoflurane. k(e)(0) values for desflurane (P(K) based: 0.30 +/- 0.17min(-1); area based: 0.32 +/- 0.25 min(-1)) were significantly higher than for isoflurane and sevoflurane. CONCLUSION: Maximizing the prediction probability P(K) for estimating k(e)(0) seems to be a promising method that researchers could use on an exploratory basis.

Comparison between bispectral index and patient state index as measures of the electroencephalographic effects of sevoflurane.

BACKGROUND: The Bispectral Index (BIS) and the Patient State Index (PSI) quantify depth of anesthesia by analyzing the electroencephalogram. The authors examined the response of BIS and PSI to sevoflurane anesthesia. METHODS: In 22 patients, sevoflurane anesthesia was induced by inhalation with a tight-fitting facemask and was maintained via a laryngeal mask. Sevoflurane concentrations were increased until burst suppression occurred and subsequently decreased until BIS recovered to values above 60. This procedure was repeated twice until patients underwent intubation for subsequent surgery. End-tidal sevoflurane concentrations, BIS, and PSI were recorded simultaneously. The performance of PSI and BIS to predict the estimated sevoflurane effect site concentration, as derived from simultaneous pharmacokinetic and pharmacodynamic modeling, was compared by determination coefficients (rho(2)) and prediction probabilities (P(K)). RESULTS: A significant (P < 0.001) correlation between BIS and PSI was found (r(2) = 0.75), and a close sigmoid relation between sevoflurane effect site concentration and both BIS (rho(2) = 0.84 +/- 0.09) and PSI (rho(2) = 0.85 +/- 0.15) was observed. The maximum sevoflurane electroencephalographic effect resulted in PSI values (1.3 +/- 4.3) that were significantly (P = 0.019) lower than BIS values (7.9 +/- 12.1), and the effect site efflux constant k(e0) was significantly smaller (P = 0.001) for PSI (0.13 +/- 0.08 min(-1)) than for BIS (0.24 +/- 0.15 min(-1)). The probability of BIS (P(K) = 0.80 +/- 0.11) to predict sevoflurane effect site concentration did not differ (P = 0.76) from that of PSI (P(K) = 0.79 +/- 0.09). CONCLUSIONS: The BIS reacted faster to changes in sevoflurane concentrations, whereas the PSI made better use of the predefined index range. However, despite major differences in their algorithms and minor differences in their dose-response relations, both PSI and BIS predicted depth of sevoflurane anesthesia equally well.

Mixed-effects modeling of the intrinsic ventilatory depressant potency of propofol in the non-steady state.

BACKGROUND: Despite the ubiquitous use of propofol for anesthesia and conscious sedation and numerous publications about its effect, a pharmacodynamic model for propofol-induced ventilatory depression in the non-steady state has not been described. To investigate propofol-induced ventilatory depression in the clinically important range (at and below the metabolic hyperbola while carbon dioxide is accumulating because of drug-induced ventilatory depression), the authors applied indirect effect modeling to Paco2 data at a fraction of inspired carbon dioxide of 0 during and after administration of propofol. METHODS: Ten volunteers underwent determination of their carbon dioxide responsiveness by a rebreathing design. The parameters of a power function were fitted to the end-expiratory carbon dioxide and minute ventilation data. The volunteers then received propofol in a stepwise ascending pattern with use of a target-controlled infusion pump until significant ventilatory depression occurred (end-tidal pressure of carbon dioxide > 65 mmHg and/or imminent apnea). Thereafter, the concentration was reduced to 1 microg/ml. Propofol pharmacokinetics and the Paco2 were determined from frequent arterial blood samples. An indirect response model with Bayesian estimates of the pharmacokinetics and carbon dioxide responsiveness in the absence of drug was used to describe the Paco2 time course. Because propofol reduces oxygen requirements and carbon dioxide production, a correction factor for propofol-induced decreasing of carbon dioxide production was included. RESULTS: The following pharmacodynamic parameters were found to describe the time course of hypercapnia after administration of propofol (population mean and interindividual variability expressed as coefficients of variation): F (gain of the carbon dioxide response), 4.37 +/- 36.7%; ke0, CO2, 0.95 min-1 +/- 59.8%; baseline Paco2, 40.9 mmHg +/- 12.8%; baseline minute ventilation, 6.45 l/min +/- 36.3%; kel, CO2, 0.11 min-1 +/- 34.2%; C50,propofol, 1.33 microg/ml +/- 49.6%; gamma, 1.68 +/- 21.3%. CONCLUSION: Propofol at common clinical concentrations is a potent ventilatory depressant. An indirect response model accurately described the magnitude and time course of propofol-induced ventilatory depression. The indirect response model can be used to optimize propofol administration to reduce the risk of significant ventilatory depression.

A model of the ventilatory depressant potency of remifentanil in the non-steady state.

BACKGROUND: The C50 of remifentanil for ventilatory depression has been previously determined using inspired carbon dioxide and stimulated ventilation, which may not describe the clinically relevant situation in which ventilatory depression occurs in the absence of inspired carbon dioxide. The authors applied indirect effect modeling to non-steady state Paco2 data in the absence of inspired carbon dioxide during and after administration of remifentanil. METHODS: Ten volunteers underwent determination of carbon dioxide responsiveness using a rebreathing design, and a model was fit to the end-expiratory carbon dioxide and minute ventilation. Afterwards, the volunteers received remifentanil in a stepwise ascending pattern using a computer-controlled infusion pump until significant ventilatory depression occurred (end-tidal carbon dioxide [Peco2] > 65 mmHg and/or imminent apnea). Thereafter, the concentration was reduced to 1 ng/ml. Remifentanil pharmacokinetics and Paco2 were determined from frequent arterial blood samples. An indirect response model was used to describe the Paco2 time course as a function of remifentanil concentration. RESULTS: The time course of hypercarbia after administration of remifentanil was well described by the following pharmacodynamic parameters: F (gain of the carbon dioxide response), 4.30; ke0 carbon dioxide, 0.92 min-1; baseline Paco2, 42.4 mmHg; baseline minute ventilation, 7.06 l/min; kel,CO2, 0.08 min-1; C50 for ventilatory depression, 0.92 ng/ml; Hill coefficient, 1.25. CONCLUSION: Remifentanil is a potent ventilatory depressant. Simulations demonstrated that remifentanil concentrations well tolerated in the steady state will cause a clinically significant hypoventilation following bolus administration, confirming the acute risk of bolus administration of fast-acting opioids in spontaneously breathing patients.

Non-steady state analysis of the pharmacokinetic interaction between propofol and remifentanil.

BACKGROUND: The pharmacokinetics of both propofol and remifentanil have been described extensively. Although they are commonly administered together for clinical anesthesia, their pharmacokinetic interaction has not been investigated so far. The purpose of the current investigation was to elucidate the nature and extent of pharmacokinetic interactions between propofol and remifentanil. METHODS: Twenty healthy volunteers aged 20-43 yr initially received either propofol or remifentanil alone in a stepwise incremental and decremental fashion a target controlled infusion. Thereafter, the respective second drug was infused to a fixed target concentration in the clinical range (0-4 microg/ml and 0-4 ng/ml for propofol and remifentanil, respectively) and the stepwise incremental pattern repeated. Frequent blood samples were drawn for up to 6 h for propofol and 40 min for remifentanil after the end of administration and assayed for the respective drug concentrations with gas chromatography-mass spectrometry. The time courses of the measured concentrations were fitted to standard compartmental models. Calculations were performed with NONMEM. After having established the individual population models for both drugs and an exploratory analysis for hypothesis generation, pharmacokinetic interaction was identified by including an interaction term into the population model and comparing the value of the objective function in the presence and absence of the respective term. RESULTS: The concentration-time courses of propofol and remifentanil were described best by a three- and two-compartment model, respectively. In the concentration range examined, remifentanil does not alter propofol pharmacokinetics. Coadministration of propofol decreases the central volume of distribution and distributional clearance of remifentanil by 41% and elimination clearance by 15%. This effect was not concentration-dependent in the examined concentration range of propofol. CONCLUSIONS: Coadministration of propofol decreases the bolus dose of remifentanil needed to achieve a certain plasma-effect compartment concentration but does not alter the respective maintenance infusion rates and recovery times to a clinically significant degree.