Consort flowchart of the study.

<p>Consort flowchart of the study.</p

Optical spectra and the corresponding blood similarity parameters.

<p>Spectra acquired from one volunteer for subcutaneous needle (upper panes) and intravascular needle positioning (lower panes), as confirmed by positive blood aspiration. Left: full spectra, indicating the intensity of light received by the stylet (linear arbitrary units, a.u.) as a function of the wavelength (nanometers, nm). Center: an enlarged image of the spectrum that is used to determine the blood similarity parameter B (dashed lines indicate the wavelengths that are used for the calculation). Right: Ln (natural logarithm) of the blood similarity parameter as calculated for these two acquisitions.</p

Picture of the console and needle tip.

<p>Picture of the console (upper part) and needle tip with optical stylet (lower part). The drawing demonstrates the needle, which is connected to the console. The console is just a drawing and not an accurate image of the real one. The picture of the needle tip shows the two fibers and indicates the measuring volume.</p

All blood similarity parameters.

<p>Overview of all blood similarity parameters (B) determined for the different measurement locations in all volunteers. Results are plotted as the average natural logarithm Ln (B) (crosses), with standard deviations determined for the set of spectra acquired at each measurement location in each subject. Volunteer 14 was excluded. Because of the considerable differences in blood similarity parameters (B) between the two groups, more details in the data are visible by plotting Ln(B) instead of B directly.</p

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

Contains fulltext : 79856.pdf (publisher's version ) (Closed access)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

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

Contains fulltext : 175657.pdf (publisher's version ) (Open Access)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