Anesthesiology
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Approximate entropy, a measure of signal complexity and regularity, quantifies electroencephalogram changes during anesthesia. With increasing doses of anesthetics, burst-suppression patterns occur. Because of the high-frequency bursts, spectrally based parameters such as median electroencephalogram frequency and spectral edge frequency 95 do not decrease, incorrectly suggesting lightening of anesthesia. The authors investigated whether the approximate entropy algorithm correctly classifies the occurrence of burst suppression as deepening of anesthesia. ⋯ Electroencephalogram approximate entropy, but not electroencephalogram median frequency or spectral edge frequency 95 without burst compensation, correctly classifies the occurrence of burst-suppression pattern as increasing anesthetic drug effect.
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Comparative Study
Effects of isoflurane, sevoflurane, and halothane on myofilament Ca2+ sensitivity and sarcoplasmic reticulum Ca2+ release in rat ventricular myocytes.
The aim of this study was to describe and compare the effects of isoflurane, sevoflurane, and halothane at selected concentrations (i.e., concentrations that led to equivalent depression of the electrically evoked Ca2+ transient) on myofilament Ca2+ sensitivity, sarcoplasmic reticulum (SR) Ca2+ content, and the fraction of SR Ca2+ released during electrical stimulation (fractional release) in rat ventricular myocytes. ⋯ Depressed myofilament Ca2+ sensitivity contributes to the negative inotropic effects of isoflurane and halothane but not sevoflurane. The decrease in the Ca2+ transient is either responsible for or contributory to the negative inotropic effects of all three anesthetics and is either primarily the result of a decrease in fractional release (isoflurane and sevoflurane) or primarily the result of a decrease in SR Ca2+ content (halothane).
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S(-)-bupivacaine reportedly exhibits lower cardiotoxicity but similar local anesthetic potency compared with R(+)-bupivacaine. The bupivacaine binding site in human heart (hH1) Na+ channels has not been studied to date. The authors investigated the interaction of bupivacaine enantiomers with hH1 Na+ channels, assessed the contribution of putatively relevant residues to binding, and compared the intrinsic affinities to another isoform, the rat skeletal muscle (mu1) Na+ channel. ⋯ Differences in bupivacaine stereoselectivity and intrinsic affinity between hH1 and mu1 Na+ channels are small and most likely of minor clinical relevance. Amino acid residues in positions hH1-F1760, hH1-N1765, and hH1-N406 may contribute to binding of bupivacaine enantiomers in hH1 Na+ channels, whereas the role of hH1-Y1767 remains unclear.
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Comparative Study
Effects of gaseous anesthetics nitrous oxide and xenon on ligand-gated ion channels. Comparison with isoflurane and ethanol.
Ligand-gated ion channels are considered to be potential general anesthetic targets. Although most general anesthetics potentiate the function of gamma-aminobutyric acid receptor type A (GABAA), the gaseous anesthetics nitrous oxide and xenon are reported to have little effect on GABAA receptors but inhibit N-methyl-d-aspartate (NMDA) receptors. To define the spectrum of effects of nitrous oxide and xenon on receptors thought to be important in anesthesia, the authors tested these anesthetics on a variety of recombinant brain receptors. ⋯ Nitrous oxide and xenon displayed a similar spectrum of receptor actions, but this spectrum is distinct from that of isoflurane or ethanol. These results suggest that NMDA receptors and nACh receptors composed of beta2 subunits are likely targets for nitrous oxide and xenon.
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Previously, mathematical theory was developed for determining when a patient should be ready for surgery on the day of surgery. To apply this theory, a method is needed to predict the earliest start time of the case. ⋯ The earliest start time of a case can be estimated using the 0.05 prediction bound for the duration of the preceding case. The authors show 0.05 prediction bounds can be estimated accurately assuming that case durations follow log-normal distributions.