The true incidence of seizures caused by general anesthetic drugs is unknown. Abnormal movements are common during induction of anesthesia, but they may not be indicative of true seizures. Conversely, epileptiform electrocortical activity is commonly induced by enflurane, etomidate, sevoflurane and, to a lesser extent, propofol, but it rarely progresses to generalized tonic-clonic seizures. Even "nonconvulsant" anesthetic drugs occasionally cause seizures in subjects with preexisting epilepsy. These seizures most commonly occur during induction or emergence from anesthesia, when the anesthetic drug concentration is relatively low. There is no unifying neural mechanism of anesthetic drug-related seizurogenesis. However, there is a growing body of experimental work suggesting that seizures are not caused simply by "too much excitation," but rather by excitation applied to a mass of neurons which are primed to react to the excitation by going into an oscillatory seizure state. Increased gamma-amino-butyric acid (GABA)ergic inhibition can sensitize the cortex so that only a small amount of excitation is required to cause seizures. This has been postulated to occur 1) at the network level by increasing the propensity for reverberation (e.g., by prolongation of the "inhibitory lag"), or 2) via different effects on subpopulations of interneurons ("inhibiting-the-inhibitors") or 3) at the synaptic level by changing the chloride reversal potential ("excitatory GABA"). On the basis of applied neuropharmacology, prevention of anesthetic-drug related seizures would include 1) avoiding sevoflurane and etomidate, 2) considering prophylaxis with adjunctive benzodiazepines (alpha-subunit GABA(A) agonists), or drugs that impair calcium entry into neurons, and 3) using electroencephalogram monitoring to detect early signs of cortical instability and epileptiform activity. Seizures may falsely elevate electroencephalogram indices of depth of anesthesia.

Quantitative electroencephalogram (qEEG) monitors are often used to estimate depth of anesthesia and intraoperative recall during general anesthesia. As with any monitor, the processed numerical output is often misleading and has to be interpreted within a clinical context. For the safe clinical use of these monitors, a clear mental picture of the expected raw electroencephalogram (EEG) patterns, as well as a knowledge of the common EEG artifacts, is absolutely necessary. This has provided the motivation to write this tutorial. We describe, and give examples of, the typical EEG features of adequate general anesthesia, effects of noxious stimulation, and adjunctive drugs. Artifacts are commonly encountered and may be classified as arising from outside the head, from the head but outside the brain (commonly frontal electromyogram), or from within the brain (atypical or pathologic). We include real examples of clinical problem-solving processes. In particular, it is important to realize that an artifactually high qEEG index is relatively common and may result in dangerous anesthetic drug overdose. The anesthesiologist must be certain that the qEEG number is consistent with the apparent state of the patient, the doses of various anesthetic drugs, and the degree of surgical stimulation, and that the qEEG number is consistent with the appearance of the raw EEG signal. Any discrepancy must be a stimulus for the immediate critical examination of the patient's state using all the available information rather than reactive therapy to "treat" a number.

Spectral entropy is a new electroencephalogram (EEG)-derived parameter that may be used to model the pharmacokinetic-pharmacodynamic (PKPD) effects of general anesthetics. In the present study we sought to derive a PKPD model of the relationship between sevoflurane concentration and spectral entropy of the EEG. We collected spectral entropy data during increasing and decreasing sevoflurane anesthesia from 20 patients. The first cycle consisted of induction and lightening phases with no supplemental medications. An effect-site compartment and inhibitory E(max) model described the relation between sevoflurane concentration and spectral entropy. PKPD parameters were derived from the full cycle and separately from the increasing and decreasing stages. The second anesthetic cycle consisted of a redeepening phase only and included airway manipulation and routinely administered adjunctives. PKPD data obtained from the first cycle were used to predict second cycle entropy changes. There was a consistent relationship between effect-site sevoflurane concentration and spectral entropy (median absolute weighted residual = 11.6%). For complete first-cycle response entropy (mean +/- sd): T1/2 K(eo) = 2.4 +/- 1.5 min, gamma = 5.9 +/- 2.3, EC50 = 1.7 +/- 0.3. We found significant differences between gamma values when the sevoflurane concentration was increasing (61.1 +/- 55.2) compared with the decreasing part of the cycle (5.7 +/- 2.8). Above an effect-site concentration of 3%, spectral entropy of the EEG is unresponsive to further increases in sevoflurane concentration. The effect-compartment inhibitory E(max) model accurately describes the relation between sevoflurane concentration and spectral entropy of the EEG. Spectral entropy decreases with increasing sevoflurane concentrations up to 3%. The steepness of the dose-response curve varies between phases of increasing and decreasing anesthetic concentrations.

We could not show that bispectral analysis gave more information than power spectral-based analysis. Most of the changes in the bispectral values result from decreases in the relative high frequency content of the EEG caused by anaesthesia.

In addition to its role in the nucleoid, the histone-like protein (HlpA) of Streptococcus pyogenes is believed to act as a fortuitous virulence factor in delayed sequelae by binding to heparan sulfate-proteoglycans in the extracellular matrix of target organs and acting as a nidus for in situ immune complex formation. To further characterize this protein, the hlpA genes were cloned from S. pyogenes, S. gordonii, S. mutans, and S. sobrinus, using PCR amplification, and sequenced. The encoded HlpA protein of S. pyogenes has 91 amino acids, a predicted molecular mass of 9,647 Da, an isoelectric point of 9.81, and 90% to 95% sequence identity with HlpA of several oral streptococci. The consensus sequence of streptococcal HlpA has 69% identity with the consensus sequence of the histone-like HB protein of Bacillusspecies. Oral viridans group streptococci, growing in chemically defined medium at pH 6.8, released HlpA into the milieu during stationary phase as a result of limited cell lysis. HlpA was not released by these bacteria when grown at pH 6.0 or below. S. pyogenes did not release HlpA during growth in vitro; however, analyses of sera from 155 pharyngitis patients revealed a strong correlation (P < 0.0017) between the production of antibodies to HlpA and antibodies to streptolysin O, indicating that the histone-like protein is released by group A streptococci growing in vivo. Extracellular HlpA formed soluble complexes with lipoteichoic acid in vitro and bound readily to heparan sulfate on HEp-2 cell surfaces. These results support a potential role for HlpA in the pathogenesis of streptococcus-induced tissue inflammation.