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The purpose of the present study was to evaluate the cardiopulmonary resuscitation (CPR) skills of medical students after a 2-h basic life support class (n = 129) and 6 months later (n = 113). Mean +/- SD written test score decreased from 6.4 +/- 0.7 to 6.2 +/- 0.8 (P = 0.03). Mean +/- SD breaths delivered before CPR decreased from 2.9 +/- 0.6 to 2.2 +/- 1.2 (P = 0.0001), ventilation rate increased from 12.2 +/- 1.9 to 14.3 +/- 5.0 breaths/min (P = 0.0001), tidal volume increased from 0.75 +/- 0.2 to 0.8 +/- 0.31 (P = 0.11), minute ventilation from 9.1 +/- 2.6 to 10.8 +/- 3.61 (P = 0.0001), and stomach inflation from 13 +/- 22 to 18 +/- 27% of CPR breaths (P = 0.11). Mean +/- SD chest compression/min decreased from 56 +/- 9 to 54 +/- 12 (P = 0.34), depth of chest compression increased from 41 +/- 6 to 46 +/- 7 mm (P = 0.0001), hands held incorrectly on the thorax increased from 22 +/- 27 to 23 +/- 32% (P = 0.59), and leaning on the chest from 4 +/- 12 to 18 +/- 28% of compressions (P < 0.0001). In summary, ventilation skills were unpredictable; there was only a 5% chance that a given student would achieve the same mouth-to-mouth ventilation performance in both the BLS class and 6 months later. Despite the respiratory mechanics of the CPR manikin which prevented stomach inflation much better than an unconscious patient with an unprotected airway, stomach inflation occurred repeatedly. Teachers of basic life support classes need to consider the respiratory mechanics of the CPR manikin being used to assure clinically realistic and appropriate mouth-to-mouth ventilation skills.

Alterations of the cerebral function caused by anesthetics or due to potentially harmful situations are reflected in the electroencephalogram (EEG). Nevertheless, the EEG has not become a routine monitoring device so far because of the complicated and time-consuming recording procedure. Furthermore, interpretation of the EEG requires special knowledge. In order to facilitate the use of the EEG in the theatre and the intensive care unit a new monitoring device the Narkograph, was developed. To our knowledge, the Narkograph is the first monitor for day-to-day use which performs an automatic classification of drug-induced changes of the EEG in real-time. Staging into different levels of anesthesia is performed according to proposals made by Kugler (1981). By means of several case reports the use of the Narkograph and the benefits of routinely conducted EEG monitoring are presented. As, due to the on-line interpretation of EEG data, information on the current functional status of the brain can easily be obtained, the Narkograph is considered an essential contribution to the patients' security.

The Gaussian properties of human EEGs, which were measured over various stages of general anesthesia, were tested. The basis of the method was to describe the EEG signals by autoregressive models and to test the normality of the regression residuals with the Shapiro-Wilk statistic. The results show that in general the human EEG during anesthesia can be considered as a realization of a Gaussian stochastic process.

In EEG analysis an automatic pattern recognition is of interest. In this paper the usefulness of autoregressive parameters to classify EEG segments recorded during anesthesia is examined. Assuming that the AR parameters are multivariate normally distributed, parametric methods of discriminant analysis can be applied. The results show that AR parameters have high discriminating power and that the lowest error classification rate (smaller than 3%) is obtained by using quadratic discriminant functions. Consequently autoregressive parameters are efficient for classifying EEG segments into general stages of anesthesia.

This study of 215 patients in a surgical intensive care unit (ICU) compares the predictive value of a new disease intensity scoring system called the Hanover Intensive System (HIS) with two previously described systems: APACHE (Acute Physiology and Chronic Health Evaluation), and TISS (Therapeutic Intervention Scoring System). HIS was superior in predicting a lethal outcome at an earlier time than the other methods of scoring. Practical use of this system in clinical decision making was made in timing of reoperation, planning nursing time, and caring for patients following liver transplantation. It is concluded that an accurate disease intensity scoring system such as HIS is of practical benefit in decision making in a surgical ICU.