International journal of clinical monitoring and computing最新文献

In this study we have investigated the application of an Artificial Neural Net classifier to the diagnosis of vascular disease using Doppler ultrasound blood-velocity/time waveforms. A multi-layer perceptron network was trained with waveforms from control subjects and from patients with arterial disease. The diseased cases were confirmed by angiography and allocated to three groups according to the location of the stenosis: proximal or distal to the site of measurement or multi-segmental. We compared network classification results with a Bayesian classifier following a Principal Component Analysis of the waveforms. Versions of both classifiers were trained to discriminate two classes (normal v. abnormal) and four classes. In both cases the neural networks gave superior discrimination to the Bayesian classifier. While the four-class network was unable to provide useful discrimination among the stenosis sites, discrimination between abnormal classes was obtained which is comparable to that achieved by a human expert observer.

Alarms in the operating room remain a major source of annoyance and confusion. A previous study by Kestin et al. utilized a specific combination of distinct, separate monitors in 50 pediatric patients. He reported a mean of 10 alarms per case with a mean frequency of one alarm every 4.5 minutes. The alarms were classified as spurious (75%), change outside the alarm limits (22%), or patient risk (3%). We performed a similar study with 50 adult patients under general anesthesia with default alarm settings on an integrated monitor, (Cardiocap, Datex, Helsinki). In our study, the number of alarms averaged 3 per case with a mean frequency of one every 34 minutes. Spurious alarms (those caused by electrocautery, accidental patient movement, or other non-physiological reasons) represented only 24% of all alarms. Those alarms sounding that were outside the limits occurred at a rate of 53%, and those that were considered patient risks occurred at a rate of 23%. Of the alarms, 67% occurred during the beginning and end of anesthesia. The end-tidal carbon dioxide accounted for 42% of the alarms, mostly during intubation and extubation. Suggestions are made for further improvement in alarm systems.

Progress in quantifying states of cerebral function and in the further development of automated EEG processing demands the application of suitable methods for the reduction of neurophysiological multi-channel data as well as their automatic classification. The method used here for reducing multi-channel data was to gain distributions of parametric descriptors from EEG data from computer-aided topographic electroencephalometry (CATEEM), for example the relative and absolute band power in the frequency bands delta, theta, alpha 1, alpha 2, beta 1, beta 2, total power, median and mode frequency, and other parameters. These values were subjected to cluster analysis. The classification of EEG parameters was carried out by means of discrimination analysis and neural networks. The practicability of both procedures was demonstrated in the reduction and classification of EEG data in the context of a normed study involving 104 healthy adults. These data have been used as the basis for a new evaluation study of 60 additional intraoperative EEG recordings obtained with CATEEM. In that newly started study, the effects of sedative and anaesthetic drugs on EEG behavior and psychophysiologic behavior remain to be investigated.

In 1986, in Buccheri La Ferla Hospital, Palermo, an anaesthesia information management project was started. Its aim was to develop a computerized anaesthesia workstation. Today, the system is in daily clinical use and has reached most of its original goals: Automatic collection of physiological signals and patient monitor trends is possible by means of analog-digital conversion or by using serial data transfer. A centralized display is included in the system to allow easy control of the progress of the anaesthetic procedures in the hospital. Available in the workstation, there is an on-line help function to assist pharmacological calculations and administration of anaesthesia drugs. Mail messages can be sent to different anaesthesia workstations and data can be shared between them. Information collected during preoperative visits is automatically transferred from a portable personal computer to the system. There is a nine-year patient data-base with both preoperative and perioperative anaesthesia information which can be accessed from each of the workstations. Today, the system is in daily routine use and comprises eight anaesthesia workstations and two portable personal computers used for preoperative visits. The operation schedule with anaesthetists' notes is printed both for surgical wards and for O.R., using information stored from preoperative visits to the system. For automated data collection a trend resolution of one minute has been used. The postoperative orders are printed from the system in the recovery room and given to the wards with the patient. The feedback from the seventeen anaesthetists and twenty-four nurses who use the system routinely is positive. Today, 16,000 patient records are available in the database. This number increases by 3,300 every year. With increasing computer utilization in patient treatment there have been no legal or administrative controversies. Based on nine years' experience, it is clear that the use of computers in anaesthesia practice improves quality of patient care.

The performance of impedance cardiography (TEBco), using the BoMed NCCOM3-R7S, and thermodilution (TDco) were compared in eight patients during major abdominal surgery. An opioid, volatile and relaxant anaesthetic technique was employed. This was supplemented with an epidural in five cases. Sets of three cardiac output readings, for both methods, were made at 10-20 min intervals throughout surgery. Data were compared using the Bland and Altman method, regression analysis and a nested model to measure variance components at different stages of surgery. Data from 157 sets of readings are presented. Agreement between the two devices was poor, with a ratio of TDco/TEBco of 115% and limits of agreement of 51-193%. The regression line was TDco = (0.98) x TEBco-0.95 with r = 0.60. A more detailed analysis, using nested data, showed good repeatability with coefficients of variation of 5.4% for TDco and 4.8% for TEBco. During surgery shifts in the bias between the two devices occurred, which were related to changes in surgical conditions. Between shifts both devices showed good repeatability over time. Variance components were 0.27 within nested data and 0.082 between bias shifts, with a significantly greater overall component of 1.2 (ANOVA; P = 0.0001). Shifts could be explained by deficiencies in the algorithm used to calculate TEBco. Current TEBco technology is too inaccurate for intra-operative use. However, under stable operating conditions TEBco and TDco showed good repeatability.

In the clinic, a major problem in train of four (TOF) muscle relaxation monitoring is incorrect placement of stimulation and recording electrodes, frequently resulting in incorrect estimates of the patient's degree of relaxation or in abandonment of relaxation monitoring. The aim of this study was to arrive at recommendations that describe how to find optimal positions for the electrodes, where 'optimal' is taken in the sense that small deviations from these positions introduce no or only a small decline in the accuracy of the computed degree of muscle relaxation. This study, which employed the Relaxograph as the stimulation and measuring device, established that incorrect positioning is a real problem that frequently occurs; that the correctness of positioning is not guaranteed when the calibration of the Relaxograph succeeds; that the inadequacy of the electrode position is sometimes discovered for the first time when relaxation deepens; that positioning errors can be discovered by analysing the shape of the evoked compound action potential (ECAP), not only upon calibration but also when relaxation deepens; that a set of optimal electrode positions can be found; and that recommendations of how to find these optimal positions could help clinicians to place the electrodes in such a way, that reliable relaxation monitoring was possible in 100% of the investigated cases. In a first test in 30 adult patients, we surveyed how clinicians routinely positioned electrodes and found that in 14 of the 30 cases positioning was unsuccessful. In a second test in 10 patients, we tested a variety of electrode positions in order to discover 'optimal' stimulation, recording and ground electrode sites. In a third test in 10 patients, electrodes were positioned at these 'optimal' sites; stimulation and recording at these sites was successful in all 10 cases.

We have been using computer driven injections in surgery for many years to the benefit of more than thousand patients. Along these years we accumulated extensive experience in remote controlled infusion pumps. Today we have solved many communication problems. Despite the attention and care we brought in our software developments we still meet with some problems.