Journal of clinical monitoring最新文献

Objective: The passage of volatile anesthetic agents through accidentally dried CO2 absorbents in anesthesia circuits can result in the chemical breakdown of anesthetics with production of greater than 10000 ppm carbon monoxide (CO). This study was designed to evaluate a portable CO monitor in the presence of volatile anesthetic agents.

Methods: Two portable CO monitors employing electrochemical sensors were tested to determine the effects of anesthetic agents, gas sample flow rates, and high CO concentrations on their electrochemical sensor. The portable CO monitors were exposed to gas mixtures of 0 to 500 ppm CO in either 70% nitrous oxide, 1 MAC concentrations of contemporary volatile anesthetics, or reacted isoflurane or desflurane (containing CO and CHF3) in oxygen. The CO measurements from the electrochemical sensors were compared to simultaneously obtained samples measured by gas chromatography (GC). Data were analyzed by linear regression.

Results: Overall correlation between the portable CO monitors and the GC resulted in an r2 value >0.98 for all anesthetic agents. Sequestered samples produced an exponential decay of measured CO with time, whereas stable measurements were maintained during continuous flow across the sensor. Increasing flow rates resulted in higher CO readings. Exposing the CO sensor to 3000 and 19000 ppm CO resulted in maximum reported concentrations of approximately 1250 ppm, with a prolonged recovery.

Conclusions: Decrease in measured concentration of the sequestered samples suggests destruction of the sample by the sensor, whereas a diffusion limitation is suggested by the dependency of measured value upon flow. Any value over 500 ppm must be assumed to represent dangerous concentrations of CO because of the non-linear response of these monitors at very high CO concentrations. These portable electrochemical CO monitors are adequate to measure CO concentrations up to 500 ppm in the presence of typical clinical concentrations of anesthetics.

Problem: Physiologic data measured in the clinical environment is frequently corrupted causing erroneous data to be displayed, periods of missing information or nuisance alarms to be triggered. To date, the possibility of combining sensors with similar information to improve the quality of the extracted data has not been developed. The objective of this work is to develop a method for combining heart rate measurements from multiple sensors to obtain: (i) an estimate of heart rate that is free of artifact; (ii) a confidence value associated with every heart rate estimate which indicates the likelihood that an estimate is correct; (iii) a more accurate estimate of heart rate than is available from any individual sensor.

Solution: The essence of the method is to discriminate between good and bad sensor measurements and combine only the good readings to derive an optimal heart rate estimate. Past estimates of heart rate are used to derive a predicted value for the current heart rate that is also fused along with the sensor measurements. Consensus between sensor measurements, the predicted value and physiologic credibility of the readings are used to distinguish between good and bad readings. Three sensor measurements and the predicted value are evaluated yielding 16 possible hypotheses for the current state of the available data. A Kalman filter uses the most likely hypothesis to derive the fused estimate. Statistical measures of the sensor error and rate of change of heart rate are adaptively estimated when data are sufficiently reliable and used to enhance the hypothesis selection process.

Discussion: The method of sensor fusion presented has been documented to perform well using clinical data. Limitations of the technique and the assumptions employed are discussed as well as directions for future research.

Objective: To design and implement the logistics of accommodating a large number of participants in individual, hands-on sessions on a full-scale patient simulator during a major scientific meeting or continuing medical education course.

Methods: We used our method during the 11th World Congress of Anaesthesiologists in Sydney, Australia to facilitate studying the impact of pulse oximetry and capnography on the time taken by anesthesiologists to correctly identify critical incidents on a full-scale patient simulator. Each study participant spent 15 minutes in 4 sections of the study area: the anesthesia and monitoring equipment briefing room, the simulator briefing room, the simulation room and the debriefing room.

Results: There were 113 participants during five days (15 during instructor training and 25, 23, 24 and 26 on subsequent exhibit days). We were oversubscribed daily. However, there were 9 no-shows during the 4 days of the study, which generated a participant absence rate of 9.2%. The average number of participants over the 4 days of the study was 24.5 per day compared to our capacity of 27 per day. The feedback we obtained from the participants about the simulation experience and the format of the exercise was positive and enthusiastic.

Conclusions: We have developed a practical and viable method that can be adapted for use at scientific meetings and courses, which improves accessibility of individual, hands-on sessions on full-scale patient simulators to a larger audience than previously attainable. Our method is applicable for continuing medical education courses as well as research purposes in the form of prospective studies during scientific meetings and courses.

Objective: To propose and verify a technique by which blood resistivity can be measured continuously and instantaneously with a conductance catheter used to measure ventricular volume by intracardiac impedance volumetry.

Methods: Intracardiac impedance volumetry involves the measurement of ventricular blood volume using a multi-electrode conductance catheter. Ventricular volume measurement with the conductance catheter requires the value of blood resistivity. Previously, blood resistivity has been determined by drawing a sample of blood and measuring resistivity in a separate measuring cell. A new technique is proposed that allows the resistivity of blood to be measured with the conductance catheter itself. Two adjacent electrodes of the catheter are chosen to establish a localized electric field. With a localized field, the resistance measured between the adjacent electrodes bears a constant ratio (resistivity ratio) to the resistivity of blood. Finite element cylindrical models with exciting electrodes were created to determine the resistivity ratio. Blood resistivity was determined by dividing the resistance found due to the localized electric field by the resistivity ratio. The proposed scheme was verified in cylindrical physical models and in in vivo canine hearts.

Results: Finite element simulations showed the resistivity ratio to be 1.30 and 1.43 for two custom-made catheters (Ohmeda Inc. and Biosensors Inc., respectively). The resistivity ratio remained constant as long as the cylindrical volume of blood around the adjacent electrodes had a radius larger than the electrode spacing. In addition, this ratio was found to be a function of electrode width. The new technique allowed us to measure saline resistivity with an error, -0.99+/-0.25% in a physical model, and blood resistivity with an error, -0.625+/-2.75% in an in vivo canine model.

Conclusion: The new in vivo technique can be used to measure and track blood resistivity instantaneously and continuously without drawing blood samples.

Objective: The objective of this study is to determine the accuracy and precision of chemiluminescence and electrochemical nitric oxide (NO) measurements and accuracy of NO dosage with electronic mass flow controllers (MFC) versus rotameters during NO inhalational therapy.

Methods: NO flow was delivered to a high frequency oscillator and mixed with ventilator flow. NO and NO2 concentrations were measured simultaneously with a standard chemiluminescence analyzer and a modified electrochemical analyzer. Dosage accuracy was assessed with gas flows adjusted with either MFC's or rotameters. Accuracy of both analyzers was validated with both NO and ventilator flow regulated with a MFC.

Results: In dry air, without pulsatile pressure, MFC controlled NO and ventilator flow resulted in an accuracy expressed as the ratio of calculated concentration to measured concentration (RCM) of 0.995 (CI: 0.983-0.988) when measured with chemiluminescence. When the ventilator rotameter was used instead of a MFC, RCM was 0.856 (CI: 0.835-0.877). With a rotameter for both NO and ventilator flow, RCM increased to 1.175 (CI: 0.793-1.740) with an increase of confidence interval limits. Chemiluminescence was sensitive to humidification of the ventilatory gases (p < 0.05), slightly sensitive to the addition of oxygen and to pulsatile pressure (not significant). RCM obtained with the modified electrochemical analyzer was in close agreement with chemiluminescence RCM, although 95% CI were wider with electrochemical analysis.

Conclusions: During high frequency oscillatory ventilation (HFOV), standard rotameter flow control of both NO and ventilator flow results in unpredictable NO concentrations that would be clinically unacceptable. When one MFC was used for NO flow control, with ventilator flow controlled with a rotameter, this resulted in moderate dosage accuracy. To achieve a still higher accuracy, MFC flow control for both NO and ventilator flow is indicated. During HFOV, standard chemiluminescence analyzers cannot be considered to be the gold standard for determination of the NO concentration delivered. Measurement of NO concentration may not be mandatory for determination of inhaled NO dose during HFOV, but may be used to monitor for unsafe or unwanted events.

Objective: To determine if Robust Sensor Fusion (RSF), a method designed to fuse data from multiple sensors with redundant heart rate information can be used to improve the quality of heart rate data. To determine if the improved estimate of heart rate can reduce the number of false and missed heart rate alarms.

Methods: A total of 85 monitoring periods were investigated, 12 from the operating room, 60 from adult ICU and 13 from pediatric ICU. The operating room periods began with induction of anesthesia and ended at the completion of the anesthetic. For the ICU data, four hour blocks of time were studied. For each monitoring period, HR values were recorded at 5 second intervals or less from the ECG, SpO2 and IAC using a SpaceLabs Medical Gateway connected to a SpaceLabs Medical PC2. Fused estimates of HR were derived for every time point using RSF and all results accepted regardless of confidence value. Data were annotated manually to identify the "reference" HR (that HR value most likely to be correct) at all time points. All HR values from the sensors and the fused estimate that were different from the reference HR by more than +/- 5 beats/min were considered inaccurate. For each monitoring period, the total time per hour that data were either inaccurate or unavailable was calculated for each sensor as well as the fused estimates. The total time of false and missed HR alarms was found for all sensors and the fused estimate by comparing the data to thresholds for both high and low HR alarms at 150 bpm, 130 bpm, 110 bpm and 50 bpm, 40 bpm, 30 bpm respectively.

Results: The fused estimate of HR was consistently as good or better than the estimate available from any individual sensor. The fused estimates also consistently reduced the incidence of false alarms compared with individual sensors without an unacceptable incidence of missed alarms.

Discussion: Redundancy in sensor measurements can be used to improve HR estimation in the clinical setting. Methods like RSF which improve the quality of monitored data and reduce nuisance alarms will enhance the value of patient monitors to clinicians.

Interference in the electrocardiogram (ECG) signal in an operating room environment is common. Interference from a variety of sources, including electrosurgical units and blood warmers, have been reported. We report the occurrence of an ECG signal that was cleared of interference whenever the electrosurgical unit (ESU) was activated.

Objective: To study whether an electrosurgery device interferes with the operation of a low-power spread-spectrum wireless network adapter.

Methods: Nonrandomized, unblinded trials with controls, conducted in the corridor of our institution's operating suite using two portable computers equipped with RoamAbout omnidirectional 250 mW spread-spectrum 928 MHz wireless network adapters. To simulate high power electrosurgery interference, a 100-watt continuous electrocoagulation arc was maintained five feet from the receiving adapter, while device reported signal to noise values were measured at 150 feet and 400 feet distance between the wireless-networked computers. At 150 feet range, and with continuous 100-watt electrocoagulation arc five feet from one computer, error-corrected local area net throughput was measured by sending and receiving a large file multiple times.

Results: The reported signal to noise (N = 50) decreased with electrocoagulation from 36.42+/-3.47 (control) to 31.85+/-3.64 (electrocoagulation) (p < 0.001) at 400 feet inter-adapter distance, and from 64.53+/-1.43 (control) to 60.12+/-3.77 (electrocoagulation) (p < 0.001) at 150 feet inter-adapter distance. There was no statistically significant change in network throughput (average 93 kbyte/second) at 150 feet inter-adapter distance, either transmitting or receiving during continuous 100 Watt electrocoagulation arc.

Conclusions: The manufacturer indicates "acceptable" performance will be obtained with signal to noise values as low as 20. In view of this, while electrocoagulation affects this spread spectrum network adapter, the effects are small even at 400 feet. At a distance of 150 feet, no discernible effect on network communications was found, suggesting that if other obstructions are minimal, within a wide range on one floor of an operating suite, network communications may be maintained using the technology of this wireless spread spectrum network adapter. The impact of such adapters on cardiac pacemakers should be studied. Wireless spread spectrum network adapters are an attractive technology for mobile computer communications in the operating room.

Objective: Evaluate the accuracy of this bedside method to determine hemoglobin (Hb) concentration in general surgery over a wide range of Hb values and to determine potential sources of error.

Methods: Accuracy of Hb measurement using HemoCue (AB Leo Diagnostics, Helsinborg, Sweden) was assessed in 140 surgical blood samples using 7 HemoCue devices in comparison with a CO-Oximeter (IL 482, Instrumentation Laboratory, Lexington, MA). To analyze potential sources of error, packed red cells and fresh frozen plasma were reconstituted to randomized Hb levels of 2-18 g/dL.

Results: In the surgical blood samples, the Hb concentration determined by the CO-Oximeter (HbCOOX) ranged from 5.1 to 16.7 g/dL and the Hb concentration measured by HemoCue (HbHC) from 4.7 to 16.0 g/dL. Bias (HbCOOX - HbHC) between HbCOOX and HbHC was 0.6+/-0.6 g/dL (mean +/- SD) or 5.4+/-5.0% (p < 0.001). Also in the reconstituted blood, the bias between HbCOOX and HbHC was significant (0.2+/-0.3 g/dL or 2.1+/-3.2%; p < 0.001). The microcuvette explained 68% of the variability between HbCOOX and HbHC. HemoCue thus underestimates the Hb concentration by 2-5% and exhibits a 8-10 times higher variability with only 86.4% of HbHC being within +/- 10% of HbCOOX. CONCLUSION. Although the mean bias between HbCOOX and HbHC was relatively low, Hb measurement by HemoCue exhibited a significant variability. Loading multiple microcuvettes and averaging the results may increase the accuracy of Hb measurement by HemoCue.

Objective: To determine the effects of sensor location and suction fixation duration on measurements of intrapartum fetal oxygen saturation (SpO2) with a new reflectance pulse oximetry system.

Design: Fetal SpO2 values (n = 18) were determined in the first stage of labor before and after moving the sensor to another part of the fetal head.

Results: Mean fetal SpO2 values did not differ with sensor location (95% CI: -3.59 to 1.48). The duration of measurement period 1, before moving the sensor, was 104 +/- 44 (range 30-240) min. No time-dependent changes in SpO2 values were seen (r = 0.17).

Conclusion: Suction is an effective and noninvasive method of securing the reflectance pulse oximetry sensor to the fetal head in the first stage of labor and does not interfere with reproducible SpO2 values over several hours.