BackgroundThe usual method for initial assessment of an acute asthma attack in the emergency room includes the use of peak flow measurement and clinical parameters. Both methods have their own disadvantages such as poor cooperation/effort from patients (peak flow meter) and lack of objective assessment (clinical parameters). We were looking into other methods for the initial asthma assessment, namely the use of capnography. The normal capnogram has an almost square wave pattern comprising phase 1, slope phase 2, plateau phase 3, phase 4 and angle α (between slopes 2 and 3). The changes in asthma include decrease in slope of phase 2, increase in slope 3 and opening of angle α.AimsOur objective was to compare and assess the correlation between the changes in capnographic indices and peak flow measurement in non-intubated acute asthmatic patients attending the emergency room.MethodsWe carried out a prospective study in a university hospital emergency department (ED). One hundred and twenty eight patients with acute asthma were monitored with peak flow measurements and then had a nasal cannula attached for microstream sampling of expired carbon dioxide. The capnographic waveform was recorded onto a PC card for indices analysis. The patients were treated according to departmental protocols. After treatment, when they were adjudged well for discharge, a second set of results was obtained for peak flow measurements and capnographic waveform recording. The pre-treatment and post-treatment results were then compared with paired samples t-test analysis. Simple and canonical correlations were performed to determine correlations between the assessment methods. A p value of below 0.05 was taken to be significant.ResultsPeak flow measurements showed significant improvements post-treatment (p < 0.001). On the capnographic waveform, there was a significant difference in the slope of phase 3 (p < 0.001) and alpha angle (p < 0.001), but not in phase 2 slope (p = 0.35). Correlation studies done between the assessment methods and indices readings did not show strong correlations either between the measurements or the magnitude of change pre-treatment and post-treatment.ConclusionPeak flow measurements and capnographic waveform indices can indicate improvements in airway diameter in acute asthmatics in the ED. Even though the two assessment methods did not correlate statistically, capnographic waveform analysis presents several advantages in that it is effort independent and provides continuous monitoring of normal tidal respiration. They can be proposed for the monitoring of asthmatics in the ED.

The development of a human respiration carbon dioxide (CO) measurement device to evaluate cardiorespiratory status inside and outside a hospital setting has proven to be a challenging area of research over the few last decades. Hence, we report a real-time, user operable CO measurement device using an infrared CO sensor (Arduino Mega2560) and a thin film transistor (TFT, 3.5″), incorporated with low pass (cut-off frequency, 10 Hz) and moving average (span, 8) filters. The proposed device measures features such as partial end-tidal carbon dioxide (EtCO), respiratory rate (RR), inspired carbon dioxide (ICO), and a newly proposed feature-Hjorth activity-that annotates data with the date and time from a real-time clock, and is stored onto a secure digital (SD) card. Further, it was tested on 22 healthy subjects and the performance (reliability, validity and relationship) of each feature was established using (1) an intraclass correlation coefficient (ICC), (2) standard error measurement (SEM), (3) smallest detectable difference (SDD), (4) Bland-Altman plot, and (5) Pearson's correlation (r). The SEM, SDD, and ICC values for inter- and intra-rater reliability were less than 5% and more than 0.8, respectively. Further, the Bland-Altman plot demonstrates that mean differences ± standard deviations for a set limit were 0.30 ± 0.77 mmHg, -0.34 ± 1.41 mmHg and 0.21 ± 0.64 breath per minute (bpm) for CO, EtCO and RR. The findings revealed that the developed device is highly reliable, providing valid measurements for CO, EtCO, ICO and RR, and can be used in clinical settings for cardiorespiratory assessment. This research also demonstrates that EtCO and RR (r, -0.696) are negatively correlated while EtCO and activity (r, 0.846) are positively correlated. Thus, simultaneous measurement of these features may possibly assist physicians in understanding the subject's cardiopulmonary status. In future, the proposed device will be tested with asthmatic patients for use as an early screening tool outside a hospital setting.

e Abstract-Study Objective: To determine if the slope of Phase II and Phase III, and the alpha angle of the expiratory capnographic waveform, as measured via computerrecognizable algorithms, can reflect changes in bronchospasm in acute asthmatic non-intubated patients presenting to the emergency department (ED). Methods: In this prospective study carried out in a university hospital ED, 30 patients with acute asthma were monitored with clinical severity scoring and peak flow measurements, and then had a nasal cannula attached for sidestream sampling of expired carbon dioxide. The capnographic waveform was recorded onto a personal computer card for analysis. The patients were treated according to departmental protocols. After treatment, when they had improved enough for discharge, a second set of results was obtained for capnographic waveform recording. The pre-treatment and posttreatment results were then compared with paired-samples t-test analysis. Results: On the capnographic waveform preand post-treatment, there was a significant difference in the slope of Phase III (p < 0.001) and alpha angle (p < 0.001), but not in the Phase II slope (p ‫؍‬ 0.35). There was significant change in peak flow meter reading, but it was poorly correlated with all the capnographic indices. Conclusion: The study provides some preliminary data showing that capnographic waveform indices can indicate improvement in airway diameter in acute asthmatics in the ED. Capnographic waveform analysis presents several advantages in that it is effort-independent, and provides continuous monitoring of normal tidal respiration. With further refined studies, it may serve as a new method of monitoring nonintubated asthmatics in the ED.

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Emergency departments open 24 hours every day and may receive patients at any time most unexpectedly. Adequate resource planning to meet the various demands in emergency departments is arguably amongst the most critical challenges faced by hospital administrators due to the complexity of the system and diverse patient flows. In this paper, we present a computer simulation model to evaluate resource utilization among personnel and physical resources in a typical emergency department (ED) of a government hospital in Malaysia. The model allows administrators to see patient movement flows as well as how these flows are affected by resource capacity level in the ED. The use of this simulation model helps to evaluate ED operations, provides useful insight for possible areas of improvement, and directs the allocation of specific resources for maximal impact. Three scenarios were tested to find out the impact of patient surge on ED performance measures. Results from the scenarios show that a 30% increase of attendances according to triage zones affects most of the performance measures. In addition, medical assistants are the critical resources with average utilization greater than 70%.

In this paper, a review on methods for detecting the asthmatic conditions by using capnogram is presented. This is included an investigation on capnography as a new approach for monitoring asthma and related researches. Finally, in this preliminary study, a new method based on signal processing approach is developed to automatic detection of asthmatic patients. This developed algorithm is expected to cluster different states of asthmatic conditions by using the RBF (Radial Basis Function) network, instantaneously. However, manual analysis of capnogram is time-consuming and led to erroneous due to human factor such as tiredness and lack of expertise. In the future, this developed algorithm is expected to help heathcare professional involved in respiratory care as it would be possible to monitor severity of asthma automatically and instantaneously.

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