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Abstract

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusions
  8. Acknowledgments
  9. References

ACADEMIC EMERGENCY MEDICINE 2011; 18:860–867 © 2011 by the Society for Academic Emergency Medicine

Abstract

Background:  Feedback devices provide verbal and visual real-time information on cardiopulmonary resuscitation (CPR) quality. Feedback devices can improve the quality of CPR during transportation. It remains unclear if feedback has an effect on the physical strain felt by providers during ongoing CPR.

Objectives:  The objective was to assess the influence of real-time automated feedback on physical strain of rescuers during ongoing chest compressions in different means of transportation.

Methods:  The study was a randomized crossover trial comparing physical strain on advanced life support (ALS) providers during chest compressions using real-time automated feedback in different transport environments: 1) a moving ambulance and 2) a flying helicopter. The authors measured objective and subjective measures of physical strain and calculated the difference in the rate pressure product (RPP) after 8 minutes of external chest compressions.

Results:  There was no difference in the RPP (mean intraindividual difference = 21; 95% confidence interval [CI] = −1,438 to 1,480; p = 0.98) between using the feedback device versus no feedback. There was no significant interaction of vehicle type on the effect of feedback on the RPP. Feedback resulted in a significant mean perceived exertion reduction of a Borg scale score by 0.89 points (95% CI = 0.42 to 1.35; p < 0.001). For systolic and diastolic blood pressure, for serum lactate concentrations, and for the modified Nine Hole Peg Test (NHPT; measurement of fine motor skills), we found no statistically significant differences.

Conclusions:  Feedback devices for CPR during transportation do not have an effect on objective components of physical strain, but decrease perceived exertion in experienced rescuers in an experimental setting.

Chest compressions are necessarily exhaustive and the quality of cardiopulmonary resuscitation (CPR) has substantial influence on a patient’s outcome.1–5 The European Resuscitation Council (ERC) Guidelines 2005 recommend compressing the patients’ chest 4–5 cm with a frequency of 100 compressions per minute.6 The health care professional CPR assessment requires that chest compressions are performed correctly, considering that each patient’s chest anatomy and resistance varies greatly.7 Also, the particular circumstances can influence the individual assessment, especially due to distractions in different transport environments. Performing and sustaining chest compressions appropriately is difficult, further complicated by transportation situations, fatigue, or the chaotic situations in which care for a critically ill patient is provided, especially in out-of-hospital settings. If, in an out-of-hospital cardiac arrest, the decision is made to transport the patient to a hospital, there are often two possibilities of transportation: ambulances or helicopters. In both, the quality of resuscitation is potentially hampered due to movement of the vehicle and confined space,8–11 even though no major difference in quality of closed chest compression between ambulances or helicopters has been shown.12 The overall physical strain due to CPR seems to be well accepted by EMS providers,13 even if CPR is performed during transportation.14 Although there is no effect of age on the physiologic response,15 the level of physical fitness,16 respective of the rescuers` individual work capacity,17 may be important to ensure the adequacy of chest compressions. Moreover, it is well known that there is a decrease in the quality of chest compression after the first minute.18,19

Feedback devices provide verbal and visual real-time information on CPR quality. We showed in a prior investigation that feedback devices can improve the quality of CPR performed in a moving ambulance or helicopter.20 Whether feedback has an effect on physical strain of the providers during ongoing CPR in different means of transportation remains unclear. Our objective was to investigate the influence of real-time automated feedback on the physical strain on rescuers during ongoing chest compressions in different means of transportation.

Methods

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusions
  8. Acknowledgments
  9. References

Study Design

The study was nested within a larger project that was a randomized crossover trial investigating the effect of real-time automated feedback in different transport environments.20 The study was approved by the ethical committee of the Medical University of Vienna and performed according to the Declaration of Helsinki.

Study Setting and Population

In September 2007, advanced cardiac life support was performed by 24 ERC-approved and certified health care professionals according to the International Guidelines 2005 for CPR and ERC,21 except for defibrillation cycles and drugs. To assure validity, all advanced life support (ALS) providers are familiar with out-of-hospital settings. Demographic data of the participants are available in Table 1.

Table 1.   Demographic Data of the 24 Health Care Professionals
VariableOverall (n = 24)Ambulance (n = 12)Helicopter (n = 12)
  1. BMI = body mass index; FFB-Mot = Fragebogen zur Erfassung des motorischen (physical fitness questionnaire);22 IQR = interquartile range; SD = standard deviation.

Female, n (%) 9 (38) 7 (58) 2 (17)
Age, mean ± SD 37 ± 8 34 ± 739 ± 8
BMI, mean ± SD 23 ± 223 ± 223 ± 2
FFB-Mot, mean ± SD114 ± 8111 ± 8118 ± 7
Right-handed, n (%) 21 (88) 10 (83) 11 (92)
Smoking history, n (%) 9 (38)  4 (33) 5 (42)
Pack-years, median (IQR)  5 (2−10)  5 (5−9)   2 (1−20)

To evaluate physical fitness, the participants had to complete the Physical Fitness Questionnaire (FBB-Mot;22Figure 1). This questionnaire measures the motor fitness status in normal populations using 28 self-report items assessing cardiorespiratory fitness, strength, flexibility, coordination, activity of daily life, and sport-specific items. Values from FFB-Mot can range from 28 up to 140 points. In a standard population, normal values for FFB-Mot are 117 (standard deviation [SD] ± 11) points.

image

Figure 1.  Physical fitness. Physical fitness as measured by FFB-Mot (possible scores from 28 to 140). Individuals are ordered by FFB-Mot. The solid line represents the mean value in our study; the dotted lines represent 1 SD around the mean. In a standard population, normal values for FFB-Mot are 117 ± 11 points. FFB-Mot = Fragebogen zur Erfassung des motorischen (physical fitness questionnaire).22

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Study Protocol

Each health care provider had to perform chest compressions in two sessions, once using the feedback device and once without using the feedback device. Each session lasted 8 minutes, which is the usual duration of transport according to 61,273 helicopter rescue operations done by the ÖAMTC Christophorus Air Ambulance Service. An independent researcher provided computer-generated block-randomized sequences of allocation to feedback or no-feedback conditions. Allocation was concealed until start of the study.

To avoid carryover effects, the interval between the out-of-hospital environments was at least 30 minutes, and the ALS provider had to rest until baseline pulse rate was not more than 10 beats/min higher than the first pulse rate before moving to the next out-of-hospital environment.

We used a special Resusci Anne Manikin (Laerdal Medical AS, Stavanger, Norway) with human-like properties.23 The manikin was intubated and ventilated with a ventilator (Oxylog 2000, Dräger, Lübeck, Germany). The feedback device was a modified Heartstart 4000 SP (Philips Medical System, Andover, MA) continuously attached to the manikin. Feedback consisted of 1) verbal commands, which in the helicopter was carried forward to the headset of the helicopter helmet, and 2) waveforms on an extra liquid crystal display (LCD) on the defibrillator as visual feedback. The feedback device therefore encourages the providers to adjust their performance. In the control phase (CPR without feedback), verbal commands were switched off and the LCD was covered, resulting in a standard CPR situation without feedback.

Twelve participants performed CPR in a modified Volkswagen LT 35 ambulance from the Vienna Municipal Ambulance Service (Magistratsabteilung 70, Wiener Rettung, Vienna, Austria) with standard medical equipment. The participant stood at the manikin’s side continuously performing chest compressions during an 8-minute predefined drive on a closed airfield in Lower Austria. To simulate public road circumstances, the drive included curves as well as phases of acceleration and deceleration.

The other 12 participants performed CPR in an EC 135 helicopter (Eurocopter, Donauwörth, Germany) of the ÖAMTC Christophorus Flugrettungsverein (Austrian Automobile Touring Club, Christophorus Air Ambulance Service) with standard medical equipment (Air Ambulance Technology, Ranshofen, Austria). The participants wore helmets but no safety belts and performed chest compressions in a kneeling position beside the manikin. The stretcher was locked in the front position. Chest compressions were continuously performed during an 8-minute predefined flight course including takeoff and landing. During the flight sequence the weather conditions were as follow: wind speed 5 knots, horizontal sight unlimited, few clouds (2/8).

Measurements

Heart rate was measured by using a digital six-lead ECG-Holter (Mortara Instrument, Milwaukee, WI). The leads were attached to the ALS providers during the experiment using standard ECG electrodes. We measured blood pressure with a noninvasive upper-arm cuff oscillometric device (Defigard 2002, Schiller, Baar, Switzerland). Two investigators measured blood pressure (ER, NR) before, immediately after, and 5 minutes after chest compressions. To measure perceived exertion we used a Borg scale 24 between 6 (no exertion) and 20 (maximal exertion). At study entry the Borg scale was explicitly explained to all participants. The same Borg scale was permanently and easily visible for participants during chest compressions. An investigator (CH) interviewed participants at minutes 2, 4, 6, and 8 during chest compressions. A drop of capillary blood was drawn from participants’ earlobes to measure capillary lactate immediately after chest compressions were finished using Accu-Chek Softclix pro and Accu-Chek Softclix pro-Lancet 200 (Accutrend Lactate, Roche-Austria, Wien, Austria). The blood drop was captured using 32-μL Ring caps and transferred to the test strip as specified in the product manual. To measure fine motor skills immediately after chest compressions, we used a modified Nine Hole Peg Test (NHPT).25 Good fine motor skills are reflected by a short time necessary to put pegs in holes with the nondominant hand. To measure longer time intervals, we used 16 instead of nine pegs and holes.

Outcome Parameters

We calculated the rate pressure product (RPP) as an index of myocardial oxygen consumption to reflect physical strain. Due to the study setting, RPP was calculated as the maximum heart rate during chest compressions multiplied by the systolic blood pressure immediately after chest compressions. Results were similar to when heart rate at 8 minutes (after chest compressions) was used instead of maximum heart rate, but the variability was lower when maximum heart rate was used. We also recorded the Borg scale of perceived exertion (ranging from 6 [no exertion] to 20 [maximum])24 at the eighth minute of chest compression, serum lactate concentration, and modified NHPT25 immediately after end of chest compressions.

Data Analysis

Continuous data are presented as mean ± SD or median and 25% to 75% interquartile range (IQR), as appropriate. Dichotomous data are presented as count and relative frequency. Given the design-specific properties of a crossover study, we handled data as paired observations within each subject. We used a paired t-test to test the null hypothesis of no difference between feedback and no feedback. For the Borg score, we had four repeated measurements at each occasion, and for heart rate we used measurements at every minute. To allow for the correlation of data across individuals and repeated measurements, we used a linear random coefficient model with the Borg score or heart rate as the outcome variable and feedback and measurement time as predictors, nested within individuals. We treated measurement time as an indicator variable in the final model, but we also tested for a linear effect. We formally tested for an interaction between type of vehicle (ambulance versus helicopter) and the effect of feedback on the Borg score using the Wald test for the interaction term.

To assess a possible carryover effect in light of the sample size constraints, we used a Mann-Whitney U-test to compare the group starting with feedback and the group starting without feedback for the ambulance group and the helicopter group together. We used MS Excel for Mac (Microsoft Corp., Redmond, WA) and Stata 9.0 (StataCorp, College Station, TX) for data management and calculations. A two-sided p-value < 0.05 was generally considered statistically significant, with no adjustments made for the multiple comparisons.

Sample Size Estimation

The study was designed to detect a pairwise difference between the intervention and control in maximum heart rate. The null hypothesis was a difference of 0. The estimated sample size for one-sample comparison of mean to hypothesized value was performed assuming a two-sided alpha level of 0.05 and a power of 80%. The clinically relevant difference is assumed to be 10 beats/min, with an estimated standard deviation of 10. The calculated sample size was 8. To allow for incomplete measurements, and given the unique possibility to measure in a flying helicopter and a moving ambulance, as well as the given time frame, we planned to examine 12 ALS providers in each vehicle. This sample size was also sufficient to detect a difference in serum lactate concentrations of 0.5 mmol/L (SD ± 0.4 mmol/L) given our statistical assumptions.

Results

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusions
  8. Acknowledgments
  9. References

All randomized participants were analyzed. There were no losses to follow-up and no missing data. The outcomes are presented in Table 2. There was no difference between using a feedback device in the RPP (mean intraindividual difference −21; 95% confidence interval [CI] = −1,480 to 1,438, p = 0.98) versus no feedback. There was no significant interaction of vehicle type on the effect of feedback on the RPP. In the group starting without feedback the intraindividual mean difference of the RPP was −760 (SD ± 3,192), and in the group starting with feedback it was 718 (SD ± 3,688), indicating that there was no significant carryover effect between those groups (p = 0.31).

Table 2.   Outcomes
 FeedbackNo FeedbackIntraindividual Differences (95% CI)p-value for Differencep-value for Interaction*
  1. NHPT = Nine Hole Peg Test; RPP = rate pressure product.

  2. *Interaction by vehicle type.

  3. †RPP calculated as individual maximum heart rate × systolic blood pressure immediately post-CPR.

  4. ‡Overall 24 participants with 48 measurements.

  5. §Twelve participants with 24 measurements during ambulance drive.

  6. ||Twelve participants with 24 measurements during helicopter flight.

  7. ¶Chest compressions.

  8. **Modified NHPT after 8 minutes of chest compression.

RPP,† mean ± SD
 Overall‡  21 (−1,438 to 1,480)0.98 
 Ambulance§20,294 ± 4,40120,752 ± 4,276−458 (−2,217 to 1,301)0.68 
 Helicopter||21,255 ± 4,64620,754 ± 4,976500 (−2,100 to 3,105)0.580.51
Systolic blood pressure post-CPR¶ (mm Hg), mean ± sd
 Overall‡  5.6 (−1.2 to 12.5)0.10 
 Ambulance§161 ± 20156 ± 175.4 ± (−6.5 to 17.3)0.34 
 Helicopter||145 ± 17139 ± 135.8 (−3.2 to 14.8)0.180.95
Maximum heart rate during CPR¶ (min−1), mean ± SD
 Overall‡  −4.4 (−10.4 to 1.6)0.14 
 Ambulance§137 ± 23146 ± 19−9.2 (−18.7 to 0.3)0.06 
 Helicopter||135 ± 21134 ± 240.3 (−7.4 to 8.1)0.930.10
NHPT** score post-CPR (seconds), mean ± sd
 Overall‡  0.1 (−1.1 to 1.4)0.82 
 Ambulance§25 ± 2.425 ± 2.6−0.3 (−2.2 to 1.6)0.72 
 Helicopter||25 ± 2.725 ± 2.40.3 (−2.0 to 2.0)0.970.78
Lactate (mmol/L), mean ± SD
 Overall  −0.2 (−0.7 to 0.2)0.25 
 Ambulance§3.0 ± 1.03.3 ± 1.0−0.3 (−1.1 to 0.5)0.41 
 Helicopter||2.7 ± 0.92.9 ± 0.8−0.2 (−0.6 to 0.29)0.420.74

Feedback resulted in a significant reduction of the mean perceived exertion Borg score by 0.89 points (95% confidence interval [CI] = 0.42 to 1.35, p < 0.001). Perceived exertion increased by resuscitation time in all groups by 0.55 Borg scale points every 2-minute increment (95% CI = 0.44 to 0.66; p < 0.001; Figure 2). There was no significant interaction of vehicle type on the effect of feedback on Borg score (p = 0.09). The effects of feedback on the other outcomes are presented in Table 2. The differences in heart rate are presented in Figure 3. We found no statistically significant differences between groups for blood pressure, heart rate, or serum lactate concentrations for the modified NHPT (Table 2). We did not observe any adverse or unexpected effects due to the intervention.

image

Figure 2.  Mean perceived exertion. Mean perceived exertion as measured by Borg rating scale during closed chest compression over 8 minutes in the moving ambulance (○) and in the helicopter (×). Possible scores range from 6 (no exertion) to 20 (maximum). The dashed lines denote chest compression without feedback; solid lines denote chest compression with feedback. The bars represent standard deviations.

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image

Figure 3.  Mean intraindividual heart rate differences. Mean intraindividual heart rate differences (no feedback minus feedback) during the experiment. Time 0 denotes start of chest compressions (duration 8 minutes). The dashed line denotes the ambulance. The solid line denotes the helicopter. The bars represent standard errors. Heart rate was not significantly different between feedback and no feedback (p = 0.09 allowing for repeated measures). This effect of feedback on heart rate did not differ significantly between ambulance vehicle and helicopter (p = 0.07 allowing for repeated measures).

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Discussion

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusions
  8. Acknowledgments
  9. References

In this study, we showed that the application of feedback devices in CPR under transportation has no effect on rescuers’ physical strain, although the rescuers’ perceived exertion measured by Borg scale decreases. This is an important finding, because despite the fact that we could demonstrate that feedback devices can improve CPR quality in a prior report,20 it was unclear whether such interventions would increase the physical strain and thus limit resuscitation efforts.

Several studies on the efficacy of feedback devices have been summarized in a systematic review.26 The authors of that review concluded that feedback devices are beneficial for training to improve skill acquisition and retention. Some evidence supports their use in clinical practice as part of an overall strategy to improve the quality of CPR. However, the actual effect on patient outcome is still unknown. Knowing that rescuers’ exhaustion is a limiting factor for CPR performance,17,19,27,28 it is important to investigate the effects of such devices on rescuers’ physical strain.

Using feedback to cope with the inherent human inability to stick with a certain chest compression frequency is not entirely new. However, studies investigating physical strain or work capacity sometimes implemented feedback, but never compared this to a control group. Studies have used some kind of feedback, e.g., a metronome,15,29–32 to maintain the required frequencies of chest compression. Some investigators also used intermittent verbal feedback,32 compared to our continuous audiovisual feedback. It is difficult to set our findings in context with some prior reports because they recorded different outcome parameters and measured physical strain heterogeneously. While earlier studies used a combination of measures such as heart rate, oxygen consumption, lactate levels, and correct chest compressions,16,17,19 recently performed studies have introduced scales such as the Borg scale.14,29

Resuscitation efforts are exhausting but well tolerated by healthy ALS providers.13 As shown in prior studies,13,16,17,32,33 resuscitation efforts are within normal physiologic, aerobic, and submaximal ranges. We provide evidence that physical strain, during different transportation modalities, stays within sensible normal physiologic ranges. However, there is decay in quality of chest compressions that is not sufficiently recognized by the rescuers themselves.18,19,28,34 This effect is not assumed to depend on rescuers’ profession, age, weight, height, or sex.19,30

Our investigation supports prior studies35 indicating that CPR with feedback devices is easy to perform and feasible. We believe that feedback devices are applicable for standard-scene CPR and also for challenging situations as described elsewhere.20

We did not systematically assess qualitative information on the perception of feedback devices. We found that perceived exertion as measured quantitatively with the Borg score was lower with the feedback device. This is in line with participants’ notions that it was somehow easier and less exhausting to work with such a device. An explanation could be that they were able to pay more attention to ergonomic aspects like proper positioning if relieved of timing issues. On the other hand, Borg scores are self-reported and the intervention could not be blinded. Therefore, there is a potential risk that providers who have a bias favoring the feedback feature will report lower exertion.

Clinical Impact

Resuscitation during transportation is always a challenge, but sometimes unavoidable,36,37 and not futile.38 Rittenberger and colleagues39 noted that quality of CPR decreases with complexity of resuscitation. This certainly applies to a transport situation. Audiovisual feedback might be a helpful tool for constant quality of CPR,20 but as we described, at the cost of higher physical strain for the rescuers. This physical strain is within physiologic range and is in the opposite direction of perceived exertion. Furthermore, feedback devices are easily implemented as additions to standard medical equipment.

Limitations

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusions
  8. Acknowledgments
  9. References

Baubin et al.17 described that effective CPR can be performed for more than 30 minutes. However, the usual duration of transport according to 61,273 helicopter rescue operations done by the ÖAMTC Christophorus Air Ambulance Service is 8 minutes. Therefore, the study duration was set to this clinically common time period. One might argue that differences would be more pronounced if observation time had been longer. However, looking at Figure 2, there is no indication of any deviation along the observation time. Furthermore, if differences appear only after a much more extended chest compression time, they might usually not be clinically relevant if not observed in practice.

Overall our measurements were within sensible physiologic ranges. The perceived exertion and systolic blood pressure were as expected constantly increasing over time during chest compressions. Systolic blood pressure returned to approximately baseline values 5 minutes after the end of chest compressions.

For some of our variables we did not find a difference. This might be explained by the power that was set to find differences in maximum heart rate. However, for other outcomes we could expect differences if they had been clinically relevant. We had no indication for a carryover effect.

This was an experimental study where CPR was performed on a manikin in a study setting. Performing resuscitation in an artificial situation is typically less stressful than in real-life situations. Weather conditions, especially the wind during the flight, were calm in our study. Hence, no conclusion can be drawn upon more challenging weather conditions. All of our ALS providers were familiar with otherwise distracting transportation situations, which also indirectly influences the effect on physiologic responses of providers and our results.

Conclusions

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusions
  8. Acknowledgments
  9. References

Feedback devices in a moving ambulance or a flying helicopter have no effects on physical strain, but decrease perceived exertion in experienced rescuers in an experimental setting. As expected, exertion increases with duration of cardiopulmonary resuscitation, but this does not depend on the vehicle used.

Acknowledgments

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusions
  8. Acknowledgments
  9. References

The authors thank the rescuers who participated in the study: A. Auer, C. Brenter, M. Dittrich, P. Eisenburger, M. Feichtinger, M. Fousek, G. Herzer, K. Janata, H. Losert, R. Malzer, S. Matzinger, G. Necid, E. Riedmueller, B. Saxinger, G. Schrattenbacher, S. Schreiber, M. Sigl, N. Tirala, M. Vlcek, J. Weinfurter, and A. Zeiner. Special thanks go to the pilot, M. Weiermayer.

References

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusions
  8. Acknowledgments
  9. References
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