- Email: [email protected]
Influence of Stressors on HEMS Crewmembers in Flight
ORIGINAL RESEARCH
Influence of Stressors on HEMS Crewmembers in Flight Elio Carchietti, MD, HEMS-MD,1 Francesca Valent, MD, MSPH,2 Adriana Cecchi, PharmD,3 and Raphael Rammer4
Abstract
Introduction
Introduction: Helicopter emergency medical service (HEMS) crew are subject to various sources of environmental, physical, and psychological stress. We measured the changes in heart rate and blood pressure as indicators of stress among the crewmembers of the regional HEMS of the Region Friuli Venezia Giulia, Italy. Methods: From August 12 to September 3, 2009, and from February 12 to April 1, 2010, heart rate (HR), diastolic blood pressure (DBP), and systolic blood pressure (SBP) were measured, on a voluntary basis, before and after each flight among the crewmembers. Oxygen saturation (SpO2) was also recorded. The effects of flight and personal characteristics on the parameters after the flight were analyzed through multivariate regression. Results: Data on 95 work shifts, corresponding to 162 flights, were collected. Only the HR changed significantly after the flight (median change: ⫹5 beats/min considering all the flights). The increase in HR was significantly greater in flights with adverse weather conditions, in hostile environments, and at high altitude than in the others. The change in HR was inversely correlated with that of SpO2. After adjusting for potential confounders, the HR after the flight was significantly higher among technical personnel than among physicians and nurses. Conclusions: The increase in HR after the flight indicates that the HEMS crew are exposed to stressful conditions during the mission. Monitoring such parameters may be helpful in recognizing the onset of acute stress and ensuring the safety of the patients and the crew themselves.
Helicopter emergency medical services (HEMS) play an important role in the prehospital care and transport of critical patients.1-3 The most important causes of stress (stressors) in HEMS crewmembers may be environmental, physical, and psychological. Environmental and physical stressors include the intermittent hypoxia dependent on the altitude of flight, the weather and temperature, the wind and turbulence in flight, the mission complexity and time, the type of flight and landing areas (highway, road, mountain, forest), the noise, and helicopter vibrations. The crew mission time, as stated by Federal Aviation Administration,4 is a frequent cause of physical fatigue and operational risk, which is defined as low risk at 1 hour, moderate risk at 2 hours, and high risk at more than 2 hours of flight. The psychological stressors are mainly represented by the interactions with the patients and the unpredictable nature of the emergency alarm. Some events, such as death or serious injury to children, mass casualty, traumatic death of a coworker, prolonged prehospital care, and HEMS crash events information, are unusually emotionally powerful. Acute stress may produce a state of psychological arousal that is known as autonomous mode behavior (AMB). The medical crewmember under stress will tend to focus on 1 problem while ignoring other more critical information. This physical and psychological condition is commonly known as “tunnel vision.” Some signs of AMB are increased heart rate (HR) and increased blood pressure.5 According to the American Heritage Dictionary, stress “…is capable of affecting physical health, usually characterized by increased heart rate, a rise in blood pressure, muscular tension, irritability and depression” as well as other symptoms often not easily detectable.6 The aim of this study is to examine any relevant flightrelated alterations of the HR and systolic and diastolic blood pressure (SBP and DBP) as indicators of stress among the members of an Italian HEMS crew.
1. Department of Hospital Services Organization, Azienda OspedalieroUniversitaria di Udine; Regional HEMS, Friuli Venezia Giulia, Italy 2. Institute of Hygiene and Clinical Epidemiology, Azienda OspedalieroUniversitaria di Udine 3. Pharmacy, Azienda Ospedaliero-Universitaria di Udine 4. Eurocopter, ETGV, Dynamics & Vibrations, Munich, Germany Address for correspondence: Francesca Valent, Institute of Hygiene and Clinical Epidemiology, Azienda Ospedaliero-Universitaria di Udine, Via Colugna 50 33100 Udine, Italy; [email protected] 1067-991X/$36.00 Copyright 2011 by Air Medical Journal Associates doi:10.1016/j.amj.2011.02.002 270
Materials and Methods From August 12 to September 3, 2009, and from February 12 to April 1, 2010, HR, DBP, and SBP were measured and recorded on a voluntary basis among the team of the 118 helicopter emergency medical service of the Friuli Venezia Giulia Region, Italy, at the beginning of the working shift and after each flight on the EC 135 helicopter. In addition to the previously mentioned parameters, the oxygen Air Medical Journal 30:5
saturation (SpO2) was recorded. All of the measurements were performed by a registered nurse using the same multiparameter device, a LIFEPAK® 12 Defibrillator/Monitor. The parameters were not recorded during the flight to avoid interfering with the specific operational needs of the helicopter in emergency situations. Flight conditions were classified as nonordinary in the case of adverse weather conditions or hostile environment (eg, search and rescue flights) and as ordinary elsewhere. The duration of the flight and the flight altitude was recorded. Data on the personnel were recorded anonymously. In addition to the previously mentioned vital parameters, information was collected on age, sex, weight, height, and role: pilot, physician, triage coordinating nurse, alpine rescue expert, winch operator, and medical flight nurse. Ground-level environmental temperature before and after each flight was also recorded. The air temperature within the flying helicopter is similar to the ET in the summer and is approximately 22 to 25 degrees Celsius (°C) in the winter because of artificial heating. All data were recorded on paper forms (1 for each work shift and for each subject) and subsequently entered into an electronic database. All forms in which at least 1 flight was recorded were analyzed. A vibration flight test on the EC 135 helicopter of the regional HEMS was implemented on March 24, 2010, at the airport of Trieste Ronchi dei Legionari. It was sunny with wind varying between 9 kts and 21 kts, gusts 27 kts (Bora wind). The duration of all flight tests was 41 minutes.
Statistical Analysis For each subject, vital parameters before the first flight were compared with those after the flight. In case of multiple flights in the same work shift, the parameters after each subsequent flight were compared with those measured at the end of the previous flight. Because the data were anonymous, analyses accounting for intrapersonal correlations were not possible for the individuals who participated in multiple work shifts within the study period. The variations of the parameters were expressed as the value of each parameter after the flight minus the value before the flight; therefore, they are positive if the parameter increases and negative if it decreases after the flight. The statistical significance of the difference of each parameter before and after the flight was assessed through Wilcoxon’s rank-sums test, because the variables were not normally distributed according to the Kolmogorov-Smirnov test. The associations between the differences in the parameters before and after the flight were assessed through Spearman’s correlation. In addition, we evaluated the correlations between those differences and the difference of the environmental temperature before and after the flight, the flight rank in the work shift, and the flight duration. The associations of each parameter modification with each subject’s role and with the flight stress level were assessed through a Kruskal-Wallis test. September-October 2011
Multivariate linear regression analyses were conducted to assess the associations between the value of each parameter after the flight with other features of the subject (parameter values before the flight, body mass index [BMI, weight/height2], role [technician vs physician/nurse]), ET before the flight, season (summer vs winter), flight stress level (nonordinary vs ordinary), and destination (mountain vs plain), adjusting for the potential impact of each variable on the others. The analyses were repeated, including only the first flights of each work shift, to eliminate the potential effects of the presence of events correlated with each other. P-values less than .05 were considered statistically significant.
Results We analyzed forms regarding 95 work shifts, corresponding to 162 flights. Participation in the study was 100% for the HEMS personnel, with the only exception being pilots who were not employees of the regional HEMS but were provided by an external company. Table 1 shows the characteristics of the 162 flights and of the personnel involved. Table 2 shows the changes in the vital parameters after the flights. The mean variation of ET was 1.3 ⫾ 4.2°C (median, 1.0; P ⫽ .0046). On average, a statistically significant increase was observed for HR. Table 3 shows the correlations between the changes in the parameters occurring during the flight and those with changes in ET and with flight duration. The modification of the HR resulted negatively and significantly correlated with the modification of the SpO2 and positively with borderline significance with the modification of the DBP. The change in DBP was positively correlated with the SBP and flight duration. None of the modifications of the vital parameters resulted in a significant difference, depending on the role of the personnel: P ⫽ .1947 for HR, P ⫽ .9240 for SBP, P ⫽ .9112 for DBP, and P ⫽ .6042 for SpO2. The change in HR was significantly greater in nonordinary flights (on average, ⫹7.8 beats/min) versus ordinary flights (on average, ⫹2.7 beats/min; P ⫽ .0018). On the contrary, changes in the other parameters were not significantly different depending on the type of flight (for SpO2, P ⫽ .1112; for SBP, P ⫽ .5440; for DBP, P ⫽ .7393). Table 4 shows the results of the multivariate analyses regarding the values of the parameters after the flight. None of the flight characteristics appeared to significantly influence vital parameters at the end of the flight. Tables 5 through 7 show the results of the analyses, including the first flights of each work shift. None of the changes in the vital parameters resulted in significant differences, depending on the role of the personnel or the stress index of the flight. Table 7 shows the results of the multivariate analyses on vital parameters after the flights. Even considering the first flights of each work shift only, none of the flight characteristics appeared to significantly influence the vital parameters measured at the end of the flights. 271
Table 1. Characteristics of the Flights and Personnel Involved Role of the personnel involved (N, %) Triage coordinating nurse Alpine rescue specialist Winch operator Pilot Medical flight nurse Physician Vital parameters of the personnel before the flight (mean ⫾ SD, median) Weight (kg) Height (cm) BMI (kg/m2) Age (years) HR before the flight (n/min) DBP before the flight (mmHg) SBP before the flight (mmHg) SpO2 before the flight (%) Flight characteristics (N, %) Ordinary flight (flight altitude 1,000–1,500 ft) Nonordinary flight (adverse weather conditions, hostile environment, search and rescue flights, flight altitude 5,000–6,000 ft) Not reported Flight duration in minutes (mean ⫾ SD, median) Flight rank within the work shift (N, %) 1 2 3 4
64, 39.5% 5, 3.1% 11, 6.8% 5, 3.1% 51, 31.5% 26, 16.0% 74.3 ⫾ 14.1, 72.0 176.8 ⫾ 7.1, 177.0 23.6 ⫾ 3.2, 23.8 41.1 ⫾ 5.4, 39.0 75.3 ⫾ 13.4, 75.0 75.4 ⫾ 11.1, 75.0 120.2 ⫾ 13.2, 120.0 98.1 ⫾ 1.3, 98.0 98, 60.4% 39, 24.1% 25, 15.4% 32.1 ⫾ 22.9, 28.0 95, 58.6% 45, 27.8% 16, 9.9% 6, 3.7%
Discussion The HEMS Friuli Venezia Giulia operates every day, in line with atmospheric conditions, on the whole region, with EC135 T2 aircraft . Many flights, approximately 900 per year, maintain an altitude between 1,000 and 1,500 feet, whereas approximately 100 flights per year maintain an altitude between 5,000 and 6,000 feet. In the vibration flight test, over the whole flight, the frequencies of vibrations were within a range between a minimum of approximately 20 Hz and a maximum of approximately 80 Hz. As a rule, the helicopter crew includes a pilot and a technician, a physician, and 2 nurses and, in hostile environment, an alpine rescue expert instead of 1 of the nurses. None of the changes in the HR, SBP, or DBP resulted in a significant difference, depending on the role of the personnel. According to a study by Iyer et al,7 the HR changes significantly at both 1,500 and 6,000 feet, although the changes were greater in the case of long flights to high altitudes. Consistently with that study, in our study we observed median HR increases of 5 and 6 beats per minute, considering all the flights and only the first flights of each shift, 272
Table 2. Changes of the Vital Parameters after the Flight— All of the Flights (N ⫽ 162) Difference (Value after the Flight – Value before the Flight) Mean ⫾ SD, Median P HR (bpm) 3.9 ⫾ 9.5, 5.0 ⬍.0001 DBP (mmHg) 0.4 ⫾ 9.4, 0 .8887 SBP (mmHg) 0.1 ⫾ 9.9, 0 .8901 SpO2 (%) -0.1 ⫾ 1.2, 0 .2062
respectively. The increase in HR was significantly greater in nonordinary than in ordinary flights. The changes of HR can be related, among the other causes, to the intermittent hypoxic environment that increases the response of the autonomic nervous system mainly through increased sympathetic activity. Exposure of healthy human subjects to intermittent hypoxia, in fact, is associated with Air Medical Journal 30:5
Table 3. Correlations between the Changes in the Vital Parameters—All Flights (N ⫽ 162) HR Difference DBP Difference SBP Difference SpO2 Difference HR difference
-
DBP difference
-
0.13 (0.0886) -
SBP difference
-
-
0.11 (0.1748) 0.50 (⬍0.0001) -
SpO2 difference
-
-
-
-0.20 (0.0098) -0.02 (0.8445) -0.08 (0.3352) -
ET Difference
Flight Minutes
-0.01 (0.8674) -0.10 (0.2055) 0.10 (0.1976) -0.05 (0.5681)
-0.04 (0.5956) 0.17 (0.0443) -0.01 (0.9195) -0.03 (0.6931)
Table 4. Association of the Value of Each Vital Parameter after the Flight with the Value of the Parameters before the Flight and the Characteristics of the Flight According to Multivariate Linear Regression Analyses—All Flights (N ⫽ 162) Dependent Variable Independent Variables HR SBP DBP SpO2 after the flight after the flight after the flight after the flight Beta P Beta P Beta P Beta P HR before the flight 0.6998 ⬍.0001 0.0438 .5958 -0.0155 0.8300 -0.0127 .1606 SBP before the flight 0.0501 .5779 0.5128 ⬍.0001 0.2204 0.0229 -0.0053 .6585 DBP before the flight -0.1020 .2871 0.2357 .0450 0.3664 0.0005 0.0085 .5049 SpO2 before the flight -0.9763 .1895 0.5188 .5664 0.4333 0.5857 0.3345 .0010 BMI -0.1092 .7186 0.6844 .0661 0.1132 0.7257 -0.1071 .0092 Technical role of personnel 6.5615 .0081 2.4361 .4137 1.3936 0.5918 -0.2210 .4985 ET before the flight -0.1751 .4669 0.2319 .4298 -0.0094 0.9710 0.0388 .2288 Non-ordinary flight 2.5543 .1798 -0.7749 .7377 -0.8357 0.6782 -0.0819 .7467 Flight duration (min) -0.0765 .1927 -0.0366 .6088 0.0923 0.1402 0.0017 .8316 Flight rank in work shift -1.8266 .0661 -0.4923 .6826 0.3315 0.7517 0.0174 .8950 Season (summer vs winter) 0.6871 .8929 -2.8046 .6526 0.7645 0.8894 -1.7662 .0108 Model R2 0.64 0.56 0.43 0.50
Table 5. Changes in the Vital Parameters after the Flight— Only First Flights of Each Work Shift (N ⫽ 95) Difference (Value after the Flight – Value before the Flight) Mean ⫾ SD, Median P HR (bpm) 5.8 ⫾ 9.2, 6.0 ⬍.0001 DBP (mmHg) 0.9 ⫾ 10.5, 0 .8171 SBP (mmHg) 1.4 ⫾ 9.7, 0 .1325 SpO2 (%) -0.3 ⫾ 1.3, 0 .0207
sympathetic activation.8,9 In our study, in fact, the modification of the HR inversely correlated with that of the SpO2. Furthermore, these HR changes may be related as well to effects of hormonal, metabolic, and circulatory modifications September-October 2011
produced by forced vibrations in flight. In fact, in every transportation by air or ground, crewmembers, as well as transported patients, are exposed to vibrations.10 In particular, the helicopters during the flight are subject to an asymmetric, turbulent aerodynamic environment, and rotors induce high vibratory forces. Vibrations are mechanical stimuli characterized by an oscillatory motion that, at specific frequencies, may have harmful effects on the human body. In fact, vibrations induce muscular contraction.11 The soft tissues act as wobbling masses that vibrate in response to 25- to 75-Hz forced vibrations; on the contrary, muscles react to those mechanical stimuli through contraction.12,13 Such muscular contractions cause metabolic responses similar to other forms of mild exercise and increase oxygen consumption for the metabolism of lipids and carbohydrates.14,15 In healthy persons, vibrations are associated with a significant reduction in blood flow of the distal limbs and increased HR. These effects are most evident in the first minutes of the flight.16 From our multivariate models, the changes in HR 273
Table 6. Correlations between Changes in the Vital Parameters—Only First Flights of Each Work Shift (N ⫽ 95) HR DBP SBP SpO2 ET Difference Difference Difference Difference Difference HR difference 0.27 0.19 -0.28 -0.07 (0.0079) (0.0649) (0.0066) (0.5101) DBP difference 0.53 -0.14 -0.08 (⬍0.0001) (0.1631) (0.4224) SBP difference -0.15 0.11 (0.1364) (0.3075) SpO2 difference -0.04 (0.6940)
Flight Minutes -0.03 (0.7553) 0.01 (0.9201) -0.10 (0.3996) -0.09 (0.4101)
Table 7. Association of the Value of Each Vital Parameter after the Flight with the Value of the Parameters before the Flight and the Characteristics of the Flight According to Multivariate Linear Regression Analyses—Only the First Flights of Each Work Shift (N ⫽ 95) Dependent Variables Independent Variables HR SBP DBP SpO2 after the flight after the flight after the flight after the flight Beta P Beta P Beta P Beta P HR before the flight 0.7808 ⬍.0001 0.0652 .5324 0.0065 .9486 -0.0171 .1406 SBP before the flight 0.0076 .9495 0.5607 .0002 0.2732 .0501 0.0034 .8291 DBP before the flight -0.1029 .3943 0.5406 .0935 0.2961 .0338 0.0227 .1491 SpO2 before the flight -0.8641 .4020 0.6812 .5738 0.8914 .4460 0.3150 .0209 BMI -0.1102 .7961 0.3865 .4423 -0.2655 .5839 -0.1494 .0088 Technical role of personnel 5.1349 .1306 1.1582 .7698 2.2729 .5521 -0.8455 .0562 ET before the flight -0.3546 .3878 0.1544 .7486 -0.0979 .8332 0.1180 .0293 Non-ordinary flight 2.6452 .2557 -2.3052 .3987 -2.4868 .3456 0.0351 .9067 Flight duration (min) -0.0901 .3180 -0.0554 .6003 0.0546 .5929 0.0018 .8801 Season (summer vs winter) 5.0507 .5505 -2.3540 .8128 2.6349 .7835 -3.4389 .0026 Model R2 0.65 0.62 0.44 0.55
appear to be affected as well by the role of the flying personnel. In fact, on average, HR after the flight was much higher among technicians than among physicians and nurses, possibly indicating a different level of psychological stress, depending on the tasks that are being performed during the flight. In addition, we observed that flights occurring in the summer were associated with a significant decrease in SpO2 after the flight. Such a parameter was inversely associated with the subject’s BMI, highlighting the importance of personal physical characteristics on metabolism during the flight. One limitation of this study is that the results are not generalizable to pilots, because most of them refused participation. Another important limitation of our research is that the effects of stress on the HEMS crew were only assessed through the measurement of physiological parameters. Because stress is a complex phenomenon, a more thorough evaluation should also include psychological and laboratory tests. However, physiologi274
cal parameters, although of little validity when studying chronic stress, are useful in the assessment of acute stress.17 In addition, the concentration of catecholamines, cortisol, and other stressrelated hormones can be influenced by a number of other factors, such as circadian rhythm,18 nicotine consumption, menstrual phase, oral contraceptive use,19 nutrition, physical activity, and sleep quality.20 Thus, measuring those hormones in the biological samples of the crew in a “real life” setting would have increased the likelihood of confounding and implied the design of a more complicated and resource-consuming research. Our study represents a first step in the assessment of stress among HEMS personnel, and further research taking into consideration psychological evaluations and biochemical markers is warranted.
Conclusions Medical emergencies and prehospital care in helicopter flight are enormous stressors themselves. The crewmembers of Air Medical Journal 30:5
HEMS are exposed to the environmental, physical, physiological, and psychological stressors. Moderate stress tends to positively affect performance of the crewmembers,5 but the mission complexity and time and the operational environment may be very important stressors. The HR changes represent the immediate response to the onset of stress. To recognize the early warning signs of acute stress by a sudden critical event or the subtle signs of “chronic stress” is essential to ensure safety. A major safety factor for critical patients in prehospital care and for HEMS crewmembers themselves is the continuous and effective control of their degree of vulnerability.
References 1. Silbergleit R, Dedrick DK, Pape J, Burney RE. Forces acting during air and ground transport on patients stabilized by standard immobilization techniques. Ann Emerg Med 1991;20:875-7. 2. Sullivent EE, Faul M, Wald MM. Helicopter emergency medical services transport is associated with reduced mortality in injured adults. Prehosp Emerg Care 2010;14(Suppl 1):7-8. 3. Bunis J, Chikani V, Mullins T, Conditt VA, Salvino CK, Bobrow BJ. An analysis of air ambulance utilization for field trauma patients in Arizona. Prehosp Emerg Care 2010;14(Supp 1):7-8. 4. Adams R, Thompson J. Risk management for air ambulance helicopter operators. U.S. Department of transportation; Final report, 1989. 5. Harris Joel S. For helicopter pilots, managing stress is part of flying safely. Flight Safety Foundation—Helicopter Safety. 1995;21:1-6. 6. American Heritage Dictionary of the English Language. Third edition, 1992. 7. Iyer EM, Rattan N, Soodan KS. Effect of hypoxia, noise & vibration stress on human performance and neuro-endocrine reactions. Ind J Aerospace Med 2000;44:21-7. 8. Povea C, Schmitt L, Brugniaux J, Nicolet G, Richalet JP, Fouillot JP. Effects of intermittent hypoxia on heart rate variability during rest and exercise. High Alt Med Biol 2005;6:215-25.
September-October 2011
9. Gilmartin GS, Lynch M, Tamisier R, Weiss JW. Chronic intermittent hypoxia in humans during 28 nights results in blood pressure elevation and increased muscle sympathetic nerve activity. Am J Physiol Heart Circ Physiol 2010;299: H925-H931. 10. McVey J, Petrie DA, Tallon JM. Air versus ground transport of the major trauma patient: a natural experiment. Prehosp Emerg Care 2010;14:45-50. 11. Konstanzer P, Enenki B, Aubourg PA, Cranga P. Recent advances in Eurocopter’s passive and active vibration control. American Helicopter Society 64th Annual Forum. Montreal, Canada, 2008. 12. Wakeling JM, Nigg BM, Rozitis AI. Muscle activity in the lower extremity damps the soft tissue vibrations which occur in response to pulsed and continuous vibrations. J Appl Physiol 2002;93:1093-103. 13. Wakeling JM, Nigg BM. Modification of soft tissue vibrations in the leg by muscular activity. J Appl Physiol 2001;90:412-20. 14. Cardinale M, Wakeling J. Whole body vibration exercise: are vibrations good for you? Br J Sports Med 2005;39:585-9. 15. Rittweger J, Beller G, Felsenberg D. Acute physiological effects of exhaustive wholebody vibration exercise in man. Clin Physiol 2000;20:134-42. 16. Lohmann EB, Petrofsky JS, Maloney-Hinds C, Betts-Scwab H, Thorpe D. The effect of whole body vibration on lower extremity skin blood flow in normal subiects. Med Sci Monit 2007;13:CR71-6. 17. Hubbard J.R, Kalimi M, Liberti JP. Handbook of Stress Medicine. Chapter 17. In: Hubbard JR, ed. Biochemical Indicators of Stress. Boca Raton, FL: CRC Press 1997. 18. Haus E, Dumitriu L, Nicolau GY, Bologa S, Sackett-Lundeen L. Circadian rhythms of basic fibroblast growth factor (bFGF), epidermal growth factor (EGF), insulin-like growth factor-1 (IGF-1), insulin-like growth factor binding protein-3 (IGFBP-3), cortisol, and melatonin in women with breast cancer. Chronobiol Int 2001;18:709-27. 19. Robertson D, Selleck K, Suikkari AM, Hurley V, Moohan J, Healy D. Urinary vascular endothelial growth factor concentrations in women undergoing gonadotrophin treatment. Hum Reprod 1995;10:2478-82. 20. Lundberg U. Stress hormones in health and illness: the roles of work and gender. Psychoneuroendocrinology 2005;30:1017-721.
275
Influence of Stressors on HEMS Crewmembers in Flight Elio Carchietti, MD, HEMS-MD,1 Francesca Valent, MD, MSPH,2 Adriana Cecchi, PharmD,3 and Raphael Rammer4
Abstract
Introduction
Introduction: Helicopter emergency medical service (HEMS) crew are subject to various sources of environmental, physical, and psychological stress. We measured the changes in heart rate and blood pressure as indicators of stress among the crewmembers of the regional HEMS of the Region Friuli Venezia Giulia, Italy. Methods: From August 12 to September 3, 2009, and from February 12 to April 1, 2010, heart rate (HR), diastolic blood pressure (DBP), and systolic blood pressure (SBP) were measured, on a voluntary basis, before and after each flight among the crewmembers. Oxygen saturation (SpO2) was also recorded. The effects of flight and personal characteristics on the parameters after the flight were analyzed through multivariate regression. Results: Data on 95 work shifts, corresponding to 162 flights, were collected. Only the HR changed significantly after the flight (median change: ⫹5 beats/min considering all the flights). The increase in HR was significantly greater in flights with adverse weather conditions, in hostile environments, and at high altitude than in the others. The change in HR was inversely correlated with that of SpO2. After adjusting for potential confounders, the HR after the flight was significantly higher among technical personnel than among physicians and nurses. Conclusions: The increase in HR after the flight indicates that the HEMS crew are exposed to stressful conditions during the mission. Monitoring such parameters may be helpful in recognizing the onset of acute stress and ensuring the safety of the patients and the crew themselves.
Helicopter emergency medical services (HEMS) play an important role in the prehospital care and transport of critical patients.1-3 The most important causes of stress (stressors) in HEMS crewmembers may be environmental, physical, and psychological. Environmental and physical stressors include the intermittent hypoxia dependent on the altitude of flight, the weather and temperature, the wind and turbulence in flight, the mission complexity and time, the type of flight and landing areas (highway, road, mountain, forest), the noise, and helicopter vibrations. The crew mission time, as stated by Federal Aviation Administration,4 is a frequent cause of physical fatigue and operational risk, which is defined as low risk at 1 hour, moderate risk at 2 hours, and high risk at more than 2 hours of flight. The psychological stressors are mainly represented by the interactions with the patients and the unpredictable nature of the emergency alarm. Some events, such as death or serious injury to children, mass casualty, traumatic death of a coworker, prolonged prehospital care, and HEMS crash events information, are unusually emotionally powerful. Acute stress may produce a state of psychological arousal that is known as autonomous mode behavior (AMB). The medical crewmember under stress will tend to focus on 1 problem while ignoring other more critical information. This physical and psychological condition is commonly known as “tunnel vision.” Some signs of AMB are increased heart rate (HR) and increased blood pressure.5 According to the American Heritage Dictionary, stress “…is capable of affecting physical health, usually characterized by increased heart rate, a rise in blood pressure, muscular tension, irritability and depression” as well as other symptoms often not easily detectable.6 The aim of this study is to examine any relevant flightrelated alterations of the HR and systolic and diastolic blood pressure (SBP and DBP) as indicators of stress among the members of an Italian HEMS crew.
1. Department of Hospital Services Organization, Azienda OspedalieroUniversitaria di Udine; Regional HEMS, Friuli Venezia Giulia, Italy 2. Institute of Hygiene and Clinical Epidemiology, Azienda OspedalieroUniversitaria di Udine 3. Pharmacy, Azienda Ospedaliero-Universitaria di Udine 4. Eurocopter, ETGV, Dynamics & Vibrations, Munich, Germany Address for correspondence: Francesca Valent, Institute of Hygiene and Clinical Epidemiology, Azienda Ospedaliero-Universitaria di Udine, Via Colugna 50 33100 Udine, Italy; [email protected] 1067-991X/$36.00 Copyright 2011 by Air Medical Journal Associates doi:10.1016/j.amj.2011.02.002 270
Materials and Methods From August 12 to September 3, 2009, and from February 12 to April 1, 2010, HR, DBP, and SBP were measured and recorded on a voluntary basis among the team of the 118 helicopter emergency medical service of the Friuli Venezia Giulia Region, Italy, at the beginning of the working shift and after each flight on the EC 135 helicopter. In addition to the previously mentioned parameters, the oxygen Air Medical Journal 30:5
saturation (SpO2) was recorded. All of the measurements were performed by a registered nurse using the same multiparameter device, a LIFEPAK® 12 Defibrillator/Monitor. The parameters were not recorded during the flight to avoid interfering with the specific operational needs of the helicopter in emergency situations. Flight conditions were classified as nonordinary in the case of adverse weather conditions or hostile environment (eg, search and rescue flights) and as ordinary elsewhere. The duration of the flight and the flight altitude was recorded. Data on the personnel were recorded anonymously. In addition to the previously mentioned vital parameters, information was collected on age, sex, weight, height, and role: pilot, physician, triage coordinating nurse, alpine rescue expert, winch operator, and medical flight nurse. Ground-level environmental temperature before and after each flight was also recorded. The air temperature within the flying helicopter is similar to the ET in the summer and is approximately 22 to 25 degrees Celsius (°C) in the winter because of artificial heating. All data were recorded on paper forms (1 for each work shift and for each subject) and subsequently entered into an electronic database. All forms in which at least 1 flight was recorded were analyzed. A vibration flight test on the EC 135 helicopter of the regional HEMS was implemented on March 24, 2010, at the airport of Trieste Ronchi dei Legionari. It was sunny with wind varying between 9 kts and 21 kts, gusts 27 kts (Bora wind). The duration of all flight tests was 41 minutes.
Statistical Analysis For each subject, vital parameters before the first flight were compared with those after the flight. In case of multiple flights in the same work shift, the parameters after each subsequent flight were compared with those measured at the end of the previous flight. Because the data were anonymous, analyses accounting for intrapersonal correlations were not possible for the individuals who participated in multiple work shifts within the study period. The variations of the parameters were expressed as the value of each parameter after the flight minus the value before the flight; therefore, they are positive if the parameter increases and negative if it decreases after the flight. The statistical significance of the difference of each parameter before and after the flight was assessed through Wilcoxon’s rank-sums test, because the variables were not normally distributed according to the Kolmogorov-Smirnov test. The associations between the differences in the parameters before and after the flight were assessed through Spearman’s correlation. In addition, we evaluated the correlations between those differences and the difference of the environmental temperature before and after the flight, the flight rank in the work shift, and the flight duration. The associations of each parameter modification with each subject’s role and with the flight stress level were assessed through a Kruskal-Wallis test. September-October 2011
Multivariate linear regression analyses were conducted to assess the associations between the value of each parameter after the flight with other features of the subject (parameter values before the flight, body mass index [BMI, weight/height2], role [technician vs physician/nurse]), ET before the flight, season (summer vs winter), flight stress level (nonordinary vs ordinary), and destination (mountain vs plain), adjusting for the potential impact of each variable on the others. The analyses were repeated, including only the first flights of each work shift, to eliminate the potential effects of the presence of events correlated with each other. P-values less than .05 were considered statistically significant.
Results We analyzed forms regarding 95 work shifts, corresponding to 162 flights. Participation in the study was 100% for the HEMS personnel, with the only exception being pilots who were not employees of the regional HEMS but were provided by an external company. Table 1 shows the characteristics of the 162 flights and of the personnel involved. Table 2 shows the changes in the vital parameters after the flights. The mean variation of ET was 1.3 ⫾ 4.2°C (median, 1.0; P ⫽ .0046). On average, a statistically significant increase was observed for HR. Table 3 shows the correlations between the changes in the parameters occurring during the flight and those with changes in ET and with flight duration. The modification of the HR resulted negatively and significantly correlated with the modification of the SpO2 and positively with borderline significance with the modification of the DBP. The change in DBP was positively correlated with the SBP and flight duration. None of the modifications of the vital parameters resulted in a significant difference, depending on the role of the personnel: P ⫽ .1947 for HR, P ⫽ .9240 for SBP, P ⫽ .9112 for DBP, and P ⫽ .6042 for SpO2. The change in HR was significantly greater in nonordinary flights (on average, ⫹7.8 beats/min) versus ordinary flights (on average, ⫹2.7 beats/min; P ⫽ .0018). On the contrary, changes in the other parameters were not significantly different depending on the type of flight (for SpO2, P ⫽ .1112; for SBP, P ⫽ .5440; for DBP, P ⫽ .7393). Table 4 shows the results of the multivariate analyses regarding the values of the parameters after the flight. None of the flight characteristics appeared to significantly influence vital parameters at the end of the flight. Tables 5 through 7 show the results of the analyses, including the first flights of each work shift. None of the changes in the vital parameters resulted in significant differences, depending on the role of the personnel or the stress index of the flight. Table 7 shows the results of the multivariate analyses on vital parameters after the flights. Even considering the first flights of each work shift only, none of the flight characteristics appeared to significantly influence the vital parameters measured at the end of the flights. 271
Table 1. Characteristics of the Flights and Personnel Involved Role of the personnel involved (N, %) Triage coordinating nurse Alpine rescue specialist Winch operator Pilot Medical flight nurse Physician Vital parameters of the personnel before the flight (mean ⫾ SD, median) Weight (kg) Height (cm) BMI (kg/m2) Age (years) HR before the flight (n/min) DBP before the flight (mmHg) SBP before the flight (mmHg) SpO2 before the flight (%) Flight characteristics (N, %) Ordinary flight (flight altitude 1,000–1,500 ft) Nonordinary flight (adverse weather conditions, hostile environment, search and rescue flights, flight altitude 5,000–6,000 ft) Not reported Flight duration in minutes (mean ⫾ SD, median) Flight rank within the work shift (N, %) 1 2 3 4
64, 39.5% 5, 3.1% 11, 6.8% 5, 3.1% 51, 31.5% 26, 16.0% 74.3 ⫾ 14.1, 72.0 176.8 ⫾ 7.1, 177.0 23.6 ⫾ 3.2, 23.8 41.1 ⫾ 5.4, 39.0 75.3 ⫾ 13.4, 75.0 75.4 ⫾ 11.1, 75.0 120.2 ⫾ 13.2, 120.0 98.1 ⫾ 1.3, 98.0 98, 60.4% 39, 24.1% 25, 15.4% 32.1 ⫾ 22.9, 28.0 95, 58.6% 45, 27.8% 16, 9.9% 6, 3.7%
Discussion The HEMS Friuli Venezia Giulia operates every day, in line with atmospheric conditions, on the whole region, with EC135 T2 aircraft . Many flights, approximately 900 per year, maintain an altitude between 1,000 and 1,500 feet, whereas approximately 100 flights per year maintain an altitude between 5,000 and 6,000 feet. In the vibration flight test, over the whole flight, the frequencies of vibrations were within a range between a minimum of approximately 20 Hz and a maximum of approximately 80 Hz. As a rule, the helicopter crew includes a pilot and a technician, a physician, and 2 nurses and, in hostile environment, an alpine rescue expert instead of 1 of the nurses. None of the changes in the HR, SBP, or DBP resulted in a significant difference, depending on the role of the personnel. According to a study by Iyer et al,7 the HR changes significantly at both 1,500 and 6,000 feet, although the changes were greater in the case of long flights to high altitudes. Consistently with that study, in our study we observed median HR increases of 5 and 6 beats per minute, considering all the flights and only the first flights of each shift, 272
Table 2. Changes of the Vital Parameters after the Flight— All of the Flights (N ⫽ 162) Difference (Value after the Flight – Value before the Flight) Mean ⫾ SD, Median P HR (bpm) 3.9 ⫾ 9.5, 5.0 ⬍.0001 DBP (mmHg) 0.4 ⫾ 9.4, 0 .8887 SBP (mmHg) 0.1 ⫾ 9.9, 0 .8901 SpO2 (%) -0.1 ⫾ 1.2, 0 .2062
respectively. The increase in HR was significantly greater in nonordinary than in ordinary flights. The changes of HR can be related, among the other causes, to the intermittent hypoxic environment that increases the response of the autonomic nervous system mainly through increased sympathetic activity. Exposure of healthy human subjects to intermittent hypoxia, in fact, is associated with Air Medical Journal 30:5
Table 3. Correlations between the Changes in the Vital Parameters—All Flights (N ⫽ 162) HR Difference DBP Difference SBP Difference SpO2 Difference HR difference
-
DBP difference
-
0.13 (0.0886) -
SBP difference
-
-
0.11 (0.1748) 0.50 (⬍0.0001) -
SpO2 difference
-
-
-
-0.20 (0.0098) -0.02 (0.8445) -0.08 (0.3352) -
ET Difference
Flight Minutes
-0.01 (0.8674) -0.10 (0.2055) 0.10 (0.1976) -0.05 (0.5681)
-0.04 (0.5956) 0.17 (0.0443) -0.01 (0.9195) -0.03 (0.6931)
Table 4. Association of the Value of Each Vital Parameter after the Flight with the Value of the Parameters before the Flight and the Characteristics of the Flight According to Multivariate Linear Regression Analyses—All Flights (N ⫽ 162) Dependent Variable Independent Variables HR SBP DBP SpO2 after the flight after the flight after the flight after the flight Beta P Beta P Beta P Beta P HR before the flight 0.6998 ⬍.0001 0.0438 .5958 -0.0155 0.8300 -0.0127 .1606 SBP before the flight 0.0501 .5779 0.5128 ⬍.0001 0.2204 0.0229 -0.0053 .6585 DBP before the flight -0.1020 .2871 0.2357 .0450 0.3664 0.0005 0.0085 .5049 SpO2 before the flight -0.9763 .1895 0.5188 .5664 0.4333 0.5857 0.3345 .0010 BMI -0.1092 .7186 0.6844 .0661 0.1132 0.7257 -0.1071 .0092 Technical role of personnel 6.5615 .0081 2.4361 .4137 1.3936 0.5918 -0.2210 .4985 ET before the flight -0.1751 .4669 0.2319 .4298 -0.0094 0.9710 0.0388 .2288 Non-ordinary flight 2.5543 .1798 -0.7749 .7377 -0.8357 0.6782 -0.0819 .7467 Flight duration (min) -0.0765 .1927 -0.0366 .6088 0.0923 0.1402 0.0017 .8316 Flight rank in work shift -1.8266 .0661 -0.4923 .6826 0.3315 0.7517 0.0174 .8950 Season (summer vs winter) 0.6871 .8929 -2.8046 .6526 0.7645 0.8894 -1.7662 .0108 Model R2 0.64 0.56 0.43 0.50
Table 5. Changes in the Vital Parameters after the Flight— Only First Flights of Each Work Shift (N ⫽ 95) Difference (Value after the Flight – Value before the Flight) Mean ⫾ SD, Median P HR (bpm) 5.8 ⫾ 9.2, 6.0 ⬍.0001 DBP (mmHg) 0.9 ⫾ 10.5, 0 .8171 SBP (mmHg) 1.4 ⫾ 9.7, 0 .1325 SpO2 (%) -0.3 ⫾ 1.3, 0 .0207
sympathetic activation.8,9 In our study, in fact, the modification of the HR inversely correlated with that of the SpO2. Furthermore, these HR changes may be related as well to effects of hormonal, metabolic, and circulatory modifications September-October 2011
produced by forced vibrations in flight. In fact, in every transportation by air or ground, crewmembers, as well as transported patients, are exposed to vibrations.10 In particular, the helicopters during the flight are subject to an asymmetric, turbulent aerodynamic environment, and rotors induce high vibratory forces. Vibrations are mechanical stimuli characterized by an oscillatory motion that, at specific frequencies, may have harmful effects on the human body. In fact, vibrations induce muscular contraction.11 The soft tissues act as wobbling masses that vibrate in response to 25- to 75-Hz forced vibrations; on the contrary, muscles react to those mechanical stimuli through contraction.12,13 Such muscular contractions cause metabolic responses similar to other forms of mild exercise and increase oxygen consumption for the metabolism of lipids and carbohydrates.14,15 In healthy persons, vibrations are associated with a significant reduction in blood flow of the distal limbs and increased HR. These effects are most evident in the first minutes of the flight.16 From our multivariate models, the changes in HR 273
Table 6. Correlations between Changes in the Vital Parameters—Only First Flights of Each Work Shift (N ⫽ 95) HR DBP SBP SpO2 ET Difference Difference Difference Difference Difference HR difference 0.27 0.19 -0.28 -0.07 (0.0079) (0.0649) (0.0066) (0.5101) DBP difference 0.53 -0.14 -0.08 (⬍0.0001) (0.1631) (0.4224) SBP difference -0.15 0.11 (0.1364) (0.3075) SpO2 difference -0.04 (0.6940)
Flight Minutes -0.03 (0.7553) 0.01 (0.9201) -0.10 (0.3996) -0.09 (0.4101)
Table 7. Association of the Value of Each Vital Parameter after the Flight with the Value of the Parameters before the Flight and the Characteristics of the Flight According to Multivariate Linear Regression Analyses—Only the First Flights of Each Work Shift (N ⫽ 95) Dependent Variables Independent Variables HR SBP DBP SpO2 after the flight after the flight after the flight after the flight Beta P Beta P Beta P Beta P HR before the flight 0.7808 ⬍.0001 0.0652 .5324 0.0065 .9486 -0.0171 .1406 SBP before the flight 0.0076 .9495 0.5607 .0002 0.2732 .0501 0.0034 .8291 DBP before the flight -0.1029 .3943 0.5406 .0935 0.2961 .0338 0.0227 .1491 SpO2 before the flight -0.8641 .4020 0.6812 .5738 0.8914 .4460 0.3150 .0209 BMI -0.1102 .7961 0.3865 .4423 -0.2655 .5839 -0.1494 .0088 Technical role of personnel 5.1349 .1306 1.1582 .7698 2.2729 .5521 -0.8455 .0562 ET before the flight -0.3546 .3878 0.1544 .7486 -0.0979 .8332 0.1180 .0293 Non-ordinary flight 2.6452 .2557 -2.3052 .3987 -2.4868 .3456 0.0351 .9067 Flight duration (min) -0.0901 .3180 -0.0554 .6003 0.0546 .5929 0.0018 .8801 Season (summer vs winter) 5.0507 .5505 -2.3540 .8128 2.6349 .7835 -3.4389 .0026 Model R2 0.65 0.62 0.44 0.55
appear to be affected as well by the role of the flying personnel. In fact, on average, HR after the flight was much higher among technicians than among physicians and nurses, possibly indicating a different level of psychological stress, depending on the tasks that are being performed during the flight. In addition, we observed that flights occurring in the summer were associated with a significant decrease in SpO2 after the flight. Such a parameter was inversely associated with the subject’s BMI, highlighting the importance of personal physical characteristics on metabolism during the flight. One limitation of this study is that the results are not generalizable to pilots, because most of them refused participation. Another important limitation of our research is that the effects of stress on the HEMS crew were only assessed through the measurement of physiological parameters. Because stress is a complex phenomenon, a more thorough evaluation should also include psychological and laboratory tests. However, physiologi274
cal parameters, although of little validity when studying chronic stress, are useful in the assessment of acute stress.17 In addition, the concentration of catecholamines, cortisol, and other stressrelated hormones can be influenced by a number of other factors, such as circadian rhythm,18 nicotine consumption, menstrual phase, oral contraceptive use,19 nutrition, physical activity, and sleep quality.20 Thus, measuring those hormones in the biological samples of the crew in a “real life” setting would have increased the likelihood of confounding and implied the design of a more complicated and resource-consuming research. Our study represents a first step in the assessment of stress among HEMS personnel, and further research taking into consideration psychological evaluations and biochemical markers is warranted.
Conclusions Medical emergencies and prehospital care in helicopter flight are enormous stressors themselves. The crewmembers of Air Medical Journal 30:5
HEMS are exposed to the environmental, physical, physiological, and psychological stressors. Moderate stress tends to positively affect performance of the crewmembers,5 but the mission complexity and time and the operational environment may be very important stressors. The HR changes represent the immediate response to the onset of stress. To recognize the early warning signs of acute stress by a sudden critical event or the subtle signs of “chronic stress” is essential to ensure safety. A major safety factor for critical patients in prehospital care and for HEMS crewmembers themselves is the continuous and effective control of their degree of vulnerability.
References 1. Silbergleit R, Dedrick DK, Pape J, Burney RE. Forces acting during air and ground transport on patients stabilized by standard immobilization techniques. Ann Emerg Med 1991;20:875-7. 2. Sullivent EE, Faul M, Wald MM. Helicopter emergency medical services transport is associated with reduced mortality in injured adults. Prehosp Emerg Care 2010;14(Suppl 1):7-8. 3. Bunis J, Chikani V, Mullins T, Conditt VA, Salvino CK, Bobrow BJ. An analysis of air ambulance utilization for field trauma patients in Arizona. Prehosp Emerg Care 2010;14(Supp 1):7-8. 4. Adams R, Thompson J. Risk management for air ambulance helicopter operators. U.S. Department of transportation; Final report, 1989. 5. Harris Joel S. For helicopter pilots, managing stress is part of flying safely. Flight Safety Foundation—Helicopter Safety. 1995;21:1-6. 6. American Heritage Dictionary of the English Language. Third edition, 1992. 7. Iyer EM, Rattan N, Soodan KS. Effect of hypoxia, noise & vibration stress on human performance and neuro-endocrine reactions. Ind J Aerospace Med 2000;44:21-7. 8. Povea C, Schmitt L, Brugniaux J, Nicolet G, Richalet JP, Fouillot JP. Effects of intermittent hypoxia on heart rate variability during rest and exercise. High Alt Med Biol 2005;6:215-25.
September-October 2011
9. Gilmartin GS, Lynch M, Tamisier R, Weiss JW. Chronic intermittent hypoxia in humans during 28 nights results in blood pressure elevation and increased muscle sympathetic nerve activity. Am J Physiol Heart Circ Physiol 2010;299: H925-H931. 10. McVey J, Petrie DA, Tallon JM. Air versus ground transport of the major trauma patient: a natural experiment. Prehosp Emerg Care 2010;14:45-50. 11. Konstanzer P, Enenki B, Aubourg PA, Cranga P. Recent advances in Eurocopter’s passive and active vibration control. American Helicopter Society 64th Annual Forum. Montreal, Canada, 2008. 12. Wakeling JM, Nigg BM, Rozitis AI. Muscle activity in the lower extremity damps the soft tissue vibrations which occur in response to pulsed and continuous vibrations. J Appl Physiol 2002;93:1093-103. 13. Wakeling JM, Nigg BM. Modification of soft tissue vibrations in the leg by muscular activity. J Appl Physiol 2001;90:412-20. 14. Cardinale M, Wakeling J. Whole body vibration exercise: are vibrations good for you? Br J Sports Med 2005;39:585-9. 15. Rittweger J, Beller G, Felsenberg D. Acute physiological effects of exhaustive wholebody vibration exercise in man. Clin Physiol 2000;20:134-42. 16. Lohmann EB, Petrofsky JS, Maloney-Hinds C, Betts-Scwab H, Thorpe D. The effect of whole body vibration on lower extremity skin blood flow in normal subiects. Med Sci Monit 2007;13:CR71-6. 17. Hubbard J.R, Kalimi M, Liberti JP. Handbook of Stress Medicine. Chapter 17. In: Hubbard JR, ed. Biochemical Indicators of Stress. Boca Raton, FL: CRC Press 1997. 18. Haus E, Dumitriu L, Nicolau GY, Bologa S, Sackett-Lundeen L. Circadian rhythms of basic fibroblast growth factor (bFGF), epidermal growth factor (EGF), insulin-like growth factor-1 (IGF-1), insulin-like growth factor binding protein-3 (IGFBP-3), cortisol, and melatonin in women with breast cancer. Chronobiol Int 2001;18:709-27. 19. Robertson D, Selleck K, Suikkari AM, Hurley V, Moohan J, Healy D. Urinary vascular endothelial growth factor concentrations in women undergoing gonadotrophin treatment. Hum Reprod 1995;10:2478-82. 20. Lundberg U. Stress hormones in health and illness: the roles of work and gender. Psychoneuroendocrinology 2005;30:1017-721.
275