a b s t r a c t

Background: Short-distance air medical transport for adult emergency patients does not significantly affect pa- tients’ body temperature and outcomes. This study aimed to examine the influence of long-distance air medical transport on patients’ body temperatures and the relationship between body temperature change and mortality. Methods: We retrospectively enrolled consecutive patients transferred via helicopter or plane from isolated islands to an emergency medical center in Tokyo, Japan between April 2010 and December 2016. Patients’ aver- age body temperature was compared before and after air transport using a paired t-test, and corrections between body temperature change and flight duration were calculated using Pearson’s correlation coefficient. Multivari- able logistic regression models were then used to examine the association between body temperature change and in-hospital mortality.

Results: Of 1253 patients, the median age was 72 years (interquartile range, 60-82 years) and median flight du- ration was 71 min (interquartile range, 54-93 min). In-hospital mortality was 8.5%, and average body tempera- ture was significantly different before and after air transport (36.7 ?C versus 36.3 ?C; difference: -0.36 ?C; 95% confidence interval, -0.30 to -0.42; p b 0.001). There was no correlation between body temperature change and flight duration (r = 0.025, p = 0.371). In-hospital death was significantly associated with

(i) hyperthermia (N38.0 ?C) or normothermia (36.0-37.9 ?C) before air transport and hypothermia after air trans- port (odds ratio, 2.08; 95% confidence interval, 1.20-3.63; p = 0.009), and (ii) winter season (odds ratio, 2.15; 95% confidence interval, 1.08-4.27; p = 0.030).

Conclusion: Physicians should consider body temperature change during long-distance air transport in patients with not only hypothermia but also normothermia or hyperthermia before air transport, especially in winter.

(C) 2018

Introduction

Air medical transport is common in emergency settings and is now the global standard. Although ambient air temperature decreases with altitude, several studies showed that the body temperature of most adult patients did not decline significantly during air medical transport [1-6]. Studies also show that body temperature change is not associated with flight duration [1,2,5,6] and outside air temperature [1-4].

* Corresponding author at: Emergency and Critical Care Center, Tokyo Metropolitan Hiroo Hospital, 2-34-10, Ebisu, Shibuya-ku, Tokyo 150-0013, Japan.

E-mail addresses: [email protected], (M. Nakajima), [email protected], (S. Aso), [email protected], (H. Yasunaga), [email protected], (H. Goto), [email protected] (Y. Yamaguchi).

However, the flight duration in previous studies was relatively short (range, 18-35 min) [1-4,6]. Also, the evaluated outcome in previous studies was body temperature change between before and after air transport. It can be reasonably assumed that patients transported via aircraft over longer distances are more prone to develop hypothermia and unfavorable outcomes. To our knowledge, no studies have ad- dressed the relationship between body temperature change and mor- tality in patients undergoing long-distance air medical transport. For example, one emergency medical center in our region conducts air medical transport for approximately 250 patients a year from isolated islands. Distances range from 100 to 1000 km, and transport usually takes from 30 min to 5 h. These flights cover longer distances and re- quire longer duration than those in previous studies [1-4,6].

The present study aimed to determine whether flight duration and outside air temperature influence body temperature change, and the

https://doi.org/10.1016/j.ajem.2018.04.064

0735-6757/(C) 2018

before air transport and hyperthermia after air transport (“normo to hyper”); hyperthermia before air transport and hypothermia after air transport (“hyper to hypo”); hyperthermia before air transport and nor- mothermia after air transport (“hyper to normo”); and hyperthermia both before and after air transport (“hyper to hyper”). The “normo to hypo” and “hyper to hypo” groups were combined to create a single group (“normo or hyper to hypo”). The “hypo to hyper”, “normo to hyper” and “hyper to hyper” groups were combined to create a single group (“any to hyper”) (Fig. 1).

Abbreviations

T_before body temperature (?C) measured at the local clinic be- fore air transport

T_after body temperature at arrival at our hospital after air transport

APACHE acute physiology and chronic health evaluation; SD standard deviations

IQR interquartile ranges

?T body temperature before air transport – body temper- ature after air transport

CI confidence interval

We also calculated the body temperature change between before and after air transport (?T= T_before – T_after).

Illness severity was evaluated according to the Acute physiology and chronic health evaluation II score [7]. Because the APACHE-II score includes body temperature and age parameters, we calculated this score without body temperature and age parameters (APACHE II – T_after

– age) on the day of admission to our hospital after air transport.

relationship between body temperature change and mortality in adult patients undergoing long-distance air medical transport.

Method

Setting and patients

This was a retrospective cohort study based on data from the medi- cal charts of inpatients admitted to our hospital between April 1, 2010, and December 31, 2016. We enrolled consecutive patients transferred via aircraft to our hospital. We defined long-distance air flight as N100 km or N 30 min’ duration. All patients underwent first-aid care by primary care physicians at a local clinic on each island before air transport; no islands were without clinics and physicians. We had no specific patient-warming protocols during air transport; blankets, ice packs, and cabin heating or cooling systems were used at the discretion of the transport team, but we used no active patient-warming devices. We excluded patients under 16 years of age and patients with cardiac arrest at admission.

Data collection

We collected the following data for each patient: age; sex; date of admission (flight date); diagnoses; duration of flight (minutes); body temperature (?C) measured at the local clinic before air transport (T_before); body temperature at arrival at our hospital after air transport (T_after); severity of illness; and in-hospital death.

Season at admission was divided into spring (March-May), summer (June-August), autumn (September-November), and winter (Decem- ber-February). Diagnosis was categorized into cerebrovascular disease, infectious disease including sepsis, cardiovascular disease, gastrointesti- nal disease, respiratory disease, trauma, post-cardiac arrest, drowning, Consciousness disturbance without intracranial lesion (e.g., seizure and epilepsy), and others (e.g., renal disease and metabolic disease).

Body temperature was measured during examination in the local clinic and at arrival at our hospital. We usually use an eardrum ther- mometer (M30, Terumo Corporation, Shibuya, Japan) or an axillary thermometer (MC-680, Omron Healthcare, Kyoto, Japan) to measure body temperature after flight. These devices differed from those used in each island’s clinic to measure before-flight temperature.

We divided T_before and T_after into three groups: hyperthermia (N38.0

?C), normothermia (36.0-37.9 ?C), and hypothermia (b36.0 ?C) [4]. The following patient categories described body temperature change: hypo- thermia both before and after air transport (“hypo to hypo”); hypother- mia before air transport and normothermia after air transport (“hypo to normo”); hypothermia before air transport and hyperthermia after air transport (“hypo to hyper”); normothermia before air transport and hy- pothermia after air transport (“normo to hypo”); normothermia both before and after air transport (“normo to normo”); normothermia

Outcome

The outcome was All-cause in-hospital mortality.

Statistical analysis

We performed complete case analysis. Continuous variables are pre- sented as means with standard deviations (SD) and medians with inter- quartile ranges (IQR), and categorical variables are reported as count and percentage. Differences in variables between T_before and T_after were compared using a paired t-test. Pearson’s correlation was used to determine the relationship between flight duration and body tempera- ture change (?T). ?T among seasons was compared using one-way analysis of variance. Multivariable logistic regression analysis was per- formed to evaluate factors associated with in-hospital mortality. We in- cluded the following clinically important independent variables: sex; age as a categorical variable; season; body temperature change between before and after air transport as a categorical variable; diagnosis; and APACHE-II score without body temperature and age parameters (APACHE II – T_after – age).

We performed three further analyses to evaluate the effect of the di- agnosis. First, we conducted a sub-group analysis that included only non-trauma patients. Second, we conducted a multivariable logistic re- gression analysis that included diagnosis category divided into trauma and non-trauma because a previous study was conducted for trauma patients only [3], and hypothermia is a risk factors for trauma patients [8]. Third, we conducted a sub-group analysis that included patients not experiencing post-cardiac arrest because post-cardiac arrest pa- tients can have high mortality regardless of body temperature change.

Fig. 1. Flow diagram for selecting the study population.

The threshold for significance was a p-value b0.05, and all statistical analyses were performed using SPSS version 23.0 (IBM Corp., Armonk, NY).

Ethics

This study was approved by the Institutional Review Board of our hospital. Because this study was based on secondary analyses of medical charts, the requirement for informed consent was waived.

Results

Patients’ characteristics

During the study period, 1518 patients were transferred and admit- ted to our hospital via helicopter or plane. We excluded 265 patients who met the exclusion criteria or who had incomplete data, which left 1253 patients for inclusion in the study.

Patients’ characteristics for each body temperature change category are shown in Table 1. Overall, the median patient age was 72 years (IQR, 60-82 years), and median flight duration was 71 min (IQR, 54-93 min). The median APACHE-II was 9 (IQR, 6-14) and APACHE II – T_after – age was 4 (IQR, 2-8). Overall in-hospital mortality was 8.5% (107/1253).

Main analysis

The mean (SD) body temperature before air transport (T_before) was

36.7 (0.94)?C and 36.3 (0.90)?C after air transport (T_after). The difference between T_before and T_after was -0.36 ?C, which was statistically signifi- cant based on the paired t-test (95% confidence interval (CI), -0.30 to

-0.42; p b 0.001) (Fig. 2).

Fig. 3 shows the relationship between body temperature change (?T

= T_before – T_after) and flight duration. There was no significant correla- tion between ?T and flight duration (r = 0.025, p = 0.371). Analysis of variance results showed no significant difference in ?T among the four seasons (p = 0.255).

In multivariate analysis (Table 2), a body temperature category change was significantly associated with an increased risk of in- hospital death. With reference to the “normo to normo” group, the odds ratio (95% CI; p-value) for in-hospital mortality was 2.08

Fig. 2. Comparison of body temperature before and after air transport T_before, body temperature before air transport; T_after, body temperature after air transport Boxes and bars show median values and interquartile ranges. *p b 0.001 with the paired t-test.

(1.20-3.63; p = 0.009) in the “normo or hyper to hypo” group. Winter was significantly associated with an increased risk of in-hospital death compared with spring. Compared with patients with cardiovascular dis- ease, those experiencing post-cardiac arrest were significantly more likely to die. Age and APACHE II – T_after – age was also significantly as- sociated with mortality.

Additional analysis

Multivariable logistic regression analysis that included only non- trauma patients (n = 1064) showed similar results to the main analysis. The “normo or hyper to hypo” group, winter season, post-cardiac arrest, age, and APACHE II – T_after – age were significantly associated with in- creased in-hospital death. In the multivariable analysis that included di- agnosis category divided into trauma and non-trauma, “normo or hyper

Table 1

Patients’ characteristics for each body temperature change category

	Overall		Normo to normo		Normo or Hyper to hypo		Any to hyper		Hypo to normo		Hypo to hypo		Hyper to ormo
	(n = 1253)		(n = 669)		(n = 266)		(n = 42)		(n = 121)		(n = 77)		(n = 78)
Male Season Spring	777 (62.0) 288 (23.0)		413 (61.7) 164 (24.5)		165 (62.0) 58 (21.8)		30 (71.4) 10 (23.8)		70 (57.9) 25 (20.7)		51 (66.2) 16 (20.8)		48 (61.5) 15 (19.2)
Summer	344 (27.5)		201 (30.0)		64 (24.1)		10 (23.8)		34 (28.1)		16 (20.8)		19 (24.4)
Autumn	334 (26.7)		153 (22.9)		84 (31.6)		12 (28.6)		35 (28.9)		23 (29.9)		27 (34.6)
Winter Diagnosis Cerebrovascular disease	287 (22.9) 243 (19.4)		151 (22.6) 134 (20.0)		60 (22.6) 65 (24.4)		10 (23.8) 2 (4.8)		27 (22.3) 26 (21.5)		22 (28.6) 14 (18.2)		17 (21.8) 2 (2.6)
Infectious disease, sepsis	239 (19.1)		110 (16.4)		41 (15.4)		22 (52.4)		8 (6.6)		8 (10.4)		50 (64.1)
gastrointestinal disease	217 (17.3)		122 (18.2)		41 (15.4)		7 (16.7)		20 (16.5)		15 (19.5)		12 (15.4)
Cardiovascular disease	212 (16.9)		117 (17.5)		45 (16.9)		3 (7.1)		28 (23.1)		18 (23.4)		1 (1.3)
Trauma	189 (15.1)		110 (16.4)		34 (12.8)		3 (7.1)		25 (20.7)		11 (14.3)		6 (7.7)
Respiratory disease	39 (3.1)		21 (3.1)		9 (3.4)		2 (4.8)		4 (3.3)		1 (1.3)		2 (2.6)
Disturbance of consciousness	37 (3.0)		22 (3.3)		9 (3.4)		1 (2.4)		2 (1.7)		2 (2.6)		1 (1.3)
Post-cardiac arrest	17 (1.4)		0 (0)		10 (3.8)		0 (0)		2 (1.7)		4 (5.2)		1 (1.3)
Drowning	13 (1.0)		5 (0.7)		1 (0.4)		1 (2.4)		3 (2.5)		2 (2.6)		1 (1.3)
Other	47 (3.8)		28 (4.2)		11 (4.1)		1 (2.4)		3 (2.5)		2 (2.6)		2 (2.6)
In-hospital death	107 (8.5)		34 (5.1)		45 (16.9)		5 (11.9)		6 (5.0)		13 (16.9)		4 (5.1)
Age, years	72 (60-82)		72 (58-82)		76 (65-83)		64 (51-78)		68 (59-79)		72 (63-83)		70 (58-82)
Duration of fright, minutes	71 (54-93)		73 (53-98)		73 (55-90)		71 (56-91)		71 (56-92)		66 (50-86)		66 (55-90)
APACHE II	9 (6-14)		9 (6-13)		11 (8-17)		12 (6-17)		8 (6-11)		12 (8-20)		10 (8-16)
APACHE II – T after – Age	4 (2-8)		4 (2-8)		5 (2-11)		6 (2-11)		4 (2-7)		7 (2-13)		5 (3-10)

Data for categorical variables are shown as n (%). Data for continuous variable are shown as median (interquartile ranges). APACHE II – T after – Age: the acute physiology and chronic health evaluation score without temperature and age component.

Fig. 3. Relationship between body temperature change and flight duration ?T = body temperature before air transport (T_before) – body temperature after air transport (T_after).

to hypo” group, winter season, post-cardiac arrest, age, and APACHE II

– T_after – age were significantly associated with increased in-hospital death. However, diagnosis divided into trauma or non-trauma catego- ries was not associated with mortality. The sub-group analysis that ex- cluded patients with post-cardiac arrest (n = 1236) also showed similar results to the main analysis.

Discussion

We demonstrated that patients’ body temperature decreased signif- icantly during long-distance air transport; however, flight duration was not associated with body temperature change. In-hospital death was

Table 2

Logistic regression for in-hospital mortality (n = 1253)

	Odds ratio	(95% CI)	P value
Sex
Female	Reference = 1
Male	1.05	(0.64-1.72)	0.854
Season
Spring	Reference = 1
Summer	1.20	(0.58-2.48)	0.630
Autumn	1.79	(0.89-3.58)	0.102
Winter	2.15	(1.08-4.27)	0.030?
Body temperature change
Normo to normo	Reference = 1
Hypo to normo	0.91	(0.34-2.46)	0.853
Hyper to normo	0.38	(0.11-1.32)	0.128
Hypo to hypo	1.50	(0.64-3.50)	0.349
Normo or hyper to hypo	2.08	(1.20-3.63)	0.009?
Any to hyper	1.94	(0.65-5.81)	0.235
Diagnosis Cardiovascular disease	Reference = 1
Infectious disease, sepsis	1.45	(0.67-3.17)	0.347
Cerebrovascular disease	1.21	(0.57-2.56)	0.622
Gastrointestinal disease	0.88	(0.38-2.05)	0.761
Trauma	1.09	(0.43-2.76)	0.857
Respiratory disease	1.98	(0.62-6.28)	0.247
Post-cardiac arrest	5.41	(1.30-22.60)	0.021?
Drowning	1.75	(0.24-12.95)	0.583
Disturbance of consciousness	0.19	(0.02-1.63)	0.130
Other	0.38	(0.08-1.72)	0.207
Age	1.03	(1.01-1.05)	0.001?
Duration of flight	1.00	(0.99-1.00)	0.214?
APACHE II – Tafter – Age	1.17	(1.13-1.20)	b0.001?

CI: confidence interval.

APACHE II – T after – Age: the acute physiology and chronic health evaluation score with- out temperature and age component.

* p b 0.05.

significantly associated with (i) normothermia or hyperthermia before air transport and hypothermia after air transport and (ii) winter season. Contrasting with previous observational studies [1-6], body temper- ature change during air transport decreased significantly in our study. The mean difference of -0.36 ?C appears clinically unimportant; how- ever, this value was based on data from patients whose body tempera- ture increased, decreased, or did not change. Therefore, the value was an average of all cases. Body temperature change in each patient is more

important than mean body temperature change.

Several previous studies stated that body temperature before air transport was the most significant risk factor [5,6]. Our study showed that the “normo or hyper to hypo” group was associated with higher in-hospital death, indicating that body temperature monitoring during long-distance air transport is important for patients with not only hypo- thermia before air transport but also normothermia or hyperthermia before air transport.

In our study, hyperthermia at admission and “hypo to hypo” group were not associated with mortality. Previous studies demonstrated that hyperthermia was not associated with mortality, whereas hypo- thermia was associated with that in critically ill patients [9,10]. In our study, the number of patients in the “any to hyper” group (n = 42) and “hypo to hypo” group (n = 77) may have been too small to detect significance.

Our results demonstrated no significant difference in ?T among the seasons; however, winter was significantly associated with an increased risk of in-hospital death in the multivariate analysis. Disease type and severity in winter may have affected this association. Post-cardiac arrest was significantly associated with higher mortality, but trauma was not associated with higher mortality even though hypothermia is part of the “deadly triad” for trauma patients [8]. Clinicians should pay atten- tion to body temperature for both non-trauma and trauma patients.

Several limitations of this study should be acknowledged. First, this was an observational study, and we had no standard protocol to mea- sure body temperature. Information regarding additional blankets, iced pads, and cabin heating or cooling were lacking. We also had no data for air temperature in the aircraft cabin or outside; however, a pre- vious prospective observational study showed that body temperature change was not significantly associated with air temperature in the air- craft cabin or outside [4]. Second, patients are exposed to outside air separate from the flight, including transfer from the scene to the airport and waiting for the flight; our data also lacked this information. Third, our records recorded only the primary disease and included no comor- bidity data. Fourth, we used the APACHE II score to adjust for disease se- verity, which is based on several parameters within 24 h after admission in the intensive care unit and may not reflect disease severity before hospitalization. Finally, we had no information on the use of neuromus- cular blockades or blood transfusions, which are reported risk factors [6,11]. However, several studies showed that these factors were not as- sociated with body temperature change during air transport [1,4,5]. We also had no information on the use of vasopressors, vasodilators, and sedatives. Each of these factors may have influenced body temperature change.

Conclusion

Our analysis suggests that body temperature may decrease during long-distance air transport. Physicians should consider body tempera- ture during long-distance air transport in patients with not only hypo- thermia but also normothermia or hyperthermia before air transport especially in winter.

Funding

This research did not receive any specific grant from funding agen- cies in the public, commercial, or not-for-profit sectors.

Declarations of interest

None.

Acknowledgements

We are indebted to Miwa Suzuki for assistance with data collection; to staff members who treated patients in each island clinic and intro- duced patients to our facility; and to the Tokyo Fire Department and Maritime Self-Defense Force who collaborated with us on the air medi- cal transport.

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