Association between baseline blood pressure variability and left heart function following short‐term extreme cold exposure

Abstract

Extreme cold exposure has been widely considered as a cardiac stress and may result in cardiac function decompensation. This study was to examine the risk factors that contribute to changes in cardiovascular indicators of cardiac function following extreme cold exposure and to provide valuable insights into the preservation of cardiac function and the cardiac adaptation that occur in real‐world cold environment. Seventy subjects were exposed to cold outside (Mohe, mean temperature −17 to −34°C) for one day, and were monitored by a 24‐h ambulatory blood pressure device and underwent echocardiography examination before and after extreme cold exposure. After exposure to extreme cold, 41 subjects exhibited an increase in ejection fraction (EF), while 29 subjects experienced a decrease. Subjects with elevated EF had lower baseline coefficients of variation (CV) in blood pressure compared to those in the EF decrease group. Additionally, the average real variability (ARV) of blood pressure was also significantly lower in the EF increase group. Multivariate regression analysis indicated that both baseline CV and ARV of blood pressure were independent risk factors for EF decrease, and both indicators proved effective for prognostic evaluation. Correlation analysis revealed a correlation between baseline blood pressure CV and ARV, as well as EF variation after exposure to extreme cold environment. Our research clearly indicated that baseline cardiovascular indicators were closely associated with the changes in EF after extreme cold exposure. Furthermore, baseline blood pressure variability could effectively predict alterations in left cardiac functions when individuals were exposed to extreme cold environment.

1. INTRODUCTION

Recently, with the advancement of polar development strategies by countries around the world, the number of personnel involved in entering and stationing in extreme cold regions has increased significantly. Under the dynamic balance of heat production and dissipation, the human body possesses a certain resistance to sudden shifts in ambient temperature. However, when exposure to prolonged extreme cold environments, the core temperature of the human body will change, posing a considerable challenge on organ metabolism and function. ¹ Cold can trigger a cascade of intricate alterations within the autonomic nervous system, affecting both the function and structure of the heart and blood vessels. Notably, compromised cardiac performance may influence oxygen delivery to tissues, and decreased cardiac functions were associated with cardiovascular diseases. ² Consequently, the prediction and assessment of cardiac responses to extreme cold exposure among healthy individuals are of great significance.

Blood pressure (BP) is a physiological parameter that undergoes continuous dynamic fluctuations over time. Blood pressure variability (BPV) represents the size and patterns characterizing these BP variations. It is also viewed as an accurate assessment of BP status and may also reflect the true cardiovascular system function. ³ , ⁴ BPV is closely related to autonomic nervous function, and accumulating evidence suggests that BPV is associated with an increased risk of end‐organ damage, adverse cardiovascular events and all‐cause mortality, which is independent of mean BP. ⁵ , ⁶ The contradictory results in current findings may be partly due to different methods of BPV measurements. ⁷ , ⁸ , ⁹ However, few studies have focused on 24‐h BP variations in extreme environmental conditions. There may be a potential relationship between BPV and abnormal changes of cardiac function after exposure to an extreme cold environment.

Thus, in this retrospective study, we analyzed data of 24‐h ambulatory blood pressure (ABP) monitoring and echocardiographic assessments obtained before and after short‐term extreme cold exposure. Subjects were categorized increased ejection fraction (EF) and decreased EF groups based on changes in their left ventricular (LV) function. We aimed to investigate cardiovascular adaptation, the impact of BPV, and provide some insights into protecting cardiac function and preventing cardiovascular diseases in the real‐world cold environment.

2. MATERIALS AND METHODS

2.1. Study population and ethical considerations

Mohe City (53.4°N, 122.3°E), Heilongjiang Province, was chosen as the study site. The mean temperature is −5.5°C and the average temperature of each month is below 0°C for 8 months, and it is the coldest county in China. Subjects included in the study were performed ABP monitoring and echocardiography both before (temperature 16°C ± 2°C) and after (mean high temperature −17°C, mean low temperature −34°C, mean wind speed 5.8 m/s) exposure to cold environment in Dem 2023. All subjects spent a whole day outdoors, performed daily activities during the daytime and rested in tents at nighttime. Winter clothing put on outside slowed down or even prevented superficial cooling of most areas of the body shin, and the main cold exposure employed in the study was respiratory tract and forehead skin. Informed consent was obtained, and all subjects underwent a comprehensive medical examination before departure. After data collection, the data were summarized and retrospectively analyzed (Figure S1). Subject data with the following conditions were not analyzed, including: (1) Any clinical conditions that may affect outdoor work in cold environment, including known pulmonary diseases, cardiovascular diseases, hematological diseases, cancer and pregnancy. (2) Use of any medication. (3) 24‐h ABP monitor recordings of less than 80% of the total data recorded and lacking echocardiography data during extreme cold exposure. In total, 70 subjects were analyzed finally. This study was conducted in agreement with the Declaration of Helsinki and was approved by the Human Ethics Committee of the PLA General Hospital.

2.2. BP measurement and BP parameters calculation

Two well‐trained cardiovascular physicians recorded BP data using an ABP measurement device (Spacelabs 90207, Redmond, WA, USA). The BP cuff was applied to the non‐dominant arm on a weekday morning and was removed 24 h later. Subjects remained still during the measurement, avoided unusual physical activities and followed a standard schedule before and after exposure to extreme cold environment. Daytime and nighttime were defined as 6:00–22:00 and 22:00–6:00, respectively. ¹⁰ The recorders measured BP every 30 min during daytime and every 60 min during nighttime. ¹¹ The lowest BP was defined as the average BP of three readings centered on the lowest nighttime reading. Morning BP surge was calculated by the difference value between Morning BP and Pre‐awaking SBP. Nocturnal BP fall was calculated by the value of nocturnal decline in BP (daytime BP—nighttime BP)*100/daytime BP. Blood pressure variability (BPV) was determined by coefficient of variation (CV) and average real variability (ARV) of BP. ¹² The CV of BP was calculated using the formula: CV = standard deviation of BP*100/mean BP. CVs and CVd denoted the CV of systolic blood pressure (SBP) and diastolic blood pressure (DBP), respectively. The ARV of BP was calculated by the following formula:

$$\mathrm{ARV}=\frac{1}{N-1}\sum _{K=1}^{\mathrm{N}-1}\left|BPk+1-BPk\right|$$

where K ranges from 1 to N, and N denotes the number of valid BP measurements in the data corresponding to a given subject. ARVs and ARVd denoted the ARV of SBP and DBP, respectively.

2.3. Calculation of the left ventricular function parameters

Echocardiographic examination was performed using an ultrasound machine (CX50, Philips Ultrasound System, Andover, MA, USA) to acquire LV data. Images were saved digitally for subsequent offline analysis using QLAB software (QLAB 10.5, Philips Healthcare, Andover, MA, USA). Two sonographers blinded to the subjects and ultrasonography operators analyzed the echocardiographic data. Measurements of LV dimensions and volumes were performed by a computerized analysis software system. EF was calculated by the LV volume data using double‐plane Simpson method. Mitral inflow pattern from the tips level was analyzed for peak early diastolic velocity (E) as well as late diastolic velocity (A), and E/A. Mitral annulus early diastolic velocity (e′) was measured at the septal and lateral mitral annulus and the E/e′ ratio was calculated by the mean septal E/e′ ratio and mean lateral E/e′ ratio. Effective arterial elastance (Ea) and end‐systolic elastance (Ees) were computed by the formulas: SBP x 0.9/stroke volume and SBP x 0.9/end‐systolic volume (ESV), while ventricular‐arterial decoupling (VAC) was the ratio of Ea and Ees. ¹³ LV mass index was calculated according to previous study. ¹⁴ We used a two‐dimensional ultrasound speckle tracking imaging technique to measure LV torsion, LV untwisting rate, and LV strain by the software. We defined LV torsion as the difference between the apical and basal angle during systole around the longitudinal LV axis relative to the starting position, and the untwisting rate was the maximum untwisting velocity calculated by the angle during diastole. The global longitudinal strain (GLS) was calculated by averaging all the values of the regional peak longitudinal strain obtained in two‐chamber, three‐chamber, and four‐chamber apical views. The global circumferential strain (GCS) was assessed as the average of three LV regional values measured in the parasternal short‐axis view at the basal level. Measurements of three cardiac cycles were averaged.

2.4. Echocardiography reproducibility

Reproducibility of main echocardiographic measurements was assessed in 20 randomly selected subjects. Interobserver variability was tested by two different physicians, and intraobserver variability was tested by the same physician at least 1 month apart. Both the interobserver and intraobserver variabilities were determined using the intraclass correlation coefficient. The ICC values of intraclass correlation coefficient were all over 0.85 and p value < .001.

2.5. Statistical analysis

Continuous variables were presented as mean ± standard deviation. Differences in measurements between different groups with normal distribution were tested using independent‐sample t‐test or paired t‐test, while the data that did not fit a normal distribution were analyzed by Wilcoxon rank sum test or Mann–Whitney U test. Categorical data were presented as percentages (%) and were compared by the chi‐square test, continuity correction, or Fisher exact test, as appropriate. Binary logistic regression was used to predict the risk factors of EF decrease after altitude exposure, and ROC curve was computed to evaluate the effectiveness of the prediction. In addition, Spearman correlation coefficients were used to determine the correlation between baseline BP variability indexes and cardiac function variation after HA exposure. Statistical significance was assumed at p < .05. Statistical analyses were performed by SPSS software 27 (IBM, Armonk, NY, USA). Statistical power calculations were performed using the PASS software, version 15 (NCSS, LLC, Kaysville, UT, USA). The results suggested that 70 subjects would provide more than 80% power to detect differences in parameters between subgroups using a two‐sided alpha of 0.05.

3. RESULTS

3.1. Basis of grouping and basic parameters

End‐diastolic volume (EDV) and ESV were both significantly decreased in the total study population. E/e′ and E/A were reduced after exposure to extreme cold environment, indicating a decreased diastolic function. On the other hand, GLS were higher in cold than in normal temperature. Moreover, ultrasound speckle tracking measurements indicated that torsion and untwisting rates increased. Furthermore, while Ees and Ea were both obviously elevated and VAC was decreased after exposure to extreme cold environment (Table 1). Finally, 41 subjects underwent EF increase while 29 subjects developed EF decrease after extreme cold exposure (Figure 1). Subjects were divided into two groups according to the variation of EF, and their demographic parameters, including age, BMI, gender, race, and smoking and alcohol history are shown in Table 2.

TABLE 1.

Effect of extreme cold exposure on LV function.

Variables	Before extreme cold exposure (n = 70)	After extreme cold exposure (n = 70)	Variation (n = 70)	P value
EDV, mL	111.71 ± 21.86	102.23 ± 18.76	−9.48 ± 21.44	.007
ESV, mL	45.70 ± 10.55	40.07 ± 10.29	−5.63 ± 12.07	.002
EF, %	59.32 ± 4.22	60.99 ± 5.88	1.67 ± 6.20	.056
LVMI, g/m2	79.40 ± 16.54	80.32 ± 16.01	0.92 ± 21.44	.740
E/A	1.87 ± 0.60	1.44 ± 0.35	−0.43 ± 0.59	<.001
E/e′	6.54 ± 1.09	5.87 ± 1.22	−0.67 ± 1.19	<.001
GLS, %	20.13 ± 2.05	21.12 ± 2.49	0.99 ± 16.52	.001
GCS, %	25.64 ± 2.74	25.21 ± 2.43	−0.43 ± 3.02	.328
Torsion, °	11.11 ± 3.10	14.87 ± 4.39	3.09 ± 4.27	.001
Untwisting rate,°/s	78.51 ± 34.60	97.48 ± 40.70	18.97 ± 29.32	.004
Ees, mmHg/mL	2.48 ± 1.02	2.92 ± 0.87	0.44 ± 1.25	.006
Ea, mmHg/mL	1.64 ± 0.35	1.82 ± 0.39	0.18 ± 0.49	.005
VAC	0.69 ± 0.12	0.66 ± 0.17	−0.04 ± 0.18	.012

Values are presented as mean ± standard deviation & percentage (%).

Abbreviations: LV, left ventricle; LVMI, left ventricular mass index; GLS, global longitudinal strain; GCS, global circumferential strain; EDV, end‐diastolic volume; ESV, end‐systolic volume; Ees, end‐systolic elastance; Ea, effective arterial elastance; VAC, ventricular‐arterial coupling; EF, ejection fraction; E/A, peak early diastolic velocity/late diastolic velocity; E/e’, peak early diastolic velocity/early diastolic velocity.

P value, total individuals before compared with after extreme cold exposure.

FIGURE 1.

Basis of grouping. EF, ejection fraction.

TABLE 2.

Demographic parameters.

Variables	All (n = 70)	EF increased (n = 41)	EF decreased (n = 29)	P value
Age, years	26.90 ± 6.83	27.29 ± 6.23	26.34 ± 7.67	.571
BMI, kg/m2	22.00 ± 2.15	22.25 ± 2.16	21.65 ± 2.11	.250
Females	26 (37.1%)	13 (31.7%)	13 (44.8%)	.263
Tibetan	1 (1.4%)	0 (0.0%)	1 (3.4%)	1.000
Living history of cold zone	19 (27.14%)	12 (29.3%)	7 (24.1%)	.634
Alcohol	14 (20.0%)	10 (24.4%)	4 (13.8%)	.587
Cigarette smoking	27 (38.6%)	14 (34.1%)	13 (44.8%)	.366

Values are presented as mean ± standard deviation & percentage (%).

Abbreviations: BMI, body mass index; EF, ejection fraction.

3.2. Differences in BP, BPV, and LV cardiac function between groups

No statistical difference was found in heart rate (HR) and BP levels between the two groups before extreme cold exposure. Subjects in the EF increased group had a lower daytime CV (daytime CVs 16.59 ± 4.75 vs. 19.80 ± 4.48, p = .007; daytime CVd 19.59 ± 5.39 vs. 24.64 ± 7.10, p = .002) and a lower nighttime CV (nighttime CVs 10.74 ± 4.67 vs. 14.39 ± 6.02, p = .009; nighttime CVd 15.18 ± 6.28 vs. 21.22 ± 10.92, p = .010) before extreme cold exposure. Moreover, daytime (daytime ARVs 16.52 ± 4.46 vs. 20.28 ± 6.15, p = .003; daytime ARVd 12.47 ± 3.58 vs. 15.98 ± 5.74, p = .004) and nighttime (nighttime ARVs 11.60 ± 5.24 vs. 17.05 ± 7.63, p = .002; nighttime ARVd 8.73 ± 3.91 vs. 12.20 ± 8.80, p = .028) ARV were also significantly lower in the EF increased group than in the EF decreased group before extreme cold exposure. After exposure to extreme cold environment, daytime CVd increased in the EF increased group but declined in the EF decreased group (Table 3 and Figure S2).

TABLE 3.

Differences of BP, BPV and LV cardiac function between groups.

	Before extreme cold exposure			After extreme cold exposure			Variation
Variables	EF increased (n = 41)	EF decreased (n = 29)	P value	EF increased (n = 41)	EF decreased (n = 29)	P value	EF increased (n = 41)	EF decreased (n = 29)	P value
24‐h HR, bpm	73.27 ± 8.09	73.15 ± 6.00	0.945	80.13 ± 8.04	76.67 ± 6.58	0.061	6.86 ± 7.85	3.53 ± 7.17	.075
Daytime HR, bpm	77.47 ± 8.85	76.38 ± 6.49	0.574	84.11 ± 8.02	80.16 ± 6.11	0.029	6.64 ± 8.47	3.78 ± 7.05	.141
Nighttime HR, bpm	57.91 ± 8.50	61.45 ± 8.45	0.090	65.92 ± 11.44	64.34 ± 10.03	0.552	8.01 ± 9.34	2.89 ± 9.57	.029
BP characteristic, mmHg
24‐h SBP	118.34 ± 8.35	119.56 ± 9.32	0.567	127.00 ± 7.63	124.70 ± 10.13	0.281	8.66 ± 6.76	5.14 ± 7.79	.047
Daytime SBP	121.45 ± 9.23	122.50 ± 10.57	0.660	130.77 ± 7.97	127.39 ± 10.81	0.136	9.33 ± 8.49	4.89 ± 9.99	.049
Nighttime SBP	106.92 ± 10.06	109.20 ± 10.62	0.365	113.56 ± 10.33	114.90 ± 12.69	0.631	6.64 ± 8.76	5.70 ± 11.08	.692
24‐h DBP	70.02 ± 6.88	70.51 ± 5.50	0.749	76.54 ± 5.97	75.16 ± 4.61	0.301	6.52 ± 5.55	4.64 ± 5.70	.173
Daytime DBP	72.49 ± 6.84	72.83 ± 6.41	0.833	79.26 ± 5.84	77.45 ± 4.85	0.178	6.77 ± 6.07	4.62 ± 7.16	.181
Nighttime DBP	60.95 ± 8.89	62.09 ± 6.27	0.553	66.80 ± 8.38	67.10 ± 9.49	0.889	5.85 ± 8.08	5.00 ± 9.09	.684
Nocturnal SBP fall, %	11.65 ± 8.67	10.44 ± 9.40	0.489	13.10 ± 6.47	9.58 ± 9.09	0.080	1.45 ± 9.62	−0.86 ± 12.18	.240
Nocturnal DBP fall, %	15.90 ± 8.77	14.27 ± 9.90	0.642	15.81 ± 7.32	13.16 ± 12.52	0.314	−0.09 ± 10.81	−1.11 ± 15.39	.463
Morning SBP surge	9.46 ± 16.86	12.12 ± 16.06	0.463	6.13 ± 18.39	9.43 ± 16.35	0.690	−3.33 ± 23.16	−2.69 ± 20.83	.877
Morning DBP surge	9.85 ± 11.38	13.03 ± 11.00	0.291	7.74 ± 13.12	9.52 ± 11.00	0.672	−2.12 ± 16.55	−3.51 ± 12.20	.761
Lowest night‐time SBP	101.54 ± 11.20	102.24 ± 13.49	0.814	113.22 ± 14.01	116.48 ± 12.42	0.738	11.68 ± 15.60	14.25 ± 17.87	.387
Lowest night‐time DBP	56.74 ± 8.52	58.41 ± 10.72	0.471	61.73 ± 9.32	62.59 ± 10.09	0.716	4.99 ± 10.11	4.18 ± 13.96	.924
24‐h CVs	16.88 ± 4.96	19.90 ± 4.80	0.013	17.37 ± 4.19	18.32 ± 4.93	0.389	0.49 ± 5.30	−1.58 ± 5.26	.111
Daytime CVs	16.59 ± 4.75	19.80 ± 4.48	0.007	17.01 ± 4.25	18.37 ± 4.68	0.184	0.42 ± 5.27	−1.43 ± 5.26	.087
Nighttime CVs	10.74 ± 4.67	14.39 ± 6.02	0.009	11.57 ± 4.90	12.11 ± 7.62	0.563	0.84 ± 7.08	−2.28 ± 8.93	0.081
24‐h CVd	20.50 ± 5.60	25.27 ± 7.68	0.004	21.99 ± 5.50	22.97 ± 6.72	0.505	1.49 ± 6.83	−2.30 ± 8.41	.042
Daytime CVd	19.59 ± 5.39	24.64 ± 7.10	0.002	21.54 ± 6.16	22.34 ± 6.65	0.743	1.94 ± 7.10	−2.30 ± 8.41	.022
Nighttime CVd	15.18 ± 6.28	21.22 ± 10.92	0.010	14.51 ± 6.38	16.53 ± 7.56	0.260	−0.67 ± 7.57	−4.69 ± 13.79	.192
24‐h ARVs	15.45 ± 3.60	19.41 ± 5.07	<0.001	18.48 ± 4.27	20.52 ± 5.93	0.099	3.03 ± 4.74	1.11 ± 6.58	.161
Daytime ARVs	16.52 ± 4.46	20.28 ± 6.15	0.003	20.20 ± 5.27	22.51 ± 6.65	0.109	3.68 ± 5.71	2.23 ± 7.51	.265
Nighttime ARVs	11.60 ± 5.24	17.05 ± 7.63	0.002	9.86 ± 3.44	12.11 ± 6.31	0.835	1.39 ± 7.98	−3.06 ± 11.62	.151
24‐h ARVd	11.68 ± 2.88	15.06 ± 5.46	0.001	14.34 ± 4.40	15.68 ± 4.44	0.218	2.66 ± 4.71	0.62 ± 7.03	.151
Daytime ARVd	12.47 ± 3.58	15.98 ± 5.74	0.004	15.76 ± 5.58	17.17 ± 5.74	0.286	3.29 ± 5.87	3.31 ± 16.04	.308
Nighttime ARVd	8.73 ± 3.91	12.20 ± 8.80	0.028	9.86 ± 3.34	12.11 ± 6.32	0.346	1.13 ± 4.71	−0.09 ± 11.52	.802
Cardiac function characteristic
EDV, ml	112.94 ± 18.26	109.97 ± 26.38	0.579	101.57 ± 17.78	103.17 ± 20.36	0.727	−11.37 ± 21.68	−6.80 ± 21.19	.337
ESV, ml	47.33 ± 9.02	43.40 ± 12.20	0.126	36.69 ± 8.74	44.86 ± 10.55	0.004	−10.64 ± 10.44	1.45 ± 10.71	<.001
EF, %	58.19 ± 3.46	60.93 ± 4.72	0.007	64.10 ± 4.28	56.60 ± 5.00	<0.001	5.91 ± 3.39	−4.33 ± 3.82	<.001
LVMI, g/m2	79.74 ± 15.39	78.92 ± 18.32	0.841	80.12 ± 14.30	80.60 ± 18.43	0.668	0.38 ± 17.04	1.68 ± 16.01	.981
E/A	1.86 ± 0.56	1.88 ± 0.66	0.971	1.45 ± 0.40	1.43 ± 0.29	0.872	−0.41 ± 0.57	−0.46 ± 0.62	.867
E/e’	6.46 ± 1.19	6.66 ± 0.93	0.267	5.64 ± 1.16	6.19 ± 1.25	0.083	−0.82 ± 1.29	−0.46 ± 1.02	.208
GLS, %	20.42 ± 1.89	19.71 ± 2.24	0.224	21.86 ± 2.23	20.07 ± 2.50	0.003	1.44 ± 1.78	0.35 ± 2.10	.033
GCS, %	25.49 ± 2.60	25.85 ± 2.96	0.463	25.57 ± 2.55	24.70 ± 2.19	0.328	0.08 ± 3.25	−1.15 ± 2.54	.167
Untwisting rate,°/s	77.54 ± 31.24	79.87 ± 39.41	0.896	98.54 ± 37.63	95.97 ± 45.33	0.663	21.00 ± 32.72	16.10 ± 23.98	.516
Torsion,°	10.93 ± 2.98	12.35 ± 3.95	0.151	14.35 ± 4.01	14.98 ± 4.67	0.779	3.41 ± 4.44	2.63 ± 4.05	.633
Ees, mmHg/ml	2.27 ± 0.50	2.77 ± 1.43	0.039	3.18 ± 0.95	2.55 ± 0.56	0.005	0.92 ± 1.01	−0.22 ± 1.27	<.001
Ea, mmHg/ml	1.61 ± 0.25	1.69 ± 0.45	0.858	1.74 ± 0.38	1.94 ± 0.39	0.028	0.13 ± 0.45	0.25 ± 0.54	.270
VAC	0.72 ± 0.10	0.65 ± 0.12	0.007	0.57 ± 0.11	0.78 ± 0.17	<0.001	−0.16 ± 0.09	0.13 ± 0.13	<.001

Values are presented as mean ± standard deviation.

Abbreviations: LV, left ventricle; LVMI, left ventricular mass index; HR, heart rate; BP, blood pressure; BPV, blood pressure variability; SBP, systolic blood pressure; DBP, diastolic blood pressure; CVs, coefficient of SBP variation; CVd, coefficient of DBP variation; ARVs, average real variability of SBP; ARVd, average real variability of DBP; GLS: global longitudinal strain; GCS, global circumferential strain; EDV, end‐diastolic volume; ESV, end‐systolic volume; Ees, end‐systolic elastance; Ea: effective arterial elastance; VAC, ventricular‐arterial coupling; EF, ejection fraction; E/A, peak early diastolic velocity/late diastolic velocity; E/e’, peak early diastolic velocity/early diastolic velocity.

There was no difference in cardiac diastolic function between the two groups both before and after extreme cold exposure. Moreover, subjects in the EF increased group showed a relatively lower EF before exposure to extreme cold environment, we found that the LV cardiac systolic mechanical indices were not significantly different. It was worth noting that, compared with subjects in the decreased group, subjects with increased EF after extreme cold exposure also showed a significant elevation of GLS (1.44 ± 1.78 vs. 0.35 ± 2.10, p = .033) and Ees (0.92 ± 1.01 vs. −0.22 ± 1.27, p < .001) and a decrease of VAC (−0.16 ± 0.09 vs. 0.13 ± 0.13, p < .001), which also demonstrated an increased myocardial contractility and systolic function of LV (Table 3).

3.3. Risk factors for LV cardiac function variation

We looked for the independent risk factors of EF increase after exposure to extreme cold environment. In the univariate analysis, we adjusted factors of age, sex, BMI, smoking and drinking status, as well as cold zone exposure history. The results of the regression analysis showed that between the baseline BPV indexes, daytime CVs (OR = 0.83, p = .008), daytime CVd (OR = 0.90, p = .011), nighttime CVs (OR = 0.89, p = .026), nighttime CVd (OR = 0.92, p = .044), daytime ARVs (OR = 0.86, p = .013), daytime ARVd (OR = 0.84, p = .006), nighttime ARVs (OR = 0.87, p = .003), and nighttime ARVd (OR = 0.86, p = .032) were independent risk factors for EF decrease after extreme cold exposure (Table 4). ROC curve analysis was performed to test the reliability of lower daytime BPV for predicting EF increase after extreme cold exposure. Daytime CVs (area under the curve [AUC] = 0.691), daytime CVd (AUC = 0.718), nighttime CVs (AUC = 0.685), nighttime CVd (AUC = 0.683), daytime ARVs (AUC = 0.707), daytime ARVd (AUC = 0.701), and nighttime ARVs (AUC = 0.717) all had effective prognostic value (Figure 2).

TABLE 4.

Risk factors of LV cardiac function variation.

Variable	Unadjusted analysis		Adjusted analysis
	OR (95% CI)	P value	OR (95% CI)	P value
Daytime SBP	0.99 (0.94–1.04)	.655	0.96 (0.90–1.02)	.212
Nighttime SBP	0.98 (0.93–1.03)	.360	0.94 (0.88–1.00)	.060
Daytime DBP	0.99 (0.92–1.07)	.830	0.95 (0.87–1.04)	.288
Nighttime DBP	0.98 (0.92–1.04)	.549	0.93 (0.85–1.01)	.089
Daytime CVs	0.86 (0.77–0.96)	.009	0.83 (0.73–0.95)	.008
Nighttime CVs	0.88 (0.79–0.97)	.010	0.89 (0.80–0.99)	.026
Daytime CVd	0.88 (0.81–0.96)	.003	0.90 (0.83–0.98)	.011
Nighttime CVd	0.91 (0.85–0.98)	.011	0.92 (0.84–1.00)	.044
Daytime ARVs	0.87 (0.78–0.96)	.008	0.86 (0.76–0.97)	.013
Nighttime ARVs	0.88 (0.80–0.95)	.002	0.87 (0.79–0.95)	.003
Daytime ARVd	0.84 (0.70–0.93)	.006	0.84 (0.73–0.95)	.006
Nighttime ARVd	0.89 (0.80–1.00)	.044	0.86 (0.74–0.99)	.032

Abbreviations: SBP, systolic blood pressure; DBP, diastolic blood pressure; CVs, coefficient of SBP variation; CVd, coefficient of DBP variation; ARVs, average real variability of SBP; ARVd, average real variability of DBP.

FIGURE 2.

ROC curve of baseline daytime BPV predictive EF increase after extreme cold exposure. CVs, coefficient of SBP variation; CVd, coefficient of DBP variation; ARVs, average real variability of SBP; ARVd: average real variability of DBP; SBP, systolic blood pressure; DBP, diastolic blood pressure; EF, ejection fraction.

3.4. Correlation between baseline BPV and LV cardiac function variation

In order to more effectively evaluate the relationship between EF changes during extreme cold exposure and BPV, we analyzed the correlation between the variation in EF and the baseline BPV indexes. The daytime CV (daytime CVs, R = −0.320, p = .007; daytime CVd, R = −0.337, p = .004), nighttime CV (nighttime CVs, R = −0.405, p < .001; nighttime CVd, R = −0.357, p = .002), daytime ARV (daytime ARVs, R = −0.348, p = 0.003; daytime ARVd, R = −0.286, p = .016) as well as nighttime ARV (nighttime ARVs, R = −0.428, p < .001; nighttime ARVd, R = −0.292, p = .014) were correlated with EF variation after exposure to extreme cold environment (Figure 3).

FIGURE 3.

Correlation between baseline daytime BPV and EF variation. CVs, coefficient of SBP variation; CVd, coefficient of DBP variation; ARVs, average real variability of SBP; ARVd: average real variability of DBP; SBP, systolic blood pressure; DBP, diastolic blood pressure; EF, ejection fraction.

4. DISCUSSION

Our research was conducted in an extremely cold region, providing an authentic outdoor setting for a comprehensive analysis of physiological responses to extreme cold stress. To the best of our knowledge, this is the first study and largest cohort performed ABP monitoring to analyze changes in BP characteristics and LV functions following exposure to extreme cold environment. Our findings revealed that short‐term extreme cold exposure can induce both increase and decrease of LV cardiac systolic function in healthy individuals. Subjects with an elevated EF exhibited significantly lower baseline BPV compared to those with decreased EF. Furthermore, we found that baseline BPV was associated with and had strong predictive ability for variations in LV cardiac systolic function. As a result, BPV may serve as a potential target for protecting cardiac function during extreme cold exposure.

4.1. Cardiovascular responses after cold exposure

Cold exposure generally leads to notable alterations in core temperature, primarily manifesting as a decrease in skin temperature. ¹⁵ , ¹⁶ This shift in skin temperature subsequently impacts various physiological indicators through neurohumoral regulation. Prior researches have demonstrated that alterations in skin temperature following cold exposure can be modulated through various strategies such as cold acclimatization or increased clothing insulation, thereby influencing bodily functions, particularly certain circulatory function indicators. ¹⁷ , ¹⁸ , ¹⁹ After cold exposure, cardiovascular responses can vary from different regions (forms) of cooling, which include whole‐body skin, restricted local exposure to facial skin, hands (cold pressor test), and the respiratory tract (cold air inhalation). ²⁰ The enhanced sympathetic nerve activity caused by decreased skin temperature during cold exposure stimulates the release of catecholamines, resulting in vasoconstriction of both peripheral and visceral arteries. ²¹ Additionally, the renin‐angiotensin‐aldosterone system is also involved. ²² These physiological responses lead to increased BP and elevated cardiac load. Moreover, elderly individuals often exhibit a heightened BP response towards cold exposure. This can be attributed to their reduced vascular function, which is associated with increased arterial stiffness. ²³ In studies where the cold pressor test or cold air inhalation was employed, an increase in HR was observed, indicating a strong sympathetic reflex. However, in other experimental reports involving skin cooling with or without facial exposure to cold, HR remained largely unchanged or even decreased. ²⁰ A recent study conducted in a climate chamber exposed to extreme cold (−15°C) have also demonstrated an increase of BP and a decrease of HR in response to cold environmental exposure. ¹⁶ Additionally, Kiess and coworkers ²⁴ found that cold exposure has significant hemodynamic consequences in healthy individuals. An initial increase in EF followed by a progressive decline was seen during exposure to cold room (1°C). In subsequent studies, the focus was primarily on changes in LV function during cold pressor testing. Notably, the E/A ratio was significantly decreased but as untwisting velocity increased, diastolic relaxation may not actually be impaired. ²⁵ , ²⁶ While several studies found only minor changes in EDV, ESV, and EF without achieving statistical significance, cardiac output (CO) and cardiac work index were both significantly increased compared to baseline levels after cold pressor testing. This increase can be interpreted as a compensatory adaptation to maintain oxygen supply for cardiac muscle cells. ²⁷ , ²⁸ However, other studies reported a decrease in EF following exposure to the test. ²⁹ , ³⁰ The conflicting results could be attributed to the various study contexts, protocols, and participant populations. It is conceivable that the reduction in EF could be due to cold‐induced coronary vasoconstriction and subclinical myocardial ischemia. Results from Meyer coworkers showed that cold chamber exposure (−20°C) lowered the ischemic threshold in patients with coronary artery disease, even if asymptomatic or had no history of cold‐induced angina. ³¹ Nevertheless, a more likely explanation lies in the stimulation of norepinephrine and α‐mediated peripheral vasoconstriction, which causing an elevation of afterload. ³² In our study, we observed a considerable number of subjects experienced a decline in LV systolic function following exposure to extreme cold. When faced with such conditions or prolonged cold exposure, the cardiovascular system may experience decompensated manifestations, leading to decreased myocardial contractility and HR, resulting in decreased BP and inadequate blood supply to tissues and organs. ³³ And cold‐induced cardiovascular diseases may be potentially associated with the impairment of LV cardiac function. Cold exposure can lead to abnormal heart conduction function and induce arrhythmias. ³⁴ A decrease in EF is associated with decreased coronary oxygen supply, which may explain higher incidences of adverse cardiac events in patients with heart failure with reduced EF during intermediate cold exposure. ³⁵ Furthermore, chronic cold stress could also result in myocardial injury in mice. ³⁶ These findings underscore the importance of identifying risk factors for changes in LV function when exposed to extremely cold environments and providing a new strategy for cardiac function maintaining and cardiovascular disease prevention during extreme cold exposure.

4.2. Clinical significance of BPV

During the 24‐h ABP monitoring, BP measurements at various time points are influenced by environmental, physical, emotional, and other factors. Consequently, BP levels are subject to continuous and dynamic fluctuations. BPV encompasses a wide range of BP variations that occur over seconds or minutes (very short‐term BPV), throughout a 24‐h period (short‐term BPV), and over the course of days (mid‐term or day‐to‐day BPV). Long‐term BPV has also been described, such as seasonal and visit‐to‐visit BPV. ¹² Previous studies have indicated that the preferred indices include ARV and CV, which are not influenced by average BP. ¹² Furthermore, the impact of nocturnal BP decline should be considered in BPV assessment. ³⁷ Autonomic nerve function is an important mechanism of BPV, and the sympathetic nervous system hyperactivity can lead to elevated BPV. Many factors, including increased age, body weight, cigarette and alcohol consumption, psychological stresses, environment, target organ diseases, and certain antihypertensive drugs have an impact on BPV. ³⁸ Recently, several studies have shown that distinct components of BPV are strongly associated with organ damage, cardiovascular events, and mortality, even after adjusting for BP levels. These studies also emphasized the independent relationship between BPV and cardiovascular outcome risk stratification. ³⁹ However, the results may vary depending on the method used to estimate BPV and the characteristics of the study participants, limiting the independent prognostic value of BPV. ⁷ , ⁸ , ⁹ Overall, the clinical value of these parameters remains in the research phase. Currently, there is no established normal reference for 24‐h BPV, and there is limited experimental evidence on BPV intervention. A previous report noted that 24‐h ARV did not further improve risk prediction beyond ABP, despite its significant association with cardiovascular and cerebrovascular events. ¹⁶ Moreover, little information about the predictive value of BPV in extreme environments has been reported. Heart rate variability (HRV) serves a similar function as BPV, reflecting the autonomic balance. Previous report has shown that cold stress can cause harmful alterations of HRV that were related with the development of cardiovascular disorders. ⁴⁰ There may be a potential association between cardiac dysfunction and a decrease in HRV, which is attributed to sympathetic tone. Notably, a recent study showed that the regulation of the parasympathetic nervous system may be more pronounced in extremely cold environments (−20°C), leading to a significant decrease in HRV. ⁴¹ However, it remains unknown whether there is a connection between BPV and cardiovascular function during extreme cold exposure.

4.3. Association between baseline BPV and LV function after cold exposure

Few studies have examined the relationship between baseline cardiovascular indices and LV function variation after cold exposure. Cold environments typically stimulate the sympathetic nerve, CO and myocardial contractility are maintained, which is viewed as compensatory mechanisms to meet the heightened oxygen demand. ²⁸ Similarly, in our study, we also observed that subjects with an increased EF experienced elevations in HR, GLS, and Ees, which is considered a normal physiological response to cold stress. BPV, a widely used clinical indicator, offers indirect insights into autonomic nerve balance and sympathetic excitability, and has garnered significant attention in recent years. ⁴² Subjects with higher BPV levels have been associated with heightened sympathetic activity and more severe target organ damage. ⁴³ Previous studies also established a link between BPV and cardiac function. ⁴⁴ Impaired sympathetic modulation of BP can lead to diastolic dysfunction. ⁴⁵ Due to a relatively slow change, systolic function was not associated with BPV. ⁴⁶ Our research has shown that cardiac diastolic function generally decreased following extreme cold exposure, but changes in systolic function were more variable. Subjects with a higher baseline level of BPV exhibited a reduced systolic function during exposure to extremely cold environments. These individuals may develop further autonomic dysfunction, leading to abnormal cardiac responses in extremely cold environments. A higher level of baseline BPV indicates a dominant sympathetic system state, which may result in increased norepinephrine secretion by the sympathetic nervous system. This excessive increase in cardiac afterload and decompensation of cardiac function can lead to a mismatch between oxygen supply and demand. Repeated intravenous injections of epinephrine has also been demonstrated to cause stress cardiomyopathy and progressive left ventricular systolic dysfunction. ⁴⁷ Additionally, in other extreme environments, such as high altitudes with hypobaric and hypoxic conditions, healthy subjects may experience abnormal autonomous nervous system responses and cardiovascular changes, which may be an important predisposing factor for altitude diseases. ⁴⁸ , ⁴⁹ Autonomic dysfunction is also commonly found in numerous prevalent conditions such as hypertension, diabetes, and heart failure. ⁵⁰ Compared to normotensives, hypertensive patients exhibited a more pronounced increase in sympathetic excitation and BP following cold stimulation. ⁵¹ Similarly, the elevation of HR during cold exposure was more pronounced among patients with coronary heart disease compared to healthy individuals. This might be attributed to maintaining CO in the context of stroke volume deficiency. ⁵² However, individuals with chronic heart failure experienced comparable haemodynamic variations due to cold stress compared to controls. Specifically, exposure to cold did not evoke an exaggerated surge in adrenergic activity. ⁵³ Besides, research has demonstrated that brief exposure to cold induced alterations in ventricular repolarization, which caused by modified cardiac autonomic regulation and were not influenced by hypertension. ³⁴ In our investigation, we discovered that baseline BPV was associated with and can predict changes in LV cardiac function variation. Thus, we hypothesized that subjects with lower baseline BPV may undergo a normal autonomic adaptative change following extreme cold exposure. Cold conditions stimulate chemoreceptors in the carotid sinus and aortic arch, leading to increased sympathetic nerve activity through neurohumoral regulation. ²² , ⁵⁴ This heightened sympathetic activity maintains LV function, possibly as a response to cold adaptation. In contrast, individuals with higher baseline BPV may lack the capacity for compensation following cold stress due to an originally high sympathetic level and potential autonomic dysfunction. Therefore, measuring baseline BPV can potentially screen for cardiac adaptation in healthy individuals exposed to extreme cold. However, further analysis is required to establish appropriate evaluation criteria and predictability. Moreover, we found that systolic BPV is a superior predictor of cardiac function changes compared to diastolic BPV. This is because DBP is more influenced by the functional status of blood vessels themselves. BPV data may be more accurate at day than at night because more measurements are taken during the daytime. Daytime BPV may be more accurate and predictive than nighttime BPV due to the higher number of measurements taken during the day. However, the underlying mechanism remains unclear, and this conclusion may only apply within a specific BPV range or to a specific population.

4.4. Limitations

Our current investigation has several limitations. Firstly, the majority of participants were young Chinese Han individuals. Whether these findings can be generalized to other population groups or circumstances remains uncertain. Secondly, due to the challenges posed by extreme cold outdoor conditions in this study, we did not measure parameters such as fluid intake, hormones, and body temperature. The underlying mechanisms require further exploration. Thirdly, the monitoring duration of ABP was shorter and the frequency was lower especially during night, so the results had some limitations. While these findings may have physiological implications, their clinical relevance remains unclear. Finally, the sample size was relatively small, and the results should be confirmed in a larger prospective cohort study.

5. CONCLUSIONS

To date, there is limited information available regarding the relationship between baseline cardiovascular indices and LV function variation in extreme environments. Our study aimed to explore this connection, revealing a close correlation between baseline cardiovascular indicators and cardiac function variation following extreme cold exposure. Notably, the level of baseline BPV held significant predictive value for changes in EF after exposure to extreme cold environment. These findings offered novel insights into the preservation of cardiac function during extreme cold exposure, potentially informing strategies for cardiac protection in such environment.

AUTHOR CONTRIBUTIONS

Conceptualization; data curation & writing‐original draft: Renzheng Chen and Feng Cao; Funding acquisition; supervision; validation; writing‐review & editing: Feng Cao and Yabin Wang; Formal analysis; investigation; methodology; software; visualization: Qian Yang and Yan Fang; Project administration: Feng Cao and Yabin Wang; Resources: Feng Cao All authors read and approved the final version of the manuscript.

CONFLICT OF INTEREST STATEMENT

There are no conflicts of interest to declare. All authors have reported that they have no relationships relevant to the contents of this paper to disclose.

Supporting information

Figure S1

Figure S2

Supporting Information

Chen R, Yang Q, Wang Y, Fang Y, Cao F. Association between baseline blood pressure variability and left heart function following short‐term extreme cold exposure. J Clin Hypertens. 2024;26:921–932. 10.1111/jch.14862

DATA AVAILABILITY STATEMENT

The datasets generated for this study are available on request to the corresponding author.