Introduction
From 1990 to 2015, the occurrence of chronic obstructive pulmonary disease (COPD) rose by 44.2%, impacting 174.483 million individuals, with a concurrent 11.6% increase in the mortality rate [1]. Due to its high incidence, mortality, and medical costs [2‐4], COPD places a significant socioeconomic burden globally, emerging as a pivotal public health concern. Acute exacerbation of COPD (AE-COPD) is characterized by a sudden escalation of symptoms beyond the typical daily fluctuations, necessitating additional therapeutic intervention [5]. A prethrombotic condition is associated with AE-COPD [6]. The additional factors like immobility and infection, in conjunction with AE-COPD, heightens the susceptibility to venous thromboembolism (VTE) among hospitalized patients. Patients with COPD may experience exacerbated gas exchange and hypoxia when exposed to low barometric pressure and high-altitude hypoxic environments, which further increases the risk of pulmonary hypertension and cor pulmonale, ultimately contributing to increased mortality [7]. In addition, the prevalence of pulmonary embolism (PE) has been noted to be higher among AE-COPD patients [8]. Additionally, COPD is a significant risk factor for PE. Yet, the similarity in clinical symptoms between PE and AE-COPD complicates the diagnosis of PE in individuals experiencing AE-COPD. Delayed anticoagulation therapy by clinicians contributes to a poorer prognosis. Postmortem findings additionally indicated that the incidence of PE in individuals with COPD ranged from approximately 28–51% [9].
High altitude exposure constitutes to thromboembolic disorders [10‐13], including venous thrombosis [14‐17], pulmonary thromboembolism, mesenteric vein thrombosis, cerebral vein thrombosis, and deep vein thrombosis (DVT) [10, 18‐20], primarily attributed to blood hypercoagulability. An earlier study indicated that people living in high-altitude areas for one year experienced thromboembolic events (including DVT and PE) 30 times more than those living in low altitude areas [13]. Compare to regions at lower altitudes, prolonged exposure to high altitudes is associated with an elevated risk of stroke and the subsequent need for hospitalization (13.7 versus 1.05 in 1000 people) [20]. Furthermore, based on a 5-year retrospective cohort study of the US military academies, the risk of thromboembolism in areas with higher elevations (2210 m) is twice that of sea level [21].
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Thereby, we aimed to explore the prevalence, risk factors, and clinical characteristics of PE in plateau regions by performing a prospective cohort study among in-hospital patients with confirmed AE-COPD.
Methods
Study population
We prospectively included all consecutive AE-COPD inpatients (n = 1,042) defined as the exacerbation of respiratory symptoms (dyspnea, cough, sputum, fever) in COPD patients, exceeding daily standards and requiring changes in medication treatment plans [5], which were previously diagnosed as COPD according to the global initiative for obstructive lung disease (GOLD) criteria [22], from January 1, 2019, to October 31, 2021, in Qinghai Provincial People’s Hospital. The study was approved by the Research Ethics Board at Qinghai Provincial People’s Hospital, Qinghai University (Ethical number:2018-53) and was in accordance with the Helsinki Declaration. Oral consent was obtained from patients involved before enrollment.
Furthermore, we excluded those: (1) complicated with pneumothorax (n = 3); (2) complicated with pulmonary interstitial fibrosis (n = 39); (3) with invalid information of computed tomography pulmonary angiography (CTPA) (n = 349); (4) with malignancy (n = 3); (5) within six weeks after delivery (n = 4); (6) with major surgery or trauma (n = 5), or myocardial infarction (n = 2) within the past three months; (7) missing important covariates (n = 1). Finally, this study enrolled 636 AE-COPD patients (Fig. 1).
Fig. 1
Flow-chart of this study
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PE diagnosis
Within the first 24 h of admission, Chest CT angiography (CTA) was conducted using a 16-section multi-detector CT scanner (GE Light Speed 16; GE Healthcare, Milwaukee, Wisconsin, USA). Patients received a 100 mL injection of non-ionic contrast media (Iohexol Omnipaque 300/100; GE Healthcare, Milwaukee, WI, USA) through an 18G needle in the antecubital vein, administered at a rate of 4 s using a power injector (Medrad Stellant Dual; Medrad, Indianola, PA, USA). A dedicated workstation (Advanced Workstation 4.0; GE Healthcare) was employed for the execution of Chest CTA. The confirmation of pulmonary embolism (PE) was achieved upon the identification of an intraluminal filling defect, enveloped by intravascular contrast, or the observation of complete occlusion within the pulmonary arterial lumen at any location throughout the pulmonary arteries.
As described in an earlier study [23], PE was identified on CT scans by the presence of a clearly defined filling defect within the pulmonary artery, which was distinctly outlined and observed in a minimum of two consecutive image sections, positioned either centrally within the vessel or displaying acute angles at its interface with the vessel wall. It was diagnosed as DVT according to a low-attenuating partial or complete intraluminal filling defect surrounded by a high-attenuating ring of enhanced blood which was identified at least two consecutive transverse images [24]. Proximal DVT was characterized by thrombosis at or above the popliteal vein level, while distal DVT was identified by thrombosis affecting the axial calf veins.
Covariates collection
We collected the social demography characteristics, disease history, disease characteristics, symptoms, comorbidities, preventive treatment, physical examination, laboratory examination, electrocardiogram and echocardiography, and treatment of ventilation as well as peripherally inserted central catheter among AE-COPD patients based on electronic medical records and diagnosis and treatment processes. Body mass index (BMI) was calculated as weight (kg) divided by the square of height (m).
Data analysis
We used the Shapiro-Wilk test to assess the normality of the continuous variables. We described those with normal distribution as means ± standard deviations and compared them by using the independent students’ t-test, and those with skew distribution were described as medians (P25, P75) and compared by the nonparametric Wilcoxon test. Categorical variables were shown as n (%) and compared by using the χ2 test and the Fisher exact probability test. We calculated the odds ratio (OR) and 95% CI for the risk factors of PE through multivariable logistic regression. Independent variables were selected based on statistical significance combined with professional knowledge in univariable analysis while considering the correlation between variables to avoid overfitting. The final model was determined based on the Akaike information criterion. The dose-response relationship between continuous variables and the logit-transformed PE probability was constructed through the restricted cubic spline function (Figure S1), and the variables with nonlinear correlation were converted into categorical variables when conducting multivariable logistic regression. The variables beyond the specified category and those exceeding the median ± three times the quartile interval were defined as outliers. Continuous variables with missing values were imputed by using multiple imputation methods based on Monte Carlo simulation and categorical variables were imputed through conditional imputation methods based on mode. We used a two-tailed test, and P < 0.05 was considered statistically significant. We used SAS 9.4 (SAS Institute, Cary, NC, USA) and R (version 4.2.1, https://www.r-project.org/) for all statistical analyses.
Results
Prevalence of PE and characteristics of AE-COPD patients
We enrolled 636 AE-COPD patients with a male proportion of 70% and an average age of 67.0 ± 10.7 years. Among them, 188 patients had PE, and the prevalence of PE was 29.6% (95% CI: 26.0%, 33.1%). Compared to non-PE patients, the proportion of PE patients with a Padua score ≥ 4 was higher, while the proportion of Han nationality was lower. The proportion of AE-COPD patients with PE who had a history of hypertension was lower, and the proportion of strokes within the past 3 months and preventive treatment was higher. Moreover, patients with PE had a higher proportion of chest pain, cardiac insufficiency or respiratory failure, and DVT (Table 1).
Table 1
Sociodemographic and disease characteristics of patients with AE-COPD
Variables | All (n = 636) | Non-PE (n = 448) | PE (n = 188) | P-value |
|---|---|---|---|---|
Sociodemographic characteristics | ||||
Males | 445 (70.0) | 308 (68.8) | 137 (72.9) | 0.301 |
Age, years | 67.0 ± 10.7 | 66.7 ± 10.5 | 67.7 ± 11.2 | 0.283 |
Han nationality | 434 (68.2) | 326 (72.8) | 108 (57.4) | < 0.001 |
BMI, kg/m2 | 23.5 ± 4.9 | 23.7 ± 4.9 | 23.0 ± 4.9 | 0.140 |
Smoked | 226 (35.5) | 157 (35.0) | 69 (36.7) | 0.690 |
Disease characteristics | ||||
Bed time > 3 days | 75 (11.8) | 51 (11.4) | 24 (12.8) | 0.622 |
Padua score ≥ 4 | 224 (35.2) | 124 (27.7) | 100 (53.2) | < 0.001 |
Geneva score ≥ 3 | 122 (19.2) | 82 (18.3) | 40 (21.3) | 0.385 |
Disease history | ||||
Hypertension | 285 (44.8) | 219 (48.9) | 66 (35.1) | 0.001 |
Diabetes | 50 (7.9) | 41 (9.2) | 9 (4.8) | 0.062 |
Autoimmune disease | 2 (0.3) | 2 (0.4) | 0 (0.0) | 0.359 |
Stroke within 3 months | 23 (3.6) | 11 (2.5) | 12 (6.4) | 0.016 |
Ventilation within 3 months | 60 (9.4) | 48 (10.7) | 12 (6.4) | 0.088 |
VTE | 22 (3.5) | 14 (3.1) | 8 (4.3) | 0.477 |
Preventive treatment | ||||
LMWH therapy | 242 (38.1) | 140 (31.3) | 102 (54.3) | < 0.001 |
New anticoagulant | 40 (6.3) | 18 (4.02) | 22 (11.7) | < 0.001 |
VTE prophylaxis | 289 (45.4) | 174 (38.8) | 115 (61.2) | < 0.001 |
Symptoms | ||||
Dyspnea | 236 (37.1) | 173 (38.6) | 63 (33.5) | 0.224 |
Chest pain | 100 (15.7) | 56 (12.5) | 44 (23.4) | 0.001 |
Hemoptysis | 17 (2.7) | 12 (2.7) | 5 (2.7) | 0.989 |
Palpitation | 27 (4.2) | 17 (3.8) | 10 (5.3) | 0.384 |
Syncope | 7 (1.1) | 4 (0.9) | 3 (1.6) | 0.438 |
Lower limb edema | 353 (55.5) | 239 (53.3) | 114 (60.6) | 0.091 |
Lower limb pain | 11 (1.7) | 5 (1.1) | 6 (3.2) | 0.067 |
Comorbidities | ||||
Infection | 535 (84.1) | 382 (85.3) | 153 (81.4) | 0.221 |
Cardiac insufficiency or respiratory failure | 422 (66.4) | 350 (78.1) | 72 (38.3) | < 0.001 |
DVT | 39 (6.1) | 5 (1.1) | 34 (18.1) | < 0.001 |
Proximal DVT | 19 (3.0) | 0 (0.0) | 19 (10.1) | < 0.001 |
Distal DVT | 15 (2.4) | 4 (0.9) | 11 (5.9) | < 0.001 |
Intermuscular DVT | 9 (1.4) | 1 (0.2) | 8 (4.3) | < 0.001 |
Cardiac injury | 23 (3.6) | 12 (2.7) | 11 (5.9) | 0.051 |
Acute renal insufficiency | 5 (0.8) | 4 (0.9) | 1 (0.5) | 0.638 |
Hepatic insufficiency | 20 (3.1) | 13 (2.9) | 7 (3.7) | 0.588 |
Tricuspid regurgitation | 496 (78.0) | 354 (79.0) | 142 (75.5) | 0.333 |
Pericardial effusion | 152 (23.9) | 103 (23.0) | 49 (26.1) | 0.407 |
Pulmonary hypertension | 489 (76.9) | 349 (77.9) | 140 (74.5) | 0.349 |
The results of physical and laboratory examination suggested that the neutrophil count, D-dimer, alanine transaminase, aspartate aminotransferase, and lactate dehydrogenase were higher in patients with PE, while systolic blood pressure, albumin, and proportion of right branch block was lower. There was no significant difference between the two groups in terms of ventilation and peripherally inserted central catheter treatment (Table 2).
Table 2
Physical examination, laboratory test indexes, and treatment in patients with AE-COPD
Variables | All (n = 636) | Non-PE (n = 448) | PE (n = 188) | P-value |
|---|---|---|---|---|
Physical examination | ||||
Systolic blood pressure, mmHg | 126.2 ± 19.1 | 127.2 ± 19.3 | 123.9 ± 18.5 | 0.050 |
Diastolic blood pressure, mmHg | 78.6 ± 13.6 | 79.1 ± 14.1 | 77.4 ± 12.3 | 0.146 |
Heart rate, /min | 84 (75, 95) | 84 (75, 95) | 84 (76, 98) | 0.365 |
Respiratory rate, /min | 20 (19, 22) | 20 (19, 22) | 20 (19, 22) | 0.832 |
Laboratory test | ||||
White blood cell count, ×109 | 5.6 (4.5, 7.0) | 5.5 (4.5, 6.8) | 5.9 (4.5, 7.9) | 0.064 |
Neutrophil count,×109 | 3.8 (2.9, 5.2) | 3.7 (2.8, 5.1) | 4.1 (3.0, 6.2) | 0.011 |
Hemoglobin, g/L | 175 (150, 201) | 174 (152, 203) | 177 (147, 198) | 0.551 |
Platelet count, ×109 | 134 (98, 175) | 137 (101, 176) | 129 (91, 172) | 0.059 |
Erythrocyte sedimentation rate, mm/h | 2.0 (1.0, 7.0) | 2.0 (1.0, 6.6) | 2.0 (1.0, 8.2) | 0.395 |
D-dimer, mg/L | 1.4 (0.9, 3.0) | 1.3 (0.9, 2.4) | 2.1 (1.2, 5.3) | < 0.001 |
PT, s | 12.9 (11.9, 14.3) | 12.8 (11.9, 14.3) | 13.1 (11.9, 14.3) | 0.480 |
APTT, s | 32.0 (28.4, 36.8) | 32.0 (28.6, 36.8) | 32.0 (27.7, 36.8) | 0.671 |
OI, mmHg | 270 (220, 330) | 274 (220, 330) | 257 (218, 316) | 0.111 |
Total protein, g/L | 61.3 (56.8, 66.1) | 61.5 (56.9, 66.0) | 60.70 (55.80, 66.40) | 0.602 |
Albumin, g/L | 34.7 (31.3, 38.0) | 34.8 (31.6, 38.2) | 34.3 (30.5, 37.3) | 0.040 |
ALT, U/L | 18 (12, 30) | 18 (12, 27) | 22 (14, 44) | < 0.001 |
AST, U/L | 24 (19, 35) | 23 (19, 32) | 26 (20, 43) | 0.002 |
LDH, IU/L | 265.0 (207.5, 340.0) | 258.0 (204.0, 332.0) | 275.0 (228.2, 360.0) | 0.010 |
BUN, mmol/L | 7.2 (5.1, 9.7) | 6.9 (5.0, 9.6) | 7.6 (5.2, 9.9) | 0.183 |
Uric acid, µmol/L | 425.0 (326.5, 560.5) | 424.5 (325.5, 559.0) | 434.5 (328.0, 568.0) | 0.724 |
Creatinine, µmol/L | 75.0 (63.0, 89.0) | 75.0 (62.0, 88.2) | 76.5 (64.0, 90.0) | 0.745 |
cTnI, ng/L | 18.1 (6.3, 50.6) | 16.2 (6.1, 49.9) | 22.1 (7.4, 53.6) | 0.298 |
CK-MB, U/L | 13.0 (10.0, 18.3) | 13.0 (10.0, 18.6) | 13.0 (9.5, 18.0) | 0.679 |
NT-proBNP, pg/mL | 410.0 (119.0, 924.4) | 406.0 (124.5, 910.2) | 425.4 (105.0, 975.1) | 0.956 |
Electrocardiogram and echocardiography | ||||
Sinus tachycardia | 43 (6.8) | 35 (7.8) | 8 (4.3) | 0.103 |
Nonspecific T-wave inversion | 21 (3.3) | 12 (2.7) | 9 (4.8) | 0.175 |
Poor R-wave progression | 57 (9.0) | 35 (7.8) | 22 (11.7) | 0.117 |
Right bundle branch block | 104 (16.4) | 83 (18.5) | 21 (11.2) | 0.022 |
S1Q3T3 pattern | 35 (5.5) | 25 (5.6) | 10 (5.3) | 0.895 |
LA diameter, mm | 36 (33, 41) | 36 (33, 41) | 36 (32, 41) | 0.963 |
LVESVI, mL/m2 | 45 (41, 48) | 45 (41, 48) | 45 (41, 48) | 0.588 |
LVEDVI, mL/m2 | 28 (25, 31) | 28 (25, 31) | 28 (25, 31) | 0.454 |
Simpson biplane EF, % | 65.0 (60.0, 69.0) | 65.0 (60.9, 68.5) | 65.0 (60.0, 70.0) | 0.723 |
RA diameter, mm | 44 (38, 50) | 44 (38, 50) | 43 (38, 49) | 0.266 |
RV diameter, mm | 36 (30, 39) | 36 (30, 40) | 36 (31, 39) | 0.876 |
PA diameter, mm | 29 (25, 32) | 29 (25, 32) | 28 (24, 32) | 0.108 |
PASP, mmHg | 63 (48, 82) | 65 (49, 83) | 60 (47, 81) | 0.292 |
Treatment | ||||
Ventilation | 57 (9.0) | 39 (8.7) | 18 (9.6) | 0.726 |
PICC | 6 (0.9) | 5 (1.1) | 1 (0.5) | 0.487 |
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Risk factors associated with PE among AE-COPD patients
Multivariable logistic regression showed that the Han nationality had a 43.4% (OR = 0.566, 95% CI 0.363, 0.883) lower probability of developing PE compared to other ethnic minorities. For every unit increase in neutral count, the patient’s risk of PE increased by 11.2% (OR = 1.112, 95% CI 1.037, 1.191). D-dimer > 1 mg/L (OR = 1.725, 95% CI 1.108, 2.686) and AST > 40 U/L (OR = 2.310, 95% CI 1.384, 3.856) showed a risk effect on PE. Furthermore, chest pain (OR = 2.121, 95% CI 1.229, 3.662), cardiac insufficiency or respiratory failure (OR = 7.451, 95% CI 4.691, 11.833), Padua score ≥ 4 (OR = 3.542, 95% CI 2.247, 5.583), and DVT (OR = 11.067, 95% CI 3.809, 32.156) were also associated higher probability of PE (Table 3). Additionally, the C-index of this model was 0.84 (Figure S2).
Table 3
Related factors of pulmonary embolism in patients with AE-COPD based on multivariable logistic regression
Variables | OR | 95%CI | P-value |
|---|---|---|---|
Nationality (Han vs. minority) | 0.566 | 0.363, 0.883 | 0.012 |
Neutrophil count (per 1 × 109) | 1.112 | 1.037, 1.191 | 0.003 |
D-dimer (> 1 mg/L vs. ≤1 mg/L) | 1.725 | 1.108, 2.686 | 0.016 |
AST (> 40 U/L vs. ≤40 U/L) | 2.310 | 1.384, 3.856 | 0.001 |
Chest pain (with vs. without) | 2.121 | 1.229, 3.662 | 0.007 |
Hypertension (with vs. without) | 0.675 | 0.438, 1.039 | 0.074 |
Cardiac insufficiency or respiratory failure (with vs. without) | 7.451 | 4.691, 11.833 | < 0.001 |
Stroke within 3 months (with vs. without) | 1.983 | 0.672, 5.856 | 0.215 |
Padua score (≥ 4 vs. 0–3) | 3.542 | 2.247, 5.583 | < 0.001 |
DVT (with vs. without) | 11.067 | 3.809, 32.156 | < 0.001 |
Lower limb pain (with vs. without) | 1.935 | 0.447, 7.849 | 0.356 |
Discussion
Currently, there is limited information on the prevalence and association between PE and AE-COPD in high-altitude areas. This study has the widest sample size to date, providing evidence to support their relationship. Initially, our research results showed that the incidence of PE was significantly higher compared to studies conducted in low altitude areas, so it is necessary to conduct further research and validation in populations living in high-altitude areas [25]. Additionally, our current study found the associations between PE and elevated Padua score, the presence of deep venous thrombosis, increased neutrophil count, chest pain, cardiac insufficiency or respiratory failure, higher levels of AST, and an elevated D-dimer level in hospitalized patients experiencing AE-COPD.
Many studies have shown that high-altitude areas are considered a potential risk factor for VTE, as challenging environmental conditions may enhance venous stasis and promote the formation of a prethrombotic environment [26‐29]. The increase in PE prevalence among AE-COPD patients at high altitudes can likely be attributed to several factors. Firstly, living in high-altitude areas can expose individuals to cooler temperatures, reduced humidity, strong solar radiation, and low-pressure hypoxia conditions, which may promote physiological adaptation, such as changes in lung capacity or diffusion capacity [7]. The high-altitude adaptation can lead to increased lung ventilation, which in turn leads to blood concentration [30]. At the same time, an increase in diffusion volume in COPD patients can also lead to an increase in blood viscosity [31]. Consequently, this may increase the risk of thromboembolism in patients with COPD, contributing to factors such as systemic inflammation, hypoxemia, oxidative stress, endothelial dysfunction, and a prothrombotic state [32]. Secondly, research has indicated that environmental factors such as hypoxia, dehydration, hemoconcentration, reduced temperature, and venous stasis resulting from severe weather conditions at high altitudes can trigger a state of hypercoagulability, amplifying the occurrence of thromboembolic events [10, 33, 34]. Thirdly, high altitude triggers compensatory proliferation of red blood cells, increases blood viscosity, accelerates the consumption of coagulation factors, and leads to prolonged prothrombin time and partial activation time of thrombin. Moreover, numerous studies have established an elevation in fibrinogen levels at high altitudes, positively correlating with plasminogen activator inhibitor-1 (PAI-1) levels, and PAI-1 is an inhibitor of plasminogen activator, reducing fibrinolytic activity and further promoting the formation of thrombosis [10, 35‐37].
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Multivariable analysis showed patients in plateau regions with higher Padua scores, DVT, chest pain, cardiac insufficiency or respiratory failure, higher neutrophil count, AST, and D-dimer were more likely to develop PE. The results indicated a complex origin or the correlation of PE with factors such as advanced age, greater chronicity and severity of illness, stasis, infection, and an elevated inflammatory and coagulopathic state in hospitalized patients experiencing AE-COPD at high altitudes. Hence, our conjecture is that the inflammatory state and activation of coagulation mechanisms could contribute to the promotion of pulmonary embolism under hypoxic conditions at high altitudes [38]. Our results imply that residing at high altitudes could pose an additional risk for PE, potentially contributing to its increased prevalence. Potential mechanisms linking PE and high altitude may involve the release of thrombogenic cytokines induced by high-altitude conditions. However, further investigation is essential to elucidate the pathophysiology of PE in plateau regions.
Clinical trial findings suggest that the prevention [39, 40] and reduction of VTE duration [41, 42] can improve the clinical outcomes of critically ill patients. Our data indicates a potential protective effect of prophylaxis against PE in this higher-risk cohort. This underscores the importance of recognizing and reinforcing thromboprophylaxis strategies for AE-COPD, which may involve considering a moderate increase in the dosage of anticoagulant drugs and enhancing the utilization of physical prophylaxis.
While the findings were anticipated, given our patient population comprised individuals with AE-COPD at elevated risk for PE in plateau regions, our data prompts consideration of screening for PE, risk stratification, and potential prophylactic measures to enhance outcomes in hospitalized AE-COPD patients. Additionally, as PE lacks specific clinical manifestations and may mimic other respiratory diseases in the early stages, the possibility of a combined presentation cannot be ruled out. These complexities make PE diagnosis challenging. Therefore, heightened attention is warranted for high-risk PE groups within the AE-COPD population, emphasizing the importance of PE prophylaxis.
We have to acknowledge that there were some limitations in this study. Primarily, our study is limited by being a single-center prospective investigation, making it challenging to eliminate the possibility of selected bias. Secondly, the constrained availability of CTPA examinations due to the acute exacerbation condition in COPD patients led to a substantial underestimation of the prevalence of PE. Consequently, prospective multi-center studies with larger sample sizes may be essential in the future to validate the outcomes observed in our current study.
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Conclusions
The prevalence of PE was higher, and the risk factors for PE are a higher Padua score, the occurrence of deep venous thrombosis, higher neutrophil count, chest pain, cardiac insufficiency or respiratory failure, higher levels of AST, and a higher level of D-dimer among AE-COPD patients. The analysis of AE-COPD may help to provide more accurate screening for PE and lead to corresponding measures to improve the clinical outcomes of patients with AE-COPD in plateau regions.
Acknowledgements
The authors thank all the following doctors for taking part in the diagnosis and treatment of PE patients with AE-COPD living at high altitudes from Qinghai Provincial People’s Hospital, Qinghai Province, People’s Republic China.
Declarations
Ethics approval and consent to participate
The studies involving human participants were reviewed and approved by the Research Ethics Board at Qinghai Provincial People’s Hospital, Qinghai University (Ethical number:2018-53) and was in accordance with the Helsinki Declaration. Oral informed consent was obtained from all patients involved in this study.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
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