Abstract
Background
Over 80 million people live above 2,500 m, where hypobaric hypoxia increases hypoxic pulmonary hypertension (HPH) risk. In Qinghai, China (> 3,000 m), over 5 million face a high HPH burden with limited medical resources.
Objective
To evaluate risk factors and outcomes of HPH in high-altitude residents using echocardiography.
Methods
This retrospective study analyzed 627 HPH patients (PASP > 50 mmHg) in Qinghai (2018–2022), categorized as moderate (50 < PASP < 70 mmHg) or severe (PASP ≥ 70 mmHg). Clinical, biochemical, and echocardiographic data were assessed, with mortality tracked via telephone follow-up after ≥ 1 year. Logistic and Cox regression identified severity and mortality predictors.
Results
Among 627 high-altitude residents with HPH, 360 (57.4%) had moderate HPH (50 < PASP < 70 mmHg) and 267 (42.6%) had severe HPH (PASP ≥ 70 mmHg). Severe HPH was associated with higher APTT (p = 0.004), LPa (p = 0.004), cyanosis (p = 0.003), and right ventricular hypertrophy (p = 0.001) via multivariate logistic regression. Mortality predictors, identified by multivariate Cox regression, included LPa (p = 0.001), atrial fibrillation (p = 0.003), heart failure (p = 0.021), and alcohol consumption (p = 0.013).
Conclusion
In Qinghai’s high-altitude residents, APTT, LPa, cyanosis, and right ventricular hypertrophy drive severe HPH, while LPa, atrial fibrillation, heart failure, and alcohol consumption predict mortality. Monitoring APTT and LPa may aid early detection, and managing modifiable factors like alcohol and atrial fibrillation could reduce mortality in resource-limited settings.
Keywords: High-altitude, Echocardiography, Hypoxic pulmonary hypertension (HPH), All-cause mortality, Risk factors
Research significance
This study identifies risk factors and clinical correlates of severe HPH in high-altitude residents, offering insights into HPH pathogenesis. Beyond advancing understanding, these findings hold potential implications for prevention and management in high-altitude regions. The association of LPa, APTT, cyanosis, and right ventricular hypertrophy with HPH severity, alongside mortality predictors like LPa, atrial fibrillation, heart failure, and alcohol consumption, suggests actionable targets. Routine screening for elevated LPa and APTT could facilitate early detection, while managing modifiable factors such as alcohol consumption and atrial fibrillation may mitigate disease progression and mortality, guiding strategies to reduce HPH burden where resources are scarce.
Introduction
Globally, more than 80 million people permanently reside above 2,500 m, with significant populations in South America (e.g., Aymara and Quechua), Central Asia (e.g., Tibetan and Sherpa), and East Africa (e.g., Ethiopian highlanders), where hypobaric hypoxia—reducing inspiratory oxygen partial pressure to 74% of sea-level values—poses a persistent physiological challenge [1]. In Qinghai Province, China, with an average elevation exceeding 3,000 m, over 5 million individuals live between 3,000 and 5,000 m, increasing the prevalence of HPH, a subtype of PH driven by chronic low oxygen levels [2–4]. This high-altitude context presents unique public health challenges due to limited medical resources and sustained environmental stress.
The adaptability to altitude hypoxia varies significantly among different populations, depending on the length of exposure. This exposure can be classified as chronic, acute, or intermittent hypoxia [5]. HPH, a subtype of pulmonary hypertension(PH) caused by lung disease or hypoxia, has become a major public health concern in mountainous areas due to prolonged exposure to low oxygen levels [6]. PH affects approximately 1% of the global population, with the prevalence rising to 10% in people over 65 years of age [7]. HPH is often accompanied by other diseases, such as chronic obstructive pulmonary disease (COPD), sleep apnea syndrome, and hypoxic pulmonary heart disease, complicating its diagnosis and management [8]. Clinical symptoms of HPH include progressive exercise dyspnea, right heart failure, and premature death [3]. Changes in the adaptive response to hypoxia and the development of HPH are currently thought to be linked to genetic, environmental, or other diseases [3, 9].
The current diagnostic standard for PH is right heart catheterization (RHC) to measure pulmonary systolic blood pressure (PASP) [10, 11]. However, due to the invasive nature and high cost of RHC, echocardiography has become a widely used, non-invasive method for assessing PH, especially in high-altitude areas [9]. Doppler echocardiography has proven to be a reliable method for evaluating pulmonary artery pressure [12]. Recent studies have shown that exposure to hypoxia can trigger various metabolic reactions, including changes in lipid metabolism, which are implicated in the development of high-altitude PH [13]. This study aims to explore the factors that promote the progression of PH in high-altitude residents and the impact of these risk factors on the survival rate of patients with HPH.
Methods
Research design
This single-center retrospective study analyzed clinical data from Qinghai Provincial People’s Hospital (Qinghai, China) for patients diagnosed with HPH between January 2018 and June 2020, with follow-up data collected through December 2022. It adhered to the Declaration of Helsinki, with informed consent obtained via telephone follow-up [14]. The protocol was approved by the Ethics Committee of Qinghai Provincial People’s Hospital (2022-55).
Research population
This retrospective study included 627 high-altitude residents in Qinghai, China (altitude 2,500–4,000 m). HPH was classified as Group 3 (PH due to hypoxia, e.g., high altitude) per the 2022 ESC/ERS Guidelines, with diagnosis based on PASP > 50 mmHg via echocardiography. Other PH groups (Groups 1, 2, 4, and 5) were excluded based on clinical symptoms, medical history, and imaging results. Patients were categorized into moderate (50 < PASP < 70 mmHg, n = 360) and severe (PASP ≥ 70 mmHg, n = 267) groups based on PASP [15, 16]. Exclusion criteria were: (1) age < 18 or > 80 years; (2) history of cardiac surgery; (3) presence of malignant tumors; (4) severe systemic diseases affecting major organs (e.g., liver, kidney, heart, brain, lung) or endocrine systems, unrelated to PH; (5) HIV infection; (6) liver or kidney failure; (7) pregnancy or lactation; (8) congenital heart disease or valvular disease; (9) incomplete clinical data. The study design is depicted in Fig. 1.
Fig. 1.
Flow diagram showing the study design of HPH patients enrolled
Clinical data collection
Data were collected using Haitai Software 3.0 from medical records, including age, sex, ethnicity, body mass index (BMI), smoking, alcohol consumption, COPD, diabetes, exertional dyspnea, cyanosis, atrial fibrillation, WHO class, hemoglobin (HB), hematocrit (HCT), C-reactive protein (CRP), albumin, creatinine, urea, B-type natriuretic peptide (BNP), prothrombin time (PT), activated partial thromboplastin time (APTT), lipoprotein(a) (LPa), and LDL/HDL ratio. Cyanosis was defined as visible bluish discoloration of the skin, lips, or nail beds, assessed clinically without consistent blood gas confirmation. Mortality data were obtained through telephone follow-up by trained staff at least 1 year post-admission, querying family members or caregivers, not sourced from community centers.
Echocardiography
Echocardiography was performed using the Philips EPIQ7 system, following the guidelines of the American Society of Echocardiography [17]. All enrolled patients underwent Doppler echocardiography, as described in Doppler Echocardiography – Knowledge and References by Taylor & Francis [18]. Continuous Doppler was used to measure the peak velocity of the tricuspid regurgitation jet, while pulsed Doppler assessed the peak velocity curves of pulmonary artery blood flow and the right ventricular outflow tract. In the absence of right ventricular outflow tract obstruction, right ventricular systolic pressure reflects PASP. PASP was estimated by combining the peak tricuspid regurgitation velocity with right atrial pressure, which was determined from the inferior vena cava diameter and its respiratory changes. If tricuspid regurgitation velocity was difficult to obtain, alternative measures such as early diastolic pulmonary regurgitation velocity or right ventricular outflow Doppler acceleration time were considered [19]. Data on PH diagnosis and treatment were evaluated against the 2022 ESC/ERS Guidelines [10]. Certified cardiologists conducted the echocardiography, adhering to both ASE guidelines and the heart color Doppler ultrasound protocols of Fuwai Hospital, ensuring standardized imaging and interpretation to reduce variability and improve accuracy.
Statistical analysis
Data were analyzed using IBM SPSS Statistics, Version 26.0 (SPSS 26.0). Normality of continuous variables was assessed using the Shapiro-Wilk test, with parametric t-tests applied unless Levine’s test indicated unequal variances (p < 0.05), in which case adjusted t-tests were used. Most continuous variables (e.g., APTT, LPa) were normally distributed, justifying the use of t-tests to compare means between moderate (50 < PASP < 70 mmHg) and severe (PASP ≥ 70 mmHg) HPH groups. Categorical variables were analyzed with chi-square tests and reported as frequencies with percentages (n, %). Multivariate logistic regression identified factors associated with severe HPH, providing odds ratios (ORs) with 95% confidence intervals (CIs). Cox proportional hazards regression assessed mortality predictors, yielding hazard ratios (HRs) with 95% CIs, adjusted for LPa, LDL/HDL ratio, atrial fibrillation, right ventricular hypertrophy, heart failure, smoking, and alcohol consumption using a forced entry approach. Continuous data are presented as mean ± standard deviation (SD), with statistical significance set at p < 0.05; significant p-values are bolded in tables.
Results
General information of the research patients
Between January 2018 and June 2020, this retrospective study analyzed medical records of 627 patients hospitalized for hypoxic pulmonary hypertension (HPH). Based on echocardiography, pulmonary artery systolic pressure (PASP) was used to categorize patients into moderate (50 < PASP < 70 mmHg, n = 360, 57.4%) and severe (PASP ≥ 70 mmHg, n = 267, 42.6%) groups. The study included 161 patients under 60 years (25.7%) and 466 aged ≥ 60 years (74.3%), with 299 females (47.7%) and 328 males (52.3%). Patients were mainly of Han (392, 62.5%), Hui (122, 19.5%), and Tibetan (66, 10.5%) ethnicity, with 47 (7.5%) from other ethnic groups. Smoking (113, 18.0%) and alcohol consumption (68, 10.8%) were reported in less than 20% of the population. Additionally, 206 patients (32.9%) had a body mass index (BMI) ≥ 24 kg/m², 69 (11.0%) had diabetes, 267 (42.6%) had chronic obstructive pulmonary disease (COPD), 329 (52.5%) experienced exertional dyspnea, 405 (64.6%) showed significant cyanosis, and 86 (13.7%) had atrial fibrillation. The World Health Organization (WHO) functional class distribution was: 112 (17.9%) in class 1, 144 (23.0%) in class 2, 239 (38.1%) in class 3, and 132 (21.0%) in class 4 (Table 1).
Table 1.
Baseline characteristics of HPH patients (N = 627)
| Variable | Number (%) |
|---|---|
| Age | |
| < 60 | 161 (25.7) |
| ≥ 60 | 466 (74.3) |
| Sex | |
| Female | 299 (47.7) |
| Male | 328 (52.3) |
| Ethnic | |
| Han | 392 (62.5) |
| Tibetan | 66 (10.5) |
| Hui | 122 (19.5) |
| Others | 47 (7.5) |
| Smoking | 113 (18.0) |
| Drinking | 68 (10.8) |
| Diabetes | 69 (11.0) |
| BMI | |
| < 24 | 421 (67.1) |
| ≥ 24 | 206 (32.9) |
| COPD | 267 (42.6) |
| Exertional Dyspnea | 329 (52.5) |
| Cyanosis | 405 (64.6) |
| Atrial Fibrillation | 86 (13.7) |
| PASP | |
| 50–70 mmHg | 360 (57.4) |
| ≥ 70 mmHg | 267 (42.6) |
| WHO | |
| 1 | 112 (17.9) |
| 2 | 144 (23.0) |
| 3 | 239 (38.1) |
| 4 | 132 (21.0) |
Data presented as n (%)
BMI Body mass index, COPD Chronic obstructive pulmonary disease, PASP Pulmonary artery systolic pressure, WHO World Health Organization functional class
Relationship between clinical parameters and PASP in HPH patients
This retrospective study compared clinical, hematological, coagulation, and echocardiographic parameters in high-altitude residents with hypoxic pulmonary hypertension (HPH), categorized by pulmonary artery systolic pressure (PASP) into moderate (50 < PASP < 70 mmHg, n = 360) and severe (PASP ≥ 70 mmHg, n = 267) groups via echocardiography.The severe HPH group had lower Albumin (33.50 ± 5.54 g/L vs. 35.45 ± 6.65 g/L, p < 0.001) and higher values for several parameters compared to the moderate group: prolonged Prothrombin Time (PT) (14.42 ± 4.99 s vs. 13.56 ± 3.46 s, p = 0.011), prolonged Activated Partial Thromboplastin Time (APTT) (34.04 ± 7.48 s vs. 31.44 ± 6.91 s, p < 0.001), elevated D-Dimer (0.81 ± 0.62 mg/L vs. 0.58 ± 0.40 mg/L, p < 0.001), higher Lipoprotein(a) (142.27 ± 126.64 mg/L vs. 110.67 ± 101.01 mg/L, p = 0.001), and increased LDL/HDL ratio (2.50 ± 0.98 vs. 2.33 ± 0.86, p = 0.022).No significant differences were observed between the two groups in Hemoglobin (156.98 ± 40.28 vs. 152.97 ± 36.46 g/L, p = 0.200), Hematocrit (49.22 ± 11.58 vs. 47.82 ± 11.16%, p = 0.136), BNP (602.67 ± 657.70 vs. 610.63 ± 914.16 ng/L, p = 0.899), or CRP (2.59 ± 4.22 vs. 2.33 ± 4.93 mg/L, p = 0.498).Echocardiographic findings indicated more pronounced right heart remodeling in the severe group, with a larger Right Atrial Diameter (47.67 ± 8.90 mm vs. 41.30 ± 7.75 mm, p < 0.001), larger Right Ventricular (RV) Diameter (38.27 ± 5.84 mm vs. 35.30 ± 7.28 mm, p < 0.001), and higher Tricuspid Velocity (3.81 ± 0.63 m/s vs. 3.69 ± 0.69 m/s, p = 0.025). Left Atrial Volume Index (LAVI) showed a borderline non-significant difference (27.99 ± 5.95 vs. 29.02 ± 7.09 mL/m², p = 0.055), with no difference in RV Wall Thickness (5.12 ± 1.07 vs. 5.06 ± 1.17 mm, p = 0.468) (Table 2).
Table 2.
Clinical and imaging characteristics in HPH Patients by PASP Severity
| Variable | 50< PASP<70 | PASP ≥ 70 | t/F | p |
|---|---|---|---|---|
| Hb (g/L) | 152.97 ± 36.46 | 156.98 ± 40.28 | -1.282 | 0.200 |
| Mononuclear (%) | 8.13 ± 2.75 | 8.42 ± 2.79 | -1.313 | 0.19 |
| HCT (%) | 47.82 ± 11.16 | 49.22 ± 11.58 | -1.492 | 0.136 |
| CRP (mg/L) | 2.33 ± 4.93 | 2.59 ± 4.22 | -0.677 | 0.498 |
| Albumin (g/L) | 35.45 ± 6.65 | 33.50 ± 5.54 | 3.881 | 0.0001 |
| Creatinine (µmol/L) | 78.82 ± 47.15 | 79.32 ± 40.05 | -0.141 | 0.888 |
| Carbamide (µmol/L) | 7.48 ± 4.63 | 8.05 ± 4.33 | -1.724 | 0.085 |
| BNP (ng/L) | 610.63 ± 914.16 | 602.67 ± 657.70 | 0.127 | 0.899 |
| PT (s) | 13.56 ± 3.46 | 14.42 ± 4.99 | -2.536 | 0.011 |
| APTT (s) | 31.44 ± 6.91 | 34.04 ± 7.48 | -4.489 | 0.0001 |
| D-Dimer (mg/L) | 0.58 ± 0.40 | 0.81 ± 0.62 | -5.685 | 0.0001 |
| LPa (mg/L) | 110.67 ± 101.01 | 142.27 ± 126.64 | -3.36 | 0.001 |
| LDL/HDL (ratio) | 2.33 ± 0.86 | 2.50 ± 0.98 | -2.302 | 0.022 |
| Right Atrial Diameter (mm) | 41.30 ± 7.75 | 47.67 ± 8.90 | -9.556 | 0.0001 |
| LAVI (mL/m²) | 29.02 ± 7.09 | 27.99 ± 5.95 | 1.924 | 0.055 |
| RV Diameter (mm) | 35.30 ± 7.28 | 38.27 ± 5.84 | -5.649 | 0.0001 |
| RV Wall Thickness (mm) | 5.06 ± 1.17 | 5.12 ± 1.07 | -0.725 | 0.468 |
| Tricuspid Velocity (m/s) | 3.69 ± 0.69 | 3.81 ± 0.63 | -2.251 | 0.025 |
Sample sizes: n = 360 for 50 < PASP < 70 mmHg, n = 267 for PASP ≥ 70 mmHg. p < 0.05 (bolded) indicates statistical significance
Data presented as mean ± SD; t-tests used for comparisons
Hb Hemoglobin, HCT Hematocrit, CRP C-reactive protein, BNP B-type natriuretic peptide, PT Prothrombin time, APTT Activated partial thromboplastin time, LPa Lipoprotein(a), LDL/HDL Low-density/high-density lipoprotein ratio, LAVI Left atrial volume index, RV Right ventricle
Comparison of arterial blood gas parameters by HPH severity
Arterial blood gas parameters showed no significant differences between the moderate (50 < PASP < 70 mmHg, n = 360) and severe (PASP ≥ 70 mmHg, n = 267) HPH groups. The partial pressure of oxygen (PO₂) was 74.30 ± 19.44 mmHg in the moderate group versus 73.51 ± 19.39 mmHg in the severe group (p = 0.618). Similarly, the partial pressure of carbon dioxide (PCO₂) was 34.92 ± 7.04 mmHg versus 34.16 ± 6.09 mmHg (p = 0.159), oxygen saturation (SO₂) was 92.61 ± 5.18% versus 92.10 ± 5.29% (p = 0.226), and lactate (LAC) levels were 2.02 ± 1.45 mmol/L versus 1.91 ± 0.81 mmol/L (p = 0.244). These findings indicate that arterial blood gas parameters do not vary significantly with HPH severity in this cohort (Table 3).
Table 3.
Arterial blood gas characteristics in HPH Patients by PASP Severity
| Variable | 50< PASP<70 | PASP ≥ 70 | t/F | p |
|---|---|---|---|---|
| PO2 (mmHg) | 74.30 ± 19.44 | 73.51 ± 19.39 | 0.498 | 0.618 |
| PCO2 (mmHg) | 34.92 ± 7.04 | 34.16 ± 6.09 | 1.410 | 0.159 |
| SO2 (%) | 92.61 ± 5.18 | 92.10 ± 5.29 | 1.211 | 0.226 |
| LAC (mmol/L) | 2.02 ± 1.45 | 1.91 ± 0.81 | 1.167 | 0.244 |
Relationship between pulmonary artery pressure and general clinical data and clinical symptoms
According to the experimental results, the severity of PASP in patients with HPH was significantly correlated with right ventricular hypertrophy, cyanosis, and heart failure (p < 0.05), with the boundary of pulmonary artery pressure estimated by echocardiographic at 70mmHg. The results of this experiment showed that there was no significant correlation between the severity of HPH and age, sex, ethnicity, BMI, smoking, drinking and diabetes (p > 0.05). Whether patients suffer from atrial fibrillation and COPD may be correlated with the severity of HPH (p = 0.092, p = 0.074), and the sample size needs to be further expanded for verification (Table 4).
Table 4.
Association between clinical characteristics and HPH severity (N = 627)
| Variable | 50< PASP<70 (n = 360) | PASP ≥ 70 (n = 267) | χ² | p |
|---|---|---|---|---|
| Age | 0.433 | 0.51 | ||
| < 60 | 96 (26.7) | 65 (24.3) | ||
| ≥ 60 | 264 (73.3) | 202 (75.7) | ||
| Sex | 0.141 | 0.707 | ||
| Female | 174 (48.3) | 125 (46.8) | ||
| Male | 186 (51.7) | 142 (53.2) | ||
| Ethnicity | 0.748 | 0.862 | ||
| Han | 223 (61.9) | 169 (63.3) | ||
| Tibetan | 36 (10.0) | 30 (11.2) | ||
| Hui | 72 (20.0) | 50 (18.7) | ||
| Others | 29 (8.1) | 18 (6.7) | ||
| BMI | 1.566 | 0.211 | ||
| < 24 | 249 (69.2) | 172 (64.4) | ||
| ≥ 24 | 111 (30.8) | 95 (35.6) | ||
| Smoking | 59 (16.4) | 54 (20.2) | 1.527 | 0.217 |
| Drinking | 43 (11.9) | 25 (9.4) | 1.056 | 0.304 |
| COPD | 143 (39.7) | 124 (46.4) | 2.831 | 0.092 |
| Diabetes | 39 (10.8) | 30 (11.2) | 0.025 | 0.873 |
| WHO | 4.30 | 0.231 | ||
| 1 | 74 (20.6) | 38 (14.2) | ||
| 2 | 79 (21.9) | 65 (24.3) | ||
| 3 | 132 (36.7) | 107 (40.1) | ||
| 4 | 75 (20.8) | 57 (21.3) | ||
| Heart Failure | 76 (21.1) | 90 (33.7) | 12.497 | 0.0001 |
| Cyanosis | 208 (57.8) | 197 (73.8) | 17.171 | 0.0001 |
| Atrial Fibrillation | 57 (15.8) | 29 (10.9) | 3.202 | 0.074 |
| Right Ventricular Hypertrophy | 10 (2.8) | 32 (12.0) | 20.794 | 0.0001 |
| Exertional Dyspnea | 194 (53.9) | 135 (50.6) | 0.68 | 0.409 |
Data presented as n (%). Chi-square tests used for comparisons
Sample sizes: n = 360 for 50 < PASP < 70 mmHg, n = 267 for PASP ≥ 70 mmHg. p < 0.05 (bolded) indicates statistical significance
BMI Body mass index, COPD Chronic obstructive pulmonary disease, WHO World Health Organization functional class
Multivariate Logistic regression analysis results of patients with moderate to severe HPH
A multivariate logistic regression analysis was performed to identify risk factors for the progression of HPH from moderate to severe, using variables that showed significant differences between the two groups. The results identified Activated Partial Thromboplastin Time (APTT; OR = 1.052, 95% CI: 1.016–1.089, p = 0.004), Lipoprotein(a) (LPa; OR = 1.002, 95% CI: 1.001–1.004, p = 0.004), Cyanosis (OR = 1.817, 95% CI: 1.222–2.707, p = 0.003), and Right Ventricular Hypertrophy (OR = 3.64, 95% CI: 1.698–7.805, p = 0.001) as significant risk factors for progression to severe HPH. Other variables, including Albumin (p = 0.085), Prothrombin Time (PT; p = 0.724), Low-Density/High-Density Lipoprotein ratio (LDL/HDL; p = 0.122), WHO functional classes (p > 0.05), Heart Failure (p = 0.09), and Atrial Fibrillation (p = 0.124), were not significantly associated with progression (Table 5).
Table 5.
Multivariate logistic regression analysis of risk factors for severe HPH
Multivariate logistic regression analysis used. p < 0.05 (bolded) indicates statistical significance
APTT Activated partial thromboplastin time, LPa Lipoprotein(a), LDL/HDL Low-density/high-density lipoprotein ratio, WHO World Health Organization Functional Classification system
Factors associated with mortality in high-altitude residents with HPH
This study followed 627 high-altitude residents diagnosed with HPH (PASP ≥ 50 mmHg) via echocardiography at a tertiary hospital in Qinghai, China, for at least one year to assess mortality. Univariate Cox regression analysis identified Lipoprotein(a) (LPa; HR = 2.946, 95% CI: 1.759–4.935, p < 0.001), Atrial Fibrillation (HR = 2.120, 95% CI: 1.162–3.867, p = 0.014), and Drinking (HR = 2.218, 95% CI: 1.200–4.101, p = 0.011) as significant predictors of mortality. Multivariate Cox regression, adjusted for LPa, LDL/HDL ratio, Atrial Fibrillation, Right Ventricular Hypertrophy, Heart Failure, Smoking, and Drinking, confirmed LPa (HR = 3.461, 95% CI: 2.021–5.928, p < 0.001), Atrial Fibrillation (HR = 2.534, 95% CI: 1.365–4.705, p = 0.003), Heart Failure (HR = 2.316, 95% CI: 1.134–4.730, p = 0.021), and Drinking (HR = 3.230, 95% CI: 1.277–8.171, p = 0.013) as independent risk factors for mortality. These findings highlight the prognostic importance of LPa, Atrial Fibrillation, Heart Failure, and Drinking in HPH patients, emphasizing the need for targeted risk management strategies (Table 6).
Table 6.
Cox regression analysis of mortality predictors in HPH patients (N = 627)
| Variable | Univariate Analysis | Multivariate Analysis | ||||
|---|---|---|---|---|---|---|
| p | HR | 95%CI | p | HR | 95%CI | |
| LPa | 0.001 | 2.946 | 1.759–4.935 | 0.001 | 3.461 | 2.021–5.928 |
| LDL/HDL | 0.276 | 1.325 | 0.798–2.201 | 0.414 | 1.238 | 0.742–2.066 |
| Atrial fibrillation | 0.014 | 2.120 | 1.162–3.867 | 0.003 | 2.534 | 1.365–4.705 |
| Right ventricular hypertrophy | 0.185 | 1.866 | 0.742–4.690 | 0.179 | 1.917 | 0.743–4.950 |
| Heart failure | 0.060 | 1.973 | 0.971–4.009 | 0.021 | 2.316 | 1.134–4.730 |
| smoking | 0.087 | 1.648 | 0.930–2.921 | 0.538 | 0.766 | 0.328–1.789 |
| drinking | 0.011 | 2.218 | 1.200-4.101 | 0.013 | 3.230 | 1.277–8.171 |
Adjusted for LPa, LDL/HDL ratio, Atrial Fibrillation, Right Ventricular Hypertrophy, Heart Failure, Smoking, and Drinking in the multivariate model
Cox regression analysis used. p < 0.05 (bolded) indicates statistical significance
LPa Lipoprotein(a), LDL/HDL Low-density/high-density lipoprotein ratio
Discussion
This study employed Doppler echocardiography to estimate PASP in a cohort of 627 high-altitude residents in Qinghai, China, where chronic hypoxia at elevations exceeding 3,000 m significantly increases the risk of HPH. Echocardiography provides a practical, non-invasive alternative to RHC in resource-limited high-altitude settings; however, its limitations warrant careful consideration. Echocardiography may overestimate PASP in the presence of high-altitude polycythemia, altered thoracic anatomy, or elevated cardiac output, potentially leading to false-positive diagnoses of PH [20, 21]. This overestimation can complicate clinical decision-making, particularly in high-altitude settings where even mild PASP elevations may be misinterpreted as pathological, a challenge highlighted by Jankowich et al., who note the lack of clear guidelines for managing such cases [22]. Compared to RHC—the gold standard, which directly measures mean pulmonary artery pressure (mPAP) and pulmonary vascular resistance—echocardiography’s sensitivity and specificity for PH diagnosis range from 85 to 88% and 63–87%, respectively [23]. In high-altitude populations, where chronic hypoxia alters hemodynamics, these discrepancies may be amplified, particularly due to the lack of validation studies specifically addressing echocardiography’s accuracy in such contexts [5]. Arterial blood gas analysis in our cohort revealed a PO2 of approximately 74 mmHg (Table 3), confirming chronic hypoxia consistent with expected declines at this altitude [24]. However, the absence of significant differences in PO2 (p = 0.618) and SO2 (p = 0.226) between the moderate (50 < PASP < 70 mmHg) and severe (PASP ≥ 70 mmHg) HPH groups suggests a uniform hypoxic burden across severity levels. This may be attributed to the high baseline altitude (> 3,000 m) in Qinghai, where compensatory mechanisms such as polycythemia (Hb 156.98 ± 40.28 g/L in severe HPH vs. 152.97 ± 36.46 g/L in moderate HPH, p = 0.200, Table 2) may mitigate oxygenation differences, potentially masking severity-specific variations in oxygenation.
Logistic regression analysis identified APTT (OR = 1.052, 95% CI: 1.016–1.089, p = 0.004), LPa (OR = 1.002, 95% CI: 1.001–1.004, p = 0.004), cyanosis (OR = 1.817, 95% CI: 1.222–2.707, p = 0.003), and right ventricular hypertrophy (OR = 3.64, 95% CI: 1.698–7.805, p = 0.001) as independent factors associated with severe HPH (Table 5). Elevated APTT in the severe HPH group (34.04 ± 7.48 s vs. 31.44 ± 6.91 s, p < 0.001, Table 2) suggests a coagulopathy, potentially driven by hypoxia-induced endothelial dysfunction or microthrombosis, both of which contribute to increased pulmonary vascular resistance [25]. This observation is consistent with prior evidence that chronic hypoxia disrupts hemostatic balance, although the precise mechanisms underlying coagulopathy in HPH remain underexplored [26]. Notably, D-dimer levels were also significantly elevated in the severe HPH group (0.81 ± 0.62 mg/L vs. 0.58 ± 0.40 mg/L, p < 0.001, Table 2), reinforcing the presence of a pro-thrombotic state in advanced HPH. These coagulation abnormalities highlight a potential therapeutic avenue, as anticoagulation or anti-thrombotic strategies may mitigate disease severity, though clinical trials are needed to establish their efficacy in this population.
The association of LPa with severe HPH is particularly intriguing. LPa, a pro-atherogenic and pro-thrombotic lipoprotein, was significantly elevated in the severe HPH group (142.27 ± 126.64 mg/L vs. 110.67 ± 101.01 mg/L, p = 0.001, Table 2). Its role in HPH may involve hypoxia-driven alterations in lipid metabolism, promoting endothelial injury and vascular remodeling through oxidized phospholipids and impaired fibrinolysis [27, 28]. However, the modest OR of 1.002 suggests a small effect size, indicating that LPa is likely a contributor rather than a primary driver of PH severity. This finding warrants cautious interpretation and further mechanistic studies to clarify LPa’s role in HPH pathogenesis, especially given its strong association with mortality (HR = 3.461, p < 0.001, Table 6). Cyanosis, observed in 64.6% of the cohort (Table 1), reflects severe hypoxemia (PO2 ~ 74 mmHg) and was associated with an 81.7% increased odds of severe HPH. This aligns with the pathophysiology of HPH, where chronic hypoxia exacerbates pulmonary vasoconstriction and vascular resistance [9]. Right ventricular hypertrophy (OR = 3.64) underscores the downstream impact of sustained PASP elevation on right heart remodeling, a hallmark of advanced HPH that often precedes right heart failure [29].
The lack of association between chronic obstructive pulmonary disease (COPD) and HPH severity (p = 0.092, Table 4) contrasts with its established role in lowland PH type 3 [8]. In our study, COPD was included as a comorbidity with a prevalence of 42.6% (267/627, Table 1), primarily caused by exposure to noxious gases (e.g., cigarette smoke) rather than high-altitude hypoxia alone. This discrepancy may reflect milder COPD phenotypes in our high-altitude cohort, as detailed phenotyping (e.g., GOLD staging) was unavailable, or the overriding effect of chronic hypoxia at > 3,000 m (PO ~ 74 mmHg, Table 3), which showed no significant difference between severity groups (p = 0.618) and may overshadow COPD’s contribution to HPH. High-altitude hypoxia likely exerts a more pronounced effect on pulmonary vascular resistance than COPD-related mechanisms in this population, though further studies with detailed COPD phenotyping are needed to confirm this hypothesis. Hemoglobin levels trended higher in the severe HPH group (156.98 ± 40.28 g/L vs. 152.97 ± 36.46 g/L, p = 0.200, Table 2), consistent with compensatory polycythemia—a common high-altitude adaptation—that may exacerbate pulmonary vasoconstriction by increasing blood viscosity [9]. Additionally, albumin levels were lower in the severe HPH group (33.50 ± 5.54 g/L vs. 35.45 ± 6.65 g/L, p < 0.001, Table 2), potentially reflecting malnutrition or liver dysfunction secondary to right heart failure, a frequent complication in advanced HPH.
Cox regression analysis identified LPa (HR = 3.461, p < 0.001), atrial fibrillation (HR = 2.534, p = 0.003), heart failure (HR = 2.316, p = 0.021), and alcohol consumption (HR = 3.230, p = 0.013) as independent predictors of all-cause mortality (Table 6). LPa’s high hazard ratio underscores its prognostic significance, likely mediated by sustained vascular injury and right heart strain, as evidenced by elevated BNP levels (> 600 ng/L, Table 2) [30]. Atrial fibrillation, present in 13.7% of patients (86/627, Table 1), may reflect right atrial pressure overload, supported by the significantly larger right atrial diameter in the severe HPH group (47.67 ± 8.90 mm vs. 41.30 ± 7.75 mm, p < 0.001, Table 2). This increased right atrial diameter may contribute to the higher prevalence of atrial fibrillation, as increased right atrial pressure and remodeling are known to predispose to arrhythmias in PH [31]. Alternatively, hypoxia-induced electrophysiological changes may also play a role, both common in HPH progression [31]. Heart failure, more prevalent in the severe HPH group (33.7%, 90/267 vs. 21.1%, 76/360, p < 0.001, Table 4), indicates advanced disease and aligns with right ventricular failure as a terminal outcome in HPH [29]. Alcohol consumption’s strong association with mortality (HR = 3.230) is consistent with its exacerbation of hypoxia and cardiac stress, likely accelerating disease progression in this vulnerable population [32]. Notably, smoking lost significance in multivariate analysis (p = 0.538, Table 6), possibly due to its low prevalence (18%, 113/627, Table 1) or the overriding impact of hypoxia in this cohort.
These findings offer practical implications for HPH management in high-altitude regions. Routine monitoring of APTT could facilitate early identification of patients at risk of severe HPH, particularly in settings with limited access to RHC. The association of elevated LPa with both HPH severity and mortality suggests a potential role for lipid-lowering therapies, though this hypothesis requires validation through clinical trials. Managing atrial fibrillation with rate control or anticoagulation and counseling patients to reduce alcohol intake may mitigate mortality risk, addressing modifiable factors in resource-scarce environments. Furthermore, the significant right heart remodeling observed in severe HPH, as indicated by increased right atrial diameter (47.67 ± 8.90 mm vs. 41.30 ± 7.75 mm, p < 0.001, Table 2), emphasizes the need for early intervention to prevent progression to right heart failure.
Despite its contributions, this study has several limitations. Its retrospective, cross-sectional design precludes the assessment of causality and longitudinal PASP changes, limiting insights into disease progression. The single-center setting may introduce selection bias, potentially overrepresenting severe cases and skewing risk estimates. Reliance on echocardiography without RHC increases the risk of misclassification, particularly in hypoxic states where PASP overestimation is a concern. The absence of detailed COPD phenotyping (e.g., GOLD staging), specific cause-of-death data, consistent blood gas measurements, and detailed smoking history (e.g., pack-years) restricts mechanistic precision; we also lack regional epidemiological data on smoking prevalence in Qinghai to contextualize the low smoking rate (18%, Table 1) and its nonsignificant association with HPH severity (p = 0.217, Table 4). The exact number of patients lost to follow-up was not recorded, which may introduce bias in the mortality analysis, as these patients were excluded from survival analysis while their baseline data were retained for severity assessments. Telephone follow-up, while practical, resulted in incomplete mortality etiologies due to reliance on family recall, a common challenge in retrospective studies. Future prospective, multicenter studies incorporating RHC, comprehensive phenotyping (e.g., COPD severity, smoking history, genetic variants in the HIF pathway), and longitudinal outcomes are essential to validate these findings and refine HPH management strategies.
Conclusion
In high-altitude residents of Qinghai, China, APTT, LPa, cyanosis, and right ventricular hypertrophy are associated with severe HPH, while LPa, atrial fibrillation, heart failure, and alcohol consumption predict mortality, reflecting chronic hypoxia’s impact in HPH. Routine monitoring of APTT, and potentially LPa, may aid in early detection, pending further validation of LPa’s role in HPH, while managing atrial fibrillation and alcohol use could reduce mortality risk in resource-limited settings. Prospective, multicenter studies with right heart catheterization are needed to validate these findings and refine HPH management strategies.
Acknowledgements
Weixin Wang and Lin Wang contributed equally to this article.
Clinical trial number
Not applicable. This is an observational study without clinical trial registration.
Authors’ contributions
S.W., L.Y., L.H., X.L., F.L., W.W., and L.W. contributed equally to data collection. S.W. and L.Y. performed data analysis equally. L.W. handled data interpretation equally with F.L., who also contributed to experimental design and writing - review and editing equally. S.W. wrote the introduction, L.H. wrote the methods, X.L. wrote the results, and W.W. wrote the discussion of the original manuscript, with W.W. also conducting statistical analysis equally. All authors reviewed the manuscript.
Funding
This work was supported by Foundation for the Qing Hai Province Health Commission Guiding project 2020-wjzdx-13 and the Key Research Program of Jining City, Shandong Province (2021YXNS006).
Data availability
The data that support the findings of this study are available from the corresponding author upon reasonable request. Due to patient privacy and ethical restrictions approved by the Ethics Committee of Qinghai Provincial People’s Hospital (2022-55), the data are not publicly available.
Declarations
Ethics approval and consent to participate
was granted by the Ethics Committee of Qinghai Provincial People’s Hospital (2022-55).
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Weixin Wang, Email: 81027262@qq.com.
Lin Wang, Email: wanglin79922@csu.edu.cn.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request. Due to patient privacy and ethical restrictions approved by the Ethics Committee of Qinghai Provincial People’s Hospital (2022-55), the data are not publicly available.