Electrocardiogram Parameters Associated With the Diagnosis of Pulmonary Hypertension in High-Altitude Tibetan Populations: A Retrospective Single-Centre Study

BACKGROUND

Electrocardiogram (ECG) is a commonly used diagnostic method for pulmonary hypertension (PH) in Tibetan areas, but its sensitivity and specificity are not good enough. This study aimed to investigate the ECG parameters associated with the diagnosis of PH in Tibetan areas.

METHODS

Ninety-four PH patients of Tibetan ethnicity who were treated at the hospital between March 2019 and October 2020, and 52 Tibetan individuals as controls, were included. The ECG parameters were compared between groups. Multivariate logistic analysis was performed to identify the ECG parameters that can be used for the diagnosis of PH. The univariate significances of ECG parameters were included in the multivariate analyses, whereas those exhibiting opposite trends between different PH subtypes were excluded.

RESULTS

Two ECG parameters were significant in multivariate analysis. The final model included S wave amplitude in lead V3 (OR 5.81; 95% CI 2.79-12.11; p<0.001) and a negative T wave in leads V1-V3 (OR 0.05; 95% CI 0.01-0.41; p=0.005). The ROC curve analysis on the final model yielded an AUC of 0.830 (95% CI 0.766-0.894; p<0.001), indicating good diagnostic performance. A nomogram for diagnosis of PH was also established using S wave amplitude in lead V3 and a negative T wave in leads V1-V3.

CONCLUSION

The ECG parameters S wave amplitude in lead V3 and a negative T wave in leads V1-V3 were independent factors associated with the diagnosis of PH in high-altitude Tibetan populations.

Residential greenness alleviated the adverse associations of long-term exposure to ambient PM1 with cardiac conduction abnormalities in rural adults

BACKGROUND

Ambient air pollution was linked to elevated risks of adverse cardiovascular events, and alterations in electrophysiological properties of the heart might be potential pathways. However, there is still lacking research exploring the associations between PM1 exposure and cardiac conduction parameters. Additionally, the interactive effects of PM1 and residential greenness on cardiac conduction parameters in resource-limited areas remain unknown.

METHODS

A total of 27483 individuals were enrolled from the Henan Rural Cohort study. Cardiac conduction parameters were tested by 12-lead electrocardiograms. Concentrations of PM1 were evaluated by satellite-based spatiotemporal models. Levels of residential greenness were assessed using Enhanced Vegetation Index (EVI) and Normalized difference vegetation index (NDVI). Logistic regression models and restricted cubic splines were fitted to explore the associations of PM1 and residential greenness exposure with cardiac conduction abnormalities risk, and the interaction plot method was performed to visualize their interaction effects.

RESULTS

The 3-year median concentration of PM1 was 56.47 (2.55) μg/m3, the adjusted odds rate (ORs) and 95% confidence intervals (CIs) for abnormal HR, PR, QRS, and QTc interval risk in response to 1 μg/m3 increase in PM1 were 1.064 (1.044, 1.085), 1.037 (1.002, 1.074), 1.061 (1.044, 1.077) and 1.046 (1.028, 1.065), respectively. Participants exposure to higher levels of PM1 had increased risks of abnormal HR (OR = 1.221, 95%CI: 1.144, 1.303), PR (OR = 1.061, 95%CI: 0.940, 1.196), QRS (OR = 1.225, 95%CI: 1.161, 1.294) and QTc interval (OR = 1.193, 95%CI: 1.121, 1.271) compared with lower levels of PM1. Negative interactive effects of exposure to PM1 and residential greenness on abnormal HR, QRS, and QTc intervals were observed (Pfor interaction < 0.05).

CONCLUSION

Long-term PM1 exposure was associated with elevated cardiac conduction abnormalities risks, and this adverse association might be mitigated by residential greenness to some extent. These findings emphasize that controlling PM1 pollution and increasing greenness levels might be effective strategies to reduce cardiovascular disease burdens in resource-limited areas.