Keywords
risk stratification
PESI
mortality
low-resource settings
How to Cite
Abstract
Introduction
Pulmonary embolism is a major cause of cardiovascular mortality worldwide. Several risk-stratification scores have been developed and validated to assess prognosis, among which the Pulmonary Embolism Severity Index (PESI) is the most widely used.
Purpose
To evaluate the prognostic performance of the PESI score in patients with pulmonary embolism in the Democratic Republic of Congo.
Methods
We conducted a single-centre retrospective cohort study at the Diamant Ngaliema Medical Center in Kinshasa from January 2022 to December 2024. Following diagnostic confirmation by computed tomography pulmonary angiography, patients were classified into high-risk (HR) and low-risk (LR) groups according to the PESI score. The primary endpoints were in-hospital mortality and 30-day mortality. Ethical approval was obtained from the Ethics Committee of the Kinshasa School of Public Health.
Results
The mean age was 63.9 ± 16.9 years. Dyspnoea was the most common presenting symptom (79.7%). Pulmonary embolism was predominantly distal (87.5%), particularly in the low-risk group (92.1%). Mechanical ventilation was required in 17.2% of patients and occurred exclusively in the HR group (42.3% vs. 0%, p < 0.001). Major adverse cardiovascular events occurred in 18.8% of patients, with shock observed only in the HR group (38.5% vs. 0%, p = 0.032). Overall in-hospital mortality was 12.5%, with all deaths occurring in the HR group (30.8% vs. 0%, p < 0.001). In multivariable analysis, mechanical ventilation (adjusted OR = 4.62, 95% CI: 1.31–16.29; p = 0.018) and shock (adjusted OR = 3.91, 95% CI: 1.08–14.17; p = 0.037) were independent predictors of mortality. Thirty-day survival was significantly lower in the HR group (log-rank p = 0.019), with a twofold increased risk of death (HR = 2.12, 95% CI: 1.13–3.97).
Conclusion
The PESI score demonstrated good prognostic performance for mortality in pulmonary embolism. Its systematic use may improve risk stratification and clinical decision-making in resource-limited settings.
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