A new nomogram prediction model for pulmonary embolism in older hospitalized patients

Abstract

Purpose: Diagnosing pulmonary embolism (PE) in older adults is relatively difficult because of the atypical clinical symptoms of PE in older adults accompanied by multiple complications. This study aimed to establish a nomogram model to better predict the occurrence of PE in older adults. Methods: Data were collected from older patients (≥65 years old) with suspected PE who were hospitalized between January 2012 and July 2021 and received confirmatory tests (computed tomographic pulmonary angiography or ventilation/perfusion scanning). The PE group and non-PE (control) group were compared using univariable and multivariable analyses to identify independent risk factors. A nomogram prediction model was constructed with independent risk factors and verified internally. The effectiveness of the nomogram model, Wells score, and revised Geneva score was assessed using the area under the receiver operating characteristic curve (AUC). Results: In total, 447 eligible older patients (290 PE patients and 157 non-PE patients) were enrolled. Logistic regression analysis revealed nine independent risk factors: smoking, inflammation, dyspnea, syncope, mean corpuscular hemoglobin concentration, indirect bilirubin, uric acid, left atrial diameter, and internal diameter of the pulmonary artery. The AUC, sensitivity, and specificity of the nomogram prediction model were 0.763 (95 % confidence interval, 0.721–0.802), 74.48 %, and 67.52 %, respectively. The nomogram showed superior AUC compared to the Wells score (0.763 vs. 0.539, P < 0.0001) and the revised Geneva score (0.763 vs. 0.605, P < 0.0001). Conclusions: This novel nomogram may be a useful tool to better recognize PE in hospitalized older adults.

Keywords

• Pulmonary embolism
• Older adults
• Hospitalized
• Nomogram
• Predictive model