Development and validation of a simple nomogram for predicting the short-term prognosis of patients with pulmonary embolism

Background: Pulmonary embolism (PE) is a disease caused by blood clots, tumor embolism, and other emboli within the pulmonary arteries. Various scoring scales are used for PE. One such same is the PESI, but it has 12 variables, making it inconvenient for clinical application.

Objectives: The aim of this study was to develop a new simple nomogram model to assess 30-day survival in PE patients. The new nomogram makes it easier and faster for clinicians to assess the prognosis of patients with PE.

Methods: We collected data about the patients with PE from the Medical Information Mart for Intensive Care-III (MIMIC-III) database and used the receiver operating characteristic (ROC) curve, area under the ROC curve (AUROC), calibration plot, integrated discrimination improvement (IDI), and decision curve analysis (DCA) to evaluate the predictive power of the new model, and compared these with the PESI.

Results: According to the multivariable Cox regression model results, alongside the actual clinical conditions, we included the following seven variables: race, bicarbonate, age, tumor, systolic blood pressure (SBP), body temperature, and oxygen saturation (Spo2). The AUROC of the new model was greater than 0.70. Its IDI exceeded 0, but with P-value>0.05.

Conclusion: The predictive performance of the new model was not worse than the PESI, but the new model only has seven variables, and is therefore more convenient for clinicians to use.