Key result
Novel nomogram identifies inpatient PE with ~0.96 AUC, outperforming Wells and Geneva scores.
Why the study?
Hospitalized patients often present with complex clinical conditions, but effective tools to assess their risk of pulmonary embolism are lacking.
Does a predictive nomogram improve the identification of pulmonary embolism in hospitalized patients compared to existing scores?
Cohort (n=652)
No
Does a predictive nomogram improve the identification of pulmonary embolism in hospitalized patients compared to existing scores?
Absolute Event Rate: 0.956% vs 0.698%
A novel 7-variable nomogram demonstrated superior discrimination for pulmonary embolism in hospitalized patients compared to the simplified Wells and revised Geneva scores.
Nomogram may aid PE identification in hospitalized patients; leaves open prospective validation before clinical adoption.
BACKGROUND: Hospitalized patients often present with complex clinical conditions, but there is a lack of effective tools to assess their risk of pulmonary embolism (PE). Therefore, our study aimed to develop a nomogram model for better predicting PE in hospitalized populations. METHODS: Data from hospitalized patients (aged ≥ 15 years) who underwent computed tomography pulmonary angiography (CTPA) to confirm PE and non-PE were collected from December 2013 to April 2023. Univariate and multivariate stepwise logistic regression analyses were conducted to identify independent predictors of PE, followed by the construction of a predictive nomogram and internal validation. The efficiency and clinical utility of the nomogram model were assessed using receiver operating characteristic (ROC) curve, decision curve analysis (DCA), and clinical impact curve (CIC). RESULTS: The study included 313 PE and 339 non-PE hospitalized patients. Male gender, dyspnea or shortness of breath, interstitial lung disease, lower limb deep vein thrombosis, elevated fibrin degradation product (FDP), pulmonary arterial hypertension, and tricuspid regurgitation were identified as independent risk factors. The AUC of the predictive nomogram model was 0.956 (95% CI: 0.939-0.974), demonstrating superior performance compared with the simplified Wells score of 0.698 (95% CI: 0.654-0.741) and the modified Geneva score of 0.758 (95% CI: 0.717-0.799). CONCLUSION: Our study demonstrated that challenges remain in the accuracy of the Wells score and revised Geneva score in assessing PE in hospitalized patients. Fortunately, the nomogram we developed has shown a favorable ability to discriminate PE cases, providing high reference value for clinical practice. However, given that this was a single-center study, we plan to expand efforts to collect data from additional centers to further validate our model.
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Cao et al. (2024) conducted a cohort in Pulmonary embolism (n=652). Predictive nomogram vs. Simplified Wells score and modified Geneva score was evaluated on Area under the ROC curve (AUC) for predicting pulmonary embolism (95% CI 0.939-0.974). A novel predictive nomogram identified pulmonary embolism in hospitalized patients with an AUC of 0.956, demonstrating superior diagnostic performance compared to the simplified Wells and modified Geneva scores.
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