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Updated: Jul 5, 2025
A Porcine Model of Acute Autologous Pulmonary Embolism
Published on: September 6, 2024
Clinical prediction tool to identify children at risk of pulmonary embolism
Tanatuch Tiratrakoonseree1, Suwanat Charoenpichitnun2, Rungrote Natesirinilkul3
1Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
Insights
This study developed a new clinical prediction tool for diagnosing pediatric pulmonary embolism (PE) in Thai children. A score of 2 or higher suggests PE, improving diagnostic accuracy for this condition.
Area of Science:
- Pediatric Medicine
- Cardiology
- Radiology
Background:
- Pediatric pulmonary embolism (PE) diagnosis is challenging due to non-specific symptoms.
- Adult prediction tools are not suitable for pediatric populations.
- Accurate diagnostic tools are needed for timely PE detection in children.
Purpose of the Study:
- To develop a clinical prediction model for pediatric PE in Thailand.
- To evaluate existing PE prediction tools in the Thai pediatric population.
- To improve the diagnostic accuracy of PE in children.
Main Methods:
- Multi-center retrospective study of children (≤18 years) undergoing CT pulmonary angiography.
- Comparison of clinical presentations and VTE risk factors between PE-positive and PE-negative groups.
- Development of a predictive model using logistic regression and performance evaluation (sensitivity, specificity, AUC).
Main Results:
- 104 children included: 43 (41.3%) PE-positive, 61 (58.7%) PE-negative.
- Significant predictors: congenital heart disease/pulmonary surgery, thrombophilia, previous VTE, nephrotic syndrome, chest pain.
- Model with score ≥2 achieved 74.4% sensitivity, 75.4% specificity, and 0.809 AUC.
Conclusions:
- A novel clinical prediction tool for pediatric PE in Thai children was successfully developed.
- The tool demonstrated satisfactory performance and validation.
- A score of ≥2 is indicative of PE in the studied pediatric population.
Introduction:
The diagnosis of pediatric pulmonary embolism (PE) is often delayed due to non-specific symptoms, and clinical prediction tools designed for adults are unsuitable for children. This study aimed to create a PE predictive model and to evaluate the reported tools in the Thai pediatric population.
Materials And Methods:
A multi-center retrospective study from 4 university hospitals included children ≤18 years of age undergoing computed tomography pulmonary angiogram from 2000 to 2020 with the suspicion of PE. Patients' clinical presentations and risk factors of venous thromboembolism (VTE) were compared between the PE-positive and PE-negative groups. Significant risk factors from univariate and multivariate logistic regression were included to create a clinical prediction tool. The performance of the model was demonstrated by sensitivity, specificity, area under the curve (AUC), Hosmer Lemeshow test, ratio of observed and expected outcomes and bootstrapping.
Results:
Of the 104 patients included, 43 (41.3 %) were grouped as PE-positive and 61 (58.7 %) as PE-negative. Five parameters, including congenital heart disease/pulmonary surgery, known thrombophilia, previous VTE, nephrotic syndrome and chest pain showed significant differences between the two groups. Score ≥ 2 yielded a 74.4 % sensitivity and a 75.4 % specificity with an AUC of the model of 0.809. The model performance and validation results were within satisfactory ranges.
Conclusion:
The study created a clinical prediction tool indicating the likelihood of PE among Thai children. A score ≥2 was suggestive of PE.
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