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Development of a nomogram prediction model for early identification of persistent coronary artery aneurysms in
Xue Gong1, Liting Tang1, Mei Wu1
1Department of Pediatrics, Ministry of Education Key Laboratory of Women and Children's Diseases and Birth Defects, West China Second University Hospital, Sichuan University, Sichuan, Chengdu, China.
Insights
Predicting coronary artery aneurysm (CAA) persistence in Kawasaki disease (KD) is vital. A new nomogram using neutrophil-to-lymphocyte ratio, γ-GT, and aneurysm size effectively predicts CAA persistence in KD patients.
Area of Science:
- Cardiology
- Pediatric Rheumatology
- Medical Diagnostics
Background:
- Kawasaki disease (KD) can lead to coronary artery aneurysms (CAA).
- Predicting the persistence of CAA is crucial for managing KD patients.
- Accurate prediction aids in long-term patient care and risk stratification.
Purpose of the Study:
- To develop and validate a nomogram prediction system for assessing the risk of CAA persistence in KD patients.
- To identify key clinical and laboratory factors associated with persistent CAA.
- To improve the accuracy of predicting CAA persistence beyond aneurysm size alone.
Main Methods:
- A cohort of 105 KD patients with diagnosed CAA was followed for at least 1 year.
- Clinical and laboratory parameters were compared between groups with CAA regression and persistence.
- Multivariable logistic regression and decision curve analysis were used to build and assess a nomogram predictive model.
Main Results:
- 27.6% of patients exhibited persistent CAA.
- CAA persistence rates were 14.1% (small), 81.3% (medium), and 100.0% (large) aneurysms.
- Neutrophil-to-lymphocyte ratio, γ-GT, and initial CAA size were independent risk factors for persistence.
Conclusions:
- Initial neutrophil-to-lymphocyte ratio, γ-GT, and CAA size are independent predictors of CAA persistence in KD.
- The developed nomogram significantly enhances the predictive efficacy for detecting persistent CAA.
- This tool can aid clinicians in better risk assessment and management of KD patients with CAA.
Background:
Coronary artery aneurysms (CAA) persistence prediction is critical in evaluating Kawasaki disease (KD). This study established a nomogram prediction system based on potential risk factors for assessing the risk of CAA persistence in a contemporary cohort of patients with KD.
Methods:
This cohort comprised 105 patients with KD who had been diagnosed with CAA during the acute or subacute phase by echocardiography. The follow-up duration was at least 1 year. The clinical and laboratory parameters were compared between the CAA regression and persistence groups. Multivariable logistic regression analysis was used to identify the independent risk factors for CAA persistence, which were subsequently used to build the nomogram predictive model. Decision curve analysis was used to assess the net benefits of different nomogram scores.
Results:
Of these patients with CAA, 27.6% of patients presented with persistent lesions. The incidences of CAA persistence were 14.1%, 81.3%, and 100.0% in patients with small, medium, and large aneurysms, respectively. The ratio of neutrophils to lymphocytes, γ-GT, and CAA size at diagnosis were considered as the independent risk factors for CAA persistence in patients with KD. The nomogram predictive models yielded a high capability in predicting CAA persistence, based on either univariable or multivariable analyses-identified parameters, compared with using CAA size as a single predictor.
Conclusion:
The initial ratio of neutrophils to lymphocytes, γ-GT, and CAA size were the independent risk factors for CAA persistence in patients with KD. Nomogram scores could help elevate predictive efficacy in detecting CAA persistence.
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