Prediction of coronary artery lesions based on C-reactive protein levels in children with Kawasaki Disease: a retrospective cohort study
J. pediatr. (Rio J.)
;
99(4): 406-412, 2023. tab, graf
Article
in English
|
LILACS-Express
| LILACS
| ID: biblio-1506638
ABSTRACT
Abstract Objective Since coronary artery lesions (CALs) are the most severe complication of Kawasaki disease (KD), clinically speaking, early prediction of CALs is crucial. The authors aimed to investigate the predictive value of C-reactive protein (CRP) in predicting CALs in KD patients. Methods KD patients were divided into the CALs group and the non-CALs group. The clinical and laboratory parameters were collected and compared. Multivariate logistic regression analysis was used to determine the independent risk factors of CALs. The receiver operating characteristic curve was applied to determine the optimal cut-off value. Results 851 KD patients who met the inclusion criteria were studied, including 206 in the CALs group and 645 in the non-CALs group. Children in the CALs group had significantly higher CRP levels than the non-CALs group (p< 0.05). Multivariable logistic regression analysis showed that incomplete KD, male, lower hemoglobin, and higher CRP were independent risk factors for predicting CAL (all p< 0.05). The optimal cut-off value of initial serum CRP for predicting CALs was 105.5 mg/L, with a sensitivity of 47.57% and a specificity of 69.61%. In addition, KD patients with high CRP (≥105.5 mg/L) had a higher occurrence of CALs than those with low CRP (<105.5 mg/L) (33% vs 19%, p< 0.001). Conclusion The incidence of CALs was significantly higher in patients with high CRP. CRP is an independent risk factor for CALs formation and may be useful for predicting CALs in KD patients.
Full text:
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Index:
LILACS (Americas)
Type of study:
Etiology study
/
Observational study
/
Prognostic study
/
Risk factors
Language:
English
Journal:
J. pediatr. (Rio J.)
Journal subject:
Pediatrics
Year:
2023
Type:
Article
/
Project document
Affiliation country:
China
Institution/Affiliation country:
University of Electronic Science and Technology of China/CN
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