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Published on: August 7, 2017
Markers for the Severity of Multisystem Inflammatory Syndrome in Children: A Multivariate Analysis
Georgi Vasilev1,2, Nadzhie Gorelyova3, Russka Shumnalieva2,4
1Laboratory of Clinical Immunology, National Specialized Hospital for Active Treatment of Hematological Diseases, Sofia, Bulgaria.
Insights
Multisystem inflammatory syndrome in children (MIS-C) can be graded by clinical severity using laboratory data. Age, ferritin, and LDH levels help predict MIS-C severity and organ involvement.
Area of Science:
- Pediatric critical care medicine
- Infectious diseases
- Clinical laboratory science
Background:
- Multisystem inflammatory syndrome in children (MIS-C) presents a significant clinical challenge.
- Accurate grading of MIS-C severity and organ involvement is crucial for effective management.
- Predictive biomarkers are needed for risk stratification and prognosis.
Purpose of the Study:
- To grade children with MIS-C by clinical severity and system involvement.
- To identify key predictors and develop scoring systems for disease prognosis.
- To stratify patients based on multivariate clinical laboratory data.
Main Methods:
- Clustering analysis (K-means) on kernel principal component analysis (K-PCA) projections of 34 laboratory parameters.
- Receiver operating characteristic (ROC) curve analysis and logistic regression.
- Analysis of clinical data including inotropic support and respiratory distress.
Main Results:
- Three distinct clusters of MIS-C patients were identified based on laboratory profiles.
- Cluster 3 showed significantly higher levels of ferritin, LDH, liver enzymes, and kidney function markers.
- Age ≥9 years, ferritin >470 ng/mL, and LDH >363 U/L were identified as predictors of severe kidney/liver involvement and higher severity clusters.
Conclusions:
- Clustering effectively grades MIS-C severity and stages of liver and kidney involvement.
- LDH, ferritin, and age are valuable indicators for assessing MIS-C severity.
- These markers aid in clinical assessment and risk stratification for improved patient outcomes.
Background:
Our goals were to find and grade children with multisystem inflammatory syndrome (MIS-C) by clinical severity and the degree of different system involvement based on multivariate clinical laboratory data and identify the best predictors and scores for disease prognosis and risk stratification.
Methods:
We enrolled 51 patients with confirmed MIS-C from a single center, and 34 general laboratory parameters and markers were included.
Results:
Using the K-means clustering method on kernel principal component analysis (K-PCA) projections, we identified that our MIS-C patients could be separated into three clusters. Children belonging to Cluster 3 have the highest levels of ferritin, LDH, ASAT, ALAT, GGT, total bilirubin, direct bilirubin, azotemia, urea, and creatinine, followed by Cluster 2. In contrast, Cluster 1 showed the lowest levels, p < 0.05. Children belonging to Clusters 3 and 2 also needed inotropic support significantly more frequently than Cluster 1 (30% and 10% vs 0%, Fisher exact test p = 0.04). Furthermore, respiratory distress was found only in patients of Clusters 2 and 3 (p = 0.002). Regarding liver involvement, Clusters 2 and 3 more frequently had cholestasis (61% and 75% vs. 28%, p = 0.012), whereas Cluster 3 was more prominently characterized by an enlarged liver (44% vs. 0% and 5%, p = 0.004). Therefore, our clusters represent different grades, and liver and kidney involvement stages are graded by severity. From ROC curve analysis and several logistic regressions, we identified that age equal to or higher than 9 years old and ferritin levels higher than 470 ng/mL could help distinguish children with more severe kidney and liver involvement with a high probability (ROC AUC = 77%, p = 0.03 and ROC AUC = 75%, p = 0.04) approximately equal to the discriminatory potential of creatinine, urea, GGT and total bilirubin. Moreover, levels of LDH with a cutoff of 363 U/l could identify the children within Cluster 3 (ROC AUC = 80%, p = 0.004).
Conclusions:
LDH and ferritin, as well as age into consideration, could help the clinical assessment of the underlying severity.