Diagnostic value of D-dimer in differentiating multisystem inflammatory syndrome in Children (MIS-C) from Kawasaki disease: systematic literature review and meta-analysis
Abstract
Coronavirus disease 2019 (COVID-19) is frequently associated with thrombo inflammation, which can predispose to developing of life-threatening conditions in children such as the multisystem inflammatory syndrome (MIS-C) and Kawasaki disease. Because of the consistent overlap in pathogenesis and symptoms, identifying laboratory tests that may aid in the differential diagnosis of these pathologies becomes crucial. We performed an electronic search in PubMed, Web of Science and Scopus, without date or language restrictions, to identify all possible studies reporting D-dimer values in separate cohorts of children with MIS-C or Kawasaki disease. Three multicenter cohort studies were included in our analysis, totaling 487 patients (270 with MIS-C and 217 with Kawasaki disease). In this meta-analysis, significantly higher D-dimer values were found in MIS-C compared to Kawasaki disease in all three studies, yielding an SMD of 1.5 (95 % CI, 1.3–1.7) mg/L. Thus, very high D-dimer values early in the course of disease should raise the clinical suspicion of MIS-C rather than Kawasaki disease. Further studies should be planned to identify harmonized D-dimer diagnostic thresholds that may help discriminate these conditions.
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Research ethics: The study was conducted in accordance with the Declaration of Helsinki and in compliance with relevant local legislation.
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Informed consent: Not applicable.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Competing interests: The authors state no conflict of interest.
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Research funding: None declared.
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Data availability: Data will be available upon reasonable request to the corresponding author.
References
1. Mattiuzzi, C, Lippi, G. Timeline analysis of clinical severity of COVID-19 in the general population. Eur J Intern Med 2023;110:97–8. https://doi.org/10.1016/j.ejim.2022.12.007.Search in Google Scholar PubMed PubMed Central
2. Payne, AB, Gilani, Z, Godfred-Cato, S, Belay, ED, Feldstein, LR, Patel, MM, et al.. Incidence of multisystem inflammatory syndrome in children among US persons infected with SARS-CoV-2. JAMA Netw Open 2021;4:e2116420. https://doi.org/10.1001/jamanetworkopen.2021.16420.Search in Google Scholar PubMed PubMed Central
3. Hoste, L, Van Paemel, R, Haerynck, F. Multisystem inflammatory syndrome in children related to COVID-19: a systematic review. Eur J Pediatr 2021;180:2019–34. https://doi.org/10.1007/s00431-021-03993-5.Search in Google Scholar PubMed PubMed Central
4. Esteve-Sole, A, Anton, J, Pino-Ramirez, RM, Sanchez-Manubens, J, Fumadó, V, Fortuny, C, et al.. Similarities and differences between the immunopathogenesis of COVID-19-related pediatric multisystem inflammatory syndrome and Kawasaki disease. J Clin Invest 2021;131:e144554. https://doi.org/10.1172/jci144554.Search in Google Scholar
5. Melgar, M, Lee, EH, Miller, AD, Lim, S, Brown, CM, Yousaf, AR, et al.. Council of state and territorial epidemiologists/CDC surveillance case definition for Multisystem Inflammatory Syndrome in Children associated with SARS-CoV-2 infection – United States. MMWR Recomm Rep 2022;71:1–14. https://doi.org/10.15585/mmwr.rr7104a1.Search in Google Scholar PubMed PubMed Central
6. World Health Organization. Multisystem inflammatory syndrome in children and adolescents temporally related to COVID-19. Available at: https://www.who.int/news-room/commentaries/detail/multisystem-inflammatory-syndrome-in-children-and-adolescents-with-covid-19 [Accessed 3 Jan 2023].Search in Google Scholar
7. Hozo, SP, Djulbegovic, B, Hozo, I. Estimating the mean and variance from the median, range, and the size of a sample. BMC Med Res Methodol 2005;5:13. https://doi.org/10.1186/1471-2288-5-13.Search in Google Scholar PubMed PubMed Central
8. Clark, BC, Sanchez-de-Toledo, J, Bautista-Rodriguez, C, Choueiter, N, Lara, D, Kang, H, et al.. Cardiac abnormalities seen in pediatric patients during the SARS-CoV2 pandemic: an international experience. J Am Heart Assoc 2020;9:e018007. https://doi.org/10.1161/jaha.120.018007.Search in Google Scholar
9. Kostik, MM, Bregel, LV, Avrusin, IS, Dondurei, EA, Matyunova, AE, Efremova, OS, et al.. Distinguishing between Multisystem Inflammatory Syndrome, associated with COVID-19 in children and the Kawasaki disease: development of preliminary criteria based on the data of the retrospective multicenter cohort study. Front Pediatr 2021;9:787353. https://doi.org/10.3389/fped.2021.787353.Search in Google Scholar PubMed PubMed Central
10. Otar Yener, G, Paç Kısaarslan, A, Ulu, K, Atalay, E, Haşlak, F, Özdel, S, et al.. Differences and similarities of multisystem inflammatory syndrome in children, Kawasaki disease and macrophage activating syndrome due to systemic juvenile idiopathic arthritis: a comparative study. Rheumatol Int 2022;42:879–89. https://doi.org/10.1007/s00296-021-04980-7.Search in Google Scholar PubMed PubMed Central
11. Wessels, PA, Bingler, MA. A comparison of Kawasaki Disease and multisystem inflammatory syndrome in children. Prog Pediatr Cardiol 2022;65:101516. https://doi.org/10.1016/j.ppedcard.2022.101516.Search in Google Scholar PubMed PubMed Central
12. Szymanski, LJ, Huss-Bawab, J, Ribe, JK. Coronary artery aneurysms and thrombosis in Kawasaki disease. Acad Forensic Pathol 2018;8:416–23. https://doi.org/10.1177/1925362118782083.Search in Google Scholar PubMed PubMed Central
13. Imamura, T, Yoshihara, T, Yokoi, K, Nakai, N, Ishida, H, Kasubuchi, Y. Impact of increased D-dimer concentrations in Kawasaki disease. Eur J Pediatr 2005;164:526–7. https://doi.org/10.1007/s00431-005-1699-7.Search in Google Scholar PubMed
14. Yin, QG, Zhou, J, Zhou, Q, Shen, L, Zhang, MY, Wu, YH. Diagnostic performances of D-dimer, prothrombin time, and red blood cell distribution width for coronary artery lesion in children with acute stage Kawasaki disease. Front Pediatr 2023;11:1141158. https://doi.org/10.3389/fped.2023.1141158.Search in Google Scholar PubMed PubMed Central
15. Trapani, S, Rubino, C, Lasagni, D, Pegoraro, F, Resti, M, Simonini, G, et al.. Thromboembolic complications in children with COVID-19 and MIS-C: a narrative review. Front Pediatr 2022;10:944743. https://doi.org/10.3389/fped.2022.944743.Search in Google Scholar PubMed PubMed Central
16. Ghazizadeh Esslami, G, Mamishi, S, Pourakbari, B, Mahmoudi, S. Systematic review and meta-analysis on the serological, immunological, and cardiac parameters of the multisystem inflammatory syndrome (MIS-C) associated with SARS-CoV-2 infection. J Med Virol 2023;95:e28927. https://doi.org/10.1002/jmv.28927.Search in Google Scholar PubMed
17. Zhao, Y, Yin, L, Patel, J, Tang, L, Huang, Y. The inflammatory markers of multisystem inflammatory syndrome in children (MIS-C) and adolescents associated with COVID-19: a meta-analysis. J Med Virol 2021;93:4358–69. https://doi.org/10.1002/jmv.26951.Search in Google Scholar PubMed PubMed Central
18. Thachil, J, Favaloro, EJ, Lippi, G. D-dimers-"normal" levels versus elevated levels due to a range of conditions, including "D-dimeritis", inflammation, thromboembolism, disseminated intravascular coagulation, and COVID-19. Semin Thromb Hemost 2022;48:672–9. https://doi.org/10.1055/s-0042-1748193.Search in Google Scholar PubMed
19. Tong, T, Yao, X, Lin, Z, Tao, Y, Xu, J, Xu, X, et al.. Similarities and differences between MIS-C and KD: a systematic review and meta-analysis. Pediatr Rheumatol Online J 2022;20:112. https://doi.org/10.1186/s12969-022-00771-x.Search in Google Scholar PubMed PubMed Central
20. García de Guadiana-Romualdo, L, Morell-García, D, Favaloro, EJ, Vílchez, JA, Bauça, JM, Alcaide Martín, MJ, et al.. Harmonized D-dimer levels upon admission for prognosis of COVID-19 severity: results from a Spanish multicenter registry (BIOCOVID-Spain study). J Thromb Thrombolysis 2022;53:103–12. https://doi.org/10.1007/s11239-021-02527-y.Search in Google Scholar PubMed PubMed Central
Supplementary Material
The online version of this article offers supplementary material (https://doi.org/10.1515/dx-2024-0013).
© 2024 Walter de Gruyter GmbH, Berlin/Boston
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Articles in the same Issue
- Frontmatter
- Editorial
- The growing threat of hijacked journals
- Review
- Effects of SNAPPS in clinical reasoning teaching: a systematic review with meta-analysis of randomized controlled trials
- Mini Review
- Diagnostic value of D-dimer in differentiating multisystem inflammatory syndrome in Children (MIS-C) from Kawasaki disease: systematic literature review and meta-analysis
- Opinion Papers
- Masquerade of authority: hijacked journals are gaining more credibility than original ones
- FRAMED: a framework facilitating insight problem solving
- Algorithms in medical decision-making and in everyday life: what’s the difference?
- Original Articles
- Computerized diagnostic decision support systems – a comparative performance study of Isabel Pro vs. ChatGPT4
- Comparative analysis of diagnostic accuracy in endodontic assessments: dental students vs. artificial intelligence
- Assessing the Revised Safer Dx Instrument® in the understanding of ambulatory system design changes for type 1 diabetes and autism spectrum disorder in pediatrics
- The Big Three diagnostic errors through reflections of Japanese internists
- SASAN: ground truth for the effective segmentation and classification of skin cancer using biopsy images
- Computable phenotype for diagnostic error: developing the data schema for application of symptom-disease pair analysis of diagnostic error (SPADE)
- Development of a disease-based hospital-level diagnostic intensity index
- HbA1c and fasting plasma glucose levels are equally related to incident cardiovascular risk in a high CVD risk population without known diabetes
- Short Communications
- Can ChatGPT-4 evaluate whether a differential diagnosis list contains the correct diagnosis as accurately as a physician?
- Analysis of thicknesses of blood collection needle by scanning electron microscopy reveals wide heterogeneity
- Letters to the Editor
- For any disease a human can imagine, ChatGPT can generate a fake report
- The dilemma of epilepsy diagnosis in Pakistan
- The Japanese universal health insurance system in the context of diagnostic equity
- Case Report – Lessons in Clinical Reasoning
- Lessons in clinical reasoning – pitfalls, myths, and pearls: a case of tarsal tunnel syndrome caused by an intraneural ganglion cyst