Home Diagnostic value of D-dimer in differentiating multisystem inflammatory syndrome in Children (MIS-C) from Kawasaki disease: systematic literature review and meta-analysis
Article
Licensed
Unlicensed Requires Authentication

Diagnostic value of D-dimer in differentiating multisystem inflammatory syndrome in Children (MIS-C) from Kawasaki disease: systematic literature review and meta-analysis

  • Giuseppe Lippi ORCID logo EMAIL logo , Camilla Mattiuzzi and Emmanuel J. Favaloro ORCID logo
Published/Copyright: February 21, 2024

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.


Corresponding Author: Prof. Giuseppe Lippi, MD, Section of Clinical Biochemistry, University Hospital of Verona, Piazzale LA Scuro, Verona 37134, Italy, Phone: +39 045 8124308, Fax: +39 045 8122970, E-mail:

  1. Research ethics: The study was conducted in accordance with the Declaration of Helsinki and in compliance with relevant local legislation.

  2. Informed consent: Not applicable.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Competing interests: The authors state no conflict of interest.

  5. Research funding: None declared.

  6. 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).


Received: 2024-01-16
Accepted: 2024-02-07
Published Online: 2024-02-21

© 2024 Walter de Gruyter GmbH, Berlin/Boston

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. The growing threat of hijacked journals
  4. Review
  5. Effects of SNAPPS in clinical reasoning teaching: a systematic review with meta-analysis of randomized controlled trials
  6. Mini Review
  7. Diagnostic value of D-dimer in differentiating multisystem inflammatory syndrome in Children (MIS-C) from Kawasaki disease: systematic literature review and meta-analysis
  8. Opinion Papers
  9. Masquerade of authority: hijacked journals are gaining more credibility than original ones
  10. FRAMED: a framework facilitating insight problem solving
  11. Algorithms in medical decision-making and in everyday life: what’s the difference?
  12. Original Articles
  13. Computerized diagnostic decision support systems – a comparative performance study of Isabel Pro vs. ChatGPT4
  14. Comparative analysis of diagnostic accuracy in endodontic assessments: dental students vs. artificial intelligence
  15. Assessing the Revised Safer Dx Instrument® in the understanding of ambulatory system design changes for type 1 diabetes and autism spectrum disorder in pediatrics
  16. The Big Three diagnostic errors through reflections of Japanese internists
  17. SASAN: ground truth for the effective segmentation and classification of skin cancer using biopsy images
  18. Computable phenotype for diagnostic error: developing the data schema for application of symptom-disease pair analysis of diagnostic error (SPADE)
  19. Development of a disease-based hospital-level diagnostic intensity index
  20. HbA1c and fasting plasma glucose levels are equally related to incident cardiovascular risk in a high CVD risk population without known diabetes
  21. Short Communications
  22. Can ChatGPT-4 evaluate whether a differential diagnosis list contains the correct diagnosis as accurately as a physician?
  23. Analysis of thicknesses of blood collection needle by scanning electron microscopy reveals wide heterogeneity
  24. Letters to the Editor
  25. For any disease a human can imagine, ChatGPT can generate a fake report
  26. The dilemma of epilepsy diagnosis in Pakistan
  27. The Japanese universal health insurance system in the context of diagnostic equity
  28. Case Report – Lessons in Clinical Reasoning
  29. Lessons in clinical reasoning – pitfalls, myths, and pearls: a case of tarsal tunnel syndrome caused by an intraneural ganglion cyst
Downloaded on 13.9.2025 from https://www.degruyterbrill.com/document/doi/10.1515/dx-2024-0013/html
Scroll to top button