Atypical Kawasaki Disease after COVID-19 Vaccination: A New Form of Adverse Event Following Immunization

Kawasaki disease (KD) is a medium-vessel vasculitis that is typically presented during childhood; fewer than 100 cases of KD have been reported worldwide in adult patients who met the criteria according to the American College of Rheumatology. This study presents the case of an 18-year-old patient with no previous history of any disease, who presented atypical KD with liver and kidney dysfunction, with a good response to intravenous immunoglobulin therapy. The symptoms began 22 days after the application of the COVID-19 vaccine (nonreplicating viral vector Vaxzevria), and other conditions were ruled out. The term Adverse Events Following Immunization (AEFI)encompasses all the reactions that follow the application of any vaccine with no necessary causal relationship and can be due to the vaccine product, quality of the vaccine, immunization errors, or anxiety or just happen to be coincident events. These reactions should be reported so that clinicians can identify compatible cases and consider that the presentation of this disease, despite being atypical, can be manifested in adult patients. Likewise, case reports are an important basis for the pharmacovigilance of vaccines.

Background incidence rates of adverse events of special interest related to COVID-19 vaccines in Ontario, Canada, 2015 to 2020, to inform COVID-19 vaccine safety surveillance

Background: Background incidence rates are critical in pharmacovigilance to facilitate identification of vaccine safety signals. We estimated background incidence rates of nine adverse events of special interest related to COVID-19 vaccines in Ontario, Canada. Methods: We conducted a population-based retrospective observational study using linked health administrative databases for hospitalizations and emergency department visits among Ontario residents. We estimated incidence rates of Bells palsy, idiopathic thrombocytopenia, febrile convulsions, acute disseminated encephalomyelitis, myocarditis, pericarditis, Kawasaki disease, Guillain-Barre syndrome, and transverse myelitis during five pre-pandemic years (2015-2019) and 2020. Results: The average annual population was 14 million across all age groups with 51% female. The pre-pandemic mean annual rates per 100,000 population during 2015-2019 were 43.9 for idiopathic thrombocytopenia, 27.8 for Bells palsy, 25.0 for febrile convulsions, 22.8 for acute disseminated encephalomyelitis, 11.3 for myocarditis/pericarditis, 8.6 for pericarditis, 2.9 for myocarditis, 1.9 for Guillain-Barre syndrome, 1.7 for transverse myelitis, and 1.6 for Kawasaki disease. Females had higher rates of acute disseminated encephalomyelitis and transverse myelitis while males had higher rates of myocarditis, pericarditis, and Guillain-Barre syndrome. Bells palsy, acute disseminated encephalomyelitis, and Guillain-Barre syndrome increased with age. The mean rates of myocarditis and/or pericarditis increased with age up to 79 years; males had higher rates than females: from 12-59 years for myocarditis and 12 years and older for pericarditis. Febrile convulsions and Kawasaki disease were predominantly childhood diseases and generally decreased with age. Conclusions: Our estimated background rates will permit estimating numbers of expected events for these conditions and facilitate detection of potential safety signals following COVID-19 vaccination.

Geometrical and Hemodynamic Variables for Thrombotic Risk Stratification in Kawasaki Disease

Objectives Thrombosis is a major adverse outcome for coronary artery aneurysms (CAA) in Kawasaki disease (KD). We investigated the geometric and hemodynamic abnormalities in patients with CAA and identified the risk factors for thrombosis by computational fluid dynamics (CFD) simulation. Methods We retrospectively studied 27 KD patients with 77 CAAs, including 20 CAAs with thrombosis in 12 patients. Patient-specific anatomic models obtained from cardiac magnetic resonance imaging (CMRI) were constructed to perform a CFD simulation. From the simulation results, we produced local hemodynamic parameters comprising of time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI) and relative resident time (RRT). The CAA’s maximum diameter (Dmax) and Z-score were measured on CMRI. Results Giant CAAs tended to present with more severe hemodynamic abnormalities. Thrombosed CAAs exhibited lower TAWSS (1.551 ± 1.535 vs. 4.235 ± 4.640dynes/cm2, p = 0.002), higher Dmax (10.905 ± 4.125 vs. 5.791 ± 2.826mm, p = 0.008), Z-score (28.301 ± 13.558 vs. 13.045 ± 8.394, p = 0.002), OSI (0.129 ± 0.132 vs. 0.046 ± 0.080, p = 0.01), and RRT (16.780 ± 11.982s vs. 9.123 ± 11.770s, p = 0.399) than the non-thrombosed group. An ROC analysis for thrombotic risk proved that all of the five parameters had area under the ROC curves (AUC) above 0.7, with Dmax delineating the highest AUC (AUCDmax = 0.871) and a 90% sensitivity, followed by Z-score (AUCZ−score = 0.849). Conclusions It is reasonable to combine the geometric index with hemodynamic information to establish a severity classification for KD cases.

Nontypical presentation of a common disease: a case report

Background Kawasaki disease is an idiopathic medium-sized vasculitis that occurs primarily in infants and children younger than 5 years of age. Atypical Kawasaki disease applies to patients who do not fulfill the complete criteria of fever of 5 days or more with at least four of five features: bilateral conjunctival injection, changes in the lips and oral cavity, cervical lymphadenopathy, extremity changes, and polymorphous rash. Acute kidney injury is defined as a sudden decline in kidney function within hours, including structural injuries and loss of function. Acute kidney injury is extremely common in hospitalized pediatric patients. However, it is rarely documented in Kawasaki disease. Acute kidney injury is underestimated in Kawasaki disease due to the lack of a clear definition of age-specific normal serum creatinine levels and routine renal functions. This report describes a case who presented with clinical features suggestive of atypical Kawasaki disease and developed acute kidney injury. Case presentation A 2-year-old Saudi girl had a history of high-grade fever for 5 days, moderate dehydration, dry cracked lips, poor appetite, and generalized erythematous rash; therefore, she was diagnosed to have incomplete Kawasaki disease. Laboratory investigations revealed normochromic normocytic anemia, leukocytosis, thrombocytosis, high inflammatory markers, and acute kidney injury stage III. An echocardiogram showed a 4-mm dilatation on the left main coronary artery and a 3-mm dilatation on the right. A renal biopsy was not performed to identify the cause of the injury as it showed improvements after the start of the specific therapy for Kawasaki disease; intravenous immune globulin at a dose of 2 g/kg, aspirin at a high dosage of 80 mg/kg/day, and prednisolone at 2 mg/kg. In addition to the acute kidney injury management, normal saline boluses were followed by furosemide at a 2 mg/kg dose. Her urine output increased, and her renal functions normalized. She was discharged in good condition after 10 days. Conclusions It is valuable to check renal function tests in a confirmed case of Kawasaki disease to reduce the negative consequences of late acute kidney injury discovery. Early detection and intervention make a substantial difference in acute kidney injury management.

An Immunological Axis Involving Interleukin 1β and Leucine-Rich-α2-Glycoprotein Reflects Therapeutic Response of Children with Kawasaki Disease: Implications from the KAWAKINRA Trial

Purpose A recent phase II open-label study of the interleukin 1 (IL-1) receptor antagonist (IL-1Ra) anakinra in treating IVIG-resistant Kawasaki Disease (KD) patients reported promising results. Here, we aimed to characterize the immunological impact of IL-1 blockade in this unique study population. Methods Patients’ and control sera and supernatants of cells (whole blood, neutrophils, coronary artery endothelial cells) stimulated with recombinant IL-1β were analyzed for single or multiple marker (n=22) expression by ELISA or multiplexed bead array assay. Data were analyzed using unsupervised hierarchical clustering, multiple correlation and multi-comparison statistics and were compared to retrospective analyses of KD transcriptomics. Results Inflammation in IVIG-resistant KD (n=16) is hallmarked by over-expression of innate immune mediators (particularly IL-6>CXCL10>S100A12>IL-1Ra). Those as well as levels of immune or endothelial cell activation markers (sICAM-1, sVCAM-1) declined most significantly in course of anakinra treatment. Prior as well as following IL-1R blockade, over-expression of leucine-rich-α2-glycoprotein 1 (LRG1) associated best with remnant inflammatory activity and the necessity to escalate anakinra dosage and separated inflammatory KD patients from sJIA-MAS (n=13) and MIS-C (n=4). Protein as well as retrospective gene expression analyses indicated tight association of LRG1 with IL-1β signaling and neutrophilia, while particularly neutrophil stimulation with recombinant IL-1β resulted in concentration-dependent LRG1 release. Conclusion Our study identifies LRG1 as known trigger of endothelial activation and cardiac re-modelling to associate with IL-1β signaling in KD. Besides a potential patho-mechanistic implication of these findings, our data suggest blood leukocyte and neutrophil counts to best predict response to IL-1Ra treatment in IVIG-resistant KD.

A Simple Scoring Model Based on Machine Learning Predicts Intravenous Immunoglobulin Resistance in Kawasaki Disease

In Kawasaki disease (KD), accurate prediction of intravenous immunoglobulin (IVIG) resistance is crucial to reduce a risk for developing coronary artery lesions. To establish a simple and accurate scoring model predicting IVIG resistance, we conducted a retrospective cohort study of 996 KD patients that were diagnosed at 11 facilities for 10 years, in which 108 cases (23.5%) were resistant to initial IVIG treatment. We performed machine learning with random forest model using 30 clinical variables at diagnosis in 796 and 200 cases for training and test datasets, respectively. Random forest model accurately predicted IVIG resistance (AUC; 0.75, sensitivity; 0.54, specificity; 0.80). Next, using top five influential features (days of illness at initial therapy, serum levels of C-reactive protein, sodium, total bilirubin, and total cholesterol) in the random forest model, we designed a simple scoring system. In spite of its simplicity, the scoring system predicted IVIG resistance (AUC; 0.73, sensitivity; 0.55, specificity; 0.83) as accurately as the random forest model itself. Moreover, accuracy of our scoring system with five clinical features was almost identical to that of Gunma score with seven clinical features (AUC; 0.73, sensitivity; 0.53, specificity; 0.83), a well-known logistic regression scoring model, and superior to that of two widely used scores (Kurume score; 0.67, 0.46 and 0.76, respectively, and Osaka score; 0.69, 0.33 and 0.84, respectively). Conclusions: Our simple scoring system based on the findings in machine learning, as well as machine learning itself, seems to be useful to accurately predict IVIG resistance in KD patients.

Predictive Factors of Medium-Large Coronary Artery Aneurysm in Children with Acute Kawasaki Disease: A Retrospective Cohort Study

Background: The severity of the cardiac complications resulting from Kawasaki disease (KD) appears to be directly correlated to the magnitude of the coronary artery aneurysm (CAA). However, there remains some unclear about the risk factors for medium-large CAA identified after acute KD.Methods: We analyzed 90 patients diagnosed with CAA in KD hospitalized from January 2013 through August 2021. Patients were stratified based on the coronary artery z-score adjusted for body surface area as the medium-large CAA group and small-sized CAA group. The association of baseline characteristics was investigated within the groups. Multivariable logistic regression analyses were performed to evaluate potential risk factors associated with medium-large CAA development.Results: In total, 353 pediatric cases with KD were investigated during the study period, of whom 90 (25.5%) presented with CAA, including medium-large CAA in 20 patients (5.7%) after acute KD. The medium-large CAA group showed significantly higher Harada risk scores, the incidence of thrombosis, serum globulin concentration values, proportions of C-reactive protein > 40 mg/L, proportions of albumin < 35 g/L, and lower values of albumin-to-globulin ratio (A/G ratio) than those in the small-sized CAA group (P < 0.05). Medium-large CAA was significantly associated with the A/G ratio (odds ratio, 3.503; 95% confidence interval [CI]: 1.068–11.492). The area under the receiver operating characteristic curve was 0.684 (95% CI: 0.558–0.810), and the cutoff point of 1.35 showed a sensitivity and specificity for predicting medium-large CAA of 80% and 59%, respectively.Conclusions: A lower A/G ratio independently predicts medium-large CAA in patients with KD. Medium-large CAA is associated with greater odds of developing thrombosis. Thus, close monitoring with routine echocardiography is recommended.

Blood routine risk factors for coronary artery aneurysm in infants younger than 8 months with Kawasaki disease

Objective The aims of this study were to characterize the evolution of routine blood values within the first 10 days of illness and coronary artery outcome in infants < 8 months with Kawasaki disease (KD) and to identify risk factors for coronary artery aneurysm (CAA). Methods Laboratory data, clinical features and coronary artery outcomes from 78 infants < 8 months old and 86 patients between 8 months and 7 years old were retrospectively analyzed. Logistic regression analysis was conducted to evaluate the potential risk factors for CAA. Results Infants < 8 months old were more likely to present with incomplete KD (37.2% vs 4.7%, P < 0.001), erythema and induration at the BCG inoculation site (24.4% vs 3.5%, P < 0.001) and CAA (47.4% vs 15.1%, P < 0.001) even with timely diagnosis and treatment with intravenous immunoglobulin (IVIG) compared with patients ≥8 months old. Clinical feature related to diagnostic criteria for KD including bilateral conjunctival injection, oral changes, unilateral cervical lymphadenopathy and extremity changes were less common in the younger group. During the acute phase, the percentage neutrophils and neutrophil to lymphocyte ratio [NLR] peaked on median illness day 3, followed by white blood cell (WBC) and CRP on median illness day 4, hemoglobin on median illness day 7 and platelet count on median illness day 9. CAA occurred on median illness day 6 and regressed on median illness day 28. Multivariate logistic regression analysis revealed that the peak percentage neutrophils (odds ratio [OR] per 0.1: 1.597, 95% confidence interval [CI]: 1.041–2.452, P = 0.032) and the peak platelet count (OR per 10 × 109/L: 1.029, 95% CI: 1.004–1.055, P = 0.024) were independent risk factors for CAA. Hemoglobin on the 5th day was associated with persistent CAA at 1 year after KD onset. Conclusion Factors associated with CAA include a high peak percentage neutrophils, increased peak platelet count, and reduced hemoglobin within 4–6 days during the acute phase of KD. Therefore, this population should receive primary therapy with IVIG and adjunctive anti-inflammatory medications.

A Diagnostic Model for Kawasaki Disease Based on Immune Cell Characterization From Blood Samples

Background: Kawasaki disease (KD) is the leading cause of acquired heart disease in children. However, distinguishing KD from febrile infections early in the disease course remains difficult. Our goal was to estimate the immune cell composition in KD patients and febrile controls (FC), and to develop a tool for KD diagnosis.Methods: We used a machine-learning algorithm, CIBERSORT, to estimate the proportions of 22 immune cell types based on blood samples from children with KD and FC. Using these immune cell compositions, a diagnostic score for predicting KD was then constructed based on LASSO regression for binary outcomes.Results: In the training set (n = 496), a model was fit which consisted of eight types of immune cells. The area under the curve (AUC) values for diagnosing KD in a held-out test set (n = 212) and an external validation set (n = 36) were 0.80 and 0.77, respectively. The most common cell types in KD blood samples were monocytes, neutrophils, CD4+-naïve and CD8+ T cells, and M0 macrophages. The diagnostic score was highly correlated to genes that had been previously reported as associated with KD, such as interleukins and chemokine receptors, and enriched in reported pathways, such as IL-6/JAK/STAT3 and TNFα signaling pathways.Conclusion: Altogether, the diagnostic score for predicting KD could potentially serve as a biomarker. Prospective studies could evaluate how incorporating the diagnostic score into a clinical algorithm would improve diagnostic accuracy further.