Imaging Evaluation of Clinical and Subclinical Myocarditis in Multisystem Inflammatory Syndrome of Children with COVID-19 Using Cardiac Magnetic Resonance: The Results and Prognosis
Bibliographic record
Abstract
Background: Coronavirus disease 2019 (COVID-19) has emerged as the most significant health crisis in recent years, leading to over 6 million deaths globally due to the disease. Objectives: Given the prevalence of multisystem inflammatory syndrome in children (MISC) following the COVID-19 pandemic, this study aims to examine the imaging findings and prognoses of clinical and subclinical myocarditis in children with MISC through cardiac magnetic resonance (CMR) imaging. Patients and Methods: This prospective cohort study carried out over eighteen months from May 2021 to November 2022, included 14 patients who underwent CMR imaging. A census of all eligible patients during the study period served as the sampling method. Inclusion criteria were patients with confirmed COVID-19 infection through serological tests, polymerase chain reaction (PCR), or recent exposure to COVID-19 patients. Exclusion criteria included patients with a history of congenital heart disease (CHD) or pulmonary disease. Additional diagnostic tests performed included blood sample tests, chest X-ray (CXR), electrocardiogram (ECG), and echocardiography. CMR imaging was conducted on patients with cardiac involvement. A diagnosis of myocardial inflammation was made if a patient met at least two of the Lake Louise Criteria. The Chi-square, Fisher's exact, and Mann-Whitney tests were used to examine the relationship between quantitative variables and treatment outcomes. Additionally, the Wilcoxon signed rank, and McNemar’s tests assessed changes in echocardiography findings from admission to follow-up. A significance level of 0.05 was set. Results: Among the 14 patients studied, 8 (57.10%) were girls and 6 (42.90%) were boys. The average age was 6.03 ± 3.71 years. The median time to CMR imaging after symptom onset was 4 weeks (interquartile range (IQR): 2 - 12, range: 30). Global function assessment using left ventricular ejection fraction (LVEF) showed that 5 (35.70%), 3 (21.40%), and 6 (42.90%) patients had normal function, mild dysfunction, and significant LV dysfunction, respectively. 71.40% of patients who recovered had mild tricuspid regurgitation (TR) and no cardiomegaly. Significant differences in mean values of polymorphonuclear neutrophil (PMN) (37.71 ± 11.75 vs. 81.44 ± 13.06), lymphocytes (48.71 ± 20.08 vs. 12.51 ± 7.26), hemoglobin (Hb) (12.60 ± 1.55 vs. 10.10 ± 1.62), mean corpuscular volume (MCV) (85.90 ± 5.67 vs. 79.37 ± 5.23), erythrocyte sedimentation rate (ESR) (8.86 ± 13.60 vs. 30.29 ± 21.33), and C-reactive protein (CRP) (18.91 ± 27.25 vs. 100.57 ± 85.67) were observed between non-recovered and recovered patients, respectively (P < 0.05). However, no statistically significant association was found between other variables, including N-terminal pro–B-type natriuretic peptide (NT-proBNP), D-dimer, and Troponin I (TPI), with treatment outcomes (P > 0.05). Conclusion: Our findings indicate that a negative COVID-19 test does not exclude an established clinical COVID-19 infection in children with MISC. The results suggest that all children with MISC and a history of COVID-19 infection should undergo assessment for myocardial fibrosis, regardless of ejection fraction (EF) as determined by Echocardiography, laboratory tests, and COVID-19 test results. Strain analysis, conducted during both the acute phase and subsequent follow-ups through CMR imaging or Echocardiography, is recommended to enhance the understanding of the prognosis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".