Long-term Cardiovascular Outcomes of Multisystem Inflammatory Syndrome in Children Associated with COVID-19 using an Institution Based Algorithm (preprint)

Background: Cardiovascular involvement is a major cause of inpatient and intensive care unit morbidity related to Multisystem inflammatory syndrome in children (MIS-C). The objective of this study was to identify long-term cardiovascular manifestations of MIS-C. Methods: We included 80 consecutive patients admitted to the intensive care unit with MIS-C who were evaluated for a year in our follow-up clinic using an institution protocol. The outcome measures were cardiac biomarkers (troponin and BNP), electrocardiogram changes, echocardiographic findings cardiovascular magnetic resonance (CMR) and graded-exercise stress test (GXT) findings. Results: The cohort included patients aged between 6 months and 17 years (median 9 years; 48.8% females). At the peak of the disease 81.3% had abnormal BNP and 58.8% had troponin leak which reduced to 33.8% and 18.8% respectively at discharge with complete normalization by 6 weeks post-discharge. At admission 33.8% had systolic dysfunction, which improved to 11.3% at discharge with complete resolution by 2 weeks. Coronary artery abnormalities were seen in 17.5% during the illness with complete resolution by 2 weeks post discharge except one (1.9%) with persistent giant aneurysm at 1 year-follow up. CMR was performed at 6 months in 23 patient and demonstrated 4 patients with persistent late gadolinium enhancement (17.4%). Normal exercise capacity with no ectopy was seen in the 31 qualifying patients that underwent a GXT. Conclusions: There is significant heterogeneity in the cardiovascular manifestations of MIS-C. Although majority of the cardiovascular manifestations resolve within 6 weeks, diastolic dysfunction, CAA and myocardial scar may persist in a small subset of patients warranting a structured long-term follow-up strategy.

Severe COVID-19 pneumonia associated with transient complete heart block and myocarditis: A case report (preprint)

A 70-year-old male presented with complaints of fever for 10 days; associated with dry cough for one week, gradually progressive shortness of breath for five days, and non-radiating chest pain for three days. Chest examination revealed bilateral basal crepitation, and cardiac examination showed muffled first heart sound with soft systolic murmur at apex. All severity markers of COVID-19 were elevated. Twelve lead electrocardiography (ECG) showed complete heart block. Troponin-I test was negative. High resolution computed tomography (HRCT) thorax showed extensive bilateral multifocal patchy and confluent areas of ground-glass opacities distributed along with peripheral subpleural and peribronchovascular regions with interlobular septal thickening suggestive of viral pneumonia .He was started on high flow oxygen, parenteral corticosteroids, and anticoagulants with antibiotics coverage. Injection Isoprenaline infusion was started for heart block, but the patient developed atrial flutter-fibrillation with premature ventricular complexes. The patient clinically improved and was discharged on the 11th day of admission. On follow up after 2 weeks, repeat ECG showed atrial fibrillation, and 2D Echocardiography revealed global hypokinesia, severe mitral regurgitation with left ventricular systolic dysfunction (ejection fraction of 28%), and dilated left ventricle and atrium. He was planned for coronary angiography after one month. High clinical suspicion, early diagnosis, and prompt treatment with corticosteroids can yield a favorable outcome. Follow up is necessary to rule out long term complications like viral cardiomyopathy.

BASELINE METABOLIC PROFILING AND RISK OF DEATH FROM COVID-19 (preprint)

ABSTRACT Objective To derive a predicted probability of death (PDeathLabs) based upon complete value sets for 11 clinical measurements (CM) obtained on patients prior to their diagnosis of coronavirus disease (COVID-19). PDeathLabs is intended for use as a summary metric for baseline metabolic status in multivariate models for COVID-19 death. Methods Cases were identified through the COVID-19 Shared Data Resource (CSDR) of the Department of Veterans Affairs. The diagnosis required at least one positive nucleic acid amplification test (NAAT). The primary outcome was death within 60 days of the first positive test. We retrieved all values for systolic blood pressure (SBP), diastolic blood pressure (DBP), oxygen saturation (O2SAT), body mass index (BMI), estimated glomerular filtration rate (EGFR), alanine aminotransferase (ALT), serum albumin (ALB), hematocrit (HCT), LDL cholesterol (LDL) hemoglobin A1c (A1C), and HDL cholesterol (HDL) if they were done at least 14 days prior to the NAAT. Clinicians evaluate several attributes of CM that are of critical importance: metabolic control, disease burden, chronicity, refractoriness, tendency to relapse, temporal trends, and lability. We derived 1-3 parameters for each of these attributes: the most recent value (metabolic control); time-weighted average and abnormal area under a severity versus time curve (disease burden); time and number of readings above or below goal (chronicity); longest abnormal cluster and time/number of consecutive readings above goal if the last value was abnormal (refractoriness); number of abnormal clusters (tendency to relapse); long- and short-term changes (temporal trends); and coefficient of variation and mean deviation between consecutive readings (lability). We created computer programs to derive cumulative values for these 13 parameters for all 11 CM as each new value is added. A fitted logistic model was developed for each CM to determine which of the 13 parameters contributed to the risk of death. A main logistic model was developed to determine which of the 13 × 11 = 143 metabolic parameters were independently predictive of death. The resulting model was used to derive PDeathLabs for each patient and the area under its receiver operating characteristic (ROC) curve calculated. Single variable logistic models were also derived for age at diagnosis, the Charlson 2-year (Charl2Yr) and lifetime (CharlEver) scores, and the Elixhauser 2-year (Elix2Yrs) and lifetime (ElixEver) scores. Stata was used to compare the ROCs for PDeathDx and each of the other metrics. Results On September 30, 2021, there were 347,220 COVID-19 patients in the CSDR. 329,491 (94.9%) patients had CM performed at least 14 days prior to the COVID-19 diagnosis and form the basis for this report. 17,934 (5.44%) died within 60 days of the diagnosis. On the subset regressions, the number of significant parameters ranged from all 13 for SBP to 7 for HDL. 239,393 patients had complete sets of data for developing the main model. Of 143 candidate predictors, 49 parameters were identified as statistically significant, independent predictors of death. The most influential domains were the most recent value, disease burden, temporal trends, and tendency to relapse. The ROC area for PDeathLabs was 0.785 +/- 0.002. No difference was found in the ROC areas of PDeathLabs and age at diagnosis (0.783 +/- 0.002; P = NS). However, the ROC area for PDeathLabs was significantly greater than that of Charl2Yrs (0.704 +/- 0.002; P < 0.001), CharlEver (0.729 +/- 0.002; P < 0.001), Elix2Yrs (0.675 ± 0.002; P < 0.001), and ElixEver (0.707 +/- 0.002; P < 0.001). A poor prognosis was found for chronic systolic hypertension. On the other hand, a higher BMI was protective once SBP, DBP, HDL, LDL and A1C were considered. Conclusions Our study confirms that parameters derived for 11 CM are significant determinants of COVID-19 death. The most recent value should not be selected over other parameters for multivariate modeling unless there is a physiologic basis for doing so. PDeathLabs has the same discriminating power as age at diagnosis and outperforms comorbidity indices as a summary metric for pre-existing conditions. If validated by others, this approach provides a robust approach to handling CM in multivariate models.