ABSTRACT
INTRODUCTION: Rhabdomyolysis describes a condition where muscle tissue destruction occurs. Mortality and morbidity can be significant especially when multi-organ injury ensues. In very few instances, myocarditis has been described in association with this condition. DESCRIPTION: An 11-year-old previously healthy female presents with vomiting, diarrhea, tactile fever, worsening severe bilateral leg pain and gross hematuria for four days. At the Emergency Department, her ECG showed ST depression in lateral leads and abnormal Q waves. Laboratory studies were notable for significantly elevated CK >330,000 U/L. Elevated Troponin T and Troponin I at 3.60 ng/ml and 0.54 ng/mL, respectively. Elevation of CRP 23.5 mg/dl, ALT 1,966 U/L, AST 5,956 U/L, and Ferritin 712.1 ng/ml. Patient had dark brown urine, which was positive for blood, and urine myoglobin peaked at 2690 ng/mL. Her renal function was normal with blood urea nitrogen 8 mg/dl and creatinine 0.4 mg/dl. C3 and C4 levels were decreased, 45 mg/dl and 5 mg/dl, respectively. Anti-dsDNA negative, ANCA negative, and ANA negative. Nasopharyngeal PCR was negative for Mycoplasma pneumoniae, influenza A and B. Blood enterovirus PCR negative. COVID PCR and antibodies negative. Neuromuscular genetic testing was non-diagnostic. Her echocardiography showed thin rim of pericardial effusion and normal ejection fraction. Cardiac MRI demonstrated myocardial edema and regional sub-epicardial delayed enhancement consistent with acute myocarditis. Patient was started on hyperhydration therapy, Solumedrol and intravenous immunoglobulin. The rhabdomyolysis resulted in severe extremity weakness requiring prolonged rehabilitation. Her condition and biomarkers normalized and was subsequently discharged home. Follow up cardiac MRI 6 months later showed increased extracellular volume (ECV) of 38% suggestive of focal and diffuse areas of fibrosis. Patient remains under physical activity restrictions and is being followed by cardiology service. DISCUSSION: Our case highlights severe rhabdomyolysis in association with acute myocarditis and subsequent cardiac structural abnormalities. Although it remains unclear whether myocarditis evolved as a complication of rhabdomyolysis or was triggered by same inciting agent, an infectious etiology overall remains the most likely culprit.
ABSTRACT
The world is facing a huge loss of both humans and the economy due to COVID-19. Utilizing limited health care facilities properly might help reduce this burden. We provide a pipeline that focuses to develop a scheduler to optimally allocate medical staff based on the predicted number of cases. First, we detect the flow of initial cases in terms of network transmission using networkx (Python package). We develop a model based on Bidirectional Long Short-Term Memory (Bi-LSTM), a deep learning technique to predict future cases using recurrent neural networks with average MSE (mean squared error) of 7.2174e-04 and a novel scheduling technique is proposed by genetic and constraint algorithm-based approach. Our tool can prepare an efficient work schedule for the medical staff at the care centers based on the predicted total COVID cases for next week(s). This is the first attempt to study the pandemic situation in a region from the above-mentioned major perspectives in an integrated way. Several graphical representations and simulation results are presented to validate the obtained results. We demonstrate our method using the data for the region of New Delhi, India. However, it is a general approach and can be applied to any region in the world. © 2021 IEEE.