Spectrum of rhabdomyolysis in an acute hospital

Trends in Pediatric Rhabdomyolysis and Associated Renal Failure: A 10-Year Population-Based Study

OBJECTIVES

Rhabdomyolysis in children is a highly variable condition with presentations ranging from myalgias to more severe complications like acute renal failure. We sought to explore demographics and incidence of pediatric rhabdomyolysis hospitalizations and rates of associated renal failure, as our current understanding is limited.

METHODS

This was a retrospective analysis using the Healthcare Cost and Utilization Project Kids' Inpatient Database to identify children hospitalized with a primary diagnosis of rhabdomyolysis. Data were analyzed for demographic characteristics, as well as geographic and temporal trends. Multivariable logistic regression was used to identify characteristics associated with rhabdomyolysis-associated acute renal failure.

RESULTS

From 2006 to 2016, there were 8599 hospitalized children with a primary diagnosis of rhabdomyolysis. Overall, hospitalizations for pediatric rhabdomyolysis are increasing over time, with geographic peaks in the South and Northeast regions, and seasonal peaks in March and August. Though renal morbidity was diagnosed in 8.5% of children requiring hospitalization for rhabdomyolysis, very few of these patients required renal replacement therapy (0.41%), and death was rare (0.03%). Characteristics associated with renal failure included male sex, age greater than 15 years, and non-Hispanic Black race.

CONCLUSIONS

Though renal failure occurs at a significant rate in children hospitalized with rhabdomyolysis, severe complications, including death, are rare. The number of children hospitalized with rhabdomyolysis varies by geographic region and month of the year. Future studies are needed to explore etiologies of rhabdomyolysis and laboratory values that predict higher risk of morbidity and mortality in children with rhabdomyolysis.

Rhabdomyolysis-Induced AKI (RIAKI) Including the Role of COVID-19

Rhabdomyolysis is a compound disease that may be induced by many factors, both congenital and acquired. Statin therapy is considered one of the most common acquired factors. However, recent scientific reports suggest that serious complications such as rhabdomyolysis are rarely observed. Researchers suggest that, in many cases, side effects that occur with statin therapy, including muscle pain, can be avoided with lower-dose statin therapy or in combination therapy with other drugs. One of the most recent agents discovered to contribute to rhabdomyolysis is COVID-19 disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Rhabdomyolysis is defined as a damage to striated muscle cells with escape of intracellular substances into the bloodstream. These substances, including myoglobin, creatine kinase (CK), potassium, and uridine acid, are markers of muscle damage and early complications of rhabdomyolysis. Symptoms may be helpful in establishing the diagnosis. However, in almost 50% of patients, they do not occur. Therefore, the diagnosis is confirmed by serum CK levels five times higher than the upper limit of normal. One of the late complications of this condition is acute kidney injury (AKI), which is immediately life-threatening and has a high mortality rate among patients. Therefore, the prompt detection and treatment of rhabdomyolysis is important. Markers of muscle damage, such as CK, lactate dehydrogenase (LDH), myoglobin, troponins, and aspartate aminotransferase (AST), are important in diagnosis. Treatment of rhabdomyolysis is mainly based on early, aggressive fluid resuscitation. However, therapeutic interventions, such as urinary alkalinization with sodium bicarbonate or the administration of mannitol or furosemide, have not proven to be beneficial. In some patients who develop AKI in the course of rhabdomyolysis, renal replacement therapy (RRT) is required.

Fatal rhabdomyolysis and disseminated intravascular coagulation after total knee arthroplasty under spinal anesthesia: A case report

BACKGROUND

Rhabdomyolysis develops as a result of skeletal muscle cell collapse from leakage of the intracellular contents into circulation. In severe cases, it can be associated with acute kidney injury and disseminated intravascular coagulation, leading to life threatening outcomes. Rhabdomyolysis can occur in the perioperative period from various etiologies but is rarely induced by tourniquet use during orthopedic surgery.

CASE SUMMARY

A 77-year-old male underwent right total knee arthroplasty using a tourniquet under spinal anesthesia. About 24 h after surgery, he was found in a drowsy mental state and manifested features of severe rhabdomyolysis, including fever, hypotension, oliguria, high creatine kinase, myoglobinuria, and disseminated intravascular coagulation. Despite supportive care, cardiac arrest developed abruptly, and the patient was not able to be resuscitated.

CONCLUSION

Severe rhabdomyolysis and disseminated intravascular coagulation can develop from surgical tourniquet, requiring prompt, aggressive treatments to save the patient.

Interpretable Machine Learning Model for Early Prediction of Mortality in ICU Patients with Rhabdomyolysis

PURPOSE

Rhabdomyolysis (RM) is a complex set of clinical syndromes that involves the rapid dissolution of skeletal muscles. Mortality from RM is approximately 10%. This study aimed to develop an interpretable and generalizable model for early mortality prediction in RM patients.

METHOD

Retrospective analyses were performed on two electronic medical record databases: the eICU Collaborative Research Database and the Medical Information Mart for Intensive Care III database. We extracted data from the first 24 h after patient ICU admission. Data from the two data sets were merged for further analysis. The merged data sets were randomly divided, with 70% used for training and 30% for validation. We used the machine learning model extreme gradient boosting (XGBoost) with the Shapley additive explanation method to conduct early and interpretable predictions of patient mortality. Five typical evaluation indexes were adopted to develop a generalizable model.

RESULTS

In total, 938 patients with RM were eligible for this analysis. The area under the receiver operating characteristic curve (AUC) of the XGBoost model in predicting hospital mortality was 0.871, the sensitivity was 0.885, the specificity was 0.816, the accuracy was 0.915, and the F1 score was 0.624. The XGBoost model performance was superior to that of other models (logistic regression, AUC = 0.862; support vector machine, AUC = 0.843; random forest, AUC = 0.825; and naive Bayesian, AUC = 0.805) and clinical scores (Sequential Organ Failure Assessment, AUC = 0.747; Acute Physiology Score III, AUC = 0.721).

CONCLUSIONS

Although the XGBoost model is still not great from an absolute performance perspective, it provides better predictive performance than other models for estimating the mortality of patients with RM based on patient characteristics in the first 24 h of admission to the ICU.

Significance of Asymptomatic Hyper Creatine-Kinase Emia

OBJECTIVES

Whether asymptomatic hyper-CKemia (AHCE) should prompt a thorough work-up for muscle disease or not is controversially discussed. This review aims at summarizing and discussing recent findings concerning the cause, frequency, evolution, and work-up of conditions manifesting as AHCE and normal or abnormal electromyography (EMG) respectively muscle biopsy.

METHODS

Systematic PubMed search.

RESULTS

There are numerous primary (hereditary) and acquired myopathies that manifest with permanent, recurrent, or temporary AHCE with/without myopathic EMG or muscle biopsy. AHCE particularly occurs at onset of these conditions, which include dystrophinopathies, myotilinopathies, calpainopathy, caveolinopathy, dysferlinopathy, central core disease, multicore disease, desminopathy, MD1, MD2, hypoPP, malignant hyperthermia susceptibility, Pompe disease, McArdle disease, myoadenylate deaminase-deficiency, CPT2-deficiency, mitochondrial disorders, or myopathy with tubular aggregates. Most likely, other primary myopathies manifest with AHCE as well, without having been reported. Patients with AHCE should be taken seriously and repeated CK determination must be conducted. If hyper-CKemia is persisting or recurrent, these patients should undergo an EMG and eventually muscle biopsy. If noninformative, genetic work-up by a panel or whole exome sequencing should be initiated, irrespective of the family history. Patients with AHCE should avoid excessive exercise, require sufficient hydration, require counseling with regard to the risk of malignant hyperthermia, and should inform anesthesiologists and surgeons about their condition before elective surgery.

CONCLUSIONS

Recurrent AHCE should be taken seriously and managed with conventional work-up. If noninformative, genetic work-up should follow irrespective of the family history.