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    1 Comment for this article
    Social media and 'rhabdo'
    Marco D. Huesch | USC, Duke Universities
    I’ve been following some of the controversy regarding over-exercise and rhabdomyolyis.(1) Separately, I’ve been using social media tools to understand their utility and limitations for biosurveillance. I was curious, so I used a commercially-available social media monitoring tool (Marketwire by Sysomos) and found that in the 12 months to 11/3/2013, there were 21,496 mentions of rhabdo or rhabdomyolysis in the media space (11% in blogs, 45% in Twitter, 33% in forums and 11% in traditional news). The most common words associated with these mentions that implied causation were ‘statins’, ‘workout’, ‘crossfit’, ‘infected’ and ‘drug’, while the most common words that implied consequences were ‘kidneys’, ‘renal’ and ‘failure’ but not any words relating to death.Restricting inquiry to just ‘rhabdo’ yielded 7,947 mentions with common associated words ‘workout’, ‘gym’, ‘athletes’, ‘squat’, ‘situps’ and ‘crossfit’ as well as ‘kidneys’. Further restricting search to just mentions of both ‘rhabdo’ and ‘kidney(s)’ yielded just 454 mentions.The intersection of youthful, ‘rhabdo’ slang users, social media use and strenuous exercise interests focuses attention on that very small subset of rhabdomyolysis events that correspond to the 2-3% of events caused by exercise in the authors’ sample. However, these superficial social media results do also suggest that among these (overwhelmingly young and female) social media users there seems little discussion of fatal events associated with exercise-induced rhabdomyolysis. This is clearly consistent with the authors’ risk model’s predictions of a low risk for this particular subset.===(1) Sepkowitz K. Cool it on the CrossFit: what’s rhabdomyolysis? Available:http://www.thedailybeast.com/articles/2013/10/11/cool-it-on-the-crossfit-what-s-rhabdomyolysis.html
    Original Investigation
    October 28, 2013

    A Risk Prediction Score for Kidney Failure or Mortality in Rhabdomyolysis

    Author Affiliations
    • 1Renal Division, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
    • 2Framingham Heart Study, National Heart, Lung, and Blood Institute, and Center for Population Studies, Framingham, Massachusetts
    • 3Department of Nephrology, West China Hospital of Sichuan University, Chengdu, China
    JAMA Intern Med. 2013;173(19):1821-1827. doi:10.1001/jamainternmed.2013.9774

    Importance  Rhabdomyolysis ranges in severity from asymptomatic elevations in creatine phosphokinase levels to a life-threatening disorder characterized by severe acute kidney injury requiring hemodialysis or continuous renal replacement therapy (RRT).

    Objective  To develop a risk prediction tool to identify patients at greatest risk of RRT or in-hospital mortality.

    Design, Setting, and Participants  Retrospective cohort study of 2371 patients admitted between January 1, 2000, and March 31, 2011, to 2 large teaching hospitals in Boston, Massachusetts, with creatine phosphokinase levels in excess of 5000 U/L within 3 days of admission. The derivation cohort consisted of 1397 patients from Massachusetts General Hospital, and the validation cohort comprised 974 patients from Brigham and Women’s Hospital.

    Main Outcomes and Measures  The composite of RRT or in-hospital mortality.

    Results  The causes and outcomes of rhabdomyolysis were similar between the derivation and validation cohorts. In total, the composite outcome occurred in 19.0% of patients (8.0% required RRT and 14.1% died during hospitalization). The highest rates of the composite outcome were from compartment syndrome (41.2%), sepsis (39.3%), and following cardiac arrest (58.5%). The lowest rates were from myositis (1.7%), exercise (3.2%), and seizures (6.0%). The independent predictors of the composite outcome were age, female sex, cause of rhabdomyolysis, and values of initial creatinine, creatine phosphokinase, phosphate, calcium, and bicarbonate. We developed a risk-prediction score from these variables in the derivation cohort and subsequently applied it in the validation cohort. The C statistic for the prediction model was 0.82 (95% CI, 0.80-0.85) in the derivation cohort and 0.83 (0.80-0.86) in the validation cohort. The Hosmer-Lemeshow P values were .14 and .28, respectively. In the validation cohort, among the patients with the lowest risk score (<5), 2.3% died or needed RRT. Among the patients with the highest risk score (>10), 61.2% died or needed RRT.

    Conclusions and Relevance  Outcomes from rhabdomyolysis vary widely depending on the clinical context. The risk of RRT or in-hospital mortality in patients with rhabdomyolysis can be estimated using commonly available demographic, clinical, and laboratory variables on admission.