A Risk Prediction Score for Kidney Failure Or Mortality in Rhabdomyolysis

Research

Original Investigation A Risk Prediction Score for Kidney Failure or Mortality in Rhabdomyolysis

Gearoid M. McMahon, MB, BCh; Xiaoxi Zeng, MD; Sushrut S. Waikar, MD, MPH

Invited Commentary 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, Massachu- setts, 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.

Author Affiliations: Renal Division, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts (McMahon, Zeng, Waikar); Framingham Heart Study, National Heart, Lung, and Blood Institute, and Center for Population Studies, Framingham, Massachusetts (McMahon); Department of Nephrology, West China Hospital of Sichuan University, Chengdu, China (Zeng). Corresponding Author: Gearoid M. McMahon, MB, BCh, Renal Division, Brigham and Women’s Hospital, 75 JAMA Intern Med. doi:10.1001/jamainternmed.2013.9774 Francis St, Boston, MA 02115 Published online September 2, 2013. ([email protected]).

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habdomyolysis is characterized by muscle injury lead- by reviewing ICD-9-CM codes (410.x), DRG codes, and medi- ing to the release of intracellular muscle contents into cal record review of selected cases. For those patients with mul- R the systemic circulation. Because muscle injury from tiple admissions during the study period, we included the first any cause can lead to rhabdomyolysis, the causes are numer- admission only. ous and include trauma or muscle compression as well as non- traumatic causes.1 The outcomes following rhabdomyolysis are Ascertainment of Clinical Characteristics and Outcomes similarly variable, ranging from asymptomatic elevations of We determined the most likely cause of rhabdomyolysis by hav- creatine phosphokinase (CPK) concentration to life- ing 1 of us (G.M.M.) review the DRG code assigned at dis- threatening electrolyte abnormalities and acute kidney in- charge, ICD-9-CM codes, CPT codes, and electronic discharge jury (AKI) requiring hemodialysis or continuous renal replace- summaries when administrative data were not informative; pa- ment therapy (RRT). Acute kidney injury is a feared and tients were then further classified as “medical” or “surgical.” common complication of rhabdomyolysis, occurring in 13% to We confirmed in-hospital mortality and dates of death ob- 50% of patients,2,3 with reported mortality rates as high as 59% tained by administrative data by reviewing electronic death in critically ill patients.4 Currently, clinicians lack tools to pre- notes and/or discharge summaries from the electronic medi- dict adverse outcomes in patients with rhabdomyolysis. The cal record. Acute kidney injury was defined and staged ac- degree of CPK elevation is often used clinically as a marker of cording to the definition by the Kidney Disease: Improving disease severity but has been reported to have a weak corre- Global Outcomes group using creatinine values but not urine lation with risk.1 output because accurate urine output data were not available.7 The ability to identify patients early in the course of rhab- For the baseline creatinine, we used the preadmission creati- domyolysis who are likely to have adverse clinical outcomes nine value or, if not available, the lowest creatinine mea- would be useful for risk stratification in the emergency de- sured during hospitalization. We confirmed every case of RRT partment, early institution of aggressive prophylactic mea- during hospitalization by reviewing the electronic medical rec- sures, and communication with patients and families about ords of all patients with appropriate diagnostic and proce- prognosis. In this study, we used clinical and laboratory data dure codes (ICD-9-CM codes 39.95 and 54.98 and CPT codes from 2 large hospitals to derive and validate a risk prediction 90935, 90937, 90945, and 909475). equation to estimate the chance of RRT or death in patients with rhabdomyolysis. Statistical Analysis Categorical covariates were described by frequency distribu- tion, while continuous covariates were expressed in terms of Methods their mean (SD) or median and interquartile range as appropriate. Unadjusted associations between the covariates and the Data Collection primary outcome were evaluated using χ2 tests for categori- We obtained data from 2 teaching hospitals in the northeast- cal data, while for continuous data, the t test was used for nor- ern United States (Brigham and Women’s Hospital [BWH] and mally distributed variables and the Kruskal-Wallis test for non- Massachusetts General Hospital [MGH]) on patients admit- parametric data. Unadjusted restricted cubic spline analysis ted between January 1, 2000, and March 31, 2011, through the was performed to explore the reported nonlinear relation- Partners Healthcare System Research Patient Data Registry, a ship between initial CPK and risk of the composite outcome. centralized clinical data warehouse designed for research and Adjusted odds ratios were estimated by multivariable logistic quality improvement purposes that has been accessed for clini- regression. cal studies.5,6 We obtained information on patient demograph- We used the MGH cohort to derive a risk prediction score ics (age, sex, and race), length of stay, vital status at hospital and then externally validated the score in the BWH cohort. We discharge, billing codes (International Classification of Dis- chose MGH as the derivation cohort because complete data eases, Ninth Revision, Clinical Modification [ICD-9-CM]; Cur- were available in 98.9% of patients (16 were missing calcium rent Procedural Terminology [CPT]; and diagnosis-related group and/or phosphate values) compared with 69.3% of patients in [DRG]), electronic discharge summaries, and inpatient labo- the BWH cohort, due primarily to missing phosphate values ratory values, including CPK, creatinine, phosphate, cal- in the latter (299 [30.7%] with missing phosphate values, of cium, potassium, albumin, bicarbonate, white blood cell count, whom 4 were also missing calcium values). Phosphate values hemoglobin, and platelet count. Approval for this study was were more likely to be missing in the BWH cohort than in the granted by the institutional review board at Partners, and the MGH cohort because of differences in ordering laboratory tests need for informed consent was waived. between the 2 hospitals. At BWH, in contrast to MGH, a standard chemistry panel includes calcium but not phosphate, Study Population whereas at MGH, calcium and phosphate are typically or- The inclusion criteria were age older than 18 years and CPK lev- dered together with the standard chemistry panel. We ex- els in excess of 5000 U/L within 72 hours of admission. We excluded those with missing values from the derivation cohort cluded patients with preexisting end-stage renal disease and and assumed normal values for missing laboratory values in those transferred from an outside facility who were receiving the validation cohort. We first selected clinically plausible vari- RRT for at least 24 hours. We also excluded 539 patients with ables that were potentially associated with the composite out- CPK elevation considered due to acute myocardial infarction come of RRT or in-hospital mortality. Those variables associ-

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ated with the composite outcome in bivariable analyses were lignant syndrome (36.4%), abdominal or thoracic surgery then subjected to a backward stepwise logistic regression pro- (27.4%), and following cardiac arrest (58.5%). The lowest rates cedure based on a Wald χ2 P value of more than .05. The final of the primary outcome were from myositis (1.7%), exercise variables included in the model were age; sex; quintiles of ini- (3.2%), and seizures (6.0%) (Figure 1). When stratified by cause tial phosphate, calcium, creatinine, and bicarbonate; CPK lev- of rhabdomyolysis, the rates of the primary outcome were simi- els in excess of 40 000; and cause of rhabdomyolysis (sei- lar in the MGH and BWH cohorts (Table 1). zure, syncope, statins, myositis, or exercise vs other causes). We selected the first available result for each laboratory vari- Degree of CPK Elevation able for analysis. For each variable, quintiles with β coeffi- In the 2 cohorts, we found no evidence of a linear association cients that were not significantly different were grouped for between CPK and risk of the composite outcome. In unad- the final logistic regression model. We then divided the β co- justed logistic regression models with restricted cubic splines, efficients for each category by the smallest value ofaβcoef- we found increased risk of the composite outcome only with ficient in the model to allocate an integer or half integer score CPK levels in excess of 40 000 U/L. The C statistics for logistic for each variable. We generated a score for each individual regression models containing initial and peak CPK were only based on the sum of the scores for every variable; this score 0.52 and 0.61, respectively. was incorporated into a final model. We assessed the model’s discrimination using the C statistic and calibration with the Derivation and Validation of Prediction Rule Hosmer-Lemeshow (H-L) goodness-of-fit test using deciles. Using MGH as the derivation cohort, we constructed a multi- Confidence intervals (95%) were calculated using a nonpara- variable logistic regression model with RRT or in-hospital mor- metric bootstrap method. We validated the final multivari- tality as the outcome. Significant predictors of the primary out- able logistic regression model in the BWH cohort. Because of come included age, female sex, cause of rhabdomyolysis, initial the large number of missing phosphate values in the valida- creatinine, CPK, phosphate, calcium, and bicarbonate (Table 2). tion cohort, we performed a sensitivity analysis to determine The C statistic for the model was 0.82 (95% CI, 0.79-0.85). The whether the model performed equally well in patients who did model was well calibrated according to the H-L test (P =.07). and did not have complete data. A risk score was generated for each individual using the β co- efficients from the logistic regression model. The parameters for the risk score are shown in Table 3. The mean (SD) risk score Results was 6.4 (3.2) (range, 0-17.5). A low risk score predicted a fa- vorable outcome: a score of less than 5 identified patients with Between January 1, 2000, and March 31, 2011, we identified 3501 a 3% risk of the primary outcome, while a score of more than hospitalizations of adults with a CPK level in excess of 5000 10 was associated with a risk of 59.2%. Using 5 as the cutoff, U/L. After excluding 58 patients with end-stage renal disease the negative predictive value for the primary outcome was or RRT on transfer from an outside institution, 74 multiple ad- 97.0%, while the positive predictive value was 29.6%. In a lo- missions, 459 with CPK elevation more than 3 days after ad- gistic regression model using the score as a predictor, the C sta- mission, and 539 admitted with an acute myocardial infrac- tistic was 0.82 (95% CI, 0.80-0.85) and the H-L P value was .14. tion, the final study population included 2371 patients (1397 Each 1-point increase in the risk score was associated with an from MGH and 974 from BWH). Mean (SD) age was 50.7 (19.2) adjusted odds ratio of 1.49 (95% CI, 1.42-1.57) for the primary years, and 73.8% were male (Table 1). Review of administra- outcome. tive codes and electronic discharge summaries identified medi- We performed external validation of the model in the BWH cal conditions as the clinical setting for rhabdomyolysis in 47.1% cohort. The C statistic for the model including the risk score of patients compared with 52.9% for surgical settings. The clini- was 0.83 (95% CI, 0.80-0.86), and the H-L P value was .28. cal conditions most frequently associated with rhabdomyoly- Figure 2 shows the observed probabilities in the derivation and sis were trauma (26.3%), immobilization (18.1%), sepsis (9.9%), validation cohorts. A score of less than 5 was associated with and vascular and cardiac operations (8.1% and 5.9%, respec- a risk of the primary outcome of 2.3%, while a score of more tively). Other causes are shown in Table 1. than 10 was associated with a risk of 61.2%. The negative predictive value for a score of less than 5 in the validation cohort Outcomes Associated With Rhabdomyolysis was 97.7%, while the positive predictive value was 27.2%. In Among patients with rhabdomyolysis in the 2 cohorts, 47.7% the validation cohort, 30.1% of patients were missing phos- developed AKI as described by the Kidney Disease: Improv- phate values. The risk of the primary outcome was lower in ing Global Outcomes consensus definition.7 The composite out- patients with missing values (8.7% vs 20.5%, P < .001), sup- come occurred in 19.0% of patients (8.0% required RRT and porting the imputation of normal values in those with miss- 14.1% died during hospitalization). In-hospital mortality was ing phosphate values. In addition, in sensitivity analyses, we higher in patients with AKI (22.5% vs 7.1%, P < .001) and sub- found similar calibration and discrimination when restrict- stantially higher in patients requiring RRT (40.0% vs 11.9%, ing the validation cohort to those with nonmissing phos- P < .001). Outcomes were comparable between MGH and BWH phate values (area under the curve [AUC] = 0.81 [0.77-0.85] and (Table 1). The clinical conditions with the highest rates of the H-L P = .73). In the validation cohort, the C statistics for the composite outcome of RRT or in-hospital mortality were com- prediction of AKI (stage I and higher), AKI stage II and higher, partment syndrome (41.2%), sepsis (39.3%), neuroleptic ma- AKI stage III, in-hospital mortality, and RRT were 0.68 (95%

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Table 1. Baseline Clinical Characteristics, Cause of Rhabdomyolysis, Laboratory Values, and Outcomes Associated With Rhabdomyolysis

No. (%) Brigham and Massachusetts Women’s Hospital General Hospital (Validation Characteristic Total (Derivation Cohort) Cohort) P Value No. 2371 1397 974 Male sex 1749 (73.8) 1029 (73.7) 720 (73.9) .89 Age, mean (SD), y 50.7 (19.2) 52.4 (19.7) 51.3 (18.6) .12 White race 1731 (73.0) 1058 (75.7) 673 (69.1) <.001 Diabetes mellitus 443 (18.7) 224 (16.0) 219 (22.5) <.001 Creatinine, mean (SD), mg/dL 1.7 (1.6) 1.8 (1.7) 1.6 (1.3) .004 Initial CPK, median (IQR), U/L 5114 5519 3759 <.001 (1101-9660) (1437-10 571) (798-8981) Phosphate, mean (SD), mg/dL 4.2 (2.5) 4.2 (2.6) 4.1 (2.3) .16 Calcium, mean (SD), mg/dL 8.4 (1.2) 8.4 (1.2) 8.3 (1.2) .02 Potassium, mean (SD), mEq/L 4.2 (1.0) 4.2 (1.1) 4.2 (0.9) .62 Bicarbonate, mean (SD), mEq/L 22.5 (5.1) 22.8 (5.2) 22.1 (4.9) .004 Surgical 1255 (52.9) 704 (50.4) 551 (56.6) .003 Trauma 624 (26.3) 398 (28.5) 226 (23.2) .004 Vascular surgery 192 (8.1) 114 (8.2) 78 (8.0) .89 Cardiac surgery 139 (5.9) 32 (2.3) 107 (11.0) <.001 Abdominal/thoracic surgery 164 (6.9) 83 (5.9) 81 (8.3) .03 Burns 69 (2.9) 46 (3.3) 23 (2.4) .18 Orthopedic surgery 50 (2.1) 19 (1.4) 31 (3.2) .002 Compartment syndrome 17 (0.7) 12 (0.9) 5 (0.5) .33 Medical 1116 (47.1) 693 (49.6) 423 (43.4) .003 Immobilization 429 (18.1) 298 (21.3) 131 (13.5) <.001 Sepsis 234 (9.9) 139 (10.0) 95 (9.8) .88 Seizures or syncope 133 (5.6) 85 (6.1) 48 (4.9) .23 Cardiac arrest 82 (3.5) 49 (3.5) 33 (3.4) .88 Statin myopathy 65 (2.7) 35 (2.5) 30 (3.1) .40 Exercise 62 (2.6) 40 (2.9) 22 (2.3) .36 Myopathy or myositis 59 (2.5) 18 (1.3) 41 (4.2) <.001 Diabetic ketoacidosis 20 (0.8) 13 (0.9) 7 (0.7) .58 Neuroleptic malignant 11 (0.5) 7 (0.5) 4 (0.4) .75 syndrome Cocaine 9 (0.4) 6 (0.4) 3 (0.3) .64 Unknown 12 (0.5) 3 (0.2) 9 (0.9) .02 Outcomes Acute kidney injury

Stage I 453 (19.1) 264 (18.9) 189 (19.4) Abbreviations: CPK, creatine Stage II 191 (8.1) 114 (8.2) 77 (7.9) .95 phosphokinase; IQR, interquartile range. Stage III 437 (18.4) 262 (18.8) 175 (18.0) SI conversion factors: To convert Renal replacement therapy 190 (8.0) 122 (8.7) 68 (7.0) .12 creatinine to micromoles per liter, In-hospital mortality 335 (14.1) 205 (14.7) 130 (13.3) .36 multiply by 88.4; calcium to Composite outcome 450 (19.0) 281 (20.1) 169 (17.4) .09 millimoles per liter, multiply by 0.25; and potassium and bicarbonate to Length of stay, median (IQR), d 9 (4-18) 9 (5-19) 8 (4-16) .01 millimoles per liter, multiply by 1.0.

CI, 0.65-0.72), 0.75 (0.72-0.79), 0.80 (0.76-0.83), 0.80 (0.77- tals, we have derived and externally validated a simple risk pre- 0.84), and 0.83 (0.78-0.88), respectively. diction score to estimate the risk of RRT or in-hospital mortality. The risk score has several important attributes for clinical utility. It is easily calculated with readily available clinical, Discussion demographic, and laboratory values; has good discrimination (ie, accuracy) and calibration (ie, accuracy across a range In this study involving more than 2000 patients admitted with of predicted probabilities); and provides estimates of “hard” rhabdomyolysis during a 10-year period to 2 teaching hospi- clinical end points of importance to clinicians caring for patients

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Figure 1. Rates of In-hospital Mortality or Acute Kidney Injury Requiring Renal Replacement Therapy, Stratified by Cause of Rhabdomyolysis

60 RRT + in-hospital mortality 50 In-hospital mortality alone RRT alone 40

10 % Mortality RRT or AKI Requiring

0 1) 59) 62) 65) 20) 50) 21) 69) 1 17) 82) = = 133) = 624) = = = 139) 429) = 192) 164) = 234) ======

Other (n Burns (n Sepsis (n Exercise (n Trauma (n

Cardiac arrest (n Statin myopathy (n Immobilization (n Cardiac surgery (n Vascular surgery (n Myopathy/myositis (nSeizures/syncope (n Orthopedic surgery (n Diabetic ketoacidosis (n Compartment syndrome (n

Abdominal/thoracic surgery (n Neuroleptic malignant syndrome (n AKI indicates acute kidney injury; RRT, renal replacement therapy.

Table 2. Outcomes by Category of Risk Score

No. (%) Mortality or Renal Renal Replacement Replacement Variable No. Therapy Therapy Mortality Total 2371 450 (19.0) 190 (8.0) 335 (14.1) Age, y ≤50 1162 165 (14.2) 93 (8.0) 99 (8.5) >50 to ≤70 759 168 (22.1) 65 (8.6) 127 (16.7) >70 to ≤80 274 68 (24.8) 26 (9.5) 61 (22.3) >80 176 49 (27.8) 6 (3.4) 48 (27.3) Male sex 1749 304 (17.4) 142 (8.1) 212 (12.1) Female sex 622 146 (23.5) 48 (7.7) 123 (19.8) Initial creatinine, mg/dL ≤1.4 1493 149 (10.0) 44 (3.0) 125 (8.4) >1.4 to ≤2.2 442 111 (25.1) 36 (8.1) 92 (20.8) >2.2 436 190 (43.6) 110 (25.2) 118 (27.1) Initial calcium, mg/dLa ≥7.5 1855 287 (15.5) 103 (5.6) 227 (12.2) <7.5 499 163 (32.7) 87 (17.4) 108 (21.6) Initial CPK, U/L ≤40 000 2235 402 (18.0) 148 (6.6) 324 (14.5) >40 000 136 48 (35.3) 42 (31.0) 11 (8.1) Cause Seizures, syncope, exercise, statins, 313 16 (5.1) 13 (4.2) 6 (1.9) or myositis Not seizures, syncope, exercise, 2058 434 (21.1) 177 (8.6) 329 (16.0) statins, or myositis Abbreviation: CPK, creatine Initial phosphate, mg/dLa phosphokinase. ≤3.9 1250 129 (10.3) 41 (3.3) 105 (8.4) SI conversion factors: To convert creatinine to micromoles per liter, >3.9 to ≤5.4 399 93 (23.3) 16 (11.5) 67 (19.8) multiply by 88.4; calcium to >5.4 410 201 (49.0) 102 (24.9) 136 (33.2) millimoles per liter, multiply by 0.25; Initial bicarbonate, mEq/L and bicarbonate to millimoles per liter, multiply by 1.0. ≥19 1902 257 (13.5) 109 (5.7) 195 (10.3) a Data may not sum to total due to a <19 469 193 (41.2) 81 (17.3) 140 (29.9) small number of missing values.

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with rhabdomyolysis. Compared with other risk prediction an important, common, costly, and morbid complication of scores in nephrology and critical care—for example, predic- rhabdomyolysis, and a score that predicted just RRT would be tion of the risk of RRT after cardiac surgery (C statistic, limited since death may be a competing outcome. In post hoc 0.78-0.81),8 prediction of contrast nephropathy following car- analyses, the risk score had reasonable discrimination for the diac catheterization (C statistic, 0.67),9 and prediction of mor- 2 individual components of the composite outcome (AUC = 0.83 tality using the admission Sequential Organ Failure Assess- and H-L P =.36forRRT;AUC=0.80andH-LP < .001 for in- ment score in the intensive care unit (C statistic, hospital mortality). 0.67-0.90)10-12—the rhabdomyolysis risk score has compa- A key finding from our analyses relates to the nature of the rable or better discrimination. We chose to develop a tool to relationship between CPK levels and risk. Previous smaller predict the composite outcome of RRT or in-hospital mortal- studies of rhabdomyolysis have shown that CPK has a weak ity because of considerations of clinical relevance: a score that relationship with the risk of RRT.2,13,14 However, other groups predicted just mortality would not provide information on RRT, have documented large rises in CPK after vigorous exercise with no deleterious consequences,15,16 and there is evidence of a ge- netic component to the variability in CPK levels following Table 3. Risk Score injury.17-19 We found an association between elevated initial Variable β Score CPK levels in excess of 40 000 U/L and the risk of RRT or in- Age (continuous) 0.022 …a hospital mortality, but admission CPK levels alone were not Age, y sufficiently predictive to enable clinical decision making. The >50 to ≤70 …b 1.5 incorporation of cause of rhabdomyolysis provides impor- >70 to ≤80 …b 2.5 tant additional prognostic information, as suggested by pre- >80 …b 3 vious smaller studies.2,20 The risk of the composite outcome Female sex 0.404 1 in the overall cohort with low-risk causes (seizures, syncope, Initial creatinine, mg/dL exercise, statins, or myositis) was only 5.1% compared with 1.4 to 2.2 0.589 1.5 21.1% in those with other causes. The components of the risk >2.2 1.083 3 score also include age, sex, and clinical laboratory values. All Initial calcium <7.5 mg/dL 0.933 2 laboratory variables are plausible as risk factors: high creati- Initial CPK >40 000 U/L 0.805 2 nine reflects AKI or CKD, which are both strong and indepen- Origin not seizures, syncope, exercise, stat- 1.301 3 dent risk factors for poor outcomes; high phosphate values may ins, or myositis signify greater severity of muscle injury and impaired renal Initial phosphate, mg/dL function; and low calcium results from deposition within dam- 4.0 to 5.4 0.565 1.5 aged skeletal muscle and may be a marker of increased muscle >5.4 1.221 3 injury.21 Initial bicarbonate <19 mEq/L 0.811 2 The risk score may be particularly useful in the emergency department to evaluate and triage patients with exer- Abbreviation: CPK, creatine phosphokinase. tional rhabdomyolysis. For example, a 30-year-old female pa- SI conversion factors: See Table 2. tient with myalgia following exercise with a CPK level of 20 000 a Age is categorical, therefore there is no value. U/L but normal laboratory values for calcium, phosphate, cre- b Age is continuous, therefore there is no value. atinine, and bicarbonate has a risk score of 1, corresponding

Figure 2. Probability of In-hospital Mortality or Acute Kidney Injury Requiring Renal Replacement Therapy

1.0 MGH—Derivation 0.9 BWH—Validation 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1

Probability of In-hospital Mortality or RRT 0 <3 3 4 5 6 7 8 9 10 11 12 13 14 15 >15 Risk Score Event rate 04 3 27 48 40 43 52 45 47 47 38 19 19 18 Patient count 130358 105 387 307 269 203 164 134 101 75 57 34 24 23

Black bars and gray bars show the observed risk at Massachusetts General Hospital (MGH) and Brigham and Women’s Hospital (BWH), respectively. RRT indicates renal replacement therapy.

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to less than a 1% risk of RRT or in-hospital mortality. Knowl- used. The study drew data from 2 large university teaching hos- edge of the predicted risk of adverse outcomes may lead cli- pitals, allowing external validation of the risk prediction model. nicians to choose intravenous fluid administration in the emer- However, we recognize some limitations. The study was ret- gency department followed by discharge with plans for rospective in nature; the cause of rhabdomyolysis was ascer- repeated outpatient laboratories rather than inpatient hospi- tained by medical record review and administrative codes and talization for observation. The safety of this approach and clini- may not have been accurate in all cases. The timing of the in- cal implementation of the risk score in this manner would result was not certain in many cases, and patients came to the quire additional study. The risk score has particular utility in hospitals at varying intervals following injury. There was no identifying low-risk patients. Although the documentation of information on urine output or the treatments that were used a high risk score may not directly influence treatment deci- or their relative effectiveness in preventing the primary out- sions, it may be useful in conveying prognosis and expecta- come. Creatine phosphokinase was not routinely checked in tions to the care team, patient, and family members. all patients seeking treatment at the hospital, and therefore a Clinical trials of therapeutic agents for rhabdomyolysis may number of patients may have developed rhabdomyolysis with- also be aided by the use of a risk score as inclusion and exclu- out being diagnosed. Finally, because this study includes pa- sion criteria. Low-risk patients, in whom the event rate may tients from 2 large tertiary teaching hospitals in a single city be too low to warrant inclusion, and high-risk patients, for in the northeastern United States, it may not be generalizable whom interventions may not carry clinical benefit due to se- to other non–tertiary care hospitals in different geographical verity of illness, may be excluded to optimize study design. locations. Further validation studies may be informative. This study has a number of important strengths. To our In summary, we have described the incidence, causes, and knowledge, it is the largest study to date of rhabdomyolysis outcomes of rhabdomyolysis in a large cohort of patients seek- and, more important, has identified patients on the basis of ing treatment at 2 large university hospitals during a 10-year CPK levels rather than administrative codes. Only patients with period. From these data, we derived and validated an easy- moderate to severe biochemical evidence of rhabdomyolysis to-use risk score based on readily available parameters that can were included, thus removing some of the ambiguity in pre- aid in estimating the probability of RRT or in-hospital mortal- vious studies in which a lower CPK cutoff for inclusion was ity in patients with rhabdomyolysis.

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