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Original Article
34 (
2
); 144-148
doi:
10.4103/ijn.ijn_311_22

Prevalence and Predictive Factors of Rhabdomyolysis in COVID-19 Patients: A Cross-sectional Study

Emergency Medicine Department, School of Medicine, Shohadaye Tajrish Hospital, Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Physiology Research Center, Iran University of Medical Sciences, Tehran, Iran
Department of Emergency Medicine, NYC Health and Hospitals, Coney Island, New York, USA
Men’s Health and Reproductive Health Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Pediatric Chronic Kidney Disease Research Center, Tehran University of Medical Sciences, Tehran, Iran
Corresponding author: Dr. Mahmoud Yousefifard, Physiology Research Center, School of Medicine, Iran University of Medical Sciences, Shahid Hemmat Highway, Tehran 14496-14535, Iran. E-mail: yousefifard20@gmail.com Dr. Saeed Safari, Men’s Health and Reproductive Health Research Center, Shohadaye Tajrish Hospital, Shahrdari Avenue, Tajrish Square, Tehran, Iran. E-mail: Safari266@gmail.com
Licence
This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.

How to cite this article: Hashemi B, Farhangi N, Toloui A, Alavi SN, Forouzanfar MM, Ramawad HA, et al. Prevalence and Predictive Factors of Rhabdomyolysis in COVID-19 Patients: A Cross-sectional Study. Indian J Nephrol. 2024;34:144–8. doi: 10.4103/ijn.ijn_311_22

Abstract

Introduction:

The aim of the present prospective observational study was to demonstrate the prevalence and predictive factors of rhabdomyolysis in coronavirus disease 2019 (COVID-19) patients.

Methods:

The study was performed on reverse transcriptase-polymerase chain reaction (RT-PCR)-confirmed COVID-19 patients admitted to the emergency department between March 2020 and March 2021. Peak creatinine phosphokinase (CPK) levels were used to define rhabdomyolysis. A CPK level equal to or more than 1000 IU/L was defined as the presence of moderate to severe rhabdomyolysis. We developed a COVID-19–related Rhabdomyolysis Prognostic rule (CORP rule) using the independent predictors of rhabdomyolysis in COVID-19 patients.

Results:

Five hundred and six confirmed COVID-19 patients (mean age 58.36 ± 17.83 years, 56.32% male) were studied. Rhabdomyolysis occurred in 44 (8.69%) cases throughout their hospitalization. Male gender (odds ratio [OR] = 2.78, 95% confidence interval [CI]: 1.28, 6.00), hyponatremia (OR = 2.46, 95% CI: 1.08, 5.59), myalgia (OR = 3.04, 95% CI: 1.41, 6.61), D-dimer >1000 (OR = 2.84, 95% CI: 1.27, 6.37), and elevated aspartate aminotransferase level (three times higher than normal range) (OR = 3.14, 95% CI: 1.52, 6.47) were the significant preliminary predictors of rhabdomyolysis. The area under the curve of the CORP rule was 0.75 (95% CI: 0.69, 0.81), indicating the fair performance of it in the prognosis of rhabdomyolysis following COVID-19 infection. The best cutoff of the CORP rule was 3, which had a sensitivity of 72.9% and a specificity of 72.7%.

Conclusion:

This prospective study showed that 8.69% of patients developed rhabdomyolysis following COVID-19 infection. The CORP rule with optimal cutoff can correctly classify 72.8% of COVID-19 patients at risk of developing rhabdomyolysis.

Keywords

COVID-19
prediction
rhabdomyolysis
risk factor

Introduction

As we enter the third year of the coronavirus disease 2019 (COVID-19) pandemic, severe acute respiratory syndrome coronavirus 2 (SAR CoV 2) still poses major health problems worldwide. Considering the growing fully vaccinated population and the development of improved patient management protocols, researchers have shifted their attention from the management of the acute respiratory symptoms to other complications of the disease.1-3 Recent studies indicate that these multiorgan and/or extrapulmonary complications are associated with a significantly higher risk of mortality.4-6

Rhabdomyolysis is caused by muscle necrosis and the subsequent dissolution of intracellular components into the bloodstream.7 Although rhabdomyolysis is most often caused by direct injuries to the muscles, compartment syndrome, exertion or prolonged immobilization, the condition can also be the result of infections. Association of rhabdomyolysis with viral infections such as influenza A, influenza B, human immunodeficiency virus (HIV), and herpes has been previously demonstrated.8,9 The severity of the condition varies from an asymptomatic illness to a severe condition involving life-threatening elevation in serum creatinine, disseminated intravascular coagulation, and renal failure.10

The SARS-CoV-2 that is responsible for COVID-19 has also been reported to cause rhabdomyolysis.11 Although it was previously reported that rhabdomyolysis mostly occurred in severe cases of COVID-19 patients with older age and comorbidities (e.g., cardiovascular disease), there are recent reports of rhabdomyolysis developing in younger patients with less-severe forms of COVID-19.12-14 Therefore, the present prospective observational study aimed to demonstrate the prevalence and predictive factors of rhabdomyolysis in COVID-19 patients.

Materials and Methods

The present observational study was performed on patients who were admitted to the emergency department (ED) of Shohadaye Tajrish Hospital in Tehran, Iran, between March 2020 and March 2021. The study was approved by the ethics committee of Shahid Beheshti University of Medical Sciences (ethics code: IR.SBMU.MSP.REC.1400.099), and the researchers adhered to the principles of the Helsinki Convention.

Patients confirmed with COIVD-19 and an established creatinine phosphokinase (CPK) level upon admission to the ED were included in this study. The diagnosis of COVID-19 was made with a positive reverse transcriptase-polymerase chain reaction (RT-PCR) for SAR-CoV-2 from a nasopharyngeal specimen and/or pulmonary complications identified by computed tomography scan. Patients without a CPK level, pregnant women, polytraumatic cases, and bedridden patients before the diagnosis of COVID-19 were all excluded.

Demographic data (age and gender), patients’ symptoms (cough, dyspnea, myalgia, headache, chest pain), vital signs, venous blood gas parameters, hematologic and blood biochemistry parameters, and data on urine analysis were collected from patients’ profile using a predesigned checklist. Peak CPK levels were used to define rhabdomyolysis. Like our previous study, a CPK level equal to or more than 1000 IU/L was defined as the presence of moderate to severe rhabdomyolysis. An emergency medicine resident under the direct supervision of an emergency medicine specialist was responsible for data gathering.

We examined normality assumption by checking kurtosis, skewness, box plot, and Q–Q plot. t-Test and Mann–Whitney U test were used for comparisons of continuous variables in alive and dead patients. Apart from evaluating the association between categorical variables, the Chi-square test and Fisher’s exact test were used. In addition, a multivariate logistic regression model was performed for investigating the independent predictive factors of COVID-19–related rhabdomyolysis. The findings were reported as odds ratio (OR) and 95% confidence interval (95% CI). P value less than 0.05 was considered statistically significant. We developed a prognostic rule using the independent predictors of rhabdomyolysis in COVID-19 patients. Accordingly, each independent variable received a score equal to 1. The receiver operating characteristic (ROC) curve, sensitivity, specificity, and likelihood ratio were calculated to assess the prognostic performance of the rule. All analyses were done using the STATA 14.0 statistical software.

Results

Five hundred and six confirmed COVID-19 patients with a mean age of 58.36 ± 17.83 years were studied (56.32% male). The demographic characteristics and laboratory findings of studied cases at baseline are presented in Tables 1 and 2, respectively. Rhabdomyolysis occurred in 44 (8.69%) cases throughout their hospitalization. The mean age of rhabdomyolysis cases was 58.58 ± 17.78 years compared to 56.11 ± 18.36 years of non-rhabdomyolysis cases (P = 0.3816). Patients with rhabdomyolysis were significantly more likely to be male (75.0% vs. 54.55%, P = 0.009).

Table 1: Baseline characteristics of included COVID-19 patients
Variable Rhabdomyolysis Total
(n=506)
P
No (n=462) Yes (n=44)
Age (years)
  Mean±SD 58.58±17.78 56.11±18.36 58.36±17.83 0.3816
Gender
  Male 252 (54.55) 33 (75) 285 (56.32) 0.009
  Female 210 (45.45) 11 (25) 221 (43.68)
Symptoms
  Fever 39 (51.73) 20 (47.62) 259 (51.39) 0.610
  Cough 233 (50.54) 17 (39.53) 250 (49.60) 0.167
  Dyspnea 293 (63.42) 20 (47.62) 313 (62.10) 0.043
  Myalgia 90 (19.48) 13 (30.23) 103 (20.40) 0.094
  Headache 42 (9.09) 5 (11.63) 47 (9.31) 0.584
  Chest pain 58 (12.55) 4 (9.3) 62 (12.28) 0.534
Vital signs
  SBP (mmHg) 120.16±18.04 112.88±21.26 119.53±18.42 0.013
  DBP (mmHg) 74.78±11.98 72.83±12.83 74.62±12.06 0.311
  MAP (mmHg) 89.91±12.78 86.18±14.48 89.59±12.96 0.072
  PR (/min) 86.67±14.40 88±14.79 86.79±14.43 0.565
  RR (/min) 18.66±4.16 18.84±3.8 18.68±4.12 0.791
  T (°C) 37.13±0.69 37.18±0.65 37.13±0.69 0.658
O2sat (%)
  Mean±SD 69.76±24.39 64.24±24.27 69.29±24.40 0.166
  ≥95 76 (16.45) 13 (27.08) 89 (17.45) 0.004
  90–95 94 (20.35) 0 (0.00) 94 (18.43)
  85–89.9 35 (7.58) 5 (10.42) 40 (7.84)
  <85 257 (5.63) 30 (62.50) 287 (56.27)

COVID-19=coronavirus disease 2019, DBP=diastolic blood pressure, MAP=mean arterial pressure, O2sat=O2 saturation, PR=pulse rate, RR=respiratory rate, SBP=systolic blood pressure, SD=standard deviation, T=body temperature. Data are presented as mean±SD or frequency (%)

Table 2: Baseline laboratory findings of included COVID-19 patients
Variables Rhabdomyolysis Total (n=506) P
No (n=462) Yes (n=44)
Venus blood gas analysis
  pH 7.343±0.063 7.338±0.077 7.343±0.064 0.602
  PCO2 (mmHg) 45.58±10.13 45.42±12.46 45.57±10.33 0.921
  PO2 (mmHg) 36.75±30.73 39.63±25.39 36.99±30.30 0.560
  HCO3 (mmol/L) 24.17±4.78 28.44±32.56 24.53±10.51 0.013
Complete blood counts
  WBC (×109 cells/L) 8.35±4.93 9.06±5.48 8.41±4.97 0.380
  PMN (%) 79.36±29.67 79.66±10.70 79.38±28.59 0.419
  Lymph (%) 19.39±10.58 18.19±9.97 19.29±10.52 0.487
  Hb (g/dL) 12.25±2.82 11.88±2.42 12.22±2.79 0.419
  Platelets (×103/L) 208.86±92.38 177.83±65.75 206.33±90.85 0.036
Coagulation profile
  PT (s) 13.76±1.77 13.95±1.76 13.77±1.77 0.547
  PTT (s) 37.26±10.81 37.12±8.71 37±10.64 0.941
  INR 1.10±0.24 1.14±0.24 1.10±0.24 0.322
Urine analysis
  RBC 22 (7.24) 3 (13.64) 25 (7.67) 0.276
Other parameters
  CRP (mg/L) 28.01±25.85 27.13±25.92 27.95±25.92 0.855
  BUN (mg/dL) 26.61±22.27 42.63±52.86 27.94±26.48 0.0002
  Creatinine(mg/dL) 1.91±9.21 1.60±1.25 1.88±8.82 0.828
  AST (U/L) 56.28±88.21 275.38±1035.73 72.63±296.82 0.0001
  ALT (U/L) 45.33±83.78 157.99±586.02 53.70±179.12 0.0009
  ALP (U/L) 275.41±240.01 339.8±333.80 280.29±248.40 0.173
  Na (mEq/L) 137.74±5.82 135.36±5.98 137.48±5.88 0.028
  K (mEq/L) 4.55±9.49 4.03±0.65 4.49±8.96 0.753
  Ca (mg/dL) 8.93±1.00 8.62±0.22 8.90±1.00 0.152
  Troponin (ng/mL) 0.40±2.52 0.55±0.83 0.41±2.44 0.729
  D-dimer (ng/mL) 947.62±2226.18 2483±4861.82 1015.22±2408.82 0.033
  CPK (IU/L) 155.16±182.03 2338.32±1509.71 254.39±581.33 <0.0001

ALP=alkaline phosphatase, ALT=alanine transaminase, AST=aspartate transaminase, BUN=blood urea nitrogen, COVID-19=coronavirus disease 2019, CPK=creatinine phosphokinase, CRP=C-reactive protein, Hb=hemoglobin, lymph=lymphocyte leukocytes percentage, PCO2=partial pressure of carbon dioxide, PMN=polymorphonuclear leukocytes percentage, PO2=partial pressure of oxygen, RBC=red blood cell count, SD=standard deviation, WBC=white blood cell count. Microscopic hematuria: presence of more than three RBCs per high-power field on microscopic evaluation of urine sediment. Data are presented as mean±SD or frequency (%), PT: Prothrombin Time, PTT: Partial Thromboplastin Time, INR: International Normalized Ratio, HCO3: Bicarbonate, Na: Sodium, K: potassium, Ca: calcium.

Dyspnea was found to be significantly more prevalent in the rhabdomyolysis group (63.42% vs. 47.62%, P = 0.043). Additionally, patients with rhabdomyolysis had significantly lower mean systolic blood pressure than patients without rhabdomyolysis (112.88 ± 21.26 vs. 120.16 ± 18.04 mmHg, P = 0.013).

The analysis of laboratory data during hospitalization revealed that venous blood bicarbonate levels were higher in patients with rhabdomyolysis (28.44 ± 32.56 vs. 24.17 ± 4.78, P = 0.013), which was probably due to adding bicarbonate to the intravenous (IV) solutions for urine alkalization in rhabdomyolysis cases. Also, the mean platelet count was significantly lower in rhabdomyolysis cases (177.83 ± 65.75 vs. 208.86 ± 92.38, P = 0.036). A significant difference was also observed between the groups regarding blood urea nitrogen (BUN; P = 0.0002), aspartate transaminase (AST; P = 0.0001), alanine transaminase (ALT; P = 0.0009), Na (P = 0.013), and D-dimer (P = 0.033), which is presented in Table 2.

Independent predictors of rhabdomyolysis

Applying a multivariate logistic regression model and utilizing a univariate analysis revealed that male gender (OR = 2.78, 95% CI: 1.28, 6.00), hyponatremia (OR = 2.46, 95% CI: 1.08, 5.59), myalgia (OR = 3.04, 95% CI: 1.41, 6.61), D-dimer >1000 (OR = 2.84, 95% CI: 1.27, 6.37), and elevated AST level (three times higher than the normal range) (OR = 3.14, 95% CI: 1.52, 6.47) were the significant preliminary predictors of rhabdomyolysis [Table 3].

Table 3: Independent predictors of rhabdomyolysis in COVID-19 patients
Predictors Coefficient (95% CI) OR (95% CI) P Weighta
Male gender 1.02 (0.25, 1.79) 2.78 (1.28, 6.00) 0.009 1
Dyspnea −0.58 (−1.26, 0.10) 0.56 (0.28, 1.11) 0.095 0
Hyponatremia 1.04 (0.24, 1.85) 2.84 (1.27, 6.37) 0.011 1
Myalgia 1.09 (0.32, 1.86) 3.04 (1.41, 6.61) 0.005 1
D-dimer >1000 (ng/mL) 1.13 (0.33, 1.94) 3.11 (1.40, 6.94) 0.006 1
AST three times higher than normal 1.14 (0.42, 1.87) 3.14 (1.52, 6.47) 0.002 1
Platelet >450,000 (cells/L) 1.54 (−0.04, 3.11) 4.65 (0.96, 22.37) 0.055 0

AST=aspartate transaminase, CI=confidence interval, COVID-19=coronavirus disease 2019, OR=odds ratio. aWeight of variable in the prognostic rule

A prognostic rule was developed using the independent predictors of rhabdomyolysis in COVID-19 patients. The COVID-19–related Rhabdomyolysis Prognostic rule (CORP rule) score ranged from zero to 5, indicating the lowest risk to the highest risk of developing rhabdomyolysis following COVID-19 infection. The area under the curve of the CORP rule was 0.75 (95% CI: 0.69, 0.81), indicating its fair performance in the prognosis of rhabdomyolysis following COVID-19 infections [Figure 1]. The best cutoff of the CORP rule was 3, with a sensitivity of 72.9% and a specificity of 72.7% [Table 4]. In this cutoff, there were 336 true-negative, 35 true-positive, 126 false-positive, and 13 false-negative cases. The CORP rule is presented in Figure 2.

Figure 1:
Area under the ROC curve of the CORP rule in the classification of high-risk COVID-19 patients for rhabdomyolysis CORP rule = coronavirus disease 2019-related Rhabdomyolysis Prognostic rule, COVID-19 = coronavirus disease 2019, ROC = receiver operating characteristic.
Figure 2:
The COVID-19 related Rhabdomyolysis Prognostic rule (CORP rule). AST=aspartate transaminase.
Table 4: Discriminatory performance of CORP rule in prediction of rhabdomyolysis in COVID-19 patients
Cutoff point Sensitivity (%) Specificity (%) LR+ LR−
≥0 100.00 0.00 1
≥1 100.00 8.87 1.0974 0
≥2 93.75 37.23 1.4935 0.1679
≥3 72.92 72.73 2.6736 0.3724
≥4 14.58 92.42 1.925 0.9242
≥5 2.08 99.78 9.6252 0.9813

CORP rule=coronavirus disease 2019-related Rhabdomyolysis Prognostic rule, COVID-19=coronavirus disease 2019, LR=likelihood ratio

Discussion

We found evidence of rhabdomyolysis in 8.69% of patients following COVID-19 infection. Male gender, hyponatremia, myalgia, elevated D-dimer, and elevated AST levels were independent predictive factors of rhabdomyolysis.

Rhabdomyolysis is a condition in which there is injury or death to muscle cells, which results in the release of cellular components into the bloodstream.15 In addition to the symptoms caused by the general reaction of tissue death, muscle cells contain specific components like myoglobin which can lead to rhabdomyolysis. Myoglobulin is toxic to the kidneys and its association with acute kidney injury is well known.16 COVID-19 can injure the muscle cells by direct invasion in conjunction with a wide spectrum of pulmonary and extrapulmonary manifestations such as rhabdomyolysis with hypovolemia, fever, acidosis, bacterial superinfection, and so on.17-19 For instance, COVID-19 can cause excessive fluid depletion due to fever, gastrointestinal loss, tachypnea, possible cardiovascular injuries, and decreased intake of fluids.20,21 The following hypovolemia could be a cause of damage to the muscle tissue. Additionally, the drop in arterial oxygen saturation in severe forms of COVID-19 is also another contributing factor to muscle injury secondary to tissue hypoxia. Moreover, COVID-19 can cause coagulopathies with elevated D-dimer and alterations in other laboratory findings descriptive of the coagulopathic state. Coagulopathies are a well-known etiology of muscular tissue death, further contributing to the development of rhabdomyolysis.22,23

For the first time, we tried to provide a prognostic rule for predicting developing rhabdomyolysis following COVID-19 infection. Male gender, hyponatremia, myalgia, elevated D-dimer, and elevated AST levels were included to calculate the rule. It appears that the CORP rule could correctly classify 72.8% of COVID-19 patients for their risk of developing rhabdomyolysis.

This study has a number of limitations. Since COVID-19 can cause myalgia and coagulopathies in the absence of rhabdomyolysis, the laboratory and clinical findings could be due to COVID-19 itself and are not specifically indicative of rhabdomyolysis. In addition, we included the admission time laboratory findings to develop the prognostic rule, and if the serial values of these variables were used in the decision rule, its predictive value might have increased. The CORP score was developed based on the available data of COVID-19 patients, and some variables such as inotropic requirement and serum phosphorus were not always available.

Conclusion

This prospective study showed that 8.69% of patients developed rhabdomyolysis following COVID-19 infection. Male gender, hyponatremia, myalgia, elevated D-dimer, and elevated AST levels were independent predictive factors of rhabdomyolysis. The CORP rule with optimal cutoff can correctly classify 72.8% of COVID-19 patients for their risk of developing rhabdomyolysis.

Conflicts of interest

There are no conflicts of interest.

Financial support and sponsorship

This project is supported by Men’s Health and Reproductive Health Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

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