Rhabdomyolysis in older adults: outcomes and prognostic factors

doi:10.21203/rs.3.rs-3209231/v1

Background : Rhabdomyolysis is a common condition in older persons, often associated with falls. However, prognostic factors of rhabdomyolysis have mainly been studied in middle-aged populations. This study aims to examine whether factors related to 30-day hospital mortality vary with patients’ age.

Methods: This single-center retrospective observational study included all patients admitted at the University Hospital of Rennes between 2013 and 2019 whose creatine phosphokinase (CPK) level was greater than five times the normal concentration. The primary endpoint was 30-day in-hospital mortality.

Results: 343 patients were included (median age: 75 years). The mean peak CPK was 21.825 IU/L. ; acute renal failure occurred in 57.7% of cases. For patients aged 70 years and over, a long lie after a fall were the main etiology. The in-hospital mortality rate at 30 days was 10.5% (23 deaths). The Charlson score, number of medications, CPK and creatinine levels varied according to age. Age was also a factor that was not proportionally associated with 30-day hospital mortality according to a multivariate analysis.

Conclusion: Factors influencing the severity of rhabdomyolysis are not evenly distributed according to age. The term rhabdomyolysis may encompass various clinical realities and be associated with different mechanisms. More research is needed to better understand physiopathological and prognostic factors of rhabdomyolysis, especially in the older population.

Rhabdomyolysis

creatine phosphokinase

older person

prognostic factors

long lie after a fall

Rhabdomyolysis is a clinicobiological entity in which striated muscle cells break down and release of their contents into the blood. It is diagnosed based on symptoms such as muscle pain, myoglobinuria, hydroelectric disorders and increased creatinine phosphokinase (CPK) levels (1.2). In rhabdomyolysis, CPK levels can reach at least five times the normal concentration. Studies on the pathophysiology of this condition have shown necrosis of striated muscle cells following direct injury (trauma/prolonged compression) or adenosine triphosphate (ATP) depletion leading to a sudden increase in intracellular calcium. Necrosis of striated muscle cells leads to the release of their contents into the serum (potassium, calcium, sodium, phosphorus, myoglobin and CPK). Precipitation of myoglobin in the renal tubules and vasoconstriction secondary to hypovolemia can lead to renal failure of varying severity, sometimes fatal to the patient (2).

Different etiologies have been described, and these can be grouped according to their mechanisms: hypoxic, traumatic, chemical or biological. In adults, the most frequent causes are traumatic, iatrogenic/drug and infectious (3.4). Long lies after falls, whose occurrence increases with age and comorbidities (5), are the most frequent cause of rhabdomyolysis in older adults. In France, approximately 450,000 people over 65 years of age fall each year, resulting in more than 9,000 deaths in 2013 (6). According to a multicenter French study on 1467 subjects, 14% of patients aged 65 years or more who were hospitalized for an injury caused by a fall presented a rhabdomyolysis (7).

An American study (8) proposed a predictive composite score for the risk of acute renal failure and mortality linked to rhabdomyolysis. It includes initial CPK level, presence of acute renal failure, etiology, age and presence of initial ionic disturbances. This approach was supported by subsequent studies (9) confirming that the composite score better predicted complications than the initial CPK level alone. However, these studies are based on data obtained in middle-aged patients (median age: 50.7 years). We found few studies that looked at the specificities of prognosis according to age.

Only two studies on rhabdomyolysis focused on older persons. The first is an American retrospective study from 2017 (10) which considered patients (n = 167) aged 65 years or older. It found 3 prognostic factors for rhabdomyolysis: polymedication, minimum glomerular filtration rate (GFR) under 30 ml/min and occurrence of acute renal failure. The second is a retrospective study from 2017, conducted in Spain on 133 patients aged 65 years or older (11). It showed that creatinine levels influence prognosis, and found that a delirium or presence of acute brain injury were factors associated with a poor prognosis.

The patients considered in the American study were, in majority (73%), of African-American descent, and only 20% of patients were Caucasian, which is not representative of the French population. The two aforementioned studies specifically focused on adults 65 years of age or older, and both showed that the occurrence of acute renal failure was indicative of a poor prognosis. These studies were based on a limited sample and found different prognostic criteria (delirium / polymedication). In the absence of comparison with a younger adult population, researchers could not conclude on the existence of specific prognostic criteria for older persons.

We therefore conducted a retrospective study on all adults admitted for rhabdomyolysis at the University Hospital of Rennes between June 2013 and December 2019 to investigate whether factors related to 30-day mortality varied according to patients’ age.

Single-center retrospective observational study

2.1 Inclusion:

We identified patients over 18 years of age who presented rhabdomyolysis and were admitted at the University Hospital of Rennes between June 2013 and December 2019, according to the medico-administrative database of the medicalized information systems program. This database provides several pieces of information associated with each hospital stay (including the emergency visit), including the main diagnosis (which justified the hospitalization) and secondary diagnoses (i.e. which are not the main cause of the hospitalization, but explain at least part of it). We used the codes of the International Classification of Diseases (10th edition, ICD10): M62.8 (Rhabdomyolysis) and T79.6 (Traumatic muscle ischemia) to identify the primary and secondary diagnoses of rhabdomyolysis. We then excluded patients whose CPK levels were under five times the normal concentration (i.e. 1000 IU/L), as they did not meet our definition of rhabdomyolysis (9). We also excluded adults under temporary legal protection and persons deprived of liberty. The remaining patients were included and we sent them a letter to inform them about their inclusion in this study. If they did not object within three weeks, their data were collected. The primary endpoint was 30-day hospital mortality.

The study met standards of the French research regulatory authority's criteria for observational studies (Declaration date: 20 August 2018. Declaration number: 2205295 v 0). All live patients have been informed about the study by regular mail, and given the possibility to refuse. The need for informed consent was waived by ethics committee of Rennes university hospital (Opinion number: 20.97), due to the low risk design (retrospective observational study) and according to French Law (official journal 2018 − 155 on the processing of personal data in research).

2.2. Collected data:

We collected data allowing comparison with previous studies (8, 10, 11): demographic data (age, sex, rural or urban lifestyle) presence of professional help at home, Charlson comorbidity index (12, 13), number of medications (active ingredients) at admission (14), weight, initial quick Sequential Organ Failure Assessment (qSOFA) score. The qSOFA prognostic score of organ failure ranges from 0 to 3, and its components include blood pressure, respiratory rate and upper function disorders. A score over 2 is associated with a mortality risk over 10%. This score was therefore compiled as a categorical variable (< 2 or ≥ 2) (15). We collected the etiology of rhabdomyolysis based on Mc Mahon's classes: long lie after fall, muscular (which includes myositis, exercise and sepsis), iatrogenic (statins, neuroleptics), toxic (cocaine) or other. We also collected biological data from the first 24 hours after admission: CPK, creatinine, GFR estimated according to the CKD EPI formula (16), hemoglobin, hematocrit, leukocytes, platelets, albumin, calcemia, phosphemia, bicarbonates and pH. We retrieved CPK and creatinine maximum concentration during the stay (“peak concentrations”, whatever the length of the stay), and recorded the presence of CPK over 5000 UI/L (5000 UI/L is considered as the threshold from which monitoring and treatment are required) (17). Finally, the occurrence of complications, such as acute renal failure (collected according to medical findings when available, or by a 30% decrease in estimated GFR), disseminated intravascular coagulation (DIC), compartment syndrome or delirium, as well as the prescribed intravenous fluid infusion, post-discharge outcome and 30-day hospital mortality were recorded.

2.3. Statistical analysis:

A univariate analysis was initially performed by comparing the presence and frequency of the different known risk factors by age group. Subsequently, a statistical link was sought between the continuous and categorical variables collected and mortality. A p-value of less than 0.05 was considered statistically significant. For categorical variables, we used the uncorrected Chi-square test or the Fisher exact test when the number of data was less than 5. For continuous variables, we used the T-test with the Satterthwaite method (different variances). The non-parametric Kruskal-Wallis test was used for comparisons of the different variables according to age groups, since some small samples did not follow a normal distribution. When several definitions were found in the literature for certain factors (CPK level or peak, measurement methods for renal function), an exploratory analysis was carried out to verify the presence of a statistically significant relationship with each of the measurement methods previously used.

Finally, we performed a multivariate analysis according to the stepwise top-down logistic regression model to identify the different independent prognostic criteria, with an entry threshold p < 0.1 in univariate analysis and an exit threshold p > 0.05. In this analysis, we excluded variables with more than 10% missing data (blood calcium, phosphorus). The variables that entered the model were age, Charlson score, qSofa score, CPK level, peak creatinine level and presence of DIC or delirium. The Epi Info 7 software was used for univariate analysis and the Jamovi software for multivariate analysis.

From June 2013 to December 2019, 567 patients aged 18 years or older were admitted to Rennes University Hospital with a primary or secondary diagnosis of "rhabdomyolysis". Among these patients, 211 had a CPK level below 5 times the normal concentration. We therefore selected the remaining 356 patients for actual rhabdomyolysis. Seven patients were excluded from the study because they were deprived of liberty. After contacting the other patients according to the planned protocol, 6 refused to participate. Thus, 343 patients were included in the analysis. Of these, 124 were transferred to another hospital after an initial hospital stay of a few hours to a few days. Therefore in-hospital mortality and complication rates were only available for 219 patients. [Figure 1 Flow chart]

3.1 Characteristics of the population:

The characteristics of the population are summarized in Table 1. The median age was 75 years, ranging from 18 to 103 years, and 45.2% were women. The population as a whole had a fairly low Charlson comorbidity index (median 1) but was exposed to polymedication with an average of 4.7 active drug ingredients per day (0–19). Long lies after falls (65.2% of cases) were the most common etiology of rhabdomyolysis, followed by muscular causes (24.3%) such as seizures, sepsis, and strenuous exercise. The mean CPK level on admission was 10,059 IU/L. The mean peak was 21,825 IU/L and a large variability was observed (standard deviation: 195,884 IU/L). The mean phosphorus level was 1.2 mmol/L and the mean potassium level, 4.3 mmol/L. The mean creatinine level on admission was 122.3 µmol/L and the mean peak was 142.3 µmol/L(standard deviation: 149 µmol/L). An acute renal failure was observed in 57.7% of cases, and 25.8% of patients received intravenous hydration greater than 2L in the first 24 hours following their admission. A renal dialysis was undertaken for 4 patients. A delirium was observed in 23.8% of cases. 71.2% patients returned home after hospitalization. We do not know the fate of the patients that were transferred to other hospitals after their stay in the emergency ward (35,9%). Finally, we observed 23 in-hospital deaths at 30 days, i.e. a mortality rate of 10.5%. The high number of missing data for phosphorus, blood calcium, pH or bicarbonate levels reveals different clinical practices for routine measurement of these parameters.

3.2 Associations between prognostic factors and age categories:

The relationship between the presence of known prognostic factors for mortality in rhabdomyolysis and the age of our patients (grouped into 10-year categories) is summarized in Table 2. The etiology of rhabdomyolysis varied with age: 90% of cases for patients aged 70 and over were explained by long lies after falls. The Charlson score varied significantly with age and was higher in patients aged 60 to 69 (p < 0.001). The number of medications was also associated with age, with a maximum of 6.1 per day in the 70–79 age group (p < 0.001). The initial and peak CPK levels were significantly higher in younger patients (p < 0.001), with a mean peak CPK in those under 50 years of 80,534 IU/L, versus 3,173 IU/L in those over 90 years of age. Peak creatinine was also significantly higher in younger patients, with a mean of 201.4 µmol/L in patients under 50 years of age, and 100.7 µmol/L in those over 90 (p < 0.001). In contrast, a qSOFA score ≥ 2 on admission to the emergency department did not appear to be significantly associated with age (p = 0.4). We found no significant difference in admission phosphorus levels by age (p = 0.2). The occurrence of complications such as acute renal failure (p = 0.6), delirium (p = 0.2), DIC (p = 0.1) and 30-day hospital mortality (p = 0.1) was not associated with age.

3.3. Factors associated with 30-day hospital mortality:

The univariate analysis between the different variables collected and 30-day in-hospital mortality is summarized in Table 3 for the 219 patients for whom in-hospital mortality data were verified. We found that the variables significantly associated with mortality were age (73.2 years versus 62.6 years respectively for deceased and surviving patients, p < 0.02), Charlson comorbidity score (2.7 vs. 1.1; p < 0.05), qSOFA score at admission ≥ 2 (34.8% vs. 6.2%; p < 0.001), admission creatinine (223.2 µmol/L vs. 114.9 µmol/L; p < 0.001), peak creatinine (282.5 µmol/L vs. 137.3 µmol/L; p < 0.001), lowest GFR (25.5 ml/min vs. 66.7 ml/min; p < 0.001), development of acute renal failure (91.3% vs. 53.6%; p < 0.001), admission phosphorus level (1.9 mmol/L vs. 1.1 mmol/L; p < 0.02), occurrence of DIC (13.6% vs. 0.5%; p < 0.01) and delirium (45.5% vs. 21.4%; p < 0.05). In contrast, baseline CPK (20,854 IU/L vs. 11,468 IU/L) and peak CPK (23,983 IU/L vs. 30,095 IU/L) did not show a statistically significant association with mortality. Analysis of over-threshold (> 5000 IU/L) CPK levels as a categorical variable also showed no significant difference in terms of 30-day hospital mortality (56.5% vs. 37.2%).

3.4. Multivariate analysis:

A multivariate analysis of in-hospital 30-day mortality according to variables that were statistically significant in univariate analysis was performed to identify independent prognostic variables [Table 4]. Five variables were identified: age (p = 0.003), Charlson score (p = 0.015), initial qSOFA score (p = 0.002), peak creatinine (p = 0.002) and the existence of DIC (p = 0.011)

In this study, we sought to identify whether there was an age difference in factors related to 30-day hospital mortality in rhabdomyolysis. We observed that certain known prognostic factors (8–11), such as sex, CPK and creatinine levels on admission, lower estimated GFR, or number of medications, are not evenly distributed according to age. We therefore demonstrated an influence of age on the prognostic profile of patients. With a median age of 75.0 years, our population was much older than the populations used to develop prognostic scores (50.7 years in McMahon, 40.0 years in Simpsons), and more representative of a geriatric population.

In univariate and multivariate analysis, age appears to be a factor inconsistently associated with 30-day in-hospital mortality after rhabdomyolysis, with an increased mortality for the 60–69 age group. Other factors associated with mortality are Charlson comorbidity score, initial qSOFA score and peak creatinine. Our results did not show an association between phosphorus levels and mortality, but such link cannot be excluded, considering the data that were missing in the file, and the possible impact on the statistical power. Further studies would be necessary to document the role of phosphorus measurements for prognostic purposes in older patients with rhabdomyolysis. The number of medications at admission did not come out as a prognostic criterion, contrary to what was described by Wongrakpanich in an exclusively older population (range: 66–101, median: 80 years) (10). In our study, age was significantly associated with the number of drugs, and the maximum was observed in the 70–79 age group (i.e. at the median of the Wongrakpanich study). This tends to validate the hypothesis that age influences prognostic factors of rhabdomyolysis, notably through multimorbidity.

One of the limitations of our study is the amount of missing data, due to the retrospective design of the study. Indeed, 124 patients with rhabdomyolysis were transferred to local hospitals and we were therefore not able to collect the biological evolution, complications and in-hospital mortality at 30 days. Similarly, we do not have data to ensure the exhaustivity of rhabdomyolysis coding in the database we used. However, as the database we analyzed is used by the health insurance for the pricing of hospital stays, its quality is regularly controlled. Since rhabdomyolysis pathology justifies high invoicing, it seems unlikely that a significant number of stays are missing.

The CPK level (initial or peak), which is representative of the damaged muscle mass, does not appear to be a prognostic criterion for mortality. This finding is in agreement with previous studies (8, 10, 11). The monitoring of myoglobinuria, an earlier reflection of rhabdomyolysis which is directly related to the occurrence of acute renal failure, could have been relevant but was not available in this retrospective study (18, 19). The CPK level and peak are significantly higher in young subjects, probably in relation to muscle mass (20, 21). Thus, our results argue in favor of defining CPK thresholds that may be lower for older persons, to retain the diagnosis or to assess the probability of its severity and thus adapt the therapeutic strategy.

Neither the occurrence of acute renal failure (48.0%) nor peak creatinine appeared in multivariate analysis to be associated with 30-day in-hospital mortality, unlike in previous studies. The definition of renal failure that we use (30% decrease in estimated GFR) is not consensual (22) but has the advantage of simplicity and availability of measurements. However, this definition carries the risk of misclassification of subjects. Indeed, some older patients may have a particularly low baseline creatinine level in relation to reduced muscle mass and acute renal failure may therefore go undetected (23). The frequency of acute renal failure during rhabdomyolysis is highly variable in the literature, ranging from 10 to 58% depending on the study (3, 4, 8). This variability can be due to different inclusion criteria (CPK level, resuscitation), different etiologies and diagnostic criteria for acute renal failure in these studies (3, 24).

Finally, we found different levels of prescribed fluid infusion according to age in our study. This may be related to different etiologies (septic and muscular origins being more frequent in young subjects), but also to a reluctance of clinicians to use volemic expansion in older patients, particularly in cases of cardiac comorbidities. Analysis of the literature shows lower levels of filling for older adults, particularly in cases of septic shock, explained by the existence of comorbidities (25, 26).

We observed a mortality rate of 10.5%, i.e. 23 deaths, which is slightly lower than the rates found in the literature (14.0% in McMahon's study (8); 14.0% in Rodriguez's study (3)) but comparable to the rate of the Wongrakpanich study (10) ((10.2%). This may be due to our inclusion criteria (CPK > 1000 IU/L vs. 5000 IU/L for many studies). Given this low number of events a larger study would be useful to confirm these results.

In our study, prognostic factors of rhabdomyolysis are not evenly distributed according to age. In view of the decrease in muscle mass with age, the CPK and creatinemia thresholds usually used in prognostic scores may be questioned: the threshold of 5000 IU/L may need to be verified in the older population. The impact of phosphorus and polymedication requires further studies in larger samples. Our results highlight age-related clinical and prognostic specificities of patients with rhabdomyolysis, which point to the necessity of further studies in the geriatric population concerning the diagnosis, prognostic criteria and ultimately therapeutic approaches for this pathology which is frequent in old age.

Ethics approval and consent to participate

All live patients have been informed about the study by regular mail, and given the possibility to refuse. The need for informed consent was waived by ethics committee of Rennes university hospital (Opinion number: 20.97), due to the low risk design (retrospective observational study) and according to French Law (official journal 2018-155 on the processing of personal data in research).

All methods have been carried in accordance with relevant guidelines and regulations.

The protocol has been approved by Rennes University Hospital Ethics Committee.

Consent for publication

Not applicable

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests

Funding

No funding

Authors Contribution

Anne-Gaëlle Morin collected and analyzed the data and wrote the first draft.
Dominique Somme assisted in the design and analysis of the study and made substantial contributions to the article.
Aline Corvol helped with the analysis of the results and made a substantive revision of the article.
All authors reviewed and validated the manuscript.

Acknowledgements

The authors would like to thank Professor Florian Naudet for his critical review of the statistical and methodological aspects.

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Table 1. Characteristics of patients with rhabdomyolysis: clinical, biological, complications and outcome

Data at inclusion		Total (n = 343)	Missing data
Gender	Female, N(%)	155 (45.2)	0
Age (years)	Median (SD)	75.0 (20.2)	0
Rural / Urban	Rural, N(%)	64 (18.7)	0
Home help	Yes, N(%)	138 (40.2)	3
Charlson	Average (SD)	1.3 (1.7)	1
Number of medications	Average (SD)	4.7 (3.5)	9
qSOFA ≥ 2	Yes, N(%)	30 (8.8)	1
Etiology	Drop, N(%) Drug abuse, N(%) Muscular, N(%) Toxic, N(%) Other, N(%)	223 (65.2) 10 (2.9) 80 (23.3) 22 (6.4) 7 (2.0)	1
Initial CPK (IU/L)	Average (SD)	10,059 (28,908)	0
Initial creatinine (µmol/L)	Average (SD)	122.3 (120.3)	2
Potassium (mmol/L)	Average (SD)	4.2 (0.4)	5
Hemoglobin (g/dl)	Average (SD)	13.3 (2.0)	5
Hematocrit (%)	Average (SD)	39.8 (6.9)	5
Platelets (G/L)	Average (SD)	222.7 (92.6)	5
Leukocytes (G/L)	Average (SD)	12.3 (5.4)	7
Calcium (mmol/L)	Average (SD)	2.2 (0.3)	150
Phosphorus (mmol/L)	Average (SD)	1.2 (0.6)	174
pH	Average (SD)	7.4 (0.1)	260
Bicarbonates (mmol/L)	Average (SD)	22.5 (5.7)	144
Complications		Total N=219
Peak CPK (IU/L)	Average (SD)	29,453 (243,744)	0
CPK > 5000 UI/L	Yes, N(%)	86 (39.3)	0
Peak creatinine (µmol/L)	Average (SD)	152.6 (150.2)	1
Acute renal failure	Yes, N(%)	124 (57.7)	4
Disseminated intravascular coagulation	Yes, N(%)	4 (1.9)	5
Compartment syndrome	Yes, N(%)	7 (3.3)	5
Delirium	Yes, N(%)	51 (23.8)	5
Treatment
Infusion Renal dialysis	No, N(%) <1L, N(%) 1-2 L, N(%) > 2 L, N(%) N(%)	18 (8.5) 66 (31.0) 70 (32.9) 55 (25.8) 4 (1.9)	6
Outcomes		N= 219
Release	Return home, N(%) PAC, N(%) NH, N(%) Deaths, N(%)	156 (71.2) 35 (16.0) 5 (2.3) 25 (11.4)	0
30-days hospital mortality	Yes, N(%)	23 (10.7)	1

N stands for number; SD stands for standard deviation; qSOFA stands for Quick Sequential Organ Failure Assessment (15); T stands for transfer; PAC stands for Post Acute Care; NH stands for Nursing Home; ERP stands for extrarenal purificationépuration extra rénale

Table 2. Association between known prognostic factors and age categories according to the Kruskal-Wallis test. qSOFA stands for quick Sequential Organ Failure Assessment (15)

	Average (standard deviation) / number (%)
	< 50 years n = 64	50 - 59 years old n = 43	60 - 69 years n = 43	70 - 79 years n = 48	80 - 89 years n = 105	> 90 years n = 40	P N=343
Charlson	0.3 (0.8)	1.8 (2.4)	1.9 (2.3)	1.5 (2.0)	1.3 (1.2)	1.3 (1.5)	< 0.001
Number of medicines	2.7 (3.3)	3.6 (3.0)	5.4 (3.3)	6.1 (4.0)	5.4 (3.0)	5.1 (3.0)	< 0.001
Drugs < 8	37 (57.8)	19 (44.2)	9 (22.5)	11 (24.9)	13 (12.9)	7 (17.5)	< 0.001
qSOFA ≥ 2	8 (12.7)	6 (14.3)	3 (7.0)	3 (6.3)	9 (8.6)	1 (3.3)	0.4
Long lie	5 (7.9)	17 (39.5)	22 (51.2)	43 (89.6)	98 (93.3)	39 (97.5)	< 0.001
Initial CPK	23,315 (56,563)	12,470 (23,426)	11,339 (22,380)	5,371 (5,637)	5,133 (13,735)	3,000 (3,057)	< 0.001
CPK peak	82,534 (448,689)	13,154 (23,474)	12,834 (22,617)	7,419 (9,103)	5,357 (13,770)	3,173 (3,189)	< 0.001
CPK ≥ 5,000 UI/L	34 (54.0)	21 (48.8)	16 (37.2)	19 (39.6)	25 (23.8)	5 (12.5)	< 0.001
Peak creatinine	201.4 (234.5)	171.8 (180.9)	156.8 (141.2)	116.3 (97.2)	115.1 (93.7)	100.7 (55.6)	0.01
Calcium	2.1 (0.4)	2.2 (0.3)	2.1 (0.2)	2.2 (0.2)	2.3 (0.2)	2.3 (0.1)	0.1
Phosphorus	1.3 (0.7)	1.2 (0.7)	1.3 (0.8)	1.0 (0.5)	1.0 (0.4)	1.1 (0.5)	0.2
Bicarbonates	23.0 (7.4)	21.8 (5.7)	21.9 (5.3)	21.2 (5.0)	22.7 (4.3)	24.0 (4.4)	0.6
IRA	35 (56.5)	26 (61.9)	29 (67.4)	19 (52.9)	40 (50.6)	16 (59.3)	0.6
DIC	1 (20)	3 (60)	1 (20)	0 (0)	0 (0)	0 (0)	0.1
Delirium	13 (21)	12 (28.6)	6 (14.3)	9 (25.7)	28 (34.6)	8 (27.6)	0.2
IV infusion>2L	27 (43.6)	13 (33.3)	12 (29.3)	11 (23.9)	14 (13.9)	1(2.6)	< 0.001
Exited living at home	48 (76.2)	21 (48.8)	24 (55.8)	15 (31.3)	34 (32.4)	11 (27.5)	< 0.001
30-day hospital mortality	1 (1.7)	2 (4.9)	7 (17.1)	4 (8.9)	8 (8.9)	3 (10)	0.1

Table 3. Univariate analysis between the different variables and 30-day hospital mortality using the T-test for continuous variables and the Chi-2 test for categorical variables (non-transferred patients N=219).

		Total	Deceased (n= 23)	Living (n = 196)	p
Gender	Female, N(%)	83 (37.9)	7 (30.4)	76 (38.8)	0.44
Age (years)	Average (SD)	63.7 (21.2)	73.2(17.0)	62.6 (21.4)	0.013
Rural / Urban	Rural, N(%)	44(20.1)	4 (17.4)	40 (20.4)	1.0
Support	Yes , N(%)	74 (34.1)	4 (19.1)	70 (35.7)	0.13
Charlson	Average (SD)	1.2 (19)	2.7 (3.6)	1.1 (1.5)	0.046
Number of medicines	Average (SD)	4.2 (3.4)	4.2 (3.2)	4.2 (3.4)	0.97
qSOFA ≥ 2	Yes, N (%)	20 (9.2)	8 (34.8)	12(6.2)	0.001
Etiology	Drop, N(%) Drug abuse, N(%) Muscular, N(%) Toxic, N(%) Other, N(%)	117 (53.4) 7 (3.2) 73 (33.3) 15 (5.0) 7 (3.2)	14 (60.1) 0 (0.0) 8 (34.8) 0 (0.0) 1 (4.3)	103 (52.6) 7 (3.6) 65 (33.2) 15 (6.9) 6 (3.1)
Initial CPK (IU/L)	Average (SD)	12,453 (35,000)	20,854 (37,386)	11,468 (34,676)	0.26
Peak CPK (IU/L)	Average (SD)	29,453 (243,744)	23,983 (42,037)	30,095 (257,323)	0.76
CPK 5000 (UI/L)	Yes, N(%)	86 (39.3)	13 (56.5)	73 (37.2)	0.11
Peak creatinine (µmol/L)	Average (SD)	152.6 (150.2)	282.5 (138.2)	137.3 (144.3)	0.001
Acute renal failure	Yes, N(%)	124 (57.7)	21 (91.3)	107(53.6)	0.001
Potassium (mmol/L)	Average (SD)	4.2 (0.9)	4.6 (1.3)	4.1 (0.8)	0.12
Hemoglobin (g/dl)	Average (SD)	13.4 (2.1)	13.0 (2.9)	13.4 (2.0)	0.46
Hematocrit	Average (SD)	39.6 (7.3)	39.5 (9.2)	39.8 (7.1)	0.88
Platelets (G/L)	Average (SD)	222.6 (100.2)	200.0 (114.2)	225.3 (98.4)	0.32
Leukocytes (G/L)	Average (SD)	12.0 (5.2)	12.6 (5.9)	12.3 (5.5)	0.61
Calcium (mmol/L)	Average (SD)	2.2 (0.3)	2.0 (0.4)	2.2 (0.3)	0.052
Phosphorus (mmol/L)	Average (SD)	1.2 (0.6)	1.9 (0.9)	1.1 (0.5)	0.015
pH	Average (SD)	7.4 (0.1)	7.4 (0.1)	7.4 (0.1)	0.45
Bicarbonates (mmol/L)	Average (SD)	22.0 (6.1)	19.3 (8.0)	22.5 (5.6)	0.11
DIC	Yes, N(%)	4 (1.9)	3 (13.6)	1 (0.5)	0.003
Compartment syndrome	Yes, N(%)	7 (3.3)	2 (9.1)	5 (2.6)	0.15
Delirium	Yes, N(%)	51 (23.8)	10 (45.5)	41 (21.4)	0.012
Intravenous hydration	No, N(%) <1L, N(%) 1-2 L, N(%) > 2 L, N(%) ERP, N(%)	18 (8.5) 66 (32.1) 70 (32.9) 55 (25.8) 4 (1.9)	2 (9.5) 4 (19.1) 4 (19.1) 11 (52.4) 0 (0)	16 (8.3) 62 (32.3) 66 (34.4) 44 (22.9) 4 (2.1)
Hydration > 2L	Yes, N(%)	59 (27.7)	11 (52.4)	48 (25.0)	0.008

N stands for number; SD stands for standard deviation, qSOFA stands for quick Sequential Organ Failure Assessment (15)

Table 4. Variables with less than 10% missing data associated with 30-day in-hospital mortality in rhabdomyolysis, according to the logistic regression model (non-transferred patients N=219).

Variables	Odds ratio	95% CI	p
Intercept	2.47e-4	[7.25e-6; 0.008]	< 0.001
Age	1.06	[1.02 ; 1.10]	0.003
Charlson	1.30	[1.05 ; 1.60]	0.015
qSOFA	5.11	[1.31 ; 19.98]	0.002
Peak creatinine	1.00	[1.00 ; 1.01]	0.002
DIC	37.68	[2.29 ; 620.59]	0.011

Accuracy: 0.919

The variables included in the model were: age, Charlson score, qSofa score, CPK level, peak creatinine level and presence of DIC or delirium.

No competing interests reported.

Rhabdomyolysis in older adults: outcomes and prognostic factors

Status:

Journal Publication

Version 1

Abstract

Figures

1. Background

2. Methodology

2.1 Inclusion:

2.2. Collected data:

2.3. Statistical analysis:

3. Results

3.1 Characteristics of the population:

3.2 Associations between prognostic factors and age categories:

3.3. Factors associated with 30-day hospital mortality:

3.4. Multivariate analysis:

4. Discussion

5. Conclusion

Declarations

References

Tables

Additional Declarations

Status:

Journal Publication

Version 1