Literature DB >> 35245308

Skeletal muscle atrophy and myosteatosis are not related to long-term aneurysmal subarachnoid hemorrhage outcome.

Yuanyuan Shen1,2, Stef Levolger3, Abdallah H A Zaid Al-Kaylani3, Maarten Uyttenboogaart3,4, Carlina E van Donkelaar1, J Marc C Van Dijk1, Alain R Viddeleer3, Reinoud P H Bokkers3.   

Abstract

The prognosis of aneurysmal subarachnoid hemorrhage (aSAH) is highly variable. This study aims to investigate whether skeletal muscle atrophy and myosteatosis are associated with poor outcome after aSAH. In this study, a cohort of 293 consecutive aSAH-patients admitted during a 4-year period was retrospectively analyzed. Cross-sectional muscle measurements were obtained at the level of the third cervical vertebra. Muscle atrophy was defined by a sex-specific cutoff value. Myosteatosis was defined by a BMI-specific cutoff value. Poor neurological outcome was defined as modified Rankin Scale 4-6 at 2 and 6-month follow-up. Patient survival state was checked until January 2021. Generalized estimating equation was performed to assess the effect of muscle atrophy / myosteatosis on poor neurological outcome after aSAH. Cox regression was performed to analyze the impact of muscle atrophy and myosteatosis on overall survival. The study found that myosteatosis was associated with poor neurological condition (WFNS 4-5) at admission after adjusting for covariates (odds ratio [OR] 2.01; 95%CI 1.05,3.83; P = .03). It was not associated with overall survival (P = .89) or with poor neurological outcomes (P = .18) when adjusted for other prognostic markers. Muscle atrophy was not associated with overall survival (P = .58) or neurological outcome (P = .32) after aSAH. In conclusion, myosteatosis was found to be associated with poor physical condition directly after onset of aSAH. Skeletal muscle atrophy and myosteatosis were however irrelevant to outcome in the Western-European aSAH patient. Future studies are needed to validate these finding.

Entities:  

Mesh:

Year:  2022        PMID: 35245308      PMCID: PMC8896675          DOI: 10.1371/journal.pone.0264616

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Aneurysmal subarachnoid hemorrhage (aSAH) is an acute neurological emergency with a global incidence of 6.1 per 100,000 person-years [1]. Its mortality ranges from 8.3% up to 66.7% [2]. One-third of the survivors have motor/language impairments or disabilities in daily living activities at five-year follow-up [3, 4]. The most important predictive factors for clinical outcome are level of consciousness and neurological deficits at admission, patient age, and the amount of blood on the initial computed tomography (CT) [5]. Recently, temporal muscle thickness and area measurements delineated on CT have been associated with poor clinical outcome in elderly aSAH patients in a Japanese population [6]. Although temporal muscle measurements are not directly linked to sarcopenia, the findings indicate that muscle-biomarkers may be used as a predictor for aSAH outcome [7]. Sarcopenia is recognized as a progressive decline in muscle mass and strength that occurs across a lifetime [7]. In overlap with frailty, it can be considered an age-related decline in physiological reserve [8]. Sarcopenia predisposes patients to a wide range of negative health-related events and worse outcome in various diseases, e.g. lung cancer, chronic obstructive pulmonary disease (COPD), cachexia or chronic heart disease [9-12] and in patients who underwent major surgery, including abdominal aortic aneurysm repair [13, 14]. Another biomarker of muscle change is myosteatosis, which is an indicator of muscle quality. It is defined as the accumulation of intramuscular and intermuscular fat [15, 16]. Neither of these muscle alterations have an identical association with increased morbidity and mortality. In hospitalized geriatric patients, myosteatosis is associated with high mortality only in male patients, while sarcopenia was a risk factor for overall death among the whole geriatric cohort [17-20]. The aim of this study was to investigate the association between skeletal muscle atrophy, myosteatosis, and poor outcome after aneurysmatic subarachnoid hemorrhage.

Methods

This is a retrospective cohort study of aSAH-patients with a CT-scan that covered the third cervical vertebral body. All patients were consecutively treated at the University Medical Center Groningen (UMCG) between January 2013 and December 2017 and had a follow-up period of at least 3 years. The UMCG is a regional comprehensive neurovascular center in the North of The Netherlands. Patients with a history of muscular disease or lacking height and weight records were excluded. The study was approved by the UMCG ethics review board (METc 2019/505). According to Dutch regulations and General Data Protection Regulation, no informed consent was required due to the retrospective and observational nature of this study. Access to the national Personal Records Database (BRP) in order to determine the survival status was approved by the National Service for Identity Data (RvIG).

Patient characteristics

Patients’ clinical data were extracted from the electronic medical records, including sex; age at ictus; height and weight (at admission or within 3 days); history of SAH and myocardial infarction; presence of hypertension (systolic blood pressure >140 mmHg or diastolic blood pressure >90 mmHg or controlled using antihypertensive drugs). The World Federation of Neurosurgical Societies (WFNS) grading system was used to assess neurological condition at admission [21]; if a resuscitation was performed before aneurysm reparation, the WFNS-grade after resuscitation within 12 hours was used [22]. WFNS 4–5 was considered a poor neurological condition. The severity of hemorrhage was assessed on the initial CT using the modified Fisher scale. Grade 3–4 was categorized as high mFisher. The size of the aneurysm was defined large if greater than 10 mm.

Image acquisition and muscle measurements

All patients had an initial CT-angiogram of the head and neck as a part of the standard clinical care. CT-imaging was performed on a Siemens SOMATOM Definition Edge or SOMATOM Sensation (Siemens Medical, Erlangen, Germany), using a 512x512 matrix, soft-tissue reconstruction kernel and a slice thickness of 3–5 mm. All scans were performed with intravenous contrast in the arterial phase. CT-images were retrieved from the hospital’s picture archiving and communications system (PACS) and saved in Digital Imaging and Communications in Medicine (DICOM) format for further analysis. Cross-sectional muscle measurement was obtained at the level of the third cervical vertebra (C3), on the slice where both superior articular processes were shown. The paravertebral muscle (PVM) included rotator cervicis, levator scapulae, longissimus capitis, interspinales cervicis, semispinalis cervicis, semispinalis capitis, splenius capitis, and trapezius muscles. Bilateral sternocleidomastoid muscles (SCM) and PVM were considered the region of interest (ROI) in this study (Fig 1).
Fig 1

Schematic diagram of cross-sectional muscle measured at the level of third cervical vertebra.

Muscles of interest are colored as cyan for sternocleidomastoid muscles; yellow for interspinales cervicis; red for rotator cervicis, levator scapulae, longissimus capitis, semispinalis cervicis, semispinalis capitis, splenius capitis, and trapezius muscles. A cross-sectional image from a patient without skeletal muscle atrophy or myosteatosis (female, BMI 27.5, SMI 13.2, mean HU 43.8); B a patient with both muscle atrophy and myosteatosis (male, BMI 21.5, SMI 12.1, mean HU 40.8); C a patient with myosteatosis but no muscle atrophy (male, BMI 26.6, SMI 14.5 mean HU 36.8); D a patient with muscle atrophy but non-myosteatosis (female, BMI 20.3, SMI 10.8, mean HU 48.0). BMI: body mass index; SMI: skeletal muscle index (SMA / patient height2); HU: Hounsfield Units.

Schematic diagram of cross-sectional muscle measured at the level of third cervical vertebra.

Muscles of interest are colored as cyan for sternocleidomastoid muscles; yellow for interspinales cervicis; red for rotator cervicis, levator scapulae, longissimus capitis, semispinalis cervicis, semispinalis capitis, splenius capitis, and trapezius muscles. A cross-sectional image from a patient without skeletal muscle atrophy or myosteatosis (female, BMI 27.5, SMI 13.2, mean HU 43.8); B a patient with both muscle atrophy and myosteatosis (male, BMI 21.5, SMI 12.1, mean HU 40.8); C a patient with myosteatosis but no muscle atrophy (male, BMI 26.6, SMI 14.5 mean HU 36.8); D a patient with muscle atrophy but non-myosteatosis (female, BMI 20.3, SMI 10.8, mean HU 48.0). BMI: body mass index; SMI: skeletal muscle index (SMA / patient height2); HU: Hounsfield Units. In-house developed software (SarcoMeas Neck 0.34; UMCG, Groningen, The Netherlands) was used to perform the skeletal muscle measurements. With this software, the neck muscles at the level of the third cervical vertebra were manually delineated by one investigator (AK) based on radiodensity as expressed in Hounsfield Units (HU). The target muscles are illustrated in Fig 1. Within these contours, voxels with a radiodensity from -29 to 150 HU were identified as skeletal muscle. The Skeletal Muscle Area (SMA) was determined by calculating the volume of all muscle voxels. The SMA was then corrected for patient length, by dividing the muscle area by the squared patient length, resulting in the Skeletal Muscle Index (SMI), expressed in cm2 /m2. Skeletal Muscle Density (SMD) was defined as the mean density of all muscle voxels within the drawn contours. To assess interobserver variability, all measurements were independently repeated by a second investigator (AV). Moreover, 50 random cases were remeasured by the first investigator (AK) after two years, for assessment of intraobserver agreement.

Treatment and follow-up

All aSAH-patients were treated following a standardized multidisciplinary protocol [22]. Ruptured aneurysms in patients with good neurological grades (WFNS 1–3) were clipped or coiled within 72 hours after the ictus. In patients with poor condition (WFNS 4–5), neurological resuscitation in the intensive care unit was instituted and urgent interventions (e.g., CSF drainage or hematoma evacuation) were performed within 24 hours.

Outcome parameters

The primary outcome was mortality. The national civil registry was consulted for long-term survival data on January 20th, 2021. Survival time was defined as the period between aSAH and death, or ultimately January 20th 2021. The secondary outcome measure was neurological function (modified Rankin Scale—mRS [23]), graded at 2 and 6 months follow-up with a questionnaire. An mRS 4–6 was considered poor.

Statistical analysis

Difference in baseline characteristics between groups was tested using a t-test for continuous variables if normally distributed, Mann-Whitney U test in case of non-normal distribution, and a chi-square test or Fisher exact test for categorical variables [24]. The presence of myosteatosis was determined by means of applying a threshold. From previous studies it is known that the threshold of myosteatosis varies significantly based on the BMI of the subject [9, 25]. Therefore, we established BMI-specific cutoff points of mean HU value for myosteatosis by optimum stratification. Optimal stratification is a strategy, based on log-rank statistics to determine at which cutoff value the most significant difference would occur with regard to a binary outcome or a time-to-event outcome, such as death in this study [26]. A two-step procedure was performed to determine the thresholds: First, all patients were split into two subgroups based on the value of BMI 25kg/m2 according to the WHO definition of overweight [27]; Secondly, within each subgroup, the mean HU value with the most significant P value for overall mortality by log rank statistics was selected as the cutoff point of the BMI-specific group. Muscle mass in males is furthermore known to differ significantly from that in females [28]. To determine the presence of muscle atrophy, we corrected for this by applying a sex-specific threshold for muscle atrophy in accordance to previous studies [25]. An attempt was made to determine the SMI threshold following the two-step procedure as stated above, however a threshold was not found within this cohort. Previously reported gender-specific cutoff points for sarcopenia were therefore used (7.8 cm2/m2 for female, and 12.1 cm2/m2 for male) [29]. Cox proportional hazards model was used to assess the correlation between muscle alternations and mortality. Proportional Hazards Assumption was not significant. Covariables were selected based on: 1. Variables that were significantly different between groups; 2. Variables that were associated with death at univariable analysis; 3. Variables that had more than 10 events (death). The two variables were binarized as good/poor WFNS and low/high mFisher. As an age of 70 or older is an independent risk factor for poor neurological outcome 2 month after aneurysmal SAH, age was dichotomized at 70 years [30]. A forward likelihood ratio method was used for model fitting. All covariables were checked for interaction and confounding. Generalized estimating equation was used to assess the effect of skeletal muscle atrophy and myosteatosis on neurological outcome. A two-tail p-value < .05 was considered statistically significant. Statistical analysis was performed with SPSS version 25.0 (IBM, Armonk, NY).

Results

During the inclusion period, 518 consecutive patients were diagnosed and treated for aSAH, of which 293 patients were eligible for skeletal muscle analysis. Fig 2 depicts the enrollment process; 58 patients were excluded because the CT-images were insufficient (cross-section at C3 level was not complete); 167 patients were excluded for unavailable patient height; 2 more patients were excluded from the myosteatosis analyses as their weight was missing. The two-month follow up interview and quality of life assessment was incomplete in 7 patients, as well as in 57 patients at six-month follow up. The survival-state was determined on January 20th, 2021 for all 293 patients.
Fig 2

Study flowchart.

Outcome of this study included two parts: survival state and quality of life represented by modified Rankin Scale. Modified Rankin Scale is assessed at 2 months and 6 months follow-up, survival state of all patients was required on January 20th, 2021. * The weight of two more patients were unavailable for defining myosteatosis.

Study flowchart.

Outcome of this study included two parts: survival state and quality of life represented by modified Rankin Scale. Modified Rankin Scale is assessed at 2 months and 6 months follow-up, survival state of all patients was required on January 20th, 2021. * The weight of two more patients were unavailable for defining myosteatosis. Baseline patient characteristics are reported in Table 1. In 293 (99%) subjects the slice thickness was 3mm and in 4 (1%) patients it was 5mm. The median follow-up time was 58.0 months (interquartile range 33.0 month). Sixty-eight patients died during follow-up. Continuous variables were all normally distributed.
Table 1

Patient characteristics.

MyosteatosisSkeletal Muscle atrophy
No (n = 160)Yes (n = 145)P valueNo (n = 279)Yes (n = 14)P value
Female 96(60.0)108(74.5) .01 193(69.2)1(7.1) < .001
Age years 53.6(13.6)62.9(11.4).3557.89(13.2)59.0(13.1).76
Age >70y 15(9.4)45(31.0) < .001 53(19.0)1(7.1).48
BMI kg/cm2 25.3(4.3)27.2(5.7) .03 26.4(5.1)22.9(2.7) .01
BMI<25kg/cm2 81(50.6)62(42.8).21126(45.5)12(85.7) < .01
Pre SAH 4(2.5)6(4.1).539(3.2)1(7.1).39
Hypertension 42(26.3)59(40.7) .01 93(33.3)3(21.4).56
MI 7(4.4)5(3.4).7710(3.6)1(7.1).42
Smoking 11(16.9)13(22).5021(18.4)1(20)1.00
Alcohol 3(4.6)4(6.8).717(6.1)01.00
WFNS 1 87(54.4)46(34.8) < .01 123(44.1)10(71.4).12
2 33(20.6)33(25.0)66(23.7)0
3 9(5.7)6(4.5)15(5.4)0
4 15(9.4)24(18.2)38(13.6)1(7.1)
5 15(9.4)23(17.4)37(13.3)3(21.4)
Poor WFNS 30(18.9)47(35.6) < .01 75(26.9)4(28.6)1.00
mFisher 0 12(7.5)0 < .001 11(3.9)1(7.1).05
1 41(25.8)16(11)51(18.3)7(50)
2 33(20.8)40(27.6)69(24.7)1(7.1)
3 23(14.5)15(10.3)37(13.3)1(7.1)
4 50(31.4)74(51)111(39.8)4(28.6)
High mFisher 73(45.9)79(59.8) .02 148(53)5(35.7).21
Large Aneurysm 34(22.5)32(23.7).8961(23.3)2(15.4).74
SMI cm2/m2 male n = 99 14.8(2.7)14.7(2.5).7815.4(2.2)10.7(1.1) < .001
female n = 194 12.0(2.0)7.4 .03 11.8(2.0)12.1(2.1).26
Skeletal Muscle atrophy 10(6.3)4(3.0).27
mean HU BMI<25 n = 143 48.7(7.2)36.6(4.3) < .001 43.5(8.5)44.5(9.0).72
BMI≥25 n = 162 44.1(4.1)34.3(4.2) < .001 39.3(6.4)43.0(5.0).41
Myosteatosis 128(46.2)4(28.6).27

All continuous variables were normally distributed, reported as mean and standard deviation. Categorical variables were presented as case number and percentage of the group. BMI, Body mass index; pre SAH, history of Subarachnoid hemorrhage; MI, myocardial infarction; Poor WFNS, World Federation of Neurosurgical Societies grading 4 or 5; High mFisher, modified Fisher scale 3 or 4; SMI, skeletal muscle index; Large aneurysm, aneurysm size larger than 10 mm. HU, Hounsfield unit.

All continuous variables were normally distributed, reported as mean and standard deviation. Categorical variables were presented as case number and percentage of the group. BMI, Body mass index; pre SAH, history of Subarachnoid hemorrhage; MI, myocardial infarction; Poor WFNS, World Federation of Neurosurgical Societies grading 4 or 5; High mFisher, modified Fisher scale 3 or 4; SMI, skeletal muscle index; Large aneurysm, aneurysm size larger than 10 mm. HU, Hounsfield unit. Both interobserver and intraobserver levels of agreement for SMA and mean HU value were found to be excellent (Table 2).
Table 2

Interobserver and intraobserver levels of agreement for SMI and mean HU value.

Agreement*Skeletal Muscle AreaMean HU
Interobserver0.988 (95%CI 0.984, 0.991)0.995 (95%CI 0.990, 0.997)
Intraobserver0.975 (95%CI 0.884, 0.991)0.908 (95%CI 0.832, 0.949)

*Intraclass correlation coefficient, absolute agreement, two-way random, average measures.

*Intraclass correlation coefficient, absolute agreement, two-way random, average measures.

Skeletal muscle atrophy

Skeletal muscle atrophy was identified in 14 of 293 (4.8%) patients. Compared to the patients without muscle atrophy, fewer female patients were present in the muscle atrophic cohort (7.1% vs 69.2%, P< .001). Also, muscle atrophic patients had a lower mean BMI (22.93 ± 2.70 vs 26.35 ± 5.12, P = .01). There was no statistical difference in age, smoking, alcohol, aneurysm size, WFNS, or mFisher scale. Overall survival was equal in patients with and without muscle atrophy (P = .56, Table 3).
Table 3

Cox regression of overall survival.

Univariable analysisMultivariable analysis
Variable HR95% CIP valueHR95% CIP value
Female 1.140.80–1.600.46
Age 1.041.02–1.05 <0.001 1.061.04–1.09 <0.001
BMI 1.030.98–1.070.27
Previous SAH 1.660.78–3.560.19
Hypertension 1.451.02–2.06 0.04 0.660.38–1.150.15
Smoking 0.750.34–1.650.47
Alcohol 1.530.61–3.840.36
Poor WFNS 5.653.99–8.00 <0.001 2.751.52–4.98 0.001
High mFisher 3.602.45–5.30 <0.001 1.400.75–2.610.29
Large aneurysm 2.151.48–3.12 <0.001 1.420.82–2.480.22
Sarcopenia 1.320.48–3.640.58
Myosteatosis 1.971.20–3.22 0.01 1.040.60–1.810.89

Covariates in multivariable analysis: age, present of hypertension, large aneurysm, high mFisher, poor WFNS, myosteatosis. HR, Hazard ratio; BMI, Body mass index; SAH, Subarachnoid hemorrhage; MI, myocardial infarction; Poor WFNS, World Federation of Neurosurgical Societies grading 4 or 5; High mFisher, modified Fisher scale 3 or 4; Large aneurysm, aneurysm size larger than 10 mm.

Covariates in multivariable analysis: age, present of hypertension, large aneurysm, high mFisher, poor WFNS, myosteatosis. HR, Hazard ratio; BMI, Body mass index; SAH, Subarachnoid hemorrhage; MI, myocardial infarction; Poor WFNS, World Federation of Neurosurgical Societies grading 4 or 5; High mFisher, modified Fisher scale 3 or 4; Large aneurysm, aneurysm size larger than 10 mm. Survival at month 12, 36, and 60 was 78.6%, 71.4%, 71.4% for muscle atrophic patients, and 84.9%, 81.7%, 78.5% for patients without muscle atrophy (Fig 3). Skeletal muscle atrophy was not associated with neurological outcome (P = .32, Table 4).
Fig 3

Kaplan-Meier survival curves of patients with skeletal muscle atrophy and myosteatosis.

Table 4

Effects of muscle alterations on neurological outcomes.

2 months*6 months*Effect over time**
Muscle atrophy Univariable analysisOR (95% CI)1.31 (0.35, 4.89)2.59 (0.32, 20.98)1.94 (0.52, 7.27)
P value.69.70.32
Myosteatosis Univariable analysisOR (95% CI)2.66 (1.55, 4.56)3.12 (1.58, 6.16)2.83(1.67, 4.79)
P value < .001 < .01 < .001
Multivariable analysisOR (95% CI)1.64 (0.78, 3.46)1.49 (0.60, 3.69)0.63 (0.31, 1.28)
P value.19.39.20

Covariates in multivariable analysis: age, present of hypertension, large aneurysm, high mFisher, poor WFNS, myosteatosis.

* Binary logistic regression

** Generalized estimating equation.

Covariates in multivariable analysis: age, present of hypertension, large aneurysm, high mFisher, poor WFNS, myosteatosis. * Binary logistic regression ** Generalized estimating equation.

Myosteatosis

Myosteatosis is the accumulation of intra- and inter-muscle adipose tissue, which leads to the decreasing of radiodensity expressed in HU value. BMI-specific mean HU cutoff values (optimum stratification) were 39.6 for BMI < 25 kg/m2, and 42.1 for BMI ≥ 25 kg/m2. Non-myosteatotic and myosteatotic patients had overlapping age-groups (53.6 ± 13.6 vs 62.9 ± 11.4, P = .35), but patients in the myosteatotic group were more likely to be above the age of 70 (31.0% vs 9.4%, P< .001). Furthermore, myosteatotic patients showed a higher female preponderance (74.5% vs 60.0%, P = .01); higher BMI (27.2 ± 5.7 vs 25.3 ± 4.3, P = .03); higher prevalence of arterial hypertension (40.7% vs 26.3%, P = .01); higher frequency of poor WFNS grade (35.6% vs 18.9%, P< .001); and higher mFisher score (59.8% vs 45.9%, P = .02). No difference was found in aneurysm size, history of previous SAH, smoking, or alcohol consumption. Considering age, presence of hypertension, aneurysm size, and mFisher scale as covariates, the adjusted OR of myosteatosis on poor WFNS grade was 2.01 (95%CI 1.05, 3.83; P = .03). The correlation coefficient of mean HU value versus WFNS grade and mFisher scale was 0.16 and 0.15 respectively (Table 5).
Table 5

Effect of myosteatosis on mFisher scale and WFNS grade.

High mFisherPoor WFNSmFisherWFNS
Myosteatosis * Univariable analysisOR (95% CI)1.76 (1.10, 2.80)2.38 (1.39, 4.05)
P value .02 < .01
Multivariable analysisOR (95%CI)1.20 (0.69, 2.08)2.01 (1.05, 3.83)
P value.51 .03
mean HU ** Correlation Coefficient0.150.160.200.15
P value < .001 < .001 < .001 < .001

OR, Odds Ratio; CI, Confidence Interval; Poor WFNS, World Federation of Neurosurgical Societies grading 4 or 5; High mFisher, modified Fisher scale 3 or 4.

*Binary logistic regression, covariates in multivariable analysis: age, present of hypertension, large aneurysm, and high mFisher scale/ poor WFNS.

** Kendall’s tau_b correlation coefficient.

OR, Odds Ratio; CI, Confidence Interval; Poor WFNS, World Federation of Neurosurgical Societies grading 4 or 5; High mFisher, modified Fisher scale 3 or 4. *Binary logistic regression, covariates in multivariable analysis: age, present of hypertension, large aneurysm, and high mFisher scale/ poor WFNS. ** Kendall’s tau_b correlation coefficient. Survival at month 12, 36, 60, and 84 was 91.7%, 77.3%, 72.0%, and 65.8% for myosteatotic patients and 92.5%, 85.5%, 85.5% and 82.8% for non-myosteatotic patients respectively (Fig 3). All-cause mortality of myosteatotic patients was increased in univariable analysis (P = .01, Table 2), but not in multivariable analysis (P = .89). Also, more myosteatotic patients had a poor neurological condition at two month (38.0% vs 18.7%, P< .001) and at six months follow up (30.8% vs 12.5%, P< .01). Considering the effect over time, the association between myosteatosis and poor neurological outcomes remained with OR 2.83 (95%CI 1.67,4.79; P< .001). However, when adjusted for covariates, the statistically significant effect disappeared (Table 4).

Discussion

The current study showed no association between skeletal muscle atrophy, myosteatosis and mortality or neurological outcome. Myosteatosis was correlated with the severity of aSAH at onset. To the author’s knowledge, the impact of muscle atrophy and myosteatosis on all-cause mortality and neurological outcome in aSAH patients in a western population has not yet been reported. Our findings contradict the association between muscle atrophy and poor mRS as reported in studies with a Japanese aSAH cohort [6, 31]. In that study, temporal muscle area and thickness were measured as indicators for sarcopenia in contrast to this study. However, since the temporal muscle is a minor muscle, its reduction may be less representative of overall skeletal muscle [32]. Measurement at the abdominal level can represent total body skeletal muscle and adipose tissue volumes [33]. Skeletal muscle mass and index (SMM/SMI) at the third lumbar vertebra (L3) is prevalently used to define sarcopenia. Since SMI at the 3rd cervical vertebra (C3) is strongly associated with the L3 level [29, 34], the C3 level was used for muscle measurement in this study. Additional to this difference in methodology, population-based differences are also important. Aneurysm rupture risk is known to be higher in Japanese than in the western population (disregarding Finland) [35]. As such, it should be pointed out that, different from that Japanese cohort, our study was based on a Dutch population. Sarcopenia and myosteatosis have been considered as negative prognostic indexes of varied chronic or consumptive conditions, (e.g. COPD, chronic heart failure, liver cirrhosis, cancers [36-39]), as well as recovery ability markers from major surgery (e.g. laryngectomy, radiotherapy, transcatheter aortic valve replacement, and abdominal aortic aneurysm repair [13, 14, 40–42]). Our primary hypothesis that skeletal muscle atrophy and myosteatosis are negative prognostic markers of aSAH is rejected. However, apart from the irrelevance to aSAH outcome, myosteatosis and mean HU value was associated with poor WFNS and high mFisher at baseline. The mFisher scale classifies the hemorrhage volume, while WFNS depicts the physical reaction to the hemorrhage. Both reflect in different ways the severity of aSAH and are nowadays the most predictive outcome predictors of aSAH [5]. Similar to undergoing surgery, aSAH induces an acute stress response. This induced stress syndrome and accompanying hypercatabolic state has been thoroughly described post-surgery and in trauma patients [43, 44]. The protein synthesis rate decreases not only after major surgery, but also after relatively minor surgery [45]. In patients with severe trauma but free from infection, the mortality is higher in a group with lower synthetic rate of proteins than those with accelerated synthetic rate of proteins [46]. Fat-free muscle mass reflects the reserve capacity of muscle proteins and is associated with the occurrence of complications in hospitalized patients and among patients with COPD [47-49]. A study on skeletal muscle mass and post-operation conditions among patients undergoing cardiac surgery suggested that preoperative fat-free muscle mass indicates the ability to cope with operative stress, reflected by post-operation complications [50]. In aSAH patients a comparable hypercatabolic state is observed [51]. Furthermore, daily systemic energy expenditure is increased in the acute phase [52]. And systemic inflammation occurs, including upregulation of cytokines such as IL-6 [53], which particularly in illness is associated with atrophy and muscle wasting [54]. Consequently, despite the negative results found in our study in relation to skeletal muscle atrophy, myosteatosis and overall survival, the differences in muscle quantity and quality observed to be associated with physical condition may reflect low physical reserve. In line with this, a recent study showed high protein intake after SAH actually reduces the rates of temporal muscle atrophy [55]. Taking all into consideration, it is of value to investigate whether early aggressive anti-catabolic treatment or nutritional supportive treatment can improve the physical performance outcome of aSAH patient, particularly for myosteatotic patients. There are several limitations of this study. The limited cases of muscle atrophic patients increased the chance of false negative results. A larger cohort or multiple center studies are expected to reduce the possibility of type II error. There is a potential selection bias. Frailest patients may have been exempted from further treatment after diagnosis, e.g., based on patient wish, or that of the patient’s representative. Thus, those who had too poor physical condition to undergo invasive treatment may have been excluded from this study. It is difficult to tell if this selection bias would lead to an over- or underestimation. Also, despite the lack of association between muscle atrophy and overall survival or neurological outcome in this study, it is important to note that due to its retrospective nature CT-assessed skeletal muscle mass is solely investigated in this study. Although this approach is common in retrospective studies [9–12, 14], the terminology of sarcopenia and muscle atrophy are mixed commonly. The operational definition of sarcopenia—as defined by the European Working Group on Sarcopenia in Older People 2 (EWGSOP2)–identifies probable sarcopenia by low muscle strength first, with secondary confirmation by the presence of low muscle quantity on imaging [7]. Thus, this study included myosteatosis as an amendment to the comprehensive EWGSOP2 definition. Although alike muscle atrophy no association between myosteatosis and poor outcome was found, patients with myosteatosis are two times more likely to experience severe neurological deficiency after the aneurysmal rupture than patients without myosteatosis. This might explain why in univariable analysis, myosteatosis is a risk factor for reduced survival rate and poor neurological outcome, but such effect vanished when adjusted for WFNS and other risk factors. Another limitation of this study is that for CT based measurements of muscle atrophy and myosteatosis, there are no standardized thresholds. In this study we have therefore performed optimal stratification to determine the threshold for myosteatosis and adopted a previously reported threshold for muscle atrophy, however further external validation is required to investigate whether these measures are generalizable. Furthermore, the measurements were made on both 3- and 5-mm slices resulting in varying spatial resolutions. Increased slice-thickness may have led an effect upon the accuracy of both the muscle volume and myosteatosis measurements, however this effect will be limited as the majority of scans (99%) were 3 mm.

Conclusions

Myosteatosis was found to be associated with poor physical condition after the aneurysmal rupture. Skeletal muscle atrophy and myosteatosis were however found to be irrelevant to overall survival and neurological outcome in the Western-European patient after aSAH. Future studies are needed to validate these finding. 12 Nov 2021
PONE-D-21-30009
Skeletal muscle atrophy and myosteatosis are not related to long-term aneurysmal subarachnoid hemorrhage outcome
PLOS ONE Dear Dr. Bokkers, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.
Please submit your revised manuscript by Dec 27 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript:
A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols. We look forward to receiving your revised manuscript. Kind regards, Ezio Lanza, M.D. Academic Editor PLOS ONE Journal Requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2. We note that you have stated that you will provide repository information for your data at acceptance. Should your manuscript be accepted for publication, we will hold it until you provide the relevant accession numbers or DOIs necessary to access your data. If you wish to make changes to your Data Availability statement, please describe these changes in your cover letter and we will update your Data Availability statement to reflect the information you provide. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: Specific comments: - should be added more detail about the in-house developed software (SarcoMeas 0.34; UMCG, Groningen, The Netherlands) as described in the Vedder IR, Levolger S, Dierckx RAJO, et al. Effect of muscle depletion on survival in peripheral arterial occlusive disease: Quality over quantity. J Vasc Surg. 2020;72(6):2006- 2016.e1. doi:10.1016/j.jvs.2020.03.050 - The authors mention that “Both interobserver and intraobserver levels of agreement for SMA and SMD were found to be excellent in a prior study”, however there might be study-specific variations as the Vedder et al assessed patients with peripheral arterial occlusive disease while the current study assess cross-sectional muscle measurement in the cervical region. Taking into account the manual segmentation issue, the both interobserver and intraobserver agreement for SMA and SMD is needed. - it's unclear how muscle atrophy was defined by a sex-specific cutoff value and how myosteatosis was defined by a BMI-specific cutoff value. Should be explain in the method section. - should be added the background why these specific thresholds for skeletal muscle and for intra- and inter-muscle adipose tissue have been selected. - As aging is associated with myosteatosis, it might be the effect of aging that the myosteatotic group in this study are more likely to be above the age of 70 - as a limitation, it is should be highlight that standardization of CT-derived diagnostic thresholds for muscle mass and myosteatosis is lucking - table 1: what is the rational behind the variables age > 70y and BMI < 25. Should be stated in the material and methods section. General comments - references need to be homogenized, for example, introduction section line 51. - typos line 77 (material and methods), line 118 (figure 1 legend) - figure 1, color names in the figure legend not correspond to color in the figure - table 1: is too busy to read. Reviewer #2: In this retrospective study, authors evaluated the correlation between sarcopenia or myosteatosis and poor outcome after subarachnoid hemorrhage due to aneurysmatic rupture. They did not find statistically significant results with mortality and poor neurological function. Overall, the manuscript is sound and clearly written; however, authors could improve the section of Methods according to the following suggestions. - Details about the CT protocol parameters - Could the thickness variability (1 to 5 mm) have influenced the cross-sectional muscle measurements? - Number of investigators in charge of muscle mass measurement [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. 11 Jan 2022 A detailed point-by-point response to the reviewers has been attached as separate file. Submitted filename: Response to Reviewers_final.docx Click here for additional data file. 15 Feb 2022 Skeletal muscle atrophy and myosteatosis are not related to long-term aneurysmal subarachnoid hemorrhage outcome PONE-D-21-30009R1 Dear Dr. Bokkers, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Please note some very minor comments that you can implement in the final draft. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Ezio Lanza, M.D. Academic Editor PLOS ONE Reviewer #2: Authors improved the readability and the quality of their manuscript, clarifying some important concepts in the Methods section. - Table 3: highlight with bold type the significant p-values - Slice thickness: “Of the 293 subjects, 289 (98.63%) had a slice thickness of 3 mm. Given that the slices varied only in 4 patients, we do not expect that this may have influenced the muscle measurements.” This idea should be clarified in the text. **********   24 Feb 2022 PONE-D-21-30009R1 Skeletal muscle atrophy and myosteatosis are not related to long-term aneurysmal subarachnoid hemorrhage outcome Dear Dr. Bokkers: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Ezio Lanza Academic Editor PLOS ONE
  50 in total

Review 1.  Frailty in Older Persons.

Authors:  Matteo Cesari; Riccardo Calvani; Emanuele Marzetti
Journal:  Clin Geriatr Med       Date:  2017-04-06       Impact factor: 3.076

2.  Neck Muscle Mass Index as a Predictor of Post-Laryngectomy Wound Complications.

Authors:  Gülpembe Bozkurt; Hassan Ahmed Elhassan; Abdullah Soydan Mahmutoğlu; İrfan Çelebi; Robert W J Mcleod; Pınar Soytaş; Zeynep Nur Erol; Esra Sözen
Journal:  Ann Otol Rhinol Laryngol       Date:  2018-09-09       Impact factor: 1.547

3.  Opportunistic Computed Tomography Imaging for the Assessment of Fatty Muscle Fraction Predicts Outcome in Patients Undergoing Transcatheter Aortic Valve Replacement.

Authors:  Julian A Luetkens; Anton Faron; Helena L Geissler; Baravan Al-Kassou; Jasmin Shamekhi; Anja Stundl; Alois M Sprinkart; Carsten Meyer; Rolf Fimmers; Hendrik Treede; Eberhard Grube; Georg Nickenig; Jan-Malte Sinning; Daniel Thomas
Journal:  Circulation       Date:  2020-01-20       Impact factor: 29.690

4.  The impact of sarcopenia on tolerance of radiation and outcome in patients with head and neck cancer receiving chemoradiation.

Authors:  Rohit G Ganju; Ryan Morse; Andrew Hoover; Mindi TenNapel; Christopher E Lominska
Journal:  Radiother Oncol       Date:  2019-05-11       Impact factor: 6.280

5.  Prediction of Outcome After Aneurysmal Subarachnoid Hemorrhage.

Authors:  Carlina E van Donkelaar; Nicolaas A Bakker; Jaqueline Birks; Nic J G M Veeger; Jan D M Metzemaekers; Andrew J Molyneux; Rob J M Groen; J Marc C van Dijk
Journal:  Stroke       Date:  2019-04       Impact factor: 7.914

6.  Laparoscopic cholecystectomy does not prevent the postoperative protein catabolic response in muscle.

Authors:  P Essén; A Thorell; M A McNurlan; S Anderson; O Ljungqvist; J Wernerman; P J Garlick
Journal:  Ann Surg       Date:  1995-07       Impact factor: 12.969

7.  Total body skeletal muscle and adipose tissue volumes: estimation from a single abdominal cross-sectional image.

Authors:  Wei Shen; Mark Punyanitya; ZiMian Wang; Dympna Gallagher; Marie-Pierre St-Onge; Jeanine Albu; Steven B Heymsfield; Stanley Heshka
Journal:  J Appl Physiol (1985)       Date:  2004-08-13

8.  Prediction of delayed cerebral ischemia, rebleeding, and outcome after aneurysmal subarachnoid hemorrhage.

Authors:  A Hijdra; J van Gijn; N J Nagelkerke; M Vermeulen; H van Crevel
Journal:  Stroke       Date:  1988-10       Impact factor: 7.914

9.  Prognosis and survival as determined by visceral amino acid clearance in severe trauma.

Authors:  R H Pearl; G H Clowes; E F Hirsch; M Loda; G A Grindlinger; S Wolfort
Journal:  J Trauma       Date:  1985-08

10.  Low skeletal muscle radiation attenuation and visceral adiposity are associated with overall survival and surgical site infections in patients with pancreatic cancer.

Authors:  David P J van Dijk; Maikel J A M Bakens; Mariëlle M E Coolsen; Sander S Rensen; Ronald M van Dam; Martijn J L Bours; Matty P Weijenberg; Cornelis H C Dejong; Steven W M Olde Damink
Journal:  J Cachexia Sarcopenia Muscle       Date:  2016-10-26       Impact factor: 12.910

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.