https://orcid.org/0000-0003-0426-5295
Figures
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.
Citation: Shen Y, Levolger S, Zaid Al-Kaylani AHA, Uyttenboogaart M, van Donkelaar CE, Van Dijk JMC, et al. (2022) Skeletal muscle atrophy and myosteatosis are not related to long-term aneurysmal subarachnoid hemorrhage outcome. PLoS ONE 17(3): e0264616. https://doi.org/10.1371/journal.pone.0264616
Editor: Ezio Lanza, Humanitas Clinical and Research Center - IRRCS, ITALY
Received: September 16, 2021; Accepted: February 15, 2022; Published: March 4, 2022
Copyright: © 2022 Shen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: Individual data cannot be shared publicly because of General Data Protection Regulation. Aggregated data can be made available upon request for researchers who meet the criteria for access to confidential data. The Data Protection Officers of the University Medical Centre Groningen can be contacted at privacy@umcg.nl.
Funding: YS receives financial support from China Scholarship Council (CSC, File No. 201706320024, https://www.csc.edu.cn/) The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
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).
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.
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.
Both interobserver and intraobserver levels of agreement for SMA and mean HU value were found to be excellent (Table 2).
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).
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).
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).
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.
References
- 1. Etminan N, Chang HS, Hackenberg K, et al. Worldwide Incidence of Aneurysmal Subarachnoid Hemorrhage According to Region, Time Period, Blood Pressure, and Smoking Prevalence in the Population: A Systematic Review and Meta-analysis. JAMA Neurol 2019;76. pmid:30659573
- 2. Nieuwkamp DJ, Setz LE, Algra A, et al. Changes in case fatality of aneurysmal subarachnoid haemorrhage over time, according to age, sex, and region: a meta-analysis. Lancet Neurol 2009;8.
- 3. Rinkel GJE, Algra A. Long-term outcomes of patients with aneurysmal subarachnoid haemorrhage. Lancet Neurol. 2011;10. pmid:21435599
- 4. Roquer J, Cuadrado-Godia E, Guimaraens L, et al. Short- and long-term outcome of patients with aneurysmal subarachnoid hemorrhage. Neurology 2020;95. pmid:32796129
- 5. Rosen DS, Macdonald RL. Subarachnoid Hemorrhage Grading Scales: A systematic review. Eur Psychol 2009;14:51–62.
- 6. Katsuki M, Yamamoto Y, Uchiyama T, et al. Clinical characteristics of aneurysmal subarachnoid hemorrhage in the elderly over 75; would temporal muscle be a potential prognostic factor as an indicator of sarcopenia? Clin Neurol Neurosurg 2019;186:105535. pmid:31569058
- 7. Cruz-Jentoft AJ, Bahat G, Bauer J, et al. Sarcopenia: Revised European consensus on definition and diagnosis. Age Ageing. 2019;48. pmid:30312372
- 8. Cesari M, Calvani R, Marzetti E. Frailty in Older Persons. Clin. Geriatr. Med. 2017;33. pmid:28689563
- 9. Martin L, Birdsell L, MacDonald N, et al. Cancer cachexia in the age of obesity: Skeletal muscle depletion is a powerful prognostic factor, independent of body mass index. J Clin Oncol 2013;31:1539–47. pmid:23530101
- 10. Jones SE, Maddocks M, Kon SSC, et al. Sarcopenia in copd: Prevalence, clinical correlates and response to pulmonary rehabilitation. Thorax 2015;70. pmid:25561517
- 11. Minarich MJ, Smucker LY, Henry LR, et al. Structured evaluation of clinical risk scores to predict morbidity after Hpb operations. HPB 2019;21.
- 12. Trestini I, Gkountakos A, Carbognin L, et al. Muscle derangement and alteration of the nutritional machinery in NSCLC. Crit. Rev. Oncol. Hematol. 2019;141. pmid:31228648
- 13. Friedman J, Lussiez A, Sullivan J, et al. Implications of sarcopenia in major surgery. Nutr Clin Pract 2015;30. pmid:25681482
- 14. Kays JK, Liang TW, Zimmers TA, et al. Sarcopenia is a Significant Predictor of Mortality After Abdominal Aortic Aneurysm Repair. JCSM Clin Reports 2018;3:1–12. pmid:30984911
- 15. Hausman GJ, Basu U, Du M, et al. Intermuscular and intramuscular adipose tissues: Bad vs. good adipose tissues. Adipocyte. 2014;3. pmid:26317048
- 16. Goodpaster BH. Measuring body fat distribution and content in humans. Curr. Opin. Clin. Nutr. Metab. Care. 2002;5. pmid:12172470
- 17. Perkisas S, Lamers S, Degerickx R, et al. The relation between mortality, intramuscular adipose tissue and sarcopenia in hospitalized geriatric patients. Eur Geriatr Med 2018;9:801–7. pmid:34674477
- 18. Visser M, Goodpaster BH, Kritchevsky SB, et al. Muscle mass, muscle strength, and muscle fat infiltration as predictors of incident mobility limitations in well-functioning older persons. Journals Gerontol—Ser A Biol Sci Med Sci 2005;60. pmid:15860469
- 19. Nam S, Al Snih S, Markides K. Lower body function as a predictor of mortality over 13 years of follow up: Findings from Hispanic Established Population for the Epidemiological Study of the Elderly. Geriatr Gerontol Int 2016;16. pmid:26627681
- 20. Hirani V, Blyth F, Naganathan V, et al. Sarcopenia Is Associated With Incident Disability, Institutionalization, and Mortality in Community-Dwelling Older Men: The Concord Health and Ageing in Men Project. J Am Med Dir Assoc 2015;16. pmid:25820131
- 21. Hijdra A, Van Gijn J, Nagelkerke N, et al. Prediction of delayed cerebral ischemia, rebleeding, and outcome after aneurysmal subarachnoid hemorrhage. Stroke 1988;19. pmid:3176085
- 22. Van Donkelaar CE, Bakker NA, Veeger NJGM, et al. Prediction of outcome after subarachnoid hemorrhage: Timing of clinical assessment. J Neurosurg 2017;126. pmid:27035175
- 23. Wilson JTL, Hareendran A, Grant M, et al. Improving the assessment of outcomes in stroke: Use of a structured interview to assign grades on the modified Rankin Scale. Stroke 2002;33. pmid:12215594
- 24. Sharples LD, Kirkwood BR. Essentials of Medical Statistics. J R Stat Soc Ser A (Statistics Soc 1989;152.
- 25. 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;72:2006–2016.e1. pmid:32330596
- 26.
Williams BA, Mandrekar JN, Mandrekar SJ, et al. Finding Optimal Cutpoints for Continuous Covariates with Binary and Time-to-Event Outcomes Department of Health Sciences Research Mayo Clinic Rochester, Minnesota Copyright 2006 Mayo Foundation. 2006.
- 27.
World Health Organisation. Obesity and overweight. Fact sheet N°311. Fact sheet N. 2013.
- 28. So JL, Janssen I, Heymsfield SB, et al. Relation between whole-body and regional measures of human skeletal muscle. Am J Clin Nutr 2004;80. pmid:15531668
- 29. Ufuk F, Herek D, Yüksel D. Diagnosis of sarcopenia in head and neck computed tomography: Cervical muscle mass as a strong indicator of Sarcopenia. Clin Exp Otorhinolaryngol 2019;12:317–24.
- 30. Van Donkelaar CE, Bakker NA, Birks J, et al. Prediction of Outcome After Aneurysmal Subarachnoid Hemorrhage: Development and Validation of the SAFIRE Grading Scale. Stroke 2019;50. pmid:30869562
- 31. Katsuki M, Suzuki Y, Kunitoki K, et al. Temporal Muscle as an Indicator of Sarcopenia is Independently Associated with Hunt and Kosnik Grade on Admission and the Modified Rankin Scale Score at 6 Months of Patients with Subarachnoid Hemorrhage Treated by Endovascular Coiling. World Neurosurg 2020;137:e526–34. pmid:32061954
- 32. Binay Safer V, Safer U. Comment on “Clinical characteristics of aneurysmal subarachnoid hemorrhage (SAH) in the elderly over 75: Would temporal muscle be a potential prognostic factor as an indicator of sarcopenia?” Clin Neurol Neurosurg 2020;188:105600. pmid:31756615
- 33. Shen W, Punyanitya M, Wang ZM, et al. Total body skeletal muscle and adipose tissue volumes: Estimation from a single abdominal cross-sectional image. J Appl Physiol 2004;97. pmid:15310748
- 34. Swartz JE, Pothen AJ, Wegner I, et al. Feasibility of using head and neck CT imaging to assess skeletal muscle mass in head and neck cancer patients. Oral Oncol 2016;62. pmid:27865369
- 35. Backes D, Vergouwen MDI, Tiel Groenestege AT, et al. PHASES Score for Prediction of Intracranial Aneurysm Growth. Stroke 2015;46:1221–6. pmid:25757900
- 36. Ebner N, Sliziuk V, Scherbakov N, et al. Muscle wasting in ageing and chronic illness. ESC Hear. Fail. 2015;2. pmid:28834653
- 37. Kim G, Kang SH, Kim MY, et al. Prognostic value of sarcopenia in patients with liver cirrhosis: A systematic review and meta-analysis. PLoS One 2017;12. pmid:29065187
- 38. Sepúlveda-Loyola W, Osadnik C, Phu S, et al. Diagnosis, prevalence, and clinical impact of sarcopenia in COPD: a systematic review and meta-analysis. J. Cachexia. Sarcopenia Muscle. 2020;11. pmid:32862514
- 39. van Dijk DPJ, Bakens MJAM, Coolsen MME, et al. Low skeletal muscle radiation attenuation and visceral adiposity are associated with overall survival and surgical site infections in patients with pancreatic cancer. J Cachexia Sarcopenia Muscle 2017;8. pmid:27897432
- 40. Ganju RG, Morse R, Hoover A, et al. The impact of sarcopenia on tolerance of radiation and outcome in patients with head and neck cancer receiving chemoradiation. Radiother Oncol 2019;137. pmid:31085391
- 41. Bozkurt G, Elhassan HA, Mahmutoğlu AS, et al. Neck Muscle Mass Index as a Predictor of Post-Laryngectomy Wound Complications. Ann Otol Rhinol Laryngol 2018;127. pmid:30198302
- 42. Luetkens JA, Faron A, Geissler HL, et al. Opportunistic computed tomography imaging for the assessment of fatty muscle fraction predicts outcome in patients undergoing transcatheter aortic valve replacement. Circulation 2020;:234–6. pmid:31958246
- 43. Finnerty CC, Mabvuure NT, Kozar RA, et al. The Surgically Induced Stress Response. J Parenter Enter Nutr 2013;37. pmid:24009246
- 44. Desborough JP. The stress response to trauma and surgery. Br J Anaesth 2000;85. pmid:10927999
- 45. Essén P, Thorell A, McNurlan MA, et al. Laparoscopic cholecystectomy does not prevent the postoperative protein catabolic response in muscle. Ann Surg 1995;222.
- 46. Pearl RH, Clowes GHA, Hirsch EF, et al. Prognosis and survival as determined by visceral amino acid clearance in severe trauma. J Trauma—Inj Infect Crit Care 1985;25. pmid:4020912
- 47. Kyle UG, Pirlich M, Lochs H, et al. Increased length of hospital stay in underweight and overweight patients at hospital admission: A controlled population study. Clin Nutr 2005;24. pmid:15681111
- 48. Vestbo J, Prescott E, Almdal T, et al. Body Mass, Fat-Free Body Mass, and Prognosis in Patients with Chronic Obstructive Pulmonary Disease from a Random Population Sample. Am J Respir Crit Care Med 2006;173. pmid:16368793
- 49. Pichard C, Kyle UG, Morabia A, et al. Nutritional assessment: Lean body mass depletion at hospital admission is associated with an increased length of stay. Am J Clin Nutr 2004;79. pmid:15051605
- 50. Van Venrooij LMW, Verberne HJ, de Vos R, et al. Postoperative loss of skeletal muscle mass, complications and quality of life in patients undergoing cardiac surgery. Nutrition 2012;28. pmid:21621393
- 51. Zetterling M, Engström BE, Hallberg L, et al. Cortisol and adrenocorticotropic hormone dynamics in the acute phase of subarachnoid haemorrhage. Br J Neurosurg 2011;25. pmid:22115015
- 52. Nyberg C, Engström ER, Hillered L, et al. Daily systemic energy expenditure in the acute phase of aneurysmal subarachnoid hemorrhage. Ups J Med Sci 2019;124. pmid:31847792
- 53. Höllig A, Stoffel-Wagner B, Clusmann H, et al. Time courses of inflammatory markers after aneurysmal subarachnoid hemorrhage and their possible relevance for future studies. Front Neurol 2017;8. pmid:29312122
- 54. Muñoz-Cánoves P, Scheele C, Pedersen BK, et al. Interleukin-6 myokine signaling in skeletal muscle: A double-edged sword? FEBS J. 2013;280. pmid:23663276
- 55. Onodera H, Mogamiya T, Matsushima S, et al. High protein intake after subarachnoid hemorrhage improves oral intake and temporal muscle volume. Clin Nutr 2021;40. pmid:33622572