Sarcopenia diagnosed using masseter muscle area predictive of early mortality following severe traumatic brain injury

Using magnetic resonance imaging to measure head muscles: An innovative method to opportunistically determine muscle mass and detect sarcopenia

BACKGROUND

Sarcopenia is associated with multiple adverse outcomes. Traditional methods to determine low muscle mass for the diagnosis of sarcopenia are mainly based on dual-energy X-ray absorptiometry (DXA), whole-body magnetic resonance imaging (MRI) and bioelectrical impedance analysis. These tests are not always available and are rather time consuming and expensive. However, many brain and head diseases require a head MRI. In this study, we aim to provide a more accessible way to detect sarcopenia by comparing the traditional method of DXA lean mass estimation versus the tongue and masseter muscle mass assessed in a standard brain MRI.

METHODS

The H70 study is a longitudinal study of older people living in Gothenburg, Sweden. In this cross-sectional analysis, from 1203 participants aged 70 years at baseline, we included 495 with clinical data and MRI images available. We used the appendicular lean soft tissue index (ALSTI) in DXA images as our reference measure of lean mass. Images from the masseter and tongue were analysed and segmented using 3D Slicer. For the statistical analysis, the Spearman correlation coefficient was used, and concordance was estimated with the Kappa coefficient.

RESULTS

The final sample consisted of 495 participants, of which 52.3% were females. We found a significant correlation coefficient between both tongue (0.26) and masseter (0.33) with ALSTI (P < 0.001). The sarcopenia prevalence confirmed using the alternative muscle measure in MRI was calculated using the ALSTI (tongue = 2.0%, masseter = 2.2%, ALSTI = 2.4%). Concordance between sarcopenia with masseter and tongue versus sarcopenia with ALSTI as reference has a Kappa of 0.989 (P < 0.001) for masseter and a Kappa of 1 for the tongue muscle (P < 0.001). Comorbidities evaluated with the Cumulative Illness Rating Scale were significantly associated with all the muscle measurements: ALSTI (odds ratio [OR] 1.16, 95% confidence interval [CI] 1.07-1.26, P < 0.001), masseter (OR 1.16, 95% CI 1.07-1.26, P < 0.001) and tongue (OR 1.13, 95% CI 1.04-1.22, P = 0.002); the higher the comorbidities, the higher the probability of having abnormal muscle mass.

CONCLUSIONS

ALSTI was significantly correlated with tongue and masseter muscle mass. When performing the sarcopenia diagnostic algorithm, the prevalence of sarcopenia calculated with head muscles did not differ from sarcopenia calculated using DXA, and almost all participants were correctly classified using both methods.

Feasibility of using cross-sectional area of masticatory muscles to predict sarcopenia in healthy aging subjects

Determination of sarcopenia is crucial in identifying patients at high risk of adverse health outcomes. Recent studies reported a significant decline in masticatory muscle (MM) function in patients with sarcopenia. This study aimed to analyze the cross-sectional area (CSA) of MMs on computed tomography (CT) images and to explore their potential to predict sarcopenia. The study included 149 adult subjects retrospectively (59 males, 90 females, mean age 57.4 ± 14.8 years) who underwent head and neck CT examination for diagnostic purposes. Sarcopenia was diagnosed on CT by measuring CSA of neck muscles at the C3 vertebral level and estimating skeletal muscle index. CSA of MMs (temporal, masseter, medial pterygoid, and lateral pterygoid) were measured bilaterally on reference CT slices. Sarcopenia was diagnosed in 67 (45%) patients. Univariate logistic regression analysis demonstrated a significant association between CSA of all MMs and sarcopenia. In the multivariate logistic regression model, only masseter CSA, lateral pterygoid CSA, age, and gender were marked as predictors of sarcopenia. These parameters were combined in a regression equation, which showed excellent sensitivity and specificity in predicting sarcopenia. The masseter and lateral pterygoid CSA can be used to predict sarcopenia in healthy aging subjects with a high accuracy.

Temporalis and masseter muscle thickness as predictors of post-stroke dysphagia after endovascular thrombectomy

PURPOSE

Post-stroke dysphagia (PSD) is a common sequela of stroke. Given the association between dysphagia and sarcopenia, we aimed to investigate the association between PSD and temporal muscle thickness (TMT) and masseter muscle thickness (MMT) following endovascular thrombectomy (EVT) in patients with large-vessel occlusion (LVO).

METHODS

This retrospective cohort study included hospitalized patients with LVO stroke who underwent EVT between January 1, 2018, and October 31, 2022. TMT and MMT were measured using brain computed tomography (CT) angiography. The correlation between relevant clinicodemographic factors and both TMT and MMT was examined. The relationship between each of two parameters (TMT and MMT) and PSD, which was defined as the retention of the nasogastric (NG) tube at 4 and 12 weeks, was evaluated in adjusted logistic regression models.

RESULTS

Among the 148 participants, the mean TMT and MMT was 5.9 ± 1.6 and 11.2 ± 2.3 mm, respectively. Lower age, male sex, higher body mass index (BMI), higher albumin levels, and a lower initial National Institute of Health Stroke Scale (NIHSS) score were associated with higher TMT and MMT (p < 0.05). In the logistic regression analysis adjusted for age, sex, BMI, serum albumin, and NIHSS score, lower TMT and MMT significantly correlated with PSD at weeks 4 and 12 (p < 0.001).

CONCLUSION

TMT and MMT are associated with age, sex, BMI, albumin, and the initial NIHSS score. Both TMT and MMT are independent indicators of post-EVT PSD in stroke patients and serve as reliable predictors of NG removal.

Use of Facial Morphology to Determine Nutritional Status in Older Adults: Opportunities and Challenges

Undiagnosed malnutrition is a significant problem in high-income countries, which can reduce the quality of life of many individuals, particularly of older adults. Moreover, it can also inflate the costs of existing health care systems because of the many metabolic complications that it can cause. The current methods for assessing malnutrition can be cumbersome. A trained practitioner must be present to conduct an assessment, or patients must travel to facilities with specialized equipment to obtain their measurements. Therefore, digital health care is a possible way of closing this gap as it is rapidly gaining traction as a scalable means of improving efficiency in the health care system. It allows for the remote monitoring of nutritional status without requiring the physical presence of practitioners or the use of advanced medical equipment. As such, there is an increasing interest in expanding the range of digital applications to facilitate remote monitoring and management of health issues. In this study, we discuss the feasibility of a novel digital remote method for diagnosing malnutrition using facial morphometrics. Many malnutrition screening assessments include subjective assessments of the head and the face. Facial appearance is often used by clinicians as the first point of qualitative indication of health status. Hence, there may be merit in quantifying these subtle but observable changes using facial morphometrics. Modern advancements in artificial intelligence, data science, sensors, and computing technologies allow facial features to be accurately digitized, which could potentially allow these previously intuitive assessments to be quantified. This study aims to stimulate further discussion and discourse on how this emerging technology can be used to provide real-time access to nutritional status. The use of facial morphometrics extends the use of currently available technology and may provide a scalable, easily deployable solution for nutritional status to be monitored in real time. This will enable clinicians and dietitians to keep track of patients remotely and provide the necessary intervention measures as required, as well as providing health care institutions and policy makers with essential information that can be used to inform and enable targeted public health approaches within affected populations.

Brain CT can predict low lean mass in the elderly with cognitive impairment: a community-dwelling study

Background

The coexistence of sarcopenia and dementia in aging populations is not uncommon, and they may share common risk factors and pathophysiological pathways. This study aimed to evaluate the relationship between brain atrophy and low lean mass in the elderly with impaired cognitive function.

Methods

This cross-sectional study included 168 elderly patients who visited the multi-disciplinary dementia outpatient clinic at Kaohsiung Chang Gung Memorial Hospital for memory issues, between 2017 and 2019. The body composition was assessed by dual energy X-ray absorptiometry (DEXA) and CT based skeletal muscle index including L3 skeletal muscle index (L3SMI) and masseter muscle mass index (MSMI). The brain atrophy assessment was measured by CT based visual rating scale. Possible predictors of low lean mass in the elderly with cognitive impairement were identified by binary logistic regression. ROC curves were generated from binary logistic regression.

Results

Among the 81 participants, 43 (53%) remained at a normal appendicular skeletal muscle index (ASMI), whereas 38 (47%) showed low ASMI. Compared with the normal ASMI group, subjects with low ASMI exhibited significantly lower BMI, L3SMI, and MSMI (all p < 0.05), and showed significant brain atrophy as assessed by visual rating scale (p < 0.001). The accuracy of predictive models for low ASMI in the elderly with cognitive impairment were 0.875, (Area under curve (AUC) = 0.926, 95% confidence interval [CI] 0.844–0.972) in model 1 (combination of BMI, GCA and L3SMI) and 0.885, (Area under curve (AUC) = 0.931, [CI] 0.857–0.979) in model 2 (combination of BMI, GCA and MSMI).

Conclusions

Global cortical atrophy and body mass index combined with either L3 skeletal muscle index or masseter skeletal muscle index can predict low lean mass in the elderly with cognitive impairment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-021-02626-8.

Temporal muscle thickness and area are an independent prognostic factors in patients aged 75 or younger with aneurysmal subarachnoid hemorrhage treated by clipping

BACKGROUND

Skeletal muscle mass is an important factor for various diseases' outcomes. As for its indicators, temporal muscle thickness (TMT) and temporal muscle area (TMA) on the head computed tomography are useful, and TMT and TMA were reported as potential prognostic factors for aneurysmal subarachnoid hemorrhage (SAH). We examined the clinical characteristics, including TMT and TMA, of SAH patients aged 75 or younger.

METHODS

We retrospectively investigated 127 SAH patients with all World Federation of Neurosurgical Societies (WFNS) grades and treated by clipping between 2009 and 2019. Clinical outcome was measured with the modified Rankin Scale (mRS) at 6 months, with favorable outcome defined as mRS 0-2. The associations between the clinical variables and the outcomes were analyzed.

RESULTS

The mean age was 60.6 (32-74) years, and 65% were women. The mean ± standard deviation of WFNS grade was 2.8 ± 1.4. TMT and TMA were larger in the favorable outcome group than the poor one. Multivariate analysis revealed that age, smoking, WFNS grade, and TMT or TMA were associated with favorable outcome. Receiver operating characteristic analysis found that the threshold of TMT was 4.9 mm in female and 6.7 mm in male, and that of TMA was 193 mm2 in female and 333 mm2 in male.

CONCLUSION

The odds ratios for TMT and TMA related to clinical outcome were lower than for smoking and WFNS grade; however, on multivariate analysis they remained independent prognostic factors in SAH patients aged 75 or younger treated by clipping. Further studies are needed to confirm these findings.

Standard values for temporal muscle thickness in the Japanese population who undergo brain check-up by magnetic resonance imaging

BACKGROUND

Skeletal muscle mass is an important factor for various diseases' outcomes. The psoas muscle cross-sectional area on the abdominal computed tomography (CT), gait speed, and handgrip strength is used to measure it. However, it is difficult to measure the neurological patients' muscle mass or function because (1) we do not perform abdominal CT. (2) Such patients have impaired consciousness, gait disturbance, paresis, and need of rest. Temporal muscle thickness (TMT) on magnetic resonance imaging (MRI) is now attractive for skeletal muscle volume indicator, but the reference values are not established. We herein investigated the standard value of the Japanese TMT using the brain check-up database by MRI.

METHODS

We retrospectively investigated 360 Japanese individuals from two institutions between 2017 and 2019. We measured TMT on the T1-weighted images in the previously reported way. The associations between TMT and other variables were analyzed.

RESULTS

TMT of 214 women and 146 men, ranging from 35 to 84 years old, was investigated. TMT ranged from 3.69 to 16.90 mm. Mean TMT values were significantly higher in men compared to women except for the over 70-year-old cohort. TMT was correlated to weight and body mass index in both sexes.

CONCLUSION

This is the first retrospective study on the standard TMT values from the Japanese brain check-up database. Our results were just reference values, but these would be useful for further investigation in other neurosurgical and neurological diseases regarding muscle volume or sarcopenia.

Prospective evaluation and comparison of the predictive ability of different frailty scores to predict outcomes in geriatric trauma patients

BACKGROUND

Different frailty scores have been proposed to measure frailty. No study has compared their predictive ability to predict outcomes in trauma patients. The aim of our study was to compare the predictive ability of different frailty scores to predict complications, mortality, discharge disposition, and 30-day readmission in trauma patients.

METHODS

We performed a 2-year (2016-2017) prospective cohort analysis of all geriatric (age, >65 years) trauma patients. We calculated the following frailty scores on each patient; the Trauma-Specific Frailty Index (TSFI), the Modified Frailty Index (mFI) derived from the Canada Study of Health and Aging, the Rockwood Frailty Score (RFS), and the International Association of Nutrition and Aging 5-item a frailty scale (FS). Predictive models, using both unadjusted and adjusted logistic regressions, were created for each outcome. The unadjusted c-statistic was used to compare the predictive ability of each model.

RESULTS

A total of 341 patients were enrolled. Mean age was 76 ± 9 years, median Injury Severity Score was 13 [9-18], and median Glasgow Coma Scale score was 15 [12-15]. The unadjusted models indicated that both the TSFI and the RFS had comparable predictive value, as indicated by their unadjusted c-statistics, for mortality, in-hospital complications, skilled nursing facility disposition and 30-day readmission. Both TSFI and RFS models had unadjusted c-statistics indicating a relatively strong predictive ability for all outcomes. The unadjusted mFI and FS models did not have a strong predictive ability for predicting mortality and in-hospital complications. They also had a lower predictive ability for skilled nursing facility disposition and 30-day readmissions.

CONCLUSION

There are significant differences in the predictive ability of the four commonly used frailty scores. The TSFI and the RFS are better predictors of outcomes compared with the mFI and the FS. The TSFI is easy to calculate and might be used as a universal frailty score in geriatric trauma patients.

LEVEL OF EVIDENCE

Prognostic, level III.

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

OBJECTIVE

Sarcopenia is defined as the loss of skeletal muscle mass and is considered an important factor for clinical outcomes in various diseases. Recent studies have shown that temporal muscle thickness (TMT) and area (TMA) can be novel indicators of sarcopenia. We examined clinical characteristics, including TMT and TMA, of patients with subarachnoid hemorrhage (SAH) treated by endovascular coiling.

METHODS

A retrospective analysis of 298 patients with SAH who were treated with endovascular coiling from 2009 to 2019 was conducted. Their premorbid modified Rankin Scale (mRS) score was 0-2. The association between the factors and Hunt and Kosnik (H-K) grades on admission and that between the clinical variables and mRS scores 6 months after the operation were analyzed.

RESULTS

In all 298 patients with SAH, Fisher group 4 and TMA <200 mm² were independently associated with H-K grade III-V on admission in the multivariate analysis. In 254 patients with H-K grades I-III on admission, age, H-K grade III, presence of ventriculoperitoneal shunt, presence of postoperative complications, and TMA <200 mm² were independent factors related to poor outcomes in the multivariate analysis.

CONCLUSIONS

The H-K grade on admission was independently associated with TMA. The mRS score 6 months after aneurysm treatment in patients with H-K grades I-III was also independently associated with TMA. Sarcopenia could be one of a few modifiable factors that prevent severe symptoms of SAH and improve outcomes after coiling by strengthened nutrition and physical activity.