Computed tomography-defined low skeletal muscle mass as a prognostic marker for short-term mortality in critically ill patients: A systematic review and meta-analysis

Skeletal Muscle Mass Assessment in Pediatric Patients: Development of a Normative Equation and Assessment of Factors Associated With a Low Skeletal Muscle Mass in PICU Patients

OBJECTIVES

To develop an equation for defining a low skeletal muscle mass (SMM) in children and to investigate risk factors and outcomes associated with low SMM in critically ill pediatric patients.

DESIGN

Single-center retrospective pediatric cohorts, 2011-2018.

SETTING

Tertiary Emergency and Critical Care Center of Kyushu University Hospital in Japan.

PATIENTS

We studied two cohorts of pediatric patients 1-15 years old who underwent abdominal CT at the level of the third lumbar vertebra (L3). First a cohort of trauma patients presented to the emergency department in whom we developed an SMM regression equation. Second, a cohort of patients who had undergone abdominal CT within 3 days of PICU admission.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The equation for estimating normal SMM used sex, age, and weight. Low SMM was defined as less than 80% of normal. In the 112 patients in the PICU cohort, median (range) age was 68 (13-191) months, and 83 (74.1%) had underlying disease. There was low SMM in 54 patients (48.2%). Regarding associations, using odds ratio (OR) and 95% CI, we found that low dietary intake (OR 4.33 [95% CI, 1.37-13.70]; p = 0.013) and the presence of underlying disease (OR 7.44 [95% CI, 2.10-26.30]; p = 0.002) were independently associated with greater odds of low SMM. Low SMM, compared with normal SMM, was also associated with longer hospital stays (42.5 d vs. 20.5 d; p = 0.007; β, 1.59; 95% CI, 1.09-2.33; p = 0.016).

CONCLUSIONS

In this retrospective PICU cohort from a single center in Japan, we found that low SMM at PICU admission was present in almost half the cases. Low SMM, as defined by being less than 80% of the normal, was associated with greater odds of low dietary intake and underlying chronic disease. Furthermore, low SMM was associated with longer hospital stays.

Myosteatosis predicts short-term mortality in patients with COVID-19: A multicenter analysis

OBJECTIVES

Body composition on computed tomography can predict prognosis in patients with COVID-19. The reported data are based on small retrospective studies. The aim of the present study was to analyze the prognostic relevance of skeletal muscle parameter derived from chest computed tomography for prediction of 30-d mortality in patients with COVID-19 in a multicenter setting.

METHODS

The clinical databases of three centers were screened for patients with COVID-19 between 2020 and 2022. Overall, 447 patients (142 female; 31.7%) were included into the study. The mean age at the time of computed tomography acquisition was 63.8 ± 14.7 y and median age was 65 y. Skeletal muscle area and skeletal muscle density were defined on level T12 of the chest.

RESULTS

Overall, 118 patients (26.3%) died within the 30-d observation period. Of the patient sample, 255 patients (57.0%) were admitted to an intensive care unit and 122 patients needed mechanical ventilation (27.3%). The mean skeletal muscle area of all patients was 96.1 ± 27.2 cm² (range = 23.2-200.7 cm²). For skeletal muscle density, the mean was 24.3 ± 11.1 Hounsfield units (range = -5.6 to 55.8 Hounsfield units). In survivors, the mean skeletal muscle density was higher compared with the lethal cases (mean 25.8 ± 11.2 versus 20.1 ± 9.6; P < 0.0001). Presence of myosteatosis was independently associated with 30-d mortality: odds ratio = 2.72 (95% CI, 1.71-4.32); P = 0.0001.

CONCLUSIONS

Myosteatosis is strongly associated with 30-d mortality in patients COVID-19. Patients with COVID-19 with myosteatosis should be considered a risk group.

Derivation of the Screening of Nutritional Risk in Intensive Care risk prediction score: A secondary analysis of a prospective cohort study

BACKGROUND

For patients who are critically ill, the recommended nutrition risk screening tools are the Nutrition Risk in the Critically Ill (NUTRIC) and the Nutritional Risk Screening 2002 (NRS-2002) have limitations.

OBJECTIVE

To develop a new screening tool, the Screening of Nutritional Risk in Intensive Care (SCREENIC score), and assess its predictive validity.

METHODS

A secondary analysis of a prospective cohort study was conducted. Variables from several nutritional screening and assessment tools were considered. The high nutrition risk cutoff point was defined using mNUTRIC as a reference. Predictive validity was evaluated using logistic regression and Cox regression.

RESULTS

The study included 450 patients (64 [54-71] years, 52.2% men). The SCREENIC score comprised six questions: (1) does the patient have ≥2 comorbidities (1.3 points); (2) was the patient hospitalized for ≥2 days before intensive care unit (ICU) admission (0.9 points); (3) does the patient have sepsis (1.0 point); (4) was the patient on mechanical ventilation upon ICU admission (1.2 points); (5) is the patient aged >65 years (1.2 points); and (6) does the patient exhibit signs of moderate/severe muscle mass loss according to the physical exam (0.6 points). The high nutrition risk cutoff point was set at 4.0. SCREENIC demonstrated moderate agreement (κ = 0.564) and high accuracy (0.896 [95% CI, 0.867-0.925]) with mNUTRIC. It predicted prolonged ICU (odds ratio [OR] = 1.81 [95% CI, 1.14-2.85]) and hospital stay (OR = 2.15 [95% CI, 1.37-3.38]).

CONCLUSION

The SCREENIC score comprises questions with variables that do not require nutrition history. Further evaluation of its applicability, reproducibility, and validity in guiding nutrition therapy is needed using large external cohorts.

The Association between the L3 Skeletal Muscle Index Derived from Computed Tomography and Clinical Outcomes in Patients with Urinary Tract Infection in the Emergency Department

The occurrence of a critical event during a urinary tract infection (UTI) can have a significant impact on mortality. This study aimed to investigate the association between the skeletal muscle index (SMI) and critical events in patients with a UTI. From April 2019 to March 2022, a total of 478 patients who met the diagnostic criteria of a UTI and underwent an abdominal CT were included in this study. Multivariate binary logistic regression analysis was used to assess independent predictors of critical events. The primary outcome was any critical event, defined as the initiation of dialysis, invasive ventilation, initiation of vasoactive medications, cardiac arrest, or death. The UTI patients were divided into two groups: those with a low SMI (n = 93) and those with a high SMI (n = 385). In multivariate analysis, a low SMI, diabetes mellitus, altered mentality, lactate levels, and creatinine levels were identified as significant predictors of critical events. A low SMI is an independent factor associated with the occurrence of critical events in UTI patients during hospitalization. Patients with a low SMI, indicating muscle wasting, may have less resilience to infections and a higher risk of experiencing severe complications. Considering the SMI along with other clinical factors can help health care providers assess and manage UTI patients.

Prevalence and mortality risk of low skeletal muscle mass in critically ill patients: an updated systematic review and meta-analysis

Background

Patients with critical illness often develop low skeletal muscle mass (LSMM) for multiple reasons. Numerous studies have explored the association between LSMM and mortality. The prevalence of LSMM and its association with mortality are unclear. This systematic review and meta-analysis was performed to examine the prevalence and mortality risk of LSMM among critically ill patients.

Methods

Three internet databases (Embase, PubMed, and Web of Science) were searched by two independent investigators to identify relevant studies. A random-effects model was used to pool the prevalence of LSMM and its association with mortality. The GRADE assessment tool was used to assess the overall quality of evidence.

Results

In total, 1,582 records were initially identified in our search, and 38 studies involving 6,891 patients were included in the final quantitative analysis. The pooled prevalence of LSMM was 51.0% [95% confidence interval (CI), 44.5-57.5%]. The subgroup analysis showed that the prevalence of LSMM in patients with and without mechanical ventilation was 53.4% (95% CI, 43.2-63.6%) and 48.9% (95% CI, 39.7-58.1%), respectively (P-value for difference = 0.44). The pooled results showed that critically ill patients with LSMM had a higher risk of mortality than those without LSMM, with a pooled odds ratio of 2.35 (95% CI, 1.91-2.89). The subgroup analysis based on the muscle mass assessment tool showed that critically ill patients with LSMM had a higher risk of mortality than those with normal skeletal muscle mass regardless of the different assessment tools used. In addition, the association between LSMM and mortality was statistically significant, independent of the different types of mortality.

Conclusion

Our study revealed that critically ill patients had a high prevalence of LSMM and that critically ill patients with LSMM had a higher risk of mortality than those without LSMM. However, large-scale and high-quality prospective cohort studies, especially those based on muscle ultrasound, are required to validate these findings.

Systematic review registration

http://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42022379200.

CT-defined pectoralis muscle mass and muscle density are associated with mortality in acute pulmonary embolism. A multicenter analysis

BACKGROUND & AIMS

Computed tomography (CT) defined muscle mass can be used as a surrogate parameter for sarcopenia. The present study used thoracic CT to assess pectoralis muscle area and density as an imaging biomarker for prognosis of 30-day mortality in patients with acute pulmonary embolism (PE) METHODS: The clinical database was retrospectively screened for patients with thoracic CT in 3 centers. Pectoralis musculature was measured on axial slices of the thoracic CT at the level of T4 of contrast enhanced pulmonary angiography CT. Skeletal muscle area (SMA), skeletal muscle index (SMI), muscle density and gauge were calculated.

RESULTS

Overall, 981 patients (440 female, 44.9%) with a mean age of 63.5 ± 15.9 years were included into the study and 144 patients (14.6%) died within the 30-days period. Every pectoral muscle value was higher in survivors compared to non-survivors (exemplarily for SMI 9.9 ± 3.5 cm²/m² versus 7.8 ± 2.6 cm²/m², p < 0.001). Moreover, 91 patients were defined as hemodynamically instable (9.3%). Comparable, every pectoral muscle parameter was higher in patients with hemodynamically stable course compared to instable course. Different muscle variables are related to 30-day mortality: SMA, OR = 0.94 (95%CI= (0.92; 0.96), p < 0.001); SMI, OR = 0.78 (95%CI= (0.72; 0.84), p < 0.001); muscle density, OR = 0.96 (95%CI = (0.94; 0.97), p < 0.001); muscle gauge OR = 0.96 (95%CI = (0.94; 0.99), p < 0.001). SMI and muscle density were independently associated with 30-days mortality: SMI, OR = 0.81 (95%CI = (0.75; 0.88), p < 0.001); muscle density: OR = 0.96 (95%CI= (0.95; 0.98), p < 0.001).

CONCLUSION

Parameters of the pectoralis musculature are associated with 30-day mortality in patients with acute PE. These findings should lead to an independent validation study and ultimately to the inclusion into clinical routine as a prognostic factor.

Prognostic Role of the Pectoralis Musculature in Patients with COVID-19. A Multicenter Study

RATIONALE AND OBJECTIVES

To evaluate the impact of low skeletal muscle mass in patients with COVID-19 on relevant outcomes like 30-day mortality, need for intubation and need for intensive care unit admission.

MATERIALS AND METHODS

For this study, data from six centers were acquired. The acquired sample comprises 1138 patients. There were 547 women (48.1%) and 591 men (51.9%) with a mean age of 54.5 ± 18.8 years; median age, 55 years; range, 18-84 years). In every case, thoracic CT without intravenous application of contrast medium was performed. The following parameters of the pectoralis muscles were estimated: muscle area as a sum of the bilateral areas of the pectoralis major and minor muscles, muscle density, muscle index (PMI) (pectoralis muscle area divided by the patient's body height square) as a ratio pectoralis major and minor muscles divided by the patient's body height², and muscle gauge as PMI x muscle density.

RESULTS

Overall, 220 patients (19.33%) were admitted to the intensive care unit. In 171 patients (15.03%), mechanical lung ventilation was performed. Finally, 154 patients (13.53%) died within the observation time of 30-day. All investigated parameters of pectoralis muscle were lower in the patients with unfavorable courses of Covid-19. All pectoralis muscle parameters were associated with 30-day mortality in multivariate analyses adjusted for age and sex: pectoralis muscle area, HR = 0.93 CI 95% (0.91-0.95) p < 0.001; pectoralis muscle density, HR = 0.94 CI 95% (0.93-0.96) p < 0.001; pectoralis muscle index, HR = 0.79 CI 95% (0.75-0.85) p < 0.001, pectoralis muscle gauge, HR = 0.995 CI 95% (0.99-0.996) p < 0.001.

CONCLUSION

in COVID-19, survivors have larger areas and higher index, gauge and density of the pectoralis muscles in comparison to nonsurvivors. However, the analyzed muscle parameters cannot be used for prediction of disease courses.

Factors associated with mortality in hospitalised, non-severe, older COVID-19 patients - the role of sarcopenia and frailty assessment

BACKGROUND

COVID-19 has affected older persons the most. The propensity to have severe COVID-19 or die of the infection was especially prevalent among older subjects with multimorbidity, frailty and sarcopenia. The aim of our study was to check which of the simple clinical biomarkers, including the assessment of muscle and frailty, would associate with the survival and the length of hospital stay in older patients with COVID-19. An additional aim was to report the influence of chronic diseases, chronic medication use, and COVID-19 signs and symptoms on the aforementioned outcome measures.

METHODS

The CRACoV study was a prospective single-center (University Hospital in Krakow, Krakow, Poland) observational study of clinical outcomes in symptomatic COVID-19 patients that required hospital treatment. We analysed data of persons aged ≥ 65 years. We assessed muscular parameters in accordance with EWGSOP2, frailty with the Rockwood Clinical Frailty Scale. We used the data of the initial and 3-month assessment. Demographic characteristics, past medical history, and baseline laboratory values were gathered as a part of routine care. We calculated sex and age, and additionally number-of-diseases adjusted odds ratios of mortality associated with studied factors and betas of the relation with these factors and the length of hospital stay.

RESULTS

The mean (standard deviation, SD) age of 163 participants (44.8% women, 14.8% died) was 71.8 (5.6) years, age range 65-89 years. One score greater SARC-F was associated with 34% (p = 0.003) greater risk of death, and 16.8 h longer hospital stay (p = 0.01). One score greater Rockwood was associated with 86% (p = 0.002) greater risk of death, but was unrelated to the length of hospital stay. Hand grip strength and dynapenia were unrelated to mortality, but dynapenia was related to longer hospital stay. Probable sarcopenia was associated with 441% (p = 0.01) greater risk of death.

CONCLUSIONS

In conclusion, the patient assessment with SARC-F and the Rockwood Clinical Frailty Scale may significantly improve the prediction of outcomes in older patients with COVID-19 and by extension might be of use in other acute severe infections. This, however, requires further research to confirm.

Low muscle mass in COVID-19 critically-ill patients: Prognostic significance and surrogate markers for assessment

INTRODUCTION

Low muscle mass is a common condition in the critically ill population and is associated with adverse clinical outcomes. The primary aim of this study was to analyze the prognostic significance of low muscle mass using computed tomography (CT) scans in COVID-19 critically ill patients. A second objective was to determine the accuracy and agreement in low muscle mass identification using diverse markers compared to CT as the gold standard.

METHODS

This was a prospective cohort study of COVID-19 critically ill patients. Skeletal muscle area at the third lumbar vertebra was measured. Clinical outcomes (intensive care unit [ICU] and hospital length of stay [LOS], tracheostomy, days on mechanical ventilation [MV], and in-hospital mortality) were assessed. Phase angle, estimated fat-free mass index, calf circumference, and mid-upper arm circumference were measured as surrogate markers of muscle mass.

RESULTS

Eighty-six patients were included (mean age ± SD: 48.6 ± 12.9; 74% males). Patients with low muscle mass (48%) had a higher rate of tracheostomy (50 vs 20%, p = 0.01), prolonged ICU (adjusted HR 0.53, 95%CI 0.30-0.92, p = 0.024) and hospital LOS (adjusted HR 0.50, 95% CI 0.29-0.86, p = 0.014). Bedside markers of muscle mass showed poor to fair agreement and accuracy compared to CT-assessed low muscle mass.

CONCLUSION

Low muscle mass at admission was associated with prolonged length of ICU and hospital stays. Further studies are needed to establish targeted nutritional interventions to halt and correct the catabolic impact of COVID-19 in critically ill patients, based on standardized and reliable measurements of body composition.

Current practice and barriers in the implementation of ultrasound-based assessment of muscle mass in Japan: A nationwide, web-based cross-sectional study

Muscle mass is an important factor for surviving an illness. Ultrasound has gained increased attention as a muscle mass assessment method because of its noninvasiveness and portability. However, data on the frequency of ultrasound-based muscle mass assessment are limited, and there are some barriers to its implementation. Hence, a web-based cross-sectional survey was conducted on healthcare providers in Japan, which comprised four parts: 1) participant characteristics; 2) general muscle mass assessment; 3) ultrasound-based muscle mass assessment; and 4) the necessity of, interest in, and barriers to its implementation. Necessity and interest were assessed using an 11-point Likert scale, whereas barriers were assessed using a 5-point Likert scale, in which “Strongly agree” and “Agree” were counted for the analysis. Of the 1,058 responders, 1,026 participants, comprising 282 physicians, 489 physical therapists, 84 occupational therapists, 120 nurses, and 51 dieticians, were included in the analysis. In total, 93% of the participants were familiar with general muscle mass assessment, and 64% had conducted it. Ultrasound-based muscle mass assessment was performed by 21% of the participants. Necessity and interest scored 7 (6–8) and 8 (7–10), respectively for ultrasound-based muscle mass assessment. The barriers to its implementation included lack of relevant education (84%), limited staff (61%), and absence of fixed protocol (61%). Regardless of the necessity of and interest in ultrasound-based muscle mass assessment, it was only conducted by one-fifth of the healthcare providers, and the most important barrier to its implementation was lack of education.

Prevalence of Sarcopenia in Patients With COVID-19: A Systematic Review and Meta-Analysis

Background

It has been speculated that patients with sarcopenia are aggravated by the current novel coronavirus disease 2019 (COVID-19) epidemic. However, there is substantial uncertainty regarding the prevalence of sarcopenia in patients with COVID-19.

Objectives

The purpose of the study was to systematically evaluate the prevalence of sarcopenia in patients with COVID-19, including stratification by gender, study location, study population, study design, and diagnostic criteria.

Design

This is the systematic literature review and meta-analysis.

Methods

An electronic search was performed in MEDLINE/PubMed, Embase, Cochrane Library, and Web of Science and Scopus to identify observational studies reporting a prevalence estimate for sarcopenia in patients with COVID-19. Studies were reviewed in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines and a meta-analysis was performed. Risk of bias (RoB) was assessed using the Newcastle–Ottawa Scale (NOS) for cohort studies and Joanna Briggs Institute (JBI) manual for cross-sectional studies, and Stata 14.0 was used to perform meta-analyses.

Results

A total of 4,639 studies were initially identified. After removing the duplicates and applying the selection criteria, we reviewed 151 full-text studies. A total of 21 studies, including 5,407 patients, were eligible for inclusion in this review finally. The prevalence of sarcopenia in patients with COVID-19 in individual studies varied from 0.8 to 90.2%. The pooled prevalence of sarcopenia in COVID-19 was 48.0% (95% confidence interval, CI: 30.8 to 65.1%, I² = 99.68%, p = 0.000). We did not find any significant differences in the prevalence estimates between gender specificity (OR = 1.34; 95% CI = 0.80–2.26; p = 0.001). By sex, the prevalence was 42.5% (95% CI: 31.7 to 53.4%) in men and 35.7% (95% CI: 24.2 to 47.2%) in women. The prevalence estimates significantly varied based on population settings and different diagnostic criteria of sarcopenia. ICU patients (69.7, 95% CI: 51.7 to 85.2%) were more likely to suffer from sarcopenia compared to other population settings.

Conclusion

To our knowledge, this is the first meta-analysis reporting on the prevalence of sarcopenia in patients with COVID-19. Sarcopenia is frequently observed in patients with COVID-19, with varying prevalence across population settings. This study would be useful for clinicians to prompt the increasing awareness of identifying sarcopenia and developing interventions at patients with COVID-19 with high risk of sarcopenia. Further prospective longitudinal studies to define the association of sarcopenia and its prognostic outcomes in COVID-19 survivors are urgently needed to propose the most appropriate treatment strategies during their admission and discharge.

Systematic Review Registration

[www.crd.york.ac.uk/prospero/], identifier [CRD42022300431].

Prevalence and prognostic value of preexisting sarcopenia in patients with mechanical ventilation: a systematic review and meta-analysis

Background

Sarcopenia is defined as age-related loss of muscle mass, strength, and/or function in the context of aging. Mechanical ventilation (MV) is one of the most frequently used critical care technologies in critically ill patients. The prevalence of preexisting sarcopenia and the clinical impact of its prognostic value on patients with MV are unclear. This review sought to identify the prevalence and prognostic value of preexisting sarcopenia on MV patient health outcomes.

Methods

Relevant studies were identified by searching MEDLINE, Embase, and the Cochrane library and were searched for all articles published as of December 2021. The prevalence of sarcopenia was determined using the authors' definitions from the original studies. Comparisons were made between patients who did and did not have sarcopenia for prognostic outcomes, including mortality, the number of days of MV, the length of intensive care unit stay, and the length of hospital stay. Odds ratios (ORs) and weighted mean differences with 95% confidence intervals (CIs) were used for pooled analyses of the relationships between sarcopenia and prognostic outcomes.

Results

The initial search identified 1333 studies, 17 of which met the eligibility criteria for the quantitative analysis, including 3582 patients. The pooled prevalence was 43.0% (95% CI 34.0–51.0%; I² = 96.7%). The pooled analyses showed that sarcopenia was related to increased mortality (OR 2.13; 95% CI 1.70, 2.67; I² = 45.0%), longer duration of MV (MD = 1.22; 95% CI 0.39, 2.05; I² = 97.0%), longer days of ICU stay (MD = 1.31; 95% CI 0.43, 2.19; I² = 97.0%), and hospital stay (MD 2.73; 95% CI 0.58, 4.88; I² = 98.0%) in patients with MV.

Conclusion

The prevalence of sarcopenia is relatively high in patients with MV, and it will have a negative impact on the prognosis of patients. However, further, large-scale, high-quality prospective cohort studies are required.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13054-022-04015-y.

Computed tomography-defined body composition as prognostic markers for unfavourable outcomes and in-hospital mortality in coronavirus disease 2019

BACKGROUND

Low skeletal muscle mass (LSMM) and visceral fat areas can be assessed by cross-sectional images. These parameters are associated with several clinically relevant factors in various disorders with predictive and prognostic implications. Our aim was to establish the effect of computed tomography (CT)-defined LSMM and fat areas on unfavourable outcomes and in-hospital mortality in coronavirus disease 2019 (COVID-19) patients based on a large patient sample.

METHODS

MEDLINE library, Cochrane, and Scopus databases were screened for the associations between CT-defined LSMM as well as fat areas and in-hospital mortality in COVID-19 patients up to September 2021. In total, six studies were suitable for the analysis and included into the present analysis.

RESULTS

The included studies comprised 1059 patients, 591 men (55.8%) and 468 women (44.2%), with a mean age of 60.1 years ranging from 48 to 66 years. The pooled prevalence of LSMM was 33.6%. The pooled odds ratio for the effect of LSMM on in-hospital mortality in univariate analysis was 5.84 [95% confidence interval (CI) 1.07-31.83]. It was 2.73 (95% CI 0.54-13.70) in multivariate analysis. The pooled odds ratio of high visceral fat area on unfavourable outcome in univariate analysis was 2.65 (95% CI 1.57-4.47).

CONCLUSIONS

Computed tomography-defined LSMM and high visceral fat area have a relevant association with in-hospital mortality in COVID-19 patients and should be included as relevant prognostic biomarkers into clinical routine.