Low skeletal muscle mass defined by thoracic CT as a prognostic marker in acute pulmonary embolism

Meyer, Hans‐Jonas; Benkert, Franz; Bailis, Nikolaos; Lerche, Marianne; Denecke, Timm; Surov, Alexey

doi:10.1016/j.nut.2022.111622

Cited by 7 publications

(17 citation statements)

References 23 publications

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“…The impact of sarcopenia on PE and PE mortality Meyer et al 23 investigated the potential role that the low skeletal muscle mass (LSMM) diagnosed by thoracic computed tomography (CT) may have for prognosis and the prediction of the mortality risk concerning cases of acute PE. They retrospectively screened the clinical database of their department for subjects who sustained acute PE between 2013 and 2017.…”

Section: Resultsmentioning

confidence: 99%

“…They retrospectively screened the clinical database of their department for subjects who sustained acute PE between 2013 and 2017. A total of 234 patients were included in the study 23 . To assess the muscle mass status and the potential sarcopenia existence, they used contrast-enhanced pulmonary angiography thoracic CT to evaluate axial slides at the thoracic vertebra 5 (Th5) level 23 .…”

Section: Resultsmentioning

confidence: 99%

“…A total of 234 patients were included in the study 23 . To assess the muscle mass status and the potential sarcopenia existence, they used contrast-enhanced pulmonary angiography thoracic CT to evaluate axial slides at the thoracic vertebra 5 (Th5) level 23 . They calculated the skeletal muscle index (SMI) by adjusting the muscle area to the subject's height.…”

Section: Resultsmentioning

confidence: 99%

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Pulmonary embolism and sarcopenia: The potential interplay

Karakousis,

Gourgoulianis,

Kotsiou

2024

Pneumon

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INTRODUCTIONDeep vein thrombosis (DVT) and pulmonary embolism (PE) compose venous thromboembolism (VTE) 1,2 . PE is recorded as the third most frequent cause of cardiovascular death globally, after stroke and heart attack 3 . It is already recorded that most PE cases derive from DVT of the lower extremities, and almost 50% of DVT cases may cause silent PE 3 . Moreover, it has been demonstrated that PE is responsible for death in nearly 5% to 10% of hospitalized subjects 3 . Entities that could obstruct the pulmonary arteries might be tumors, clots, fat, or air, and everything that leads to this obstruction could be considered as PE 3 .It is well-established that VTE and atherothrombosis may have common risk factors and pathophysiology profile, including inflammation, endothelial injury and hypercoagulability 1 . In addition, VTE is a clinical condition that could reinforce a pan-vascular syndrome that might consist of coronary artery disease, cerebrovascular disease, and peripheral arterial disease, while risk factors for VTE, including hypertension, diabetes mellitus (DM), cigarette smoking, and obesity, may often overlap with risk factors for atherosclerosis 1,4 .Concerning PE, risk factors might be old age (>65 years), long-haul travel, associated with thrombophilia (factor V Leiden or prothrombin gene mutation), hypertension, metabolic syndrome, cigarette smoking, air pollution, obesity, postoperative, immobilization, oral contraceptives, trauma, postmenopausal, hormonal replacement, pregnancy, malignancy, and acute disease such as congestive heart failure and pneumonia 1,5 .Diagnosis and clinical probability assessment of PE consist of tools such as the 'Wells scoring system', the D-dimer test, computed tomography pulmonary angiography (CTPA), and the VQ (ventilation perfusion) scan, are commonly utilized by clinical practitioners and other healthcare professionals to diagnose PE and VTE 1,6,7 .Concerning the management of PE and treatment implementation, primary reperfusion treatment, which usually includes systemic thrombolysis, is the therapy of choice for subjects with increased risk for PE, while surgical pulmonary embolectomy or percutaneous catheter-directed therapy are other reperfusion techniques and choices in subjects who cannot sustain thrombolysis 8,9 . In addition, following reperfusion therapy and hemodynamic stabilization of the patient, subjects recovering from high-risk PE can be redirected from parenteral to oral anticoagulation 8 . In cases of intermediate-risk and low-risk PE, anticoagulant treatment is appropriate 8 .Sarcopenia is a skeletal muscle mass condition that might be progressive and can be related to both skeletal muscle mass and muscle function, associated with many adverse clinical results, such as falls, disability, hospitalizations,

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Pulmonary embolism and sarcopenia: The potential interplay

Karakousis,

Gourgoulianis,

Kotsiou

2024

Pneumon

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“…The topic of body composition is an emerging field of research with extensive studies in various disorders [8][9][10][11][12][13][14][15]. Of note, there are various possible applications and interesting prognostic implications of low-skeletal muscle mass (LSMM) and VAT quantification throughout many fields of clinical care [8][9][10][11][12][13][14][15]. Importantly, these calculations are a by-product of cross-sectional imaging and can easily be estimated in clinical routine.…”

Section: Discussionmentioning

confidence: 99%

“…SMA was calculated on the level L3 including psoas muscle, paraspinal muscles, and the abdominal wall muscles. The muscle area was semiautomatically measured using the HU threshold levels of −29 and 150 HU, as proposed in similar studies [ 12 , 13 ]. The SMA was divided by the height squared to calculate the skeletal muscle index (SMI).…”

Section: Methodsmentioning

confidence: 99%

Computed Tomography-Defined Body Composition as Prognostic Parameter in Acute Mesenteric Ischemia

Schwartner,

Mehdorn,

Gockel

et al. 2023

Dig Surg

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Introduction: Body composition comprising Low-skeletal muscle mass (LSMM) and subcutaneous and visceral adipose tissue (SAT and VAT) can be assessed by using cross-sectional imaging modalities. Aim of this study was to analyze possible associations of body composition parameters on mortality in patients with clinically suspected acute mesenteric ischemia (AMI). Methods: Overall, 137 patients (52 female patients, 37.9%) with a median age of 71 years were included. For all patients, the preoperative abdominal computed tomography (CT) was used to calculate LSMM, VAT and SAT. Results: Overall, 94 patients (68.6%) of the patient cohort died within 30-days within a median of 2 days, range 1-39 days. Of these, 27 patients (19.7%) died within 24-hours. According to the CT, 101 patients (73.7%) were classified as being visceral obese, 102 patients (74.5%) as being sarcopenic, and 69 patients (50.4%) as being sarcopenic obese. Skeletal muscle index (SMI) was lower in non-survivors compared to survivors (37.5 ± 12.4 cm²/m² versus 44.1 ± 13.9 cm²/m², p=0.01). There were no associations between body composition parameters with mortality in days (SMI r=0.07, p=0.48, SAT r=-0.03, p=0.77 and VAT r=0.04, p=0.68, respectively). In Cox regression analysis, a non-significant trend for visceral obesity was observed (HR 0.62, 95%CI 0.36-1.05, p=0.07). Conclusions: SMI might be a valuable CT based parameter, which could help to discriminate between survivors and non-survivors. Further studies are needed to elucidate the associations between body composition and survival in patients with AMI.

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Short‐term mortality prediction in acute pulmonary embolism: Radiomics values of skeletal muscle and intramuscular adipose tissue

Shahzadi,

Zwanenburg,

Frohwein

et al. 2024

J cachexia sarcopenia muscle

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BackgroundAcute pulmonary embolism (APE) is a potentially life‐threatening disorder, emphasizing the importance of accurate risk stratification and survival prognosis. The exploration of imaging biomarkers that can reflect patient survival holds the potential to further enhance the stratification of APE patients, enabling personalized treatment and early intervention. Therefore, in this study, we develop computed tomography pulmonary angiography (CTPA) radiomic signatures for the prognosis of 7‐ and 30‐day all‐cause mortality in patients with APE.MethodsDiagnostic CTPA images from 829 patients with APE were collected. Two hundred thirty‐four features from each skeletal muscle (SM), intramuscular adipose tissue (IMAT) and both tissues combined (SM + IMAT) were calculated at the level of thoracic vertebra 12. Radiomic signatures were derived using 10 times repeated three‐fold cross‐validation on the training data for SM, IMAT and SM + IMAT for predicting 7‐ and 30‐day mortality independently. The performance of the radiomic signatures was then evaluated on held‐out test data and compared with the simplified pulmonary embolism severity index (sPESI) score, a well‐established biomarker for risk stratification in APE. Predictive accuracy was assessed by the area under the receiver operating characteristic curve (AUC) with a 95% confidence interval (CI), sensitivity and specificity.ResultsThe radiomic signatures based on IMAT and a combination of SM and IMAT (SM + IMAT) achieved moderate performance for the prediction of 30‐day mortality on test data (IMAT: AUC = 0.68, 95% CI [0.57–0.78], sensitivity = 0.57, specificity = 0.73; SM + IMAT: AUC = 0.70, 95% CI [0.60–0.79], sensitivity = 0.74, specificity = 0.54). Radiomic signatures developed for predicting 7‐day all‐cause mortality showed overall low performance. The clinical signature, that is, sPESI, achieved slightly better performance in terms of AUC on test data compared with the radiomic signatures for the prediction of both 7‐ and 30‐day mortality on the test data (7 days: AUC = 0.73, 95% CI [0.67–0.79], sensitivity = 0.92, specificity = 0.16; 30 days: AUC = 0.74, 95% CI [0.66–0.82], sensitivity = 0.97, specificity = 0.16).ConclusionsWe developed and tested radiomic signatures for predicting 7‐ and 30‐day all‐cause mortality in APE using a multicentric retrospective dataset. The present multicentre work shows that radiomics parameters extracted from SM and IMAT can predict 30‐day all‐cause mortality in patients with APE.

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Low skeletal muscle mass defined by thoracic CT as a prognostic marker in acute pulmonary embolism

Cited by 7 publications

References 23 publications

Pulmonary embolism and sarcopenia: The potential interplay

Pulmonary embolism and sarcopenia: The potential interplay

Computed Tomography-Defined Body Composition as Prognostic Parameter in Acute Mesenteric Ischemia

Short‐term mortality prediction in acute pulmonary embolism: Radiomics values of skeletal muscle and intramuscular adipose tissue

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