Online citations, reference lists, and bibliographies.
Please confirm you are human
(Sign Up for free to never see this)
← Back to Search

Lumbar Skeletal Muscle Index Derived From Routine Computed Tomography Exams Predict Adverse Post‐extubation Outcomes In Critically Ill Patients☆

G. Fuchs, T. Thevathasan, Y. R. Chretien, Julia Mario, Annop Piriyapatsom, U. Schmidt, M. Eikermann, F. Fintelmann
Published 2018 · Medicine

Save to my Library
Download PDF
Analyze on Scholarcy
Purpose: To evaluate the effect of a skeletal muscle index derived from a routine CT image at the level of vertebral body L3 (L3SMI) on outcomes of extubated patients in the surgical intensive care unit. Materials and methods: 231 patients of a prospective observational trial (NCT01967056) who had undergone CT within 5 days of extubation were included. L3SMI was computed using semi‐automated segmentation. Primary outcomes were pneumonia within 30 days of extubation, adverse discharge disposition and 30‐day mortality. Secondary outcomes included re‐intubation within 72 h, total hospital costs, ICU length of stay (LOS), post‐extubation LOS and total hospital LOS. Outcomes were analyzed using multivariable regression models with a priori‐defined covariates height, gender, age, APACHE II score and Charlson Comorbidity Index. Results: L3SMI was an independent predictor of pneumonia (aOR 0.96; 95% CI 0.941–0.986; P = 0.002), adverse discharge disposition (aOR 0.98; 95% CI 0.957–0.999; P = 0.044) and 30‐day mortality (aOR 0.94; 95% CI 0.890–0.995; P = 0.033). L3SMI was significantly lower in re‐intubated patients (P = 0.024). Secondary analyses suggest that L3SMI is associated with total hospital costs (P = 0.043) and LOS post‐extubation (P = 0.048). Conclusion: The lumbar skeletal muscle index, derived from routine abdominal CT, is an objective prognostic tool at the time of extubation. HighlightsLumbar skeletal muscle index is an objective prognostic tool in ICU patients.L3SMI independently predicts pneumonia, adverse discharge and 30‐day mortality.L3SMI can be derived from a single axial CT image with minimal training.Simplified model including only L3SMI and age predicts primary outcomes.CT metrics add clinically useful prognostic information without additional cost.
This paper references
Critical care medicine in the United States 2000–2005: An analysis of bed numbers, occupancy rates, payer mix, and costs*
N. Halpern (2010)
Predictors of extubation outcome in patients who have successfully completed a spontaneous breathing trial.
M. Khamiees (2001)
Acquired Muscle Weakness in the Surgical Intensive Care Unit: Nosology, Epidemiology, Diagnosis, and Prevention
Hassan N Farhan (2016)
Can Sarcopenia Quantified by Ultrasound of the Rectus Femoris Muscle Predict Adverse Outcome of Surgical Intensive Care Unit Patients as well as Frailty? A Prospective, Observational Cohort Study
N. Mueller (2016)
A practical and precise approach to quantification of body composition in cancer patients using computed tomography images acquired during routine care.
M. Mourtzakis (2008)
Acute skeletal muscle wasting in critical illness.
Z. Puthucheary (2013)
NT-proBNP levels at spontaneous breathing trial help in the prediction of post-extubation respiratory distress
L. Ouanes-Besbes (2012)
Involuntary cough strength and extubation outcomes for patients in an ICU.
Wen-lin Su (2010)
Body Composition Assessment in Axial CT Images Using FEM-Based Automatic Segmentation of Skeletal Muscle
K. Popuri (2016)
Sarcopenia is a Predictor of Outcomes in Very Elderly Patients Undergoing Emergency Surgery
Y. Du (2014)
Diaphragmatic dysfunction in patients with ICU-acquired weakness and its impact on extubation failure
B. Jung (2015)
The influence of body composition on respiratory muscle, lung function and diaphragm thickness in adults with cystic fibrosis.
S. Enright (2007)
Pixel-Level Deep Segmentation: Artificial Intelligence Quantifies Muscle on Computed Tomography for Body Morphometric Analysis
Hyunkwang Lee (2017)
Low skeletal muscle area is a risk factor for mortality in mechanically ventilated critically ill patients
P. Weijs (2014)
Sarcopenia and Frailty in Elderly Trauma Patients
B. Fairchild (2014)
Skeletal muscle predicts ventilator-free days, ICU-free days, and mortality in elderly ICU patients
L. Moisey (2013)
Prospective Observational Study of Predictors of Re-Intubation Following Extubation in the Surgical ICU
A. Piriyapatsom (2016)
Development and Validation of a Score for Prediction of Postoperative Respiratory Complications
B. Brueckmann (2013)
Skeletal muscle mass and distribution in 468 men and women aged 18-88 yr.
I. Janssen (2000)
daver validation of skeletal muscle measurement by magnetic resonance imaging and computerized tomography
N Mitsiopoulos (1998)
Nutritional status is an important predictor of diaphragm strength in young patients with cystic fibrosis.
N. Hart (2004)
Muscle Weakness Predicts Pharyngeal Dysfunction and Symptomatic Aspiration in Long-term Ventilated Patients
H. Mirzakhani (2013)
Sarcopenia is highly prevalent in patients undergoing surgery for gastric cancer but not associated with worse outcomes
J. Tegels (2015)
Global Muscle Strength But Not Grip Strength Predicts Mortality and Length of Stay in a General Population in a Surgical Intensive Care Unit
J. Lee (2012)
Risk Factors for and Prediction by Caregivers of Extubation Failure in ICU Patients: A Prospective Study*
A. Thille (2015)
Cost of major surgery in the sarcopenic patient.
K. Sheetz (2013)
Epidemiology of sarcopenia among the elderly in New Mexico.
R. Baumgartner (1998)
Analytic Morphomics, Core Muscle Size, and Surgical Outcomes
M. Englesbe (2012)
Body composition assessment in axial CT images using FEM - based automatic segmentation of skeletal mus
K Popuri (2016)
Functional compromise reflected by sarcopenia, frailty, and nutritional depletion predicts adverse postoperative outcome after colorectal cancer surgery.
K. Reisinger (2015)
APACHE II--a severity of disease classification system.
J. Legall (1986)
Handgrip Strength Predicts Difficult Weaning But Not Extubation Failure in Mechanically Ventilated Subjects
G. Cottereau (2015)
The Long-Term and Post-Acute Care Continuum.
T. H. Goldberg (2016)
Lean Tissue Imaging
C. Prado (2014)
Muscle mass predicts outcomes following liver transplantation
A. Dimartini (2013)
The emerging role of computerized tomography in assessing cancer cachexia
C. Prado (2009)
When is critical care medicine cost-effective? A systematic review of the cost-effectiveness literature*
D. Talmor (2006)
Total body skeletal muscle and adipose tissue volumes: estimation from a single abdominal cross-sectional image.
Wei Shen (2004)
Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases.
R. Deyo (1992)
An international definition for "nursing home".
A. Sanford (2015)
The prevalence of sarcopenia in patients with respiratory failure classified as normally nourished using computed tomography and subjective global assessment.
P. Sheean (2014)
Respiratory muscle strength and maximal voluntary ventilation in undernourished patients.
N. Arora (1982)
Clinical predictive value of manual muscle strength testing during critical illness: an observational cohort study
B. Connolly (2013)
Cadaver validation of skeletal muscle measurement by magnetic resonance imaging and computerized tomography.
N. Mitsiopoulos (1998)
Age-associated changes in skeletal muscles and their effect on mobility: an operational diagnosis of sarcopenia.
F. Lauretani (2003)

This paper is referenced by
Identifying critically ill patients with low muscle mass: Agreement between bioelectrical impedance analysis and computed tomography.
Willem Looijaard (2019)
ROUNDS Studies: Relation of OUtcomes with Nutrition Despite Severity—Round One: Ultrasound Muscle Measurements in Critically Ill Adult Patients
Carlos Alfredo Galindo Martín (2018)
Assessment of muscle mass in critically ill patients: role of the sarcopenia index and images studies
A. Lopez-Ruiz (2020)
ROUNDS Studies: Relation of OUtcomes with Nutrition Despite Severity-Round One: Ultrasound Muscle Measurements in Critically Ill Adult Patients.
Carlos Alfredo Galindo Martín (2018)
Computed Tomography–based Body Composition Analysis and Its Role in Lung Cancer Care
Amelie S Troschel (2019)
Machine Learning for Automatic Paraspinous Muscle Area and Attenuation Measures on Low-Dose Chest CT Scans.
R. Barnard (2019)
Low Thoracic Skeletal Muscle Area Predicts Morbidity after Pneumonectomy for Lung Cancer.
M. Madariaga (2019)
ICU Admission Muscle and Fat Mass, Survival, and Disability at Discharge: A Prospective Cohort Study
A. Jaitovich (2019)
Assessment of muscle mass using ultrasound with minimal versus maximal pressure compared with computed tomography in critically ill adult patients.
K. Fetterplace (2020)
Measuring and monitoring lean body mass in critical illness
W. G. Looijaard (2018)
Early high protein intake and mortality in critically ill ICU patients with low skeletal muscle area and -density.
W. G. Looijaard (2019)
Semantic Scholar Logo Some data provided by SemanticScholar