Accelerometer-derived Movement Features As Predictive Biomarkers for Muscle Atrophy in Neurocritical Care: a Prospective Cohort Study

Overview

Journal Crit Care

Specialty Critical Care

Date 2024 Aug 31

PMID 39217360

Authors

Moritz L Schmidbauer

Timon Putz

Leon Gehri

Luka Ratkovic

Andreas Maskos

Julia Zibold

Johanna Bauchmuller

Sophie Imhof

Thomas Weig

Max Wuehr

Konstantinos Dimitriadis

Affiliations

Soon will be listed here.

Abstract

Background: Physical inactivity and subsequent muscle atrophy are highly prevalent in neurocritical care and are recognized as key mechanisms underlying intensive care unit acquired weakness (ICUAW). The lack of quantifiable biomarkers for inactivity complicates the assessment of its relative importance compared to other conditions under the syndromic diagnosis of ICUAW. We hypothesize that active movement, as opposed to passive movement without active patient participation, can serve as a valid proxy for activity and may help predict muscle atrophy. To test this hypothesis, we utilized non-invasive, body-fixed accelerometers to compute measures of active movement and subsequently developed a machine learning model to predict muscle atrophy.

Methods: This study was conducted as a single-center, prospective, observational cohort study as part of the MINCE registry (metabolism and nutrition in neurointensive care, DRKS-ID: DRKS00031472). Atrophy of rectus femoris muscle (RFM) relative to baseline (day 0) was evaluated at days 3, 7 and 10 after intensive care unit (ICU) admission and served as the dependent variable in a generalized linear mixed model with Least Absolute Shrinkage and Selection Operator regularization and nested-cross validation.

Results: Out of 407 patients screened, 53 patients (age: 59.2 years (SD 15.9), 31 (58.5%) male) with a total of 91 available accelerometer datasets were enrolled. RFM thickness changed - 19.5% (SD 12.0) by day 10. Out of 12 demographic, clinical, nutritional and accelerometer-derived variables, baseline RFM muscle mass (beta - 5.1, 95% CI - 7.9 to - 3.8) and proportion of active movement (% activity) (beta 1.6, 95% CI 0.1 to 4.9) were selected as significant predictors of muscle atrophy. Including movement features into the prediction model substantially improved performance on an unseen test data set (including movement features: R = 79%; excluding movement features: R = 55%).

Conclusion: Active movement, as measured with thigh-fixed accelerometers, is a key risk factor for muscle atrophy in neurocritical care patients. Quantifiable biomarkers reflecting the level of activity can support more precise phenotyping of ICUAW and may direct tailored interventions to support activity in the ICU. Studies addressing the external validity of these findings beyond the neurointensive care unit are warranted.

Trial Registration: DRKS00031472, retrospectively registered on 13.03.2023.

References

Mourtzakis M, Parry S, Connolly B, Puthucheary Z . Skeletal Muscle Ultrasound in Critical Care: A Tool in Need of Translation. Ann Am Thorac Soc. 2017; 14(10):1495-1503. PMC: 5718569. DOI: 10.1513/AnnalsATS.201612-967PS. View

Piva S, Fagoni N, Latronico N . Intensive care unit-acquired weakness: unanswered questions and targets for future research. F1000Res. 2019; 8. PMC: 6480958. DOI: 10.12688/f1000research.17376.1. View

Leblanc A, Rowe R, Schneider V, Evans H, Hedrick T . Regional muscle loss after short duration spaceflight. Aviat Space Environ Med. 1995; 66(12):1151-4. View

Wright S, Thomas K, Watson G, Baker C, Bryant A, Chadwick T . Intensive versus standard physical rehabilitation therapy in the critically ill (EPICC): a multicentre, parallel-group, randomised controlled trial. Thorax. 2017; 73(3):213-221. PMC: 5870467. DOI: 10.1136/thoraxjnl-2016-209858. View

Needham D, Davidson J, Cohen H, Hopkins R, Weinert C, Wunsch H . Improving long-term outcomes after discharge from intensive care unit: report from a stakeholders' conference. Crit Care Med. 2011; 40(2):502-9. DOI: 10.1097/CCM.0b013e318232da75. View

Hermans G, Van den Berghe G . Clinical review: intensive care unit acquired weakness. Crit Care. 2015; 19:274. PMC: 4526175. DOI: 10.1186/s13054-015-0993-7. View

Suetta C, Hvid L, Justesen L, Christensen U, Neergaard K, Simonsen L . Effects of aging on human skeletal muscle after immobilization and retraining. J Appl Physiol (1985). 2009; 107(4):1172-80. DOI: 10.1152/japplphysiol.00290.2009. View

Hodgson C, Bailey M, Bellomo R, Brickell K, Broadley T, Buhr H . Early Active Mobilization during Mechanical Ventilation in the ICU. N Engl J Med. 2022; 387(19):1747-1758. DOI: 10.1056/NEJMoa2209083. View

Schaller S, Anstey M, Blobner M, Edrich T, Grabitz S, Gradwohl-Matis I . Early, goal-directed mobilisation in the surgical intensive care unit: a randomised controlled trial. Lancet. 2016; 388(10052):1377-1388. DOI: 10.1016/S0140-6736(16)31637-3. View

10.

Valenzuela P, Morales J, Pareja-Galeano H, Izquierdo M, Emanuele E, de la Villa P . Physical strategies to prevent disuse-induced functional decline in the elderly. Ageing Res Rev. 2018; 47:80-88. DOI: 10.1016/j.arr.2018.07.003. View

11.

Hermans G, Van Mechelen H, Bruyninckx F, Vanhullebusch T, Clerckx B, Meersseman P . Predictive value for weakness and 1-year mortality of screening electrophysiology tests in the ICU. Intensive Care Med. 2015; 41(12):2138-48. DOI: 10.1007/s00134-015-3979-7. View

12.

Fazio S, Doroy A, Da Marto N, Taylor S, Anderson N, Young H . Quantifying Mobility in the ICU: Comparison of Electronic Health Record Documentation and Accelerometer-Based Sensors to Clinician-Annotated Video. Crit Care Explor. 2020; 2(4):e0091. PMC: 7188433. DOI: 10.1097/CCE.0000000000000091. View

13.

Van Aerde N, Meersseman P, Debaveye Y, Wilmer A, Gunst J, Casaer M . Five-year impact of ICU-acquired neuromuscular complications: a prospective, observational study. Intensive Care Med. 2020; 46(6):1184-1193. DOI: 10.1007/s00134-020-05927-5. View

14.

Maskos A, Schmidbauer M, Kunst S, Rehms R, Putz T, Romer S . Diagnostic Utility of Temporal Muscle Thickness as a Monitoring Tool for Muscle Wasting in Neurocritical Care. Nutrients. 2022; 14(21). PMC: 9654352. DOI: 10.3390/nu14214498. View

15.

Hvid L, Aagaard P, Justesen L, Bayer M, Andersen J, Ortenblad N . Effects of aging on muscle mechanical function and muscle fiber morphology during short-term immobilization and subsequent retraining. J Appl Physiol (1985). 2010; 109(6):1628-34. DOI: 10.1152/japplphysiol.00637.2010. View

16.

Singer P, Reintam Blaser A, Berger M, Alhazzani W, Calder P, Casaer M . ESPEN guideline on clinical nutrition in the intensive care unit. Clin Nutr. 2018; 38(1):48-79. DOI: 10.1016/j.clnu.2018.08.037. View

17.

Friedrich O, Reid M, Van den Berghe G, Vanhorebeek I, Hermans G, Rich M . The Sick and the Weak: Neuropathies/Myopathies in the Critically Ill. Physiol Rev. 2015; 95(3):1025-109. PMC: 4491544. DOI: 10.1152/physrev.00028.2014. View

18.

Sanchez-Sanchez J, Manas A, Garcia-Garcia F, Ara I, Antonio Carnicero J, Walter S . Sedentary behaviour, physical activity, and sarcopenia among older adults in the TSHA: isotemporal substitution model. J Cachexia Sarcopenia Muscle. 2019; 10(1):188-198. PMC: 6438335. DOI: 10.1002/jcsm.12369. View

19.

Kelmenson D, Quan D, Moss M . What is the diagnostic accuracy of single nerve conduction studies and muscle ultrasound to identify critical illness polyneuromyopathy: a prospective cohort study. Crit Care. 2018; 22(1):342. PMC: 6296115. DOI: 10.1186/s13054-018-2281-9. View

20.

Jones S, Hill R, Krasney P, OConner B, Peirce N, Greenhaff P . Disuse atrophy and exercise rehabilitation in humans profoundly affects the expression of genes associated with the regulation of skeletal muscle mass. FASEB J. 2004; 18(9):1025-7. DOI: 10.1096/fj.03-1228fje. View