Association of CT-based diagnosis of sarcopenia with prognosis and treatment response in patients at risk of malnutrition - A secondary analysis of the Effect of early nutritional support on Frailty, Functional Outcomes, and Recovery of malnourished medical inpatients Trial (EFFORT) trial.


Journal

Clinical nutrition (Edinburgh, Scotland)
ISSN: 1532-1983
Titre abrégé: Clin Nutr
Pays: England
ID NLM: 8309603

Informations de publication

Date de publication:
02 2023
Historique:
received: 23 06 2022
revised: 07 12 2022
accepted: 08 12 2022
pubmed: 6 1 2023
medline: 3 2 2023
entrez: 5 1 2023
Statut: ppublish

Résumé

CT-derived measures of muscle mass may help to identify patients with sarcopenia. We investigated the prognostic significance of CT-derived sarcopenia and muscle attenuation with nutritional markers, clinical outcomes and response to nutritional support in medical in-patients at nutritional risk. Within this secondary analysis of the randomized-controlled Effect of early nutritional support on Frailty, Functional Outcomes, and Recovery of malnourished medical inpatients Trial (EFFORT) comparing individualized nutritional support with usual care nutrition in medical inpatients, we investigated associations of CT-based sarcopenia and muscle attenuation at the level L3 with different nutritional and clinical outcomes, and the response to the nutritional intervention. The primary composite endpoint was adverse clinical outcome within 30 days of hospital admission. We included 573 of 2028 EFFORT patients with available CT scans, of which 68.4% met the CT-based definition of sarcopenia and 72.9% had low muscle attenuation. In multivariate analysis, low skeletal muscle index was associated with higher nutritional risk (coefficient per NRS class -0.94 (95%CI -1.87 to -0.01) p = 0.049) and higher risk for adverse clinical outcomes (adjusted odds ratio 1.59 (95% CI 1.06 to 2.38), p = 0.024). Low muscle attenuation was also associated with adverse clinical outcome (adjusted odds ratio 1.67 (95%CI 1.08 to 2.58), p = 0.02). Nutritional support tended to be more effective in reducing mortality in non-sarcopenic patients compared to patients with CT-based sarcopenia (p for interaction 0.058). Within a population of medical patients at nutritional risk, CT-based sarcopenia and muscle attenuation were associated with several nutritional parameters and predicted adverse clinical outcomes. Information from CT scans, thus may help to better characterize these patients, and may be helpful in guiding therapeutic interventions.

Sections du résumé

BACKGROUND & AIM
CT-derived measures of muscle mass may help to identify patients with sarcopenia. We investigated the prognostic significance of CT-derived sarcopenia and muscle attenuation with nutritional markers, clinical outcomes and response to nutritional support in medical in-patients at nutritional risk.
METHOD
Within this secondary analysis of the randomized-controlled Effect of early nutritional support on Frailty, Functional Outcomes, and Recovery of malnourished medical inpatients Trial (EFFORT) comparing individualized nutritional support with usual care nutrition in medical inpatients, we investigated associations of CT-based sarcopenia and muscle attenuation at the level L3 with different nutritional and clinical outcomes, and the response to the nutritional intervention. The primary composite endpoint was adverse clinical outcome within 30 days of hospital admission.
RESULTS
We included 573 of 2028 EFFORT patients with available CT scans, of which 68.4% met the CT-based definition of sarcopenia and 72.9% had low muscle attenuation. In multivariate analysis, low skeletal muscle index was associated with higher nutritional risk (coefficient per NRS class -0.94 (95%CI -1.87 to -0.01) p = 0.049) and higher risk for adverse clinical outcomes (adjusted odds ratio 1.59 (95% CI 1.06 to 2.38), p = 0.024). Low muscle attenuation was also associated with adverse clinical outcome (adjusted odds ratio 1.67 (95%CI 1.08 to 2.58), p = 0.02). Nutritional support tended to be more effective in reducing mortality in non-sarcopenic patients compared to patients with CT-based sarcopenia (p for interaction 0.058).
CONCLUSIONS
Within a population of medical patients at nutritional risk, CT-based sarcopenia and muscle attenuation were associated with several nutritional parameters and predicted adverse clinical outcomes. Information from CT scans, thus may help to better characterize these patients, and may be helpful in guiding therapeutic interventions.

Identifiants

pubmed: 36603460
pii: S0261-5614(22)00434-4
doi: 10.1016/j.clnu.2022.12.006
pii:
doi:

Banques de données

ClinicalTrials.gov
['NCT02517476']

Types de publication

Randomized Controlled Trial Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

199-207

Informations de copyright

Copyright © 2022 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Déclaration de conflit d'intérêts

Conflicts of interest All other authors report no conflicts of interest.

Auteurs

Annic Baumgartner (A)

Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland.

Tobias Olpe (T)

Medical Faculty of the University of Basel, Switzerland.

Stephanie Griot (S)

Medical Faculty of the University of Basel, Switzerland.

Nicole Mentil (N)

Medical Faculty of the University of Basel, Switzerland.

Nathalie Staub (N)

Medical Faculty of the University of Basel, Switzerland.

Felice Burn (F)

Department of Radiology Kantonsspital Aarau, Aarau, Switzerland.

Sebastian Schindera (S)

Department of Radiology Kantonsspital Aarau, Aarau, Switzerland.

Nina Kaegi-Braun (N)

Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland.

Pascal Tribolet (P)

Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland; Department of Health Professions, Bern University of Applied Sciences, Bern, Switzerland.

Claus Hoess (C)

Internal Medicine, Kantonsspital Muensterlingen, Switzerland.

Vojtech Pavlicek (V)

Internal Medicine, Kantonsspital Muensterlingen, Switzerland.

Stefan Bilz (S)

Internal Medicine & Endocrinology/Diabetes, Kantonsspital St.Gallen, Switzerland.

Sarah Sigrist (S)

Internal Medicine & Endocrinology/Diabetes, Kantonsspital St.Gallen, Switzerland.

Michael Brändle (M)

Internal Medicine & Endocrinology/Diabetes, Kantonsspital St.Gallen, Switzerland.

Christoph Henzen (C)

Internal Medicine, Kantonsspital Luzern, Switzerland.

Robert Thomann (R)

Internal Medicine, Buergerspital Solothurn, Switzerland.

Jonas Rutishauser (J)

Internal Medicine, Kantonsspital Baden, Switzerland.

Drahomir Aujesky (D)

Department of General Internal Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.

Nicolas Rodondi (N)

Department of General Internal Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland; Institute of Primary Health Care (BIHAM), University of Bern, Switzerland.

Jacques Donzé (J)

Department of General Internal Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland; Division of General Internal Medicine, Brigham and Women's Hospital, Boston, MA, USA.

Zeno Stanga (Z)

Division of Diabetology, Endocrinology, Nutritional Medicine & Metabolism, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.

Beat Mueller (B)

Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland; Medical Faculty of the University of Basel, Switzerland.

Philipp Schuetz (P)

Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland; Medical Faculty of the University of Basel, Switzerland. Electronic address: philipp.schuetz@ksa.ch.

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Classifications MeSH