ArticleEuropean journal of clinical nutrition2019
Muscle mass assessment by computed tomography in chronic kidney disease patients: agreement with surrogate methods.
Article in European journal of clinical nutrition, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Comparison of Diagnostic Value for Chronic Kidney Disease between 640-Slice Computed Tomography Kidney Scan and Conventional Computed Tomography Scan.Contrast media & molecular imaging · 2022Trial
- The role of L3 skeletal muscle index in the diagnosis and prognosis prediction of sarcopenia and malnutrition in cancer patients.Frontiers in oncology · 2026Article
- Chronic Kidney Disease, Sarcopenia, and Hormonal-Metabolic Alterations: An Intriguing Association.Kidney & blood pressure research · 2026Review
- Predicting Sarcopenia in Peritoneal Dialysis Patients: A Multimodal Ultrasound-Based Logistic Regression Analysis and Nomogram Model.Diagnostics (Basel, Switzerland) · 2025Article
- Myosteatosis: an underrecognized risk factor for mortality in non-dialysis chronic kidney disease patients.Journal of nephrology · 2024Article
- Effect of low muscle mass on total mortality related to metabolic disease in chronic kidney disease patients.Scientific reports · 2024Article
- Making the invisible visible: imaging techniques for assessing muscle mass and muscle quality in chronic kidney disease.Clinical kidney journal · 2024Review
- An Exploratory Study on a New Method for Nutritional Status Assessment in Patients with Chronic Kidney Disease.Nutrients · 2023Article
- Low skeletal muscle mass by computerized tomography is associated with increased mortality risk in end-stage kidney disease patients on hemodialysis.Journal of nephrology · 2022Article
- Sarcopenia in chronic kidney disease: what have we learned so far?Journal of nephrology · 2021Review
- CT-Determined Sarcopenia in GLIM-Defined Malnutrition and Prediction of 6-Month Mortality in Cancer Inpatients.Nutrients · 2021Observational
- Feasibility of computed tomography-based assessment of skeletal muscle mass in hemodialysis patients.Journal of nephrology · 2021Article
- Muscle mass assessment in renal disease: the role of imaging techniques.Quantitative imaging in medicine and surgery · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND/
objectivesPatients with chronic kidney disease (CKD) are subjected to muscle wasting. Therefore, it is important to investigate surrogate methods that enable the assessment of muscle mass loss in the clinical setting. We aimed to analyze the agreement between computed tomography (CT) and surrogate methods for the assessment of muscle mass in non-dialysis CKD patients. SUBJECTS/
methodsCross-sectional study including 233 non-dialysis patients on CKD stages 3 to 5 (61 ± 11 years; 64% men; glomerular filtration rate 22 (14-33) mL/min/1.73 m
resultsIn males, the MAMC showed the best agreement with CT as indicated by the kappa test (k = 0.57, P < 0.01), sensitivity (S = 68%), specificity (S = 89%) and accuracy (area under the curve-AUC = 0.78), followed by the Baumgartner equation (kappa = 0.46, P < 0.01; sensitivity = 60%; specificity = 87% and AUC = 0.73). In female, the Baumgartner equation showed the best agreement with CT (kappa = 0.43, P < 0.01; sensitivity = 57%; specificity = 86% and AUC = 0.71).
conclusionsThe MAMC and Baumgartner equation showed the best agreement with CT for the assessment of muscle mass in non-dialysis CKD patients.
Indexed as
Identifiers
29559719What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.