ReviewSensors (Basel, Switzerland)2026
Metrology in Bioelectrical Impedance Analysis (BIA): From Measurement Science to Clinical and Research Applications.
Review in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bioelectrical impedance analysis (BIA) is a widely used technique in clinical and research settings because it provides non-invasive estimates of body composition. However, the quality of a measurement depends on more than the perceived accuracy and precision of numbers produced by a BIA device. This review considers BIA through the lens of metrology, defined as the science of measurement. It highlights several key factors that affect measurement quality. These include accuracy, precision, calibration, standardisation, and uncertainty quantification, all of which are essential for meaningful, clinically feasible BIA measurements. Applying prediction equations generated by the device outside their intended context, poor electrode placement, or uncalibrated devices can introduce bias, whereas biological variability can complicate the interpretation of bioimpedance results. The traditional emphasis on using a reference method for validation is considered along with clinical relevance, which is argued to be an equally important benchmark for evaluating measurement utility. We also present best practices and practical guidelines for improving measurement quality, interpretation, and integration into clinical workflows. By adopting a metrological mindset in clinical practice and treating BIA with the same rigour as other diagnostic tools, its utility in areas such as fluid management, nutrition, and preventive health can be further enhanced. Trustworthy decisions depend not only on the data itself but also on how it is measured, interpreted, and used.
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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.