ReviewCardiovascular ultrasound2026
Noise in clinical data: insights from assessment of aortic stenosis by echocardiography.
Review in Cardiovascular ultrasound, 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
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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
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Noise (synonyms: variability, imprecision) in clinical data is underappreciated. All measurements are affected by noise and bias. Research studies enrol many patients to average out noise and use randomisation and double-blinding to counter bias. These mitigation techniques are often not available in clinical medicine, where individual patients typically have a variable measured only once.The example of echocardiographic assessment of aortic stenosis severity illustrates how the conventional presentation of data as point estimates masks wide variability in noise between variables, which affects utility. Adding aortic valve area to the quantification of aortic stenosis may result in poorer (noisier) estimates.Every clinical variable reported as a point estimate comes with an invisible cloud of uncertainty (noise) of varying size across variables. Being mindful of how this noise varies across variables should facilitate optimal clinical decisions.
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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.