ReviewAnnals of laboratory medicine2025
Are Your Laboratory Data Reproducible? The Critical Role of Imprecision from Replicate Measurements to Clinical Decision-making.
Review in Annals of laboratory medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Analytical Imprecision and Reference Change Values for Longitudinal Monitoring of NCD-Related Biochemical Analytes.Diagnostics (Basel, Switzerland) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Measurement results of biological samples are not perfect and vary because of numerous factors related to the biological samples themselves and the measurement procedures used to analyze them. The imprecision in patients' laboratory data arising from the measurement procedure, known as analytical variation, depends on the conditions under which the data are collected. Additionally, the sample type and sampling time significantly affect patients' laboratory results, particularly in serial measurements using samples collected at different time points. For accurate interpretation of patients' laboratory data, imprecision-both its analytical and biological components-should be properly evaluated and incorporated into data management. With advancements in measurement technologies, analytical imprecision can be minimized to an insignificant level compared to biological imprecision, which is inherent to all biomolecules because of the dynamic nature of metabolism. This review addresses: (i) the theoretical background of variation, (ii) the statistical and metrological evaluation of measurement variation, (iii) the assessment of variation under different conditions in medical laboratories, (iv) the impact of measurement variation on clinical decisions, (v) the influence of biases on measurement variation, and (vi) the variability of analytes in human metabolism. Collectively, both analytical and biological imprecision are inseparable aspects of all measurements in biological samples, with biological imprecision serving as the foundation of personalized laboratory medicine.
Indexed as
Identifiers
What Socratic 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 Socratic graph.