ReviewAnnals of laboratory medicine2024
Bias in Laboratory Medicine: The Dark Side of the Moon.
Review in Annals of laboratory medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed.
- Characterizing placental dysfunction with DNA methylation profiling and placental histopathology.Placenta · 2026Article
- Article
- Application of sigma-based quality control rules for the efficiency of internal quality control.Practical laboratory medicine · 2025Article
- Calibration Error, a Neglected Error Source in the Clinical Laboratory Quality Control.EJIFCC · 2025Article
- Comparative Evaluation of Serum Separator V-Tube™, VQ-Tube™, and KDiagnostics (Basel, Switzerland) · 2025Article
- Article
- Are Your Laboratory Data Reproducible? The Critical Role of Imprecision from Replicate Measurements to Clinical Decision-making.Annals of laboratory medicine · 2025Review
- Adjustment Formula for Harmonizing Triglyceride Values in the Korea National Health and Nutrition Examination Survey, 2005-2022.Annals of laboratory medicine · 2025Article
- Investigating and quantifying selection bias in research using placental pathology samples.Pregnancy (Hoboken, N.J.) · 2025Article
- What is the probability that higher versus lower quality of evidence represents true effects estimates?Journal of evaluation in clinical practice · 2025Article
- Prevalence and determinants of stunting and anaemia in children aged 6-23 months: A multilevel analysis from rural Ethiopia.Maternal & child nutrition · 2025Article
- The accuracy of estimating equations for the evaluation of kidney function in adult survivors of unilateral, nonmetastatic, non-syndromic Wilms tumor: A pilot study from the St. Jude Lifetime Cohort Study.Pediatric blood & cancer · 2025Article
- The impact of sensor application site on continuous noninvasive haemoglobin trends.Computational and structural biotechnology journal · 2025Article
- Article
- Laboratory Preparation for Digital Medicine in Healthcare 4.0: An Investigation Into the Awareness and Applications of Big Data and Artificial Intelligence.Annals of laboratory medicine · 2024Article
- Benchmarking medical laboratory performance on a global scale.Frontiers in public health · 2024Article
- Role of apolipoprotein B in the clinical management of cardiovascular risk in adults: An Expert Clinical Consensus from the National Lipid Association.Journal of clinical lipidologyArticle
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
Physicians increasingly use laboratory-produced information for disease diagnosis, patient monitoring, treatment planning, and evaluations of treatment effectiveness. Bias is the systematic deviation of laboratory test results from the actual value, which can cause misdiagnosis or misestimation of disease prognosis and increase healthcare costs. Properly estimating and treating bias can help to reduce laboratory errors, improve patient safety, and considerably reduce healthcare costs. A bias that is statistically and medically significant should be eliminated or corrected. In this review, the theoretical aspects of bias based on metrological, statistical, laboratory, and biological variation principles are discussed. These principles are then applied to laboratory and diagnostic medicine for practical use from clinical perspectives.
Indexed as
Identifiers
What 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.