ArticleJournal of diabetes science and technology2020
Evaluation of Precision and Bias Specifications Required to Achieve the 2018 FDA Guidance Criteria for Glucose Meter Performance Using Simulation Models.
Article in Journal of diabetes science and technology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed, 4 citations in OpenAlex.
- Detecting and Mitigating Bias for Inclusive and Trustworthy Clinical Research: A Scientific Statement From the American Heart Association.Circulation. Genomic and precision medicine · 2026Review
- Strategies for optimization of hypoglycemia rat models.Animal models and experimental medicine · 2025Review
- The clinical effect of glucose meter selection upon the detection of neonatal hypoglycemia.Paediatrics & child health · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe objective of this study was to estimate the combinations of total bias and total imprecision required for devices to meet the Food and Drug Administration (FDA) specifications using Monte Carlo simulation rather than collection and analysis of experimental data.
methodsA model Gaussian distribution of true-glucose values was altered by adding bias and imprecision to create measured-glucose values affected by analytic error. The fraction of measured-glucose values that met the 2018 FDA criteria for blood glucose monitoring system (BGMS) or self-monitoring blood glucose (SMBG) devices was determined as a function of bias and imprecision.
resultsThe BGMS model determined that a maximum total imprecision of 6% was required with no bias, and with a total bias of +10 mg/dL the total imprecision allowed was reduced to 5% to achieve the 95% FDA performance expectation: 95% of results ≥75 mg/dL within ±12% and 95% of results <75 mg/dL within ±12 mg/dL. The SMBG model determined that a maximum total imprecision of 6% was required at no bias, and with a total bias of +10 mg/dL the total imprecision allowed was reduced to 4% to achieve the 98% FDA expectation: 98% of results ±75 mg/dL within ±15% and 98% of results <75 mg/dL within ±15 mg/dL.
conclusionsThe 2018 FDA guidance criteria require strict conditions for glucose meter clinical trials to achieve <10 mg/dL total bias and total imprecision of <5%. Total imprecision and bias values assessed in models in this study represent the cumulative imprecision and bias errors for the glucose meters, the reference method, and preanalytic processes.
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.