ArticleJournal of diabetes science and technology2019
Reducing Glucose Meter Adverse Events by Using Reliability Growth With the FDA MAUDE Database.
Article in Journal of diabetes science and technology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Adverse Event Causes From 2022 for Four Continuous Glucose Monitors.Journal of diabetes science and technology · 2025Article
- An Analysis of 2019 FDA Adverse Events for Two Insulin Pumps and Two Continuous Glucose Monitors.Journal of diabetes science and technology · 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
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Glucose meter evaluations are common and provide important information about glucose meter performance versus standards. Although some meters meet guidelines and others fall short in these evaluations, most results are within the A and B zones of a glucose meter error grid. Another data source that is seldom used is the FDA adverse event database (MAUDE). This database describes glucose meter malfunctions and injury as reported by actual users and returned 10 837 adverse events across all meters for the first 7 months of 2018. Reliability growth management is an established tool to reduce failure rates. A reliability growth example is presented followed by a discussion of how this tool could be applied to reduce glucose meter failure events using the MAUDE database.
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.