ArticleMethodsX2022
Burst-pause criterion derivation for drinkometer measurements of ingestive behavior.
Article in MethodsX, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It reports registered trial NCT07457424. Cited by 1 paper.
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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.
Direct Measurement of Changes in Food Selection and Intake Behaviour After Using the Maximum Dose of GLP-1 Receptor Agonists
Direct Measurement of Ingestive Behaviour in Relation to Sex Differences and Gastrointestinal Hormone Levels in Patients After Metabolic and Bariatric Surgery
Investigating in Humans the Impact of Training Status on Dietary Consumption With Direct Measurement of Ingestive Behaviour
Who cites it
1 citing paper in PubMed, 4 citations in OpenAlex.
- Changes in food preferences and ingestive behaviors after glucagon-like peptide-1 analog treatment: techniques and opportunities.International journal of obesity (2005) · 2025Review
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Authors and funding
11 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The drinkometer is a promising device for the study of ingestive behavior of liquid meals in humans. It can be used to investigate behavior in different target populations. However, ingestive behavior has a great variability across study participants. Therefore, a new analytical approach is required for the extraction and analysis of drinkometer-derived data that could account for this variability. We developed an optimized protocol to predict an optimal burst-pause criterion (PC) for the extraction of PC-dependent microstructural parameters of ingestive behavior. These describe the microstructure of bursts, while PC-independent parameters describe the microstructure of sucks. Therefore, a PC is required to analyze separately two physiologically different parts of behavior. To accomplish this burst-pause criterion derivation (BPCD), a Gaussian Mixture Model (GMM) was built for estimation of two probability density functions (PDFs). These model the distribution of inter-suck intervals (ISIs) and inter-burst intervals (IBIs), respectively. The PC is defined at the intersection point of the two density functions. A Kaplan-Meier (KM) survival analysis was performed for post-hoc verification of the fit of the predicted optimal PC to the ISI distribution. In this protocol paper, we present a walkthrough of the data analysis of drinkometer-derived data for the measurement of microstructure of ingestive behavior based on previous results published by our group [1].•Standardization of the burst-pause criterion derivation for drinkometer measurements of ingestive behavior.•All codes are publicly available in a repository.•The method can be easily adapted to studies with larger sample size or more than one study stimulus.
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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.