ArticleMicroorganisms2021
Predicting the Role of the Human Gut Microbiome in Constipation Using Machine-Learning Methods: A Meta-Analysis.
Article in Microorganisms, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed, 19 citations in OpenAlex.
- Gut microbiota and constipation: from causal evidence to therapeutic strategies-a state-of-the-art narrative review.Frontiers in microbiology · 2026Review
- The association between the intake of polyunsaturated fatty acids and chronic constipation and diarrhea: NHANES 2005-2010.Lipids in health and disease · 2025Article
- Metabolomics Insights into Gut Microbiota and Functional Constipation.Metabolites · 2025Review
- Microbial imbalance in Chinese children with diarrhea or constipation.Scientific reports · 2024Article
- Artificial intelligence-powered early identification of refractory constipation in children.Translational pediatrics · 2024Article
- The Paraguayan gut microbiome contains high abundance of the phylum Actinobacteriota and reveals the influence of health and lifestyle factors.Gut microbes reports · 2024Article
- MaLiAmPi enables generalizable and taxonomy-independent microbiome features from technically diverse 16S-based microbiome studies.Cell reports methods · 2023Article
- Functional constipation and the effect of prebiotics on the gut microbiota: a review.The British journal of nutrition · 2023Review
- Gut Microbiome-Brain Alliance: A Landscape View into Mental and Gastrointestinal Health and Disorders.ACS chemical neuroscience · 2023Review
- Overview of data preprocessing for machine learning applications in human microbiome research.Frontiers in microbiology · 2023Review
- Subtyping intractable functional constipation in children using clinical and laboratory data in a classification model.Frontiers in pediatrics · 2023Article
- Crosstalk between the Gut Microbiome and Colonic Motility in Chronic Constipation: Potential Mechanisms and Microbiota Modulation.Nutrients · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 1 institution in 2 countries.
Funding
Abstract
(1) Background: Constipation is a common condition that affects the health and the quality of life of patients. Recent studies have suggested that the gut microbiome is associated with constipation, but these studies were mainly focused on a single research cohort. Thus, we aimed to construct a classification model based on fecal bacterial and identify the potential gut microbes' biomarkers. (2) Methods: We collected 3056 fecal amplicon sequence data from five research cohorts. The data were subjected to a series of analyses, including alpha- and beta-diversity analyses, phylogenetic profiling analyses, and systematic machine learning to obtain a comprehensive understanding of the association between constipation and the gut microbiome. (3) Results: The alpha diversity of the bacterial community composition was higher in patients with constipation. Beta diversity analysis evidenced significant partitions between the two groups on the base of gut microbiota composition. Further, machine learning based on feature selection was performed to evaluate the utility of the gut microbiome as the potential biomarker for constipation. The Gradient Boosted Regression Trees after chi2 feature selection was the best model, exhibiting a validation performance of 70.7%. (4) Conclusions: We constructed an accurate constipation discriminant model and identified 15 key genera, including
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.