ArticleSystematic reviews2019
Effect of mushrooms on obesity in animal models: study protocol for a systematic review and meta-analysis.
Article in Systematic reviews, 2019. 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.
- Hypoglycemic Properties ofJournal of fungi (Basel, Switzerland) · 2024Article
- Edible Mushrooms as Novel Myco-Therapeutics: Effects on Lipid Level, Obesity and BMI.Journal of fungi (Basel, Switzerland) · 2022Review
- Is There Scope for a Novel Mycelium Category of Proteins alongside Animals and Plants?Foods (Basel, Switzerland) · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundObesity and its consequences are worldwide epidemic problem; therefore, studies with strategies and mechanisms that favor weight loss to improve outcomes in health are necessary. Effects of mushrooms on body weight are uncertain. The aim of this systematic review is to determine the efficacy of mushrooms in weight loss in animal preclinical models.
methodThis is a systematic review of preclinical studies of animal models of obesity (any type of non-aquatic mammal), which were exposed to edible and medicinal mushrooms orally in comparison with the control. The following databases will be used: MEDLINE (PubMed), Web of Science, BIOSIS, SCOPUS, and gray literature. There will be no restriction of language, date, or publication status. The primary outcome will be body weight loss. And the secondary outcomes include the total amount of food consumed by the animals, analysis of metabolic parameters, inflammatory mediators, mortality for any causes, and any adverse effect reported. A team of reviewers will select, in pairs and independently, the titles and abstracts, extract data from qualifying studies, and assess bias risk (using SYstematic Review Centre for Laboratory animal Experimentation SYRCLE's risk of bias tool and the Collaborative Approach to Meta-Analysis and Review of Animal Data from Experimental Studies (CAMARADES) checklist). The standardized mean difference (SMD) will be calculated to measure treatment effect, with 95% confidence intervals (95% CI). The heterogeneity between-study will be calculated by I DISCUSSION: Although many experimental studies about the effects of mushrooms on obesity have already been published, there is still no consensus in the literature. This study will provide evidences of preclinical research on mushrooms and their relation to body weight loss in animal models of obesity, being non-aquatic mammals. Also, this systematic review will show the limitations and strengths of the studies available in the literature, as well as it will to encourage the financing of new studies by public health managers and governmental entities. SYSTEMATIC REVIEW REGISTRATION: PROSPERO (CRD42019125299).
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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.