Evidence map›Paper›PMID 33062587›Full record

ArticleJournal of translational internal medicine2020

A P4 Medicine Perspective of Gut Microbiota and Prediabetes: Systems Analysis and Personalized Intervention.

Qiongrong Huang, Qiaojun Fang, Zhiyuan Hu

Abstract read
In one paragraph

Article in Journal of translational internal medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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  5. Influence of group BWorld journal of clinical cases · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Qiongrong HuangFujian Provincial Key Laboratory of Brain Aging and Neurodegenerative Diseases, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, Fujian Province, China.
Qiaojun FangCAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology of China, Beijing 100190, China.
Zhiyuan HuFujian Provincial Key Laboratory of Brain Aging and Neurodegenerative Diseases, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, Fujian Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Type 2 diabetes (T2D) accounts for approximately 90% of diabetes worldwide and has become a global public health problem. Generally, individuals go to hospitals and get healthcare only when they have obvious T2D symptoms. While the underlying cause and mechanism of the disease are usually not well understood, treatment is for the symptoms, but not for the disease cause, and patients often continue to progress with more symptoms. Prediabetes is the early stage of diabetes and provides a good time window for intervention and prevention. However, with few symptoms, prediabetes is usually ignored without any treatment. Obviously, it is far from ideal to rely on the traditional medical system for diabetes healthcare. As a result, the medical system must be transformed from a reactive approach to a proactive approach. Root cause analysis and personalized intervention should be conducted for patients with prediabetes. Based on systems medicine, also known as P4 medicine, with a predictive, preventive, personalized, and participatory approach, new medical system is expected to significantly promote the prevention and treatment of chronic diseases such as prediabetes and diabetes. Many studies have shown that the occurrence and development of diabetes is closely related to gut microbiota. However, the relationship between diabetes and gut microbiota has not been fully elucidated. This review describes the research on the relationship between gut microbiota and diabetes and some exploratory trials on the interventions of prediabetes based on P4 medicine model. Furthermore, we also discussed how these findings might influence the diagnosis, prevention and treatment of diabetes in the future, thereby to improve the wellness of human beings.

Indexed as

interventionmicrobiomeP4 medicineprediabetessystems medicinewellness

Identifiers

PMID33062587
PMCPMC7534502

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Registered trials

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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.