Evidence map›Paper›PMID 35340868›Full record

ArticleExperimental and therapeutic medicine2022

Application of machine learning tools: Potential and useful approach for the prediction of type 2 diabetes mellitus based on the gut microbiome profile.

Xiaochun Ge, Aimin Zhang, Lihui Li, Qitian Sun, Jianqiu He, Yu Wu, Rundong Tan, Yingxia Pan, Jiangman Zhao, Yue Xu and 2 more

Abstract read
In one paragraph

Article in Experimental and therapeutic medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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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

12 authors.

Xiaochun GeDepartment of Endocrinology, Affiliated Hospital of Chengde Medical University, Chengde, Hebei 067000, P.R. China.
Aimin ZhangDepartment of Endocrinology, Affiliated Hospital of Chengde Medical University, Chengde, Hebei 067000, P.R. China.
Lihui LiDepartment of Endocrinology, Affiliated Hospital of Chengde Medical University, Chengde, Hebei 067000, P.R. China.
Qitian SunDepartment of Endocrinology, Affiliated Hospital of Chengde Medical University, Chengde, Hebei 067000, P.R. China.
Jianqiu HeDepartment of Endocrinology, Affiliated Hospital of Chengde Medical University, Chengde, Hebei 067000, P.R. China.
Yu WuShanghai Biotecan Pharmaceuticals Co., Ltd., Shanghai 201204, P.R. China.
Rundong TanShanghai Biotecan Pharmaceuticals Co., Ltd., Shanghai 201204, P.R. China.
Yingxia PanShanghai Biotecan Pharmaceuticals Co., Ltd., Shanghai 201204, P.R. China.
Jiangman ZhaoShanghai Biotecan Pharmaceuticals Co., Ltd., Shanghai 201204, P.R. China.
Yue XuShanghai Biotecan Pharmaceuticals Co., Ltd., Shanghai 201204, P.R. China.
Hui TangShanghai Biotecan Pharmaceuticals Co., Ltd., Shanghai 201204, P.R. China.
Yu GaoDepartment of Endocrinology, Affiliated Hospital of Chengde Medical University, Chengde, Hebei 067000, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The gut microbiota plays an important role in the regulation of the immune system and the metabolism of the host. The aim of the present study was to characterize the gut microbiota of patients with type 2 diabetes mellitus (T2DM). A total of 118 participants with newly diagnosed T2DM and 89 control subjects were recruited in the present study; six clinical parameters were collected and the quantity of 10 different types of bacteria was assessed in the fecal samples using quantitative PCR. Taking into consideration the six clinical variables and the quantity of the 10 different bacteria, 3 predictive models were established in the training set and test set, and evaluated using a confusion matrix, area under the receiver operating characteristic curve (AUC) values, sensitivity (recall), specificity, accuracy, positive predictive value and negative predictive value (npv). The abundance of

Indexed as

Bifidobacteriumgut microbiomemachine learning toolsRoseburiainulinivoranstype 2 diabetes mellitus

Identifiers

PMID35340868
PMCPMC8931625

What OpenQuestion holds

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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.