Evidence map›Paper›PMID 31737686›Full record

Trial reportJournal of diabetes research2019

Effect of 12-Month Resistance Training on Changes in Abdominal Adipose Tissue and Metabolic Variables in Patients with Prediabetes: A Randomized Controlled Trial.

Juan Yan, Xia Dai, Jitao Feng, Xiaodan Yuan, Jianing Li, Lihong Yang, Panpan Zuo, Zhaohui Fang, Chao Liu, Cunyi Hsue and 3 more

Registry-linked trialOpen access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of diabetes research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02561377 (Effect of Resistance Training on Metabolic Control and Outcome in Prediabetes), which is not on this map. Cited by 22 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 7 pooled it
3.5field-weighted citation impact, top 7% of its field
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.

NCT02561377 naunknown statusnot on this map

Effect of Resistance Training on Metabolic Control and Outcome in Prediabetes (NMR-based Metabonomics)

TypeinterventionalSponsorNanjing University of Traditional Chinese MedicineRan2015 to 2016Enrolled276ConditionsPrediabetic StateArmsresistance training, aerobic training
3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 7 syntheses or guidelines pooled it, 39 citations in OpenAlex.

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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

13 authors at 6 institutions in 2 countries.

Juan YanAffiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, China.ORCID https://orcid.org/0000-0002-0185-7693
Xia DaiDepartment of Endocrinology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.ORCID https://orcid.org/0000-0003-2839-7698
Jitao FengAffiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, China.ORCID https://orcid.org/0000-0003-2578-8407
Xiaodan YuanAffiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, China.ORCID https://orcid.org/0000-0001-5529-5705
Jianing LiAffiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, China.ORCID https://orcid.org/0000-0002-5892-9934
Lihong YangNursing College, Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, China.ORCID https://orcid.org/0000-0003-3591-5262
Panpan ZuoNursing College, Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, China.ORCID https://orcid.org/0000-0002-7220-3697
Zhaohui FangDepartment of Endocrinology, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, China.ORCID https://orcid.org/0000-0003-4181-2294
Chao LiuAffiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, China.
Cunyi HsueUniversity of Massachusetts Amherst, Amherst, MA, USA.ORCID https://orcid.org/0000-0002-9547-3972
Junya ZhuJohns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Joshua D MillerStony Brook University Hospital, NY, USA.
Qingqing LouAffiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, China.ORCID https://orcid.org/0000-0002-4743-0900
Nanjing University of Chinese Medicine · CNAnhui University of Traditional Chinese Medicine · CNGuangxi Medical University · CNJohns Hopkins University · USStony Brook University Hospital · USUniversity of Massachusetts Amherst · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo examine the effects of resistance training relative to aerobic training on abdominal adipose tissue and metabolic variables in adults with prediabetes.

methods105 participants with prediabetes were randomized into the resistance training group (RT,

resultsA total of 93 participants completed the study. There were nonsignificant differences between groups before intervention. After training, VAT decreased significantly in AT and RT compared with CG (

conclusionBoth aerobic training and resistance training are effective in reducing abdominal adipose tissue and fasting plasma glucose in adults with prediabetes. Importantly, resistance training but not aerobic training is effective in augmenting muscle mass.

trial registrationThe trial is registered with NCT02561377 (date of registration: 24/09/2015).

Indexed as

Resistance TrainingAbdominal FatAgedBody CompositionBody Mass IndexFemaleHumansLipidsMaleMiddle AgedPrediabetic StateTomography, X-Ray ComputedTreatment OutcomeLipids

Identifiers

PMID31737686
PMCPMC6815994
OpenAlexW2980321688

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.